Review nutritional life cycle assessment indicators and integrated outcomes.
| Paper number | Author | Reference | Year | Location / country(s) | Consideration of product or diet | Livestock type | Product type | system boundary | Terminology of indicator | Study methodology | Environmental indicator(s) | Nutritional Indicator (s) | Public Health indicator (s) | Combined (nutritional-environmental) indicator: the Functional unit | Positive / negative impact | Combined indicator outcome | impact actor - What is the impact on? | Co-Efficient / n-lca output | Fus mass, protein quantity or protein quality | (indicator) Impact summary | Study outcome summary | Additional information for disucssion |
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| 10 | R. Abejón; L. Batlle-Bayer; J. Laso; A. Bala; I. Vazquez-Rowe; G. Larrea-Gallegos; M. Margallo; J. Cristobal; R. Puig; P. Fullana-i-Palmer; R. Aldaco | Abejón, R., Batlle-Bayer, L., Laso, J., Bala, A., Vazquez-Rowe, I., Larrea-Gallegos, G., Margallo, M., Cristobal, J., Puig, R., Fullana-i-Palmer, P. and Aldaco, R. (2020) 'Multi-Objective Optimization of Nutritional, Environmental and Economic Aspects of Diets Applied to the Spanish Context', Foods, 9(11). | 2020 | Spain | GHG emissions of all the food products within the food basket of a given diet were considered. | poultry, beef, lamb, pork, dairy, rabbit | Eggs, beef, chicken, rabbit, lamb, pork, processed meat, hake, pilchard, tuna, atlantic mackerel, salmon, Hake, mussels, squid and octopus, prawns and shrimps, tuna, canned anchovies, Milk, rice, legumes, sunflower oil, margarine, potatoes, other vegetables, citrus fruits, peaches, olives, salt, shakes, icecream, yoghurt, butter, fresh cheese, semi-hard cheese, hard cheese, bread, rice, pasta, biscuits, cereals, tablet, snack choco, cacao powder, sugar, legumes, olive oil, sunflower oil, tomatoes, lettuce, citric, bananas, apples, nuts, tomato products, Gazpacho, fabada, letchup, coffee, wine, beer, water, juice, soft drinks, | cradle-to-consumption | indicator, functional unit | Distance-to-target approach for multi-objective non-linear optimization of 6 dietary scenarios. This method has been adapted here to diets, and three objectives were considered simultaneously: the minimization of both the GHG emissions and the cost of the diet, and the maximization of the diet’s nutritional value. The first one, the average current consumption (CC) pattern, was defined as the sum of the household food purchases and the food eaten out of home, known as Food Away From Home (FAFH), of an average Spanish citizen in 2018. Data on both types of food consumption were based on the data published by the Spanish Ministry of Agriculture, Fisheries, and Food. Regarding the other five diets, they were designed based on the recommendations given by each of the dietary guidelines: • The diet based on the National Dietary Guidelines—NDG. • The diet followed the Mediterranean diet pyramid—MED. • The diet followed taking into account ovo-lacto-vegetarian (OLV) recommendations from the Spanish Vegetarian Union • The diet based on the recommendations for a vegan diet (VEG) provided by the Spanish Vegetarian Union • The diet followed taking into consideration the Planetary Health (PLH) diet proposed by the EAT-Lancet Commission. |
GHG Emmisions (kgCO2 eq/d). | Nutrient rich diet - NRD 9.3w - Constant nutritonal index. TNR9, TNÑ3, and NRD9.3 of the pre-defined diets. TNR9 = Proteins, fiber, K, Ca, Fe, Mg, vitamin A, Vitamin C, vitamin E. TNL3 = Saturated fat, Na, Added sugar. the nutritional quality of each diet was evaluated with the Nutrient Rich Diet 9.3 index (NRD9.3) [31]. This index takes into consideration the intake of the 9 encouraging nutrients (protein, fiber, minerals Ca, Fe, Mg and K, and vitamins A, C and E) and the 3 limiting nutrients (saturated fats, added sugar, and Na). | In this regard, this study applied the methodology of Batlle-Bayer et al., which uses two scores (i.e., RIS and NS) to correct GHG emissions, in order to consider the nutritional and economic aspects when comparing the environmental performance of diets. | negative | Negative - impact on livestock contibtion to GHG emissions, esp red meat and dairy products. Vegan diet insufficient intake of protein, calcium and vitamin A. | c-kg CO2eq./day−1 | Optimised diets have significant decreases in animal protein, namely red meat. In relation to the environmental dimension, the maximal daily GHG emissions corresponded to the Current consumption (4.52 kg CO2eq./day), three times higher than the emissions of the vegan diet (1.41 kg CO2eq./day)—the diet with the lowest emissions—due to the great contribution of the food products from animal sources, specifically red meat. | The search for optimal sustainable diets implies simultaneous optimization of their environmental, economic, health (nutrition), and other socio-cultural dimensions, and partial optimization should be avoided. The intrinsic relations among these different aspects may result in opposing objectives and, therefore, only trade-offs can give the best solutions. To compare sustainability among diets is challenging due to its multidimensionality. In this regard, this study applied the methodology of Batlle-Bayer et al., which uses two scores (i.e., RIS and NS) to correct GHG emissions, in order to consider the nutritional and economic aspects when comparing the environmental performance of diets. Once GHG emissions are corrected, the VEG-opt has the best performance (1.92 c-kg CO2eq./day−1) among the optimized diets. Nevertheless, the VEG diet has still the lowest corrected emissions (1.65 c-kg CO2eq./day−1), due to the lower GHG emissions and the larger affordability. However, the insufficient intake of protein, Ca, and vitamin A should be kept in mind (Table A1 in Appendix A). Regarding the remaining diets, PLH-Opt and OLV-Opt also show relatively low corrected emissions, whereas the optimized CC-Opt diet had the highest value (3.90 c-kg CO2/day), being the dairy products and red meat the largest contributors. | As recommended by Drewnowski [32], the intakes were capped to avoid crediting the overconsumption of nutrients to be encouraged. In other words, the intake of a nutrient was set to its RV when the intake of a certain nutrient exceeded it. From an economic perspective, the MED diet was the most expensive one (4.51 €/day), followed by the CC diet. The higher costs of the MED diet can be mainly attributed to vegetables and fruits (Figure 2). Conversely, the VEG diet was the alternative with the lowest costs (2.36 €/day). the largest cost of the curent consumption diet was attributed to red meat | |||
| 57 | R. Aidoo; C. K. Romana; E. M. Kwofie; J. I. Baum | Aidoo, R., Romana, C. K., Kwofie, E. M. and Baum, J. I. (2023) 'An integrated environmental nutrition model for dietary sustainability assessment', Journal of Cleaner Production, 399. | 2023 | Canada | 1l of milk or 1kg meat | dairy, beef | cows milk, soy milk / soya meatballs and beef sausage | cradle to gate | functional unit , impact categories | Global Warming Fossil Fuel Depletion Land Use Eutrophication Acidification Respiratory Effects Ozone Depletion |
weighted daily value | Carcinogenics, respiratory effects | Comparison of LCA impact results with EIWDVs - Environmental Impact Weighted Daily Value Score | positive | Environemtal impact value reduced when EIWDVs considered. | On a mass basis (L) - Soy meatballs preforms better for Global Warming, Fossil Fuel Depletion, Land Use, Eutrophication, Acidification, Respiratory Effects and carcinogens whereas beef suasage preforms better for ozone depletion. Cows milk preforms better for ozone deplention whereas soymilk preforms better for all other factors. Considering EIWDVs, improvements in all impact categories for cows milk and beef sausage, opposite impact on soy products. | Cows milk LCA Ecotoxicity 1.00E+02 Fossil Fuel Depletion 1.00E+009 Global Warming 1.00E+01 Smog 1.00E-004 Eutrophication 1.00E-01 Acidification 1.00E-011 Respiratory Effects 1.00E-02 Ozone Depletion 1.00E-051 Non-Carcinogenics 1.00E-0 Carcinogenics 1.00E-06 Cows milk EIWDVS Ecotoxicity 1.00E+025 Fossil Fuel Depletion 1.00E+012 Global Warming 1.00E+013 Smog 1.00E-001 Eutrophication 1.00E-007 Acidification 1.00E-008 Respiratory Effects 1.00E-018 Ozone Depletion 1.00E-049 Non-Carcinogenics 1.00E-0 Carcinogenics 1.00E-056 Soy milk LCA Ecotoxicity 1.00E+017 Fossil Fuel Depletion 1.00E+008 Global Warming 1.00E+005 Smog 1.00E-009 Eutrophication 1.00E-018 Acidification 1.00E-019 Respiratory Effects 1.00E-021 Ozone Depletion 1.00E-051 Non-Carcinogenics 1.00E-06 Carcinogenics 1.00E-063 Soy milk EIWDVS Ecotoxicity 1.00E+015 Fossil Fuel Depletion 1.00E+005 Global Warming 1.00E+003 Smog 1.00E-011 Eutrophication 1.00E-02 Acidification 1.00E-021 Respiratory Effects 1.00E-023 Ozone Depletion 1.00E-053 Non-Carcinogenics 1.00E-062 Carcinogenics 1.00E-067 |
EIWDVs results for cow milk were consistently higher in all impact categories than the LCA re sults. In contrast, the EIWDVs results for soymilk were consistently lower than their LCA impact results. This trend supposes that the nutritional quality of cowmilk was not enough to displace the environmental impacts associated to its production. However, soymilk offered better contribution to daily nutritional needs that permitted a substantial displacement of environmental footprint, rendering minimization in impact values. Again, from the environmental-nutrition perspective, soymilk posits as a sustainable alternative to milk consumption. EIWDVs values constantly decreased for beef sausage and soy meatballs. How- ever, the reduction was consistently higher in soy meatballs than in beef sausage, emphasizing that though the nutritional quality of both prod- ucts compensated for their environmental impact to a great extent, soy meatballs better compensated for environmental impact through the satisfaction of required daily values of nutrients. Therefore, in the evolving transition to plant-based dieting, soy meatballs could be considered as a nutritionally adequate and environmentally friendly meat alternative to beef sausage. | Though the plant-based diets performed better in both approaches, the environmental nutrition scores pointed at a significant compensation for environmental impacts when nutrition was considered in impact estimation. we find the trends for the milk and meat products explicitly describe the compensation that could be achieved when nutrition is considered as a critical parameter in sustainability assessment. They add up to establish the necessity of conducting sustainability assessment in a multiparametric manner, also highlighting environmental nutrition, or N-LCA, as a significant concept and a promising research area that can change the paradigm in sustainability assessment within the food value chain. | |||
| 457 | C. Cambeses-Franco; S. González-García; G. Feijoo; M. T. Moreira | Cambeses-Franco, C., González-García, S., Feijoo, G. and Moreira, M. T. (2021) 'Is the Paleo diet safe for health and the environment?', Science of the Total Environment, 781. | 2021 | Spain | Paleo diet | Red Meat, white meat, poultry | Olive oil, fish and seafood, meat, eggs, nuts, starch based products, vegetables, fruits | factory/farm to distribution/household | INDEXES, BENCHMARKS | Water footprint, WF green, WF blue and WF grey (L·person−1 day−1) and carbon footprint (kg CO2·person−1·day−1) | dietary quality index | disease-specific relative risk - T2D, CVD, stroke, obesity and CRCA | Association per food category between the carbon footprint (kgCO2eq·kg−1) and a) the water footprint (expressed as L of water consumed per kg of daily intake), b) the cost (expressed as € per kg of food in a food category c) the relative risk of all-cause mortality. | NEGATIVE | Vegetables, fruits and potatoes were associ- ated with lower impacts on environmental, economic and disease met- rics. Eggs were associated with environmental benefits (low CF and WF), but not with benefits for health impacts in terms of all-cause mor- tality risk. Conversely, red meat was associated with the greatest in- creases in all-cause mortality risk and with the largest negative environmental impacts and expenses. However, the other type of meat, poultry, commonly referred to as white meat, showed lower WF and CF values than red meat and was not associated with a RR of all- cause mortality higher than 1. Regarding fish and seafood group, it re- sulted an expensive category with a relatively high CF. Finally, nuts and olive oil presented a high WF, but low CF and RR of all-cause mor- tality. Nuts were the second most expensive food category after fish and shellfish. | Nutrition // Environment - Fish and seafood and meat products were the largest emitters of carbon dioxide. Foods of animal origin high contributor to green WF however plant food such as nuts high contributor to blue WF Eggs positive environemtal impacts. // public health - red meat, fish and seafood, and poultry associated with the largest increases in diet-related diseases. red meat high contributor to all cause mortality // Economic - red meat expensive. | no quantitative data - plots on graph | The WF for the Paleo diet was estimated on 3499 L·person−1·day−1 (70% green, 16% blue and 14% grey) (see Fig. 5a). Foods of animal origin were the major contributors to the WF (over 64% of the total WF). By far, the largest representation of all animal products comes from the meat category. Approximately 49% of the total WF (1709 L·person−1·day−1) in the Paleo diet was due to meat consumption. However, meat does not represent the most consumed category. It was the fourth in terms of consumption, behind fish and seafood. Additionally, nuts, fish and seafood accounted for 15% and 10% of the dietary WF, respectively. Fig. 5b shows the distribution of the WF between the eight food categories for the Paleo diet. The general findings on green WF were the same. Animal products was largely responsible for the green WF compared to crop products, with meat and fish and seafood having the largest green WF (1373 L·person−1·day−1 and 254 L·person−1·day−1, respectively). Olive oil, with an associated green WF per tonne of 15 L·g−1·day−1, was the major water consuming product, even more than beef meat (11 L·g−1·day−1). However, although animal-based foods were the major contributors to the green and total WF, plant-based food featured as the major contributor to the blue WF (61% of the total), with nuts as an outstanding element (30% of the blue WF). These results were consistent with the conclusions of the meta-analysis conducted by Harris et al. (2020), who reported that plant-based foods dominated the blue WF of healthy diets. Vegetables, fruits and potatoes were associated with lower impacts on environmental, economic and disease metrics. Eggs were associated with environmental benefits (low CF and WF), but not with benefits for health impacts in terms of all-cause mortality risk. Conversely, red meat was associated with the greatest increases in all-cause mortality risk and with the largest negative environmental impacts and expenses. However, the other type of meat, poultry, commonly referred to as white meat, showed lower WF and CF values than red meat and was not associated with a RR of all-cause mortality higher than 1. Regarding fish and seafood group, it resulted an expensive category with a relatively high CF. Finally, nuts and olive oil presented a high WF, but low CF and RR of all-cause mortality. Nuts were the second most expensive food category after fish and shellfish. While fruits and vegetables were consistently associated with improved health (disease specific RR˂1 for T2D, CVD, stroke, obesity and CRCA), red meat was associated with increased risk for the five health indicators. Regarding the other animal-based foods, while the RR-value of eggs for obesity, CVD, and stroke was 0.95, 0.98, and 0.99 respectively (less than 1), the RR-value of eggs for T2D and CRCA was higher than 1. Poultry, fish and seafood were associated with increased risk of T2D and obesity, but not with CRCA, CVD, or stroke. The opposite result could be seen with potatoes, for which a RR higher than 1 was reported for T2D, CRCA and CVD. Nuts and olive oil reduced the risk of four of the five diseases analysed. The RR value was higher than 1 for stroke in the case of nuts and for obesity in the case of olive oil. |
Paleo Diet can be considered as an expensive and not nutritionally adequate diet with a high carbon footprint. According to the main results of this study, the Paleo diet can be con- sidered an expensive dietary choice with a significant effect on GHG emissions. Fish and seafood and meat products were the largest emitters of carbon dioxide in the Paleo diet, although their average daily per capita consumption was not as significant as that of other food categories such as fruits or vegetables. Moreover, while fruits and vegetables were associated with better adult health, food groups with the largest carbon footprint (red meat, fish and seafood, and poultry) were also associated with the largest increases in diet-related diseases. In terms of nutritional profile, the Paleo diet is rich in fats, proteins and PUFA and restricts carbohydrates, which leads to lose weight and improve muscle development. However, the high levels of cholesterol and EPA in the Paleo diet could cause negative health effects, increasing the risk of cancer and cardiovascular disease. | |||
| 481 | R. P. M. Cardinaals; E. Verly, Jr.; O. Jolliet; H. H. E. Van Zanten; T. Huppertz | Cardinaals, R. P. M., Verly, E., Jr., Jolliet, O., Van Zanten, H. H. E. and Huppertz, T. (2024) 'The complementarity of nutrient density and disease burden for Nutritional Life Cycle Assessment', Frontiers in Sustainable Food Systems, 8. | 2024 | Netherlands | Meat, dairy | Beef Broccoli Chickpeas Milk Almonds Salmon Peanut butter Rice Apple Dutch confectionery |
cultivation to consumer, including end of life processes for food losses and packaging materials. | indicator | Global Warming Potential (GWP), land use (LU) and freshwater use (WU). GWP was calculated as the sum of CO2 equivalents per kilogram of product for CO2, CH4 and N2O emissions throughout the supply chain of a product. Land use was expressed as the number of square meters required per year for cultivation of food and animal feed and/or for raising livestock (including land transformation if applicable). Freshwater use was calculated as the amount of water consumed by producing 1 kg of product, expressed as m3 per kg. For this study, GWP, land use and freshwater use were recalculated per 100 kcal of product. | Nutrient Rich Food index with 24 essential nutrients (NRF24) and the HEalth Nutritional Index (HENI). NRF24 covered 24 essential nutrients: protein, essential fatty acids (DHA, ALA and LA), sodium, potassium, calcium, phosphorous, magnesium, iron, copper, selenium, iodine, zinc, vitamins A, C, D, E, B1, B2, B3, B6, B9 and B12. These 24 nutrients covered all essential vitamins and minerals except for biotin, chloride, choline, chromium, fluoride, manganese, molybdenum and pantothenic acid. These eight nutrients were excluded as nutrient content data was lacking in the NEVO database. the NRF24 was calculated by default per 100kcal food item. | The HEalth Nutritional Index (HENI) - The HENI for a food item indicates the minutes of healthy life lost or gained due to a marginal shift in the dietary risk component content of an adult’s diet under the assumption that the health effect from multiple dietary risk components is independent and additive and that food components not covered by the GBD have neutral health effects. focusing on nutritious diets that are low in dietary risk factors such as trans-fatty acids, sugar sweetened beverages and processed meat is urgently needed to reduce diet-related diseases and obesity. This focus is also applicable to low-income countries where current diets suffer from nutrient inadequacy. | positive | per 100kcal and considering NRF24 - beef does not have the worst water footprint (almonds do) whereas per HENI beef does. Plant based products GWP and land use scores increase when considering NRF24, whereas beef stays the same. | GWP (kg CO2eq)/100kcal Beef 2.5 Milk 0.4 Almonds 0.1 GWP (kg CO2eq)/ NRF24 Beef 0.8 Milk 0.2 Almonds 0.08 GWP (kg CO2eq)/HENI Beef 0.7 Milk 0.02 Almonds 0.01 Land use (m2a)/ 100kcal Beef 1.25 Milk 0.3 Almonds 0.28 Land use (m2a)/ NRF24 Beef 0.34 Milk 0.18 Almonds 0.2 Land use (m2a) HENI Beef 0.33 Milk 0.1 Almonds 0.05 Water use (m3)/ 100kcal Beef 0.02 Milk 0.002 Almonds 0.001 Water use (m3)/ NRF24 Beef 0.005 Milk 0.001 Almonds 0.05 Water use (m3)/ HENI Beef 0.0051 Milk 0.0001 Almonds 0.00035 |
Animal source foods had a low water use compared to plant source foods but LU was variable with the highest LU observed for veal and smoke-dried beef. | the synergic environmental and health benefit from a reduction of animal source foods is also dependent on the functional unit used, e.g., water use in our study is relatively high for 100 kcal of fruits and vegetables, and will even be higher when expressed on protein content, but when expressed on a mass base, these food groups perform relatively well. This study stresses the importance of addressing essential nutrient content and disease burden of single food items individually in nLCA. a high nutrient density does not directly imply a low risk for non-communicable diseases, or the other way around. In addition, trade-offs and synergies between nutrition and environment are also different for nutrient density and disease burden, with a high variety for individual food items. Our results therefore do not support the statement that changing towards a healthy diet inherently reduces the overall environmental impact of the diet. | To complicate things further, unsustainable consumption is not limited to the types of food consumed but also the extent of overconsumption and food waste, two aspects that are positively associated with the environmental impact of the diet. However, food items are not consumed in isolation but together in a meal, as part of a whole diet. Some food items may score low on nutrient density but may be important for the overall dietary quality because they provide unique nutrients that cannot be provided by other foods. nutrient density of the whole diet is associated with modestly lower risks of chronic diseases and all-cause mortality. Furthermore, a narrow selection of nutrients can limit the comparison of food items over a wide variety of food groups (McAuliffe et al., 2020) and it has been recommended to include as many essential nutrients as possible in nLCA. calculation on energy basis favors the nutritional impact and disfavors environmental impact of low energy foods, such as fruits vegetables. That is, reaching 100 kcal for low energy foods will require a higher volume of production and consumption and thereby higher benefits for human health and a higher environmental impact. | |||||
| 592 | C. Colizzi; M. C. Harbers; R. E. Vellinga; W. M. M. Verschuren; J. M. A. Boer; S. Biesbroek; E. H. M. Temme; Y. T. van der Schouw | Colizzi, C., Harbers, M. C., Vellinga, R. E., Verschuren, W. M. M., Boer, J. M. A., Biesbroek, S., Temme, E. H. M. and van der Schouw, Y. T. (2023) 'Adherence to the EAT-Lancet Healthy Reference Diet in Relation to Risk of Cardiovascular Events and Environmental Impact: Results From the EPIC-NL Cohort', Journal of the American Heart Association, 12(8). | 2023 | Nethelands | Healthy reference diet (HRD) | dairy, poultry,red meat | fruits and vegetables, whole grains, legumes, nuts, and unsaturated oils, dairy, starchy vegetables, poultry, fish, red meat, products containing saturated fat, sweeteners. | unspecified | indicator | GHGE (kg carbon dioxide equivalent per day); land use (m2 per year); blue water use (m3 per day), which refers to irrigation water; freshwater eutrophication; and terrestrial acidification (kg sulfur dioxide equivalent per day), which refers to the process by which chemicals in acidifying forms enter the soil, leading to biodiversity loss. | HRD healthy referecne diet - The diet includes high consumption of fruits and vegetables, whole grains, legumes, nuts, and unsaturated oils; low to moderate consumption of dairy, starchy vegetables, poultry, and fish; and no or low consumption of saturated fats, red meat, and all sweeteners. As such, the HRD generally emphasizes the intake of plant‐based foods and suggests to limit the intake of animal‐sourced foods and starchy vegetables. | cardiovascular events | HRDea score, energy‐adjusted healthy reference diet score | Negative | A reduction or omitting ASFs and starchy vegetables from diet and increasing plant based food reuslts in all lower environmental impacts as well as lower risk of CVD and CHD. | HRDea score, energy‐adjusted healthy reference diet score. Kg CO2‐eq = kilograms of carbon dioxide equivalent; Kg N‐eq, kilograms of nitrogen equivalent; Kg P‐eq, kilograms of phosphorus equivalent; Kg SO2‐eq, kilograms of sulfur dioxide equivalent; m2 per year, square meters per year; m3 per day, cubic meters per day. Q4 - High adherence to HRD • Greenhouse gases: 4.94 x 10^0 kg carbon dioxide equivalent • Land use: 2.76 x 10^0 m² per year • Blue water use: 1.7 x 10^-1 m³ per day • Freshwater eutrophication: 3.5 x 10^-4 g phosphate equivalent • Marine eutrophication: 9 x 10^-3 kg nitrogen equivalent • Terrestrial acidification: 5.0 x 10^-2 g sulfur dioxide equivalent Q1 - Low adherence to HRD • Greenhouse gases: 6.17 x 10^0 kg carbon dioxide equivalent • Land use: 3.54 x 10^0 m² per year • Blue water use: 1.4 x 10^-1 m³ per day • Freshwater eutrophication: 4.3 x 10^-4 g phosphate equivalent • Marine eutrophication: 1.0 x 10^-2 kg nitrogen equivalent • Terrestrial acidification: 6.5 x 10^-2 g sulfur dioxide equivalent |
The present study suggests that adhering to the Healthy Reference Diet was associated with lower risk of cardiovascular disease and coronary heart disease but was not associated with lower risk of total stroke, ischemic stroke, and hemorrhagic stroke. High adherence to the HRD was associated with 14%, 12%, and 11% lower risks of cardiovascular disease (hazard ratio [HR]Q4vsQ1, 0.86 [95% CI, 0.78–0.94]), coronary heart disease (HRQ4vsQ1, 0.88 [95% CI, 0.78–1.00]), and total stroke (HRQ4vsQ1, 0.89 [95% CI, 0.72–1.10]), respectively. The EAT‐Lancet report projected that 19.0% to 23.6% of premature adult deaths could potentially be avoided by adopting the HRD, while remaining within acceptable environmental boundaries. However, these projections were based on theoretical models. Higher adherence to the HRD was also associated with 3.5% lower GHGE, 2.6% less land use, 0.5% less freshwater eutrophication, 2.5% less marine eutrophication, and 8.1% less terrestrial acidification but with 30.6% higher blue water use. High HRD adherence was associated with 2.4% (95% CI, −5.0 to 0.2) lower greenhouse gas emissions, 3.9% (95% CI, −5.2 to −2.6) less land use, 0.5% (95% CI, −2.6 to 1.6), less freshwater eutrophication, 3.3% (95% CI, −5.8 to −0.8), less marine eutrophication, 7.7% (95% CI, −10.8 to −4.6), less terrestrial acidification, and 32.1 % (95% CI, 28.5–35.7) higher blue water use. | |||||
| 598 | B. Coluccia; G. P. Agnusdei; F. De Leo; Y. Vecchio; C. M. La Fata; P. P. Miglietta | Coluccia, B., Agnusdei, G. P., De Leo, F., Vecchio, Y., La Fata, C. M. and Miglietta, P. P. (2022) 'Assessing the carbon footprint across the supply chain: Cow milk vs soy drink', Science of the Total Environment, 806. | 2022 | Italy | dairy | cows milk, soy drink | When analyzing the cow milk supply chain, the following steps were considered: forage cultivation (including the use of diesel, gasoline, propane, electricity and heating fuel), animal breeding (including enteric fermentation and manure management), beverage production and packaging. | to provide a reference point for the inputs and outputs and quantify the product system performance, the functional unit (FU) used in this study was a 1 L beverage (cow milk or soy drink). In order to calculate the total CF of cow milk and soy drink, the study adopted a Life Cycle (LC) approach and took into account the total amount of GHG emissions associated with each product along the whole supply-chain. GHG emissions were computed as Global Warming Potential (GWP) in a 100-year time horizon and expressed as CO2 equivalents (CO2eq). accounting for CH4, N2O, NH4. GWP of N2O emissions amounted to 265 kg CO2eq/kgN2O. | carbon footprint | WEIGHTED PROTEIN SCORE - (PRO) protein content (PER 100G OF PRODUCT) & digestible indispensable amino acid score (DIAAS). | Carbon Footprint Protein Score (CFPRO) as shown in Eq. (12) to capture the protein content and quality in the en- vironmental comparison of the products:CFPRO is computed as the average Carbon Footprint (CFp) of the analyzed products in kg CO2-eq divided by Weighted Protein Score (PRO). | positive | The value of CFPRO reveals a lower amount of CO2 emissions by proteins contained in the soy drink, compared to those in the cow milk. | per litre, soy milk had half the environmetal affect of cows milk. Cows milk has a greater nutritional value (protein) than soy drink. | cows milk 0.115 kg CO2 eq / PRO score /// soy drink 0.064 kg CO2 eq / PRO score | The CF of cow milk fell in the range 0.99–1.08 Kg CO2eq/L while that of soy drink in the range 0.51–0.52 Kg CO2eq/L both with 90% confidence interval. production of one liter of soy drink has an environmental impact 50% lower than the production of one liter of cow milk. The PRO results demonstrate a higher nutritional score associated with the proteins contained in cow's milk (9.18) than those contained in the soy drink (8.14). Soy milk cannot be considered a nutiritonal substitute for cow milk, especially in childrens diet due to deficinecy in the intake of calcium, vitamin B12 and lower nutritional quality of vegetable pro- teins compared to animal proteins. the value of CFPRO reveals a lower amount of CO2 emissions by proteins contained in the soy drink, compared to those in the cow milk. | Results highlight that, considering the environmental perspective, soy drink could be a valid substitute of cow milk: its production has a lower carbon footprint, allowing for the achievement of food security objectives. How- ever, focusing on the economic and nutritional perspectives, the high average consumer price of soy drink is as- sociated with an overall lower nutritional level. In order to reach the same nutritional value as 1 L of cow milk in terms of protein intake, the consumption of soy drink should be increased by 13%. Furthermore, soy drink con- sumption implies paying 66% more than for cow milk, when considering the same protein content. While the production of cow milk reveals greater impacts on animal farms, the production of soy drink is characterized by major impacts within the food process- ing industries.However, the value of CFPRO confirms a lower environmental impact of the soy drink. | Soy drink has a higher average con- sumer price and a lower nutritional level. The Sustainable Development Goal 12 of the 2030 Agenda intends to ensure sustainable dietary patterns, reducing the production and consumption of animal products, thus limiting the contribution of agricul- ture to climate vulnerability. |
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| 613 | M. Cooreman-Algoed; S. Huysveld; C. Lachat; J. Dewulf | Cooreman-Algoed, M., Huysveld, S., Lachat, C. and Dewulf, J. (2020) 'How to integrate nutritional recommendations and environmental policy targets at the meal level: A university canteen example', Sustainable Production and Consumption, 21, pp. 120-131. | 2020 | Belgium | beef, poultry | entire meal - The functional unit was one served hot meal, with a protein, vegetable and carbohydrate component, in a Ghent University canteen | cradle-to-plate | indicator | First, the environmental impact of meals are quantified through Life Cycle Assessment. Second, the meals are classified based on international environmental policy targets. Third, the nutritional value is assessed based on two methods: Weighted Nutrient Density Score (WNDS) and nutritional thresholds. The WNDS is estimated for every meal. In addition, the nutritional composition of meals is compared with four nutritional thresholds. Fourth, the nutritional results are classified based on the results of both the WNDS and the nutritional thresholds. For the environmental and nutritional classification, three reference values are introduced, resulting in four environmental and four nutritional classes, i.e. 16 integrated classes in total. The environmental reference values were based on the 2020 and 2030 European Commission targets on greenhouse gas emission reduction. The nutritional reference values were based on food recommendations from national public health authorities. | Greenhouse gas emissions | Weighted nutrient density score. Based on 6 nutrients. Three nutrients have positive health impacts: protein, fiber, and unsaturated fat. Three nutrients have negative health impacts: saturated fat, added sugar, and sodium content. method was cho- sen because no data on vitamin and mineral composition was available.protein, fiber, unsaturated fat, saturated fat, and added sugar are expressed as g per 100 kcal and sodium as mg per 100 kcal. | Mixed | When considering nutrition and environment integrated, beef preforms poorly, however chicken dishes do not place so poorly | ReCIPe single score (Pt)/ Weighted Nutrient Density Score. Beef preforms worst consdiering both scores. No quantitative data. | Meals with fish had the best nutritional value. Vegetarian and ruminant meat meals had the lowest nutrition score. In general, meals with ‘the best score’ contain fish and boiled potatoes and meals with ‘the worst score’ ruminant meat (Fig. 7). Meals with fish have on average a ReCiPe single score of 0.223 Pt and WNDS of 24.22. Meals with ruminant meat have an environ- mental and a nutritional score of 0.824 Pt and 12.64, respectively. The vegetarian meals have the best environmental score (0.177 Pt). Yet, they have, similarly to ruminant meals, the worst nu- tritional score (12.65). Meals with non-ruminant meat have an intermediate score for both the environment and nutrition. | |||||||
| 628 | A. Cortesi; G. Y. L. Bris; C. Pénicaud | Cortesi, A., Bris, G. Y. L. and Pénicaud, C. (2024) 'Using nutritional functional units provides a nuanced view of the environmental performance of food products within the same category', International Journal of Life Cycle Assessment, 29(5), pp. 838-856. | 2024 | France | dairy | 80 industrial pizzas and 44 artisanal cheeses. | unspecified | indicator | We then examined how the relative environmental performance (ranking) of the 80 pizzas and the 44 cheeses changed depending on the FU used for analysis.For the cheeses, environmental impacts were assessed for two different ripening scenarios: an energy-intensive scenario in which the cheeses were ripened in a small on-site ripening room and a low-energy scenario in which the cheeses were rip- ened in a large off-site shared ripening room. The main difference between the two scenarios is that the electrical consumption per kg of ripened cheese was lower for the low-energy scenario than for the energy-intensive scenario. Both of these scenarios are investigated in the current study. To calculate environmental impacts with a FU based on the SAIN score, the environmental impacts of 100 g of product were divided by the SAIN score of that product. This means that, unlike units based on nutrient amounts, the FU for the SAIN score is qualitative and not quantitative. | climate change. However, the results obtained with other environmental indicators (ozone depletion, ionizing radiation, photochemical ozone forma- tion, particulate matter, acidification, freshwater eutrophi- cation, marine eutrophication, terrestrial eutrophication, land use, water use, fossil resource use, and mineral/metal resource use) will also be shortly explained at the end of the result section. | mass, energy, and protein FUs , calcium, protein + calcium, and SAIN FUs SAIN (score for the nutritional adequacy of individual foods). energy content, protein content, and a French nutritional index (SAIN). For pizza, we assessed additional FUs based on portion size, fiber content, and a combination of protein and fiber content; for cheese, we also calculated FUs for calcium content and a combination of protein and calcium content. | In order to study the influence of the choice of FU on the environmental performance calculated for each product, performance rankings were established for each functional unit tested. To do this, we first ranked the products from the most to the least impacting on climate change with a mass FU of 1 kg. We then studied the evolution of this ranking when other FUs were used. The aim was to see whether the products considered to have the greatest impact with a 1 kg FU were still the most impacting when another FU was used, and vice versa. | positive | The use of a FU based on a particular nutrient always improved the apparent environmental performance of products that were rich in that nutrient. Cheeses with the lowest impact when mass FU had improved climate change rankings when calcium, protein + calcium and SAIN score functional units were used. | no quantitative data | For calcium, the high- est reference flow (i.e., the mass of cheese needed to ingest 1/18 of the daily recommended intake of calcium) was 13 times higher than the lowest reference flow. For protein, instead, the cheeses were more similar to each other, with the highest and lowest reference flows differing by only a fac- tor of 1.6. With pizzas, we observed little difference in the distri- bution of environmental impacts from one FU to another These results raise questions about the relevance of using calcium as a basis for comparing the environmen- tal impacts of different cheeses. If one product has a lower environmental impact than another, but 10 times more must be consumed to obtain the same amount of calcium, is this really a useful comparison? The use of different functional units did not greatly impact the distribution of environmental impacts for pizza. When calcium, protein + calcium, and SAIN FUs were considered with cheese rather than a mass, energy, or protein FU, significant differences were seen in environmental impact. This is logical since the cheeses with the highest energy, protein, and calcium contents are the driest ones, which require the most milk to make and thus have higher concentrations of milk-based nutrients. This increased use of milk, however, is associated with higher impacts on climate change when assessed using a mass FU. Similarly, the calculation of the SAIN score for cheese takes into account the content per 100 kcal of protein and calcium, two nutrients that are most concentrated in dry cheeses. As expected, the cheeses that are richest in energy, protein, or calcium, or with the best SAIN scores, had poor rankings overall (lower than 32nd out of 44). These results were con- sistent with those obtained for the energy-intensive scenario (Fig. 6). However, in the low-energy scenario, the use of a FU based on energy, protein, or calcium led to a stronger improve- ment in these cheeses’ rankings than in the energy-intensive scenario.FUs based on energy content, protein content, and a French nutritional index (SAIN). For pizza, we assessed additional FUs based on portion size, fiber content, and a combination of protein and fiber content; for cheese, we also calculated FUs for calcium content and a combination of protein and calcium content. The energy FU was used for both food categories because it is the most commonly used nutritional FU in the literature. With the mass FU, the 10 pizzas with the highest energy content and the 10 pizzas with the highest protein content tended to have globally worse rankings than the 10 pizzas with the highest fiber content and those with the best SAIN scores. This makes sense because, generally speaking, the pizzas with the highest impacts on climate change in this group are the ones containing beef and/or those with a high cheese content (Cortesi et al. 2022a), which are thus rich in protein but highly caloric. Instead, pizzas that contain fewer animal products and more vegetables and dough, and which are therefore richer in fiber, tended to be among those with the lowest impacts on climate change. | The use of a FU based on a given nutrient/score tended to improve the rankings of the pizzas that were richest/highest in that nutrient or score. For example, the use of an energy FU improved the rankings of the most caloric pizzas. The same was true for the protein-rich pizzas, which saw their average ranking improve from 60th with a mass FU to bet- ter than 45th with a protein FU. Similarly, the 10 pizzas that were richest in fiber had an average ranking of 30th out of 80 with a mass FU, and this improved to better than 17th with a fiber FU. Finally, the average ranking of the 10 piz- zas with the highest SAIN scores changed from 38th out of 80 with a mass FU to higher than 22nd with a FU based on the SAIN score. This suggests that greater variation in a nutrient among products increases the chance that a FU based on that nutrient will have a strong influence on the ranking. Furthermore, if this nutrient is most concentrated in the products with the highest environmental impacts (as assessed with a mass FU), its use as a FU can reverse the mass-based ranking, as occurred here for the calcium- based ranking of cheeses. Our finding that a FU based on a given nutrient favors the performance of the products richest in that nutrient is also consistent with the literature. The use of a FU based on a particular nutrient always improved the apparent environmental performance of products that were rich in that nutrient. This phenomenon was particularly pronounced in cases where a mass-based FU revealed only small variation in environmental impacts between products, when products were rich in the nutrients analyzed by the FU, and when there was a range in the nutrient content of products.products from the same category were not necessarily nutritionally similar, and that nutritional and environmental dimensions could be contradictory, meaning that both should be evaluated together. Using nutritional FU can influence greatly the results when the goal is to compare different food products from the same category. | The results presented here focus on climate change, which is the most commonly used indicator in the literature of food LCAs and is considered to be the most robust of the environ- mental indicators available. This means that the reversal of the mass-based ranking with a calcium-based FU was even stronger for the low-energy scenario than for the energy-intensive scenario. This might be explained by the fact that, compared to the energy-inten- sive scenario, the low-energy scenario reduces differences in climate change impacts among the 44 cheeses. With the energy-intensive scenario, the daily electricity consumption of the ripening rooms is higher than in the low-energy sce- nario, and as a result, cheeses that are ripened a long time have much more significant environmental impacts than those that are ripened for only a short time. This suggests that, when the differences in impacts calculated by mass- based FUs are small, it is more likely that nutritional FUs will yield different results.For food products, the use of a mass-based FU for assessing environmental impacts has been called into question because this approach does not represent the function of a food product. However, the use of non-mass-based FUs also has limitations. For example, as mentioned in the Introduction and discussed by McLaren et al. (2021), the use of a single nutrient as a FU reduces the function of the product to containing this nutrient. The same problem arises with the use of an energy FU. A FU based on the combination of two nutrients may be slightly more informative but still does not take into account all of the nutrients of interest in a category of products. Furthermore, as shown here with pizza, when one nutrient is universally more limiting than the other, a FU based on two nutrients will generate the same results as one based only on the limiting nutrient. This underlines the advantage of using a food group scale when selecting the nutrients (or nutritional index) to be used in the FU. For example, Saarinen et al. (2017) compared the GHG emissions of different protein-rich food products and concluded that, while the GHG emissions related to some food products are clearly lower than others, the wide range in product mass to be considered in the refer- ence flows can make a detailed comparison very difficult. For example, using a protein FU, peas have lower GHG emissions than beef; however, to reach the recommended daily amount of protein, it is necessary to consume 1.41 kg of cooked dry peas but only 290 g of beef. This difference in reference flows should be taken into consideration when interpreting the results of this type of analysis. In other words, does the reference flow calculated for a food product correspond to a realistic pattern of daily consumption? In reality, a person is not going to eat 4.9 times more of a food product to obtain the same amount of nutrients, which calls into question the per- tinence of using a protein FU. In any case, the interpretation of this kind of results is greatly aided by data on real-life con- sumption patterns, when available. Generally speaking, this shows the limitations of conducting nutritional LCA studies on the scale of the food product. Indeed, the diet is complex, and it is important to note that the nutrients provided by a food product are multiple and the total nutrient intake depends to a large extent on the balance of the diet. | ||||
| 767 | A. Detzel; M. Krüger; M. Busch; I. Blanco-Gutiérrez; C. Varela; R. Manners; J. Bez; E. Zannini | Detzel, A., Krüger, M., Busch, M., Blanco-Gutiérrez, I., Varela, C., Manners, R., Bez, J. and Zannini, E. (2022) 'Life cycle assessment of animal-based foods and plant-based protein-rich alternatives: an environmental perspective', Journal of the Science of Food and Agriculture, 102(12), pp. 5098-5110. | 2022 | Europe | pork, poultry, beef, dairy | European-grown grain legumes such as lentils, faba beans and lupins, combined with pseudocereals such as buckwheat, quinoa and amaranth. pig, poultry and beef meat, as well as cowʼs milk. only the milk alternatives made from soy, pea and lentil proteins have protein content comparable to that of cowʼs milk. | The LCA was designed as a ‘cradle-to-gate’ LCA comprising all the life cycle steps from biotic and abiotic raw material sourcing up to the final food products at the factory gate, including all transports as well as all energy and raw material pre-chains. Production and disposal of the infrastructure (machines, transport media, roads, etc.) and their maintenance (spare parts, heating of production halls) as well as packaging material related to the final products were excluded based on Agrifootprint 2.0.33 | indicator | This article examines the sustainability of an extrudated vegetable meat alternative (‘VMA extrudate’), providing an alternative for chicken meat and a vegetable milk as an alternative for cowʼs milk. The VMA extrudate developed in Protein2Food is a high-moisture meat substitute without soy or wheat, using grain legumes and pseudocereals. It can be produced in the form of nuggets, chunks, strips and burgers and can be flavoured with various aromas to satisfy different tastes. | Environmental profiles of the selected food products have been calculated through life cycle assessment (LCA). Climate change kg CO2-e FU–1. Stratospheric ozone depletion kg CFC-11-e FU–1. Photo-oxidant formation kg O3-e FU–1. Acidification kg SO2-e FU–1. Terrestrial eutrophication/kg PO4-e FU–1. Aquatic eutrophication/kg PO4-e FU–1. Particulate matter/kg PM2,5-e FU–1. Land footprint/m2 year FU–1. Water footprint/ m3 FU–1. Cumulated energy demand (CED, total)/ MJ FU–1. Cumulated energy demand (CED, non-renewable)/ MJ FU–1. Cumulated energy demand (CED, renewable)/ MJ FU–1. Use of phosphorus/ kg FU–1 | mass-based and a protein-based FU were applied in the LCA, as well as an energy-based FU in the case of milk. | mixed | Considering energy content rather than mass, cows milk preforms better. Considering 30g of protein, there was a smakk increase in chicken breast meat and a large increase in land use change. | g CO2 equivalents per 100g product Plant based VMA (variant 1) 240 g CO2 equivalents per 100g Chicken breast meat (conventional) 342 g CO2 equivalents per 100g g CO2 equivalents per 30g protein Plant based VMA (variant 1) 240 g CO2 equivalents per 30g protein Chicken breast meat (conventional) 479 g CO2 equivalents per 30g protein |
The carbon footprints of Protein2Food prototypes and those of their animal-based counterparts are shown in Figs 3 and 4. The carbon footprints of VMA extrudates (Fig. 3) refer to 100 g food product with a protein content of 30 g. Comparisons that were conducted on a mass basis show values of 235 g CO2 equivalents and 240 g CO2 equivalents for VMA extrudates from lupin protein combined with amaranth or buckwheat flour, respectively. The carbon footprint of the optimized vegetable VMA made from faba bean protein in combination with amaranth (variant 3) is 130 g CO2 equivalents per 100 g food product. The corresponding carbon footprints of 100 g chicken meat are 232 g CO2 equivalents and 342 g CO2 equivalents for chicken breast obtained from high-performance chicken and from conventional chicken, respectively. Compared to high-performance chicken, the optimized variant has a significantly lower carbon footprint. Interestingly, the carbon footprint of high-performance chicken is in the range of the VMA extrudates, if compared on a mass basis but becomes somewhat larger if compared on a protein equivalence basis due to the smaller protein content of chicken breast as compared to the VMA extrudates. In the case of cowʼs milk and lentil protein-based milk (Fig. 4), the differences are much more apparent. Even without accounting for direct land use change and when considering the energy-based functional unit, the carbon footprint of cowʼs milk is three times up to almost four times larger than that of the plant-based milk. The environmental footprint of plant-based VMA (base product) tends to be better than that of chicken meat for most of the indicators, with the exception of cumulative energy and process water demand as well as land use. Strongly reduced nitrogen fertilizer requirements of legume crops relative to classical feed crops are the reason for favourable results of meat substitutes in aquatic eutrophication. the environmental footprint of lentil-based milk is mostly favourable as compared to cowʼs milk, with land use being the single indicator showing a clear disadvantage. With regard to aquatic eutrophication, the comparative results of the milk substitute show a more differentiated picture. Lentil-based milk tends to have a lower impact when compared to conventional cowʼs milk, but provides an ambiguous result when compared to the more efficient cowʼs milk. The overall advantage of the plant-based prototype is more outstanding in the case of milk. However, both plant-based prototypes still bear a substantial improvement potential that can be seen in the optimized variants. Carbon footprints per 100 g meat replacers are reported to be 272 g CO2 equivalents if soy meal based, 130 g CO2 equivalents if tofu based and 390 g CO2 equivalents for minced soy.25, 58, 59 238 g CO2 equivalents (cradle to factory gate) was reported for 100 g of a meat replacer from isolated pea protein.57 A meat replacer using potato and soy protein accounted for 347 g CO2 equivalents per 100 g (cradle to factory gate),60 while wheat gluten-based meat replacer was calculated to generate 381 g CO2 equivalents per 100 g.29. Overall, the lupin-based meat replacer prototypes developed within Protein2Food are well within the lower range of the carbon footprints reported for meat replacers based on soy (excluding the more mildly processed tofu) and pea proteins. | Extrudated vegetable meat alternatives consisting of protein combined with amaranth or buckwheat flour and a vegetable milk alternative made from lentil proteins were shown to have the potential to generate significantly less environmental impact than their animal-based counterparts in most of the environmental indicators examined, taking into account both functional units (mass and protein content). Development of higher processed and therefore higher performing products is crucial for appealing to potential user groups beyond dedicated vegetarians and vegans and ultimately achieving market expansion. The Protein2Food project showed that prototypes made from European-grown legumes and pseudocereals are a valuable source for high-quality protein foods, and despite being substantially processed they could help reduce the environmental impact of food consumption, especially when replacing cowʼs milk-based food products. When replacing chicken, the future aim should be to further reduce energy demand of the processing stage (as commercial production matures) as well as optimize legume farming towards higher and stable yields. | Future research should also be directed towards yield variations in legume farming, also depending on the type of crop management (organic vs. conventional, tillage practices), the degree of irrigation and regarding its implications for water and energy requirements. Development of higher processed and therefore higher performing products is crucial for appealing to potential user groups beyond dedicated vegetarians and vegans and ultimately achieving market expansion.72 However, due to the high contribution of food processing to the environmental footprint, even with optimized processing, the highly processed plant-based meat and milk replacer foods are expected still to have a higher environmental impact than less processed products. Therefore, mildly processed protein crops such as cooked grain legumes should also be examined regarding their environmental performance in future research in order to identify if those are a suitable permanent component of diets as sources of low-cost dietary proteins for human consumption with a low-impact environmental profile. | |||||
| 806 | N. A. Doran-Browne; R. J. Eckard; R. Behrendt; R. S. Kingwell | Doran-Browne, N. A., Eckard, R. J., Behrendt, R. and Kingwell, R. S. (2015) 'Nutrient density as a metric for comparing greenhouse gas emissions from food production', Climatic Change, 129(1-2), pp. 73-87. | 2015 | Australia | N/A | Milk, beef, lamb | N/A | paper introduces the metric, emissions/unit nutrient density, and compares the results with three other metrics: emissions intensity (t CO2e/t product), emissions/t protein and emissions/GJ. The food products examined are wheat flour, milk, canola oil, lean lamb, lean beef, untrimmed lamb and untrimmed beef. The metric t CO2e/unit nutrient density was the preferred metric to use when examining GHGE from food production because it compares different types of products based on their nutritional value, rather than according to singular nutrients such as protein, or specific attributes such as product weight or energy content.Eight food products are examined in this study: lamb from untrimmed or lean cuts, beef from untrimmed or lean cuts, regular milk (minimum of 3.5 % fat), reduced fat milk (1.0 % fat), wheat flour and canola oil. The GHGE of the modelled farm enterprises whose products are transformed into these eight food products are estimated as part of this study. | t CO2e | Nutrient Rich Food (NRF) nutrient profile models against a Healthy Eating Index to determine which models most accurately described variations in food. The model that captured most variation was the NRF9.3 | N/A | t CO2e/unit nutrient density was used … emissions/unit nutrient density (not just protein), and compares the results with three other metrics: emissions intensity (t CO2e/t product), emissions/t protein and emissions/GJ | Positive / negative | Environment-public health | Beef (t CO2e/unit nutrient density = 2.00 ) (t CO2e/t product = 37.7) (emissions/t protein = 166 ) (emissions/GJ = 7.7) Lamb (t CO2e/unit nutrient density = 1.9) (t CO2e/t product = 28.3) (emissions/t protein = 130) (emissions/GJ = 5.18) Milk (t CO2e/unit nutrient density = 0.19 ) (t CO2e/t product = 0.9) (emissions/t protein = 27) (emissions/GJ = 0.3 ) |
Quantity / quality | N/A | Widening the review of the desirability of this metric when other policy considerations apply, such as the expense of food, or environmental factors such as water use, are also a potentially worthwhile extension of this study. | ||||
| 821 | N. Draijer; A. R. del Rio; A. Lie-Piang; A. E. M. Janssen; R. M. Boom | Draijer, N., del Rio, A. R., Lie-Piang, A., Janssen, A. E. M. and Boom, R. M. (2023) 'Nutritional value in sustainability assessment of protein-rich ingredients and foods: A 'farm-to-faeces' approach', Journal of Cleaner Production, 417. | 2023 | Netherlands | whey protein | mildly fractionated pea protein ingredients were compared to a whey protein isolate acting as a reference of animal-sourced proteins. Whey protein isolate (WPI, UltraWhey90 standard, Volac Interna- tional, UK) and yellow pea protein isolate | farm-to-faeces | indicator | Whey protein isolate (WPI) and yellow pea protein isolate (PPI) were used as reference materials. Dry yellow peas (Pisum sativum L., Alimex, The Netherlands) were milled to obtain pea flour and mildly separated aqueous protein-rich (PRF), soluble (SPF) and non-soluble (NSPF) protein fractions | environmental impact in this single score format since it aggregates all impact categories and is therefore convenient for comparison. This implies that we do not focus on just one midpoint impact category (such as climate change), but we consider a variety of environmental impacts which, in our view, allows a more holistic comparison. | protein digestibility. The following product-oriented FU were applied in this study: ingredient (kg), dry matter (kg), and protein (kg). Moreover, two digestibility-oriented FU were used to reflect the effect of the processing history of these materials, namely, the quantity of in vitro hydrolysable protein (kg), which is the average DH after 120 min of small intestinal digestion of the five gastric emptying steps, determined by the o- phthalaldehyde method (Fig. S3a), and the minimum digestible, limiting, IAA (kg m-IAA, Equation (1)) | Single score mPT - The indicators calculated with the midpoint methodology focus on single environmental issues, such as global warming potential (expressed in CO2 equivalents) or land use (expressed in m2a crop eq). Indicators calculated with the endpoint methodology aggregate the impacts on higher levels, namely the damage to human health, ecosystems and resource availability. In addition, those endpoint categories may be normalized to a single score, having the unit millipoint (mPt), representing the total environmental impact. | negative | Environemntal impact of whey protein isolate remains worse than pea protein isolate even when considering Kg protein, Kg hydrolysable protein and Kg m-IAA. | Single score (mPT)/Kg ingredient Whey protein isolate unheated 760 mPT Pea protein isolate unheated 150 mPT Single score (mPT)/Kg dry matter Whey protein isolate unheated 800 mPT Pea protein isolate unheated 130 mPT Single score (mPT)/Kg protein Whey protein isolate unheated 820 mPT Pea protein isolate unheated 230 mPT Single score (mPT)/Kg hydrolysable protein Whey protein isolate unheated 1190 mPT Pea protein isolate unheated 450 mPT Single score (mPT)/Kg m-IAA Whey protein isolate unheated 920 mPT Pea protein isolate unheated 240 mPT |
The environmental impact of WPI (whey protein isolate) was significantly higher than those of all pea ingredients when expressed per kg of ingredient (Figs. 2 and 3A). This stems largely from the impact of the embodied raw material for WPI (whey). Most impact of the dairy production system is caused by feed and enteric fermentation. For pea production, no such feed con- versions take place. In addition to the impact of the raw material, the isolation methods also add to the impact of WPI. Especially the spray drying step greatly impacts the environment, since it requires large quantities of energy that is supplied by fossil fuel. This is also the case for PPI, as shown by the higher score compared to the mild fractions. pea materials are consistently less environmentally impactful than WPI. The differential was smaller when more specific FU were used to report the single score of the materials.. For ingredients with the purpose of supplying nutritious protein, the most specific FU would be taking digestibility into account like done in the current work using DH or m-IAA values. The presented results considering protein ingredients confirmed the overall lower environmental impact of the pea plant protein fractions compared to the isolated whey protein, even when the nutritional quality is considered. This advantage might be maintained for struc- tured, plant-based products. | Mild aqueous fractionation of pea protein presents an attractive alternative to both animal-based protein (WPI) and also conventionally produced PPI as it significantly is less environmental impactful to pro- duce one kg of digestible protein, compared to the isolates. An inter- esting observation is that heating the mild ingredients had less impact on their digestibility than it had on conventional, fully refined protein isolates. We recommend producing protein-rich ingredients while using as little processing as possible, as they have overall lower environmental impact for the same nutritional effect. As the protein transition proceeds, it is clearly important to include the processing history of foods, particularly protein-rich crops, since it significantly influences both the impact of the production, and the digestibility, both negatively and positively. Therefore, instead of just referring to the origin of a protein, it is essential that chain actors also include the type of processing in their investigations. Mild pro- cessing was shown to have clear advantage over conventional process- ing of proteins into isolates. | |||||
| 889 | X. Esteve-Llorens; C. Darriba; M. T. Moreira; G. Feijoo; S. González-García | Esteve-Llorens, X., Darriba, C., Moreira, M. T., Feijoo, G. and González-García, S. (2019) 'Towards an environmentally sustainable and healthy Atlantic dietary pattern: Life cycle carbon footprint and nutritional quality', Science of the Total Environment, 646, pp. 704-715. | 2019 | Spain | the nutritional quality has been analysed through daily menus. This perspective will facilitate comparison with alternative dietary patterns. | dairy, beef, pork, poultry | seasonal foods, vegetables, fruits, potatoes, bread and cereals, chestnut, whole nuts, legumes and honey, fish, molluscs and crustaceans; ii) a moderate consumption of milk, cheese, meat (beef and pork), eggs. An abundant intake of complex sugars, fibre, polyunsaturated fatty acids, vitamins, minerals and functional components is therefore guaranteed. (fruits, vegetables, legumes, grains, dairy, meat, fish/crusta- ceans, eggs, olive oil and sweets) | cradle-to-mouth | carbon footprint. GHG emissions | nutritional quality. The Nutrient Rich Diet (NRD9.3) score was considered in this study to estimate the nutritional quality of the Atlantic diet. as a modification of the NRF9.3 index as it is not scaled to energy intake. A total of nine nutrients to encourage (protein, fibre, calcium, iron, magnesium, potassium, vitamin A, vitamin C, vitamin E) and three nu- trients to limit (sodium, saturated fat and added sugar) have been con- sidered for the estimation of the score. | The high consumption of fruits, vegetables and whole grains in the diet is closely related to the reduction of the risk of developing chronic diseases such as cancer and cardiovascular diseases, which are the main causes of death in industrialized countries. | negative | no quantitative data to state state a co-efficient | The Atlantic diet is characterised by an abundant consumption of plant-based products, as well as local and fresh products (seasonal food) with reduced cooking time. The consumption of meat (mainly beef and pork) and eggs is reasonable and olive oil is considered as the main source of fat for cooking and seasoning. The high intake of plant-based products was beneficial from environmental and nutritional approaches. The high protein intake observed is related to the outstanding consumption of fish and moderate consumption of meat (mainly beef and pork). Meat and dairy production (livestock-based items) is primarily responsible for GHG emissions at this stage (26% and 30%, respectively). Moreover, both food categories are primarily responsible for variations in the carbon footprint between different daily diets. Looking more closely at the contribution of meat production, red meat accounts for 23%, followed by white meat (1.6% pork and 1.4% chicken, respectively). Meat, dairy and fish products have the highest individual footprint, especially cheese and beef, although their quantities consumed are not as important as other foods such as vegetables or fruits, which are considered basic foods in the recommended Atlantic diet. Ac- cording to our results, daily diets with higher values of AP are associated with higher GHGs emissions. In this way, the possibility of a change in the direction of a lower consumption of animal protein is related with more sustainable diets, as mentioned in several studies in many coun- tries (Perignon et al., 2016). The total carbon footprint of the diet could be reduced by minimiz- ing the intake of livestock products in agreement with other studies. Thus, even though the ingested quantities of meat and dairy products are not very high in the Atlantic pattern, they could still be reduced, being compensated for by the intake of plant origin protein. |
According to the main results, the consumption of livestock products and shellfish is responsible for most GHG emissions (70% of the total). The basic ingredients of the AD, such as vegetables and legumes, make a relatively minor contribution (with an inpact of 30% of the total) to the total corbon footprint of 3.01 kg CO2 eq person -1 per day. with regards nutritional quality, AD has a high nutritional score (474), mainly due to the low intake of sodium, added sugars and saturated fats (nutrients to be limited in healthy diets). In general, both the carbon footprint and the nutritional index score are consistent with those of other studies on the Mediterranean diet, which has been recognised as beneficial. Therefore, it can be concluded that the AD may be recommended from a nutritional and environmental point of view, mainly due to the high intake of fish and vegetables. As final recommendations to moving dietary patterns towards more environmentally sustainable ones, the following actions should be taken into consideration: • Promote the reduction of meat and dairy products by increasing con- sumption of plant based products • Promote the consumption of local and seasonal products, which should lead to a reduction in transport activities and management, re- spectively • Reduction of red meat intake by consuming white meat such as chicken and pork • Social campaign (cultural training, special taxes for ecologic products, ...) to promote the benefits of environmental sustainable diets. |
The communication of this valuable environmental and nutritional information to consumers should be taken into account when considering strategic actions for the adoption of healthy and sustainable dietary patterns. | ||||||
| 891 | X. Esteve-Llorens; M. T. Moreira; G. Feijoo; S. Gonzalez-Garcia | Esteve-Llorens, X., Moreira, M. T., Feijoo, G. and Gonzalez-Garcia, S. (2019) 'Linking environmental sustainability and nutritional quality of the Atlantic diet recommendations and real consumption habits in Galicia (NW Spain)', The Science of the total environment, 683, pp. 71-79. | 2019 | North west Spain | The selected functional unit to report the results corresponds to the daily amount of food eaten per person, that is, the individual daily diet. the nutritional quality of both dietary scenarios (RAD and GD) has been analyzed from an average daily menu perspective rather than from a single meal evaluation, which would not provide sufficient representative information on consumer habits. | dairy, meat, poultry | 67 foodstuffs grouped into 11 different categories (i.e., fruits, vegetables, legumes, grains, nuts, dairy products, eggs, meat, fish, sweets and oils/fats), all of which are recommended ingredi- ents in the Atlantic food pyramid (Tojo and Leis, 2009) as well as in the traditional Galician gastronomy. the average daily intake of each food group (g·day−1) has been considered for evaluation to facilitate the resulting comparison with the other scenarios proposed for analysis. food categories: fruits, vegetables, legumes, grains, nuts, dairy, eggs, meat, fish, processed food, sweets and oil/fats. | cradle-to- mouth | indicator | detect the existing deviations between the current Galician diet (GD) and the traditional and increasingly relevant Recommended Atlantic Diet (RAD), allowing verifying whether current consumption patterns ensure an optimal and sustainable nutritional profile. An additional objective of this work has been to consider a sensitivity analysis to determine the effect of replacing beef with alternative sources. | carbon footprint | nutritional quality has been determined by the Nutrient Rich Diet 9.3 index and the Health gain score. This score considers the daily intake of nine nutrients to encourage (protein, fiber, calcium, iron, magnesium, potassium, vitamin A, vitamin E and vitamin C) and three nutrients to limit (total sugar, saturated fats and sodium). The following parameters have been considered for the estimation: the daily intake of two food groups (i.e., vegetables and fruits), the daily percentage of energy obtained from total fatty acids and free sugars, the daily intake of sodium and fiber and the total daily energy in- take (kcal·day−1). | to contextualize the health gain score obtained for the RAD and GD scenarios, the recommended refer- ence values of the mentioned parameters reported by the WHO (WHO, 2003) have been considered. the health gain score is the result of the ratio between the reference intake values considered for vegetables, fruits, total fatty acids, free sugars, fiber, sodium and energy and those for actual intake in both scenarios. | Positive | 45.167% reduced carbon impact when considering nutritional quality rather than mass only. | Beef-meat 4.53 kg CO2 eq·person−1·day−1 Lentils 2.63 kg CO2 eq·person−1·day−1 % difference when considering mass 53.07% Beef-meat 474 NRD9.3 Lentils 513 NRD9.3 % difference when considering nutrient quality 7.903% |
The carbon footprint of both dietary models is moderately high compared to recommended diets such as the Mediterranean one. Comparing the two scenarios, the associated greenhouse gas emissions are about 15% higher for GD than for RAD, mainly due to the higher intake of beef and dairy products. On the other hand, nutritional quality is comparatively higher for Recommended Atlantic Diet RAD than for Galician diet GD, associated with higher consumption of vegetables and fruits. Livestock products (meat and dairy products) are the main contributor to the carbon footprint. This is because there foods are most consumed but also the foods with the worst associated environmental profiles. Focusing on meat products, both scenarios have a similar CF (i.e. 1.9 kg CO2 eq and 2.2 kg CO2 eq respectively for RAD and GD), despite the fact that the amount of meat ingested is roughly double in the GD compared to RAD. The rationale behind this result is associated with beef consumption, which is similar in both scenarios (66.9 g and 56.6 g respectively in RAD and GD), being this type of meat the one with the worst associated environmental profile: 28.60 kg CO2 eq·kg−1 according to the average value reported by Clune et al. (2017). The CF associated with this amount of beef is 1.91 kg CO2 eq and 1.62 kg CO2 eq per person and day, being responsible for 42% and 31% of total GHG emissions in RAD and GD, respectively. Total carbon footprint contribution from overalll meat consumption is much lower than that from beef and veal. Beef alone accounts for about half of the total CF in RAD, and about a third in the GD. In RAD, dairy products are responsible for 16% of the total CF. In the case of GD, their con- tribution is lightly lower (15%). This is a consequence of the notable intake of dairy products in the Galician region. The higher intake of protein in GD (2.5 times higher than the RDV) is related to the remarkable consumption of meat, considerably higher than the recommended values (see Table 1). The higher intake of dairy products in GD conse- quently increases the amount of calcium ingested, being 0.2 times higher than the RDV. For the RAD scenario - Beef-meat has the highest carbon footprint at 4.53 kg CO2 eq·person−1·day−1, with an NRD9.3 score of 474. When substituting beef with other meats: Pork reduces the CF to 2.81, increases the NRD9.3 to 512. Chicken slightly increases the CF to 2.84, raises the NRD9.3 to 515. Legume substitutions show: Lentils lower the CF to 2.63, increase the NRD9.3 to 513. Peas have the lowest CF at 2.62, the highest NRD9.3 at 523. Fish alternatives indicate: Hake increases the CF to 3.08, maintains the NRD9.3 at 512. Tuna reduces the CF to 2.72, slightly increases the NRD9.3 to 515. |
The removal of beef meat in both cases results in a drastic reduction in the CF. In this sense, the highest variation in both the CF and NRD9.3 scores occurs when beef is replaced by legumes, with a reduction in the CF of about 40% and 30% for RAD and GD respectively, and an improve- ment in the nutritional quality of about 10% in both situations. On the other hand, the consideration of alternative meats reduces the CF by 40% and 30% in RAD and GD respectively, resulting in an improvement of the nutritional quality in both scenarios, around 10% for RAD and 2% for GD. Finally, the alternative of fish products also leads to an im- provement in the nutritional quality, in this case the highest one in the GD. Regarding the CF score, it is also reduced in both scenarios al- though the reduction is lower if hake is considered than tuna, which has a moderately high GHG emission factor. It could therefore be re- ported that the replacement of beef with alternative food products would be a beneficial measure both environmentally and nutritionally. | The carbon footprint is selected as an environmental indicator due to its great relevance and widespread use in related studies of dietary patterns. Consequently, the greater the amount of nutrients ingested to encourage and the smaller the amount of nutrients to limit, the higher the NRD 9.3 index is. Nevertheless, when the 9 nutrients to encourage exceed the Recommended Daily Value (RDV), they are capped to this former value, in order to avoid overesti- mation caused by overconsumption. As previously mentioned, the nutritional quality of a diet is as impor- tant as its environmental impact, whether or not it is considered a sus- tainable diet, and it is also an important concept in our time, when the growing trend towards a healthy lifestyle includes the consumption of nutrient-rich foods instead of high-calorie products (FAO, 2010). | |||
| 937 | A. Fernández-Ríos; L. Batlle-Bayer; S. Azarkamand; J. Laso; P. Fullana-i-Palmer; A. Bala; R. Puig; R. Aldaco; M. Margallo | Fernández-Ríos, A., Batlle-Bayer, L., Azarkamand, S., Laso, J., Fullana-i-Palmer, P., Bala, A., Puig, R., Aldaco, R. and Margallo, M. (2024) 'Development and application of a nutritional quality model for life cycle assessment of protein-rich foods', Sustainable Production and Consumption, 50, pp. 35-44. | 2024 | Spain | Emissions are reported per 1 kg of product | beef, dairy, poultry, pork | * **Pulses and Legumes:** * Hemp seeds * Peas * Earth seeds * Mixed beans * Lentils * Broad beans * Chickpeas * **Grains and Cereals:** * Wheat * Rice * Barley * Oats * Buckwheat * **Soy Products:** * Soy * **Nuts and Seeds:** * Flax seed * **Vegetables:** * Cassava * **Animal Products:** * Beef * Cheese * Eggs * Pork * Chicken |
unspecified | climate change - kg CO2 eq | 100 g of digestible protein (protein content multiplied by the DIAAS), and 1000qNRF1.10.2. To analyze the influence of the FU selection | To analyze the influence of the FU selection, it was first carried out a comparison of the environmental implications of shifting from a mass- based FU – 1 kg of food – to two nutrition-related FUs – 100 g of bioavailable protein and 1000qNRF1.10.2. | POSITIVE | Despite what is popularly believed, animal-based products do not always have the worst environmental performance when compared to other protein- rich foods. When burden calculated using FU of 10000qNRF1.10.2. animal based products contributed most to land, cereals most to water, and algae most to fossil resources and mineral resources. When moving from the mass-based to the protein-related FU (100g digestible protein), the ranking of foods was almost completely modified, especially for plant products. | considering BOVINE MEAT RAW: 28Kg C02 eq./kg food // 17Kg C02 eq./ 100g protein.DIAAS // 19Kg C02 eq./1000qNRF1.10.2 | The analysis revealed a drastic change in the interpretation of the GWP impacts of protein-rich products when the FU of 1 kg of product moves to 100 g of digestible protein, and a more moderate influence when this in turn is adjusted to 1000qNRF1.10.2. When moving from the mass-based to the protein-related FU, the ranking of foods was almost completely modified, especially for plant products. On the other hand, influences of moving from the simple nutrient-based FU to the complex nutrient profile model were less abrupt, although significant in some cases. For example, corn had a carbon footprint 52 % lower than flaxseeds by mass reference, whereas it was 57 % and 70 % higher per protein and qNRF1.10.2 units respectively. Likewise, spirulina rose in ranking when changing the mass reference to 100 g of protein due to its protein concentration, but dropped again when considering the overall nutritional system (from 16th to 27th) as a result of a more balanced micronutrient profile. However, there was a common negative associa- tion between GHG (greenhouse gas) emissions and conventional animal- derived products: they held the lowest positions in the ranking across all three FUs, indicating that their carbon footprints are sufficiently high to outweigh their strong nutritional profiles. A noteworthy difference emerged for eggs that remained in the middle of the list. The application of the qNRF1.10.2 model to different animal- and plant-based products, including emerging APSs, discovered that conventional bovine and porcine meat, as well as eggs, have complete nutritional profiles, reaching qNRF1.10.2100kcal scores up to 134 (burger 80 % lean beef). Results also reinforced the evidence as to why animal-derived products are so popular; in addition to having high protein content, the digestibility of its amino acids is the best compared to other foods, in some cases exceeding 100 %, e.g., ribeye roast (111 %) or burger 80 % lean pork (119 %). Moreover, vitamin B12 or cyanocobalamin, which plays an essential role in the health of the brain, nervous system and blood, is naturally present only in foods of animal origin, which gives them a better rating. plant-based products, cereals, vegetables and tubers re- ported the lowest qNRF1.10.2100kcal scores – below 70 – as well as a relatively low estimated bioavailable protein content this was mainly due to the insufficient digestibility of the IAAs, e.g., 47 % of rice or 36 % of corn. In contrast, nuts, legumes and seeds were awarded higher po- sitions in the ranking, highlighting fava bean (111), lupin seeds (93) and soy (95). In these vegetable products, DIAAS were estimated at between 75 and 91 %, with a maximum protein and fiber concentration of 36 g/100 g and 19 g/100 g respectively. Consequently, the combination of these food groups resulted in intermediate scores, between 23 and 91, with DIAAS reaching 100 % in some mixtures like pea/wheat/potato in a proportion of 25 %, 25 % and 50 % respectively, or fava bean/corn/potato (15/20/65). Quite encouraging results were discovered for emerging APSs. The qNRF1.10.2100kcal score of dried spirulina accounted for 103, boosted by its concentration in bioavailable protein, as well as its content of other micronutrients such as vitamin E or iron. Particularly surprising was the trend of insect products. While yellow mealworm (Tenebrio molitor) totaled a qNRF1.10.2100kcal score of 60, the banded cricket (Gryllodes sigillatus) score was more than twofold (179), especially driven by its vitamin B12 content (Fig. 2; yellow line), which makes it the main po- tential alternative to meat from a nutritional perspective. | Despite what is popularly believed, animal-based products do not always have the worst environmental performance when compared to other protein- rich foods. When burden calculated using FU of 10000qNRF1.10.2. animal based products contributed most to land, cereals most to water, and algae most to fossil resources and mineral resources. When focus on ecosystems health-related indicators; climate change, acidification, freshwater and marine EP, when burden calculated using FU of 10000qNRF1.10.2., Animal based products scored highest in all areas. | ||||||
| 1129 | A. Green; T. Nemecek; A. Chaudhary; A. Mathys | Green, A., Nemecek, T., Chaudhary, A. and Mathys, A. (2020) 'Assessing nutritional, health, and environmental sustainability dimensions of agri-food production', Global Food Security-Agriculture Policy Economics and Environment, 26. | 2020 | Zurich, Switzerland | dairy, beef | nuts, cultured meat, traditional crops, or insects | unspecified | metric | Cimate change, GHG emissions, biogeochemical flows e.g. eutrophication and acidification potentials, freshwater use, biodiversity loss, water scarcity and biofortification such as mineral fertilizer. | food supply's nutrient-content - (i) nutrient quantity (e.g., Nutrient-Rich Food Index (NRF) 9.3), (ii) nutrient diversity (e.g., Rao's Quadratic Entropy), and (iii) nutrient quality [e.g., Digestible Indispensable Amino Acids Score (DIAAS) and digestibility]. Nutrient indicies and included nutritents: nutrient index ONQI Macronutrients; Fiber, omega 3 (n-3) fatty acids, protein quality, fat quality; vitamins Folate, A, C, D, E, B-12, B-6; minerals K, Ca, Zn, Mg, Fe. Disqualifying nutrients Saturated fat, trans fat, sodium, total/added sugar, cholesterol; other Total bioflavonoids, total carotenoids | DALYs measures years of healthy life lost due to premature death, disability, or illness. DALYs consequent from food intake, like colorectal cancer, are directly comparable to those caused by pollution and other environmental factors such as asthma or heat-induced mortality. Other metrics include the: (i) cox proportional hazard ratio, which estimates the chance of surviving based on survival factors like food intake and other predictor variables. | no quantitative data | Agricultural and processing practices can influence nutrition and the environment by altering nutritional compositions of foods, reducing yields, and engendering environmental degradation. factors like biofortification can increase or decrease nutrient-contents in foods. | organic systems have higher land use impacts due to lower yields but lower energy use and can produce foods with higher antioxidant contents that have the potential to influence health outcomes. ASF-proteins are of a higher quality than plant-based proteins like legumes or nuts. | ||||||||
| 1130 | A. Green; T. Nemecek; A. Mathys | Green, A., Nemecek, T. and Mathys, A. (2023) 'A proposed framework to develop nutrient profiling algorithms for assessments of sustainable food: the metrics and their assumptions matter', International Journal of Life Cycle Assessment. | 2023 | Swizerland | Our case study focuses on various food groups representa- tive of a food supply | beef, pork, poultry, dairy | We selected more standard forms of cooked foods (e.g., ground beef, broiled pork chops, or roasted chicken and not bacon or sausages—the latter of which have a mul- titude of additional ingredients). For vegetables, we also included cooked forms. In total, we assessed 144 food items that we classified into 34 food groups and then into 11 larger groups for visualization purposes: fruits, vegetables, tubers, grains, fortified foods, vegetarian animal-sourced foods (ASF)— i.e., cheese, milk, eggs—, other, meat, sea- food, pulses, and nuts. | Cradle to retail | metric, impacts | We classify nutrient metrics into three main categories: namely, nutrient adequacy, nutrient diversity, and nutrient quality. Nutrient adequacy metrics measure the amount of nutrients in a food item against recommended intake values, nutrient diversity metrics measure the diversity of nutrients in a food supply or diet (e.g., Rao’s quadratic entropy, Shannon’s diversity, and modified functional attribute diversity), and nutrient quality metrics measure the quality of a specific nutrient (e.g., amino acid content and digestibility for protein quality and the glycemic index for carbohydrates). Relatedly, bioavailability is also important. For example, iron quality is broadly determined by animal versus plant sources (i.e., heme versus non-heme) and zinc absorption is hindered by anti-nutrients such as phytate. Poor nutrient quality can lead to unknown deficiencies and a lack of nutrient diversity can lead to dietary risks or agricultural resilience challenges (Green et al. 2021). Over time, our food supply has been homogenising; for example, 40% of our calories come from only three crops (FAO 2018). Additionally, diversity metrics may implicitly capture aspects of food consumption that we would otherwise ignore. Most sustainability studies only consider the adequacy category (Green et al. 2020) and, to a lesser but growing extent, protein quality. When using nutrient metrics, there are two overarching issues to consider: the choice of metric and the assumptions behind it (i.e., how the metric is applied). We conceptualise these issues in the “points of differentiation” framework. The “points” include the selection of nutrients, weighting, energy standardisation, context- and dietary-specific considerations, reference amount, across-the-board versus group-specific metrics, disqualifying nutrients, capping, processing quality, validation, and data quality. The choice of metric for the nutrient index in the impact assessment phase or n-FU can greatly influence results, as demonstrated in our case studies and previous reports (Green et al. 2021; McAuliffe et al. 2019; McLaren 2021). |
GHG emissions (kg CO2eq), water use (L), land use (m2), acidification (kg SO2eq), and eutrophication (kg PO43−eq) | We chose the NR metrics as one of the bases because the NR9 or NRF9.3 is the most commonly used index (Green et al. 2020); moreover, the NBC is also being used more frequently. The NR metrics are composed of 9 nutrients including, iron, protein, fiber, vitamin A, vitamin C, vitamin E, calcium, magnesium, and potassium. The NBC metrics include all essential nutrients for which we have data; which is the essence of the NBC. In our study, we include protein, fiber, calcium, iron, magnesium, phospho- rus, potassium, zinc, copper, selenium, vitamin C, thiamin, riboflavin, niacin, vitamin B6, vitamin A, folate, vitamin E, vitamin D and vitamin K, choline, and vitamin B12. The NRprot-sub includes nutrients relevant to non-omnivore diets (protein, riboflavin, vitamin B12, iron, and calcium)— all of these are commonly cited nutrients of concern when assessing vegan and vegetarian products for dietary substitution, however, the metric can be adapted based on pop- ulation specificities or updated scientific information regard- ing non-omnivore diets. | Nutrient metrics can address three major areas of concern for nutrition: (i) micronutrient deficiencies, (ii) undernutri- tion/hunger, and (iii) overweight/obesity. These areas are further linked to dietary non-communicable diseases (e.g., cancer, heart complications, and anemia) (WHO 2021), which dietary metrics, such as disability-adjusted life years (DALYs), can capture. Nutrient metrics can help to allevi- ate micronutrient deficiencies by weighting nutrients against deficiencies either on a population (public health needs) or individual (personalized nutrition) basis and they can also capture issues related to hunger or obesity by assessing under or over consumption of calories. Micronutrient deficiencies are primarily associated with populations in lower-income countries; however, subpopulations in high-income countries are at risk as well. For example, increasing iron and iodine deficiencies in reproductive women are of concern (Afshin et al. 2019). Moreover, some studies argue that we are likely underestimating deficiencies across all countries due to a lack of data (Hawkes et al. 2020; Hossain et al. 2020). Nevertheless, while non-omnivores should watch their protein intake, few populations need sig- nificantly more protein than currently consumed; what is of greater need is increased intakes of micronutrients associ- ated with ASF like zinc and iron. Nevertheless, pertinent cases for a single-nutrient analysis include examining a specific population deficient in this nutrient or comparing production systems under different management practices that are supposed to influence the amount of this nutrient in a certain food. | combined sustainability results, we are interested if there is a statistical difference in environmental results from before and after the use of a specific nutrient-based FU, and this is determined by the Wilcoxon signed rank test. | positive | NRprot-sub metric (specific nutrients of concern for non-omnivores) compared to generic nutrient metrics applicable to all populations and contexts - ASF foods like meat, vegetarian ASF (e.g., eggs and cheese), and seafood rank much higher than plant- based foods, which do relatively worse under the NRprot-sub metric. | no quantitative data | There appears to be a relatively smaller variation in rankings for nutritionally-invested environmental impacts when compared to differences for the nutrient indices. The choice of metric has a considerable impact on certain food groups such as fruits, fortified foods, pulses, vegetables (except in the case of land use), and tubers. Vegetables have much lower land use impacts; therefore, variations in scores of nutrient indices have a lower influence on results. Likewise, “points” have little effect on high-impacting food groups like meat when concerning GHG emissions, land use, acidification, and eutrophication because the environmental impacts are much higher in comparison to other foods that the nutrient density does not affect relative quintile rankings. For example, beef has a quintile ranking of 4 regardless of the metric used, lamb and mutton only moved to a more favorable quintile ranking with one metric. On the other hand, milk which has moderate environmental impacts on a kg basis moves between quintile rankings of 0 and 3 depend- ing on the metric used. Weighted metric - seafood and nuts higher nutrient densities, public policy communication would emphasise these food groups to address deficiencies. Tubers and vegetables have positive quintile ranking shifts, categorised into more nutrient dense food groups within the weighted metric. Energy standardised - fruit, seafood and vegetables higher nutrient densities when energy standardised, reflecting lower energy density per calorie. Nuts score worse when energy standardised. NRprot-sub metric (specific nutrients of concern for non-omnivores) compared to generic nutrient metrics applicable to all populations and contexts - ASF foods like meat, vegetarian ASF (e.g., eggs and cheese), and seafood rank much higher than plant- based foods, which do relatively worse under the NRprot-sub metric. Fortified foods also score as more nutrient dense with the dietary-specific metric. This has implications when recommending food items to improve health based on if someone is a pescatarian, vegetarian, or vegan. Pulses also have a high nutrient density with the NRprot-sub, but due to their already high nutrient density with the generic metrics, they do not shift rankings under this “point. When comparing NR_A and NR_D fruits, vegetables, and pulses have strong and posi- tive quintile shifts because high LIM scores penalize the over- all nutrient density of groups such as meat that had higher nutrient density scores with the NR_A. The high LIM of nuts did not impact nutrient density scores as intensely as it did for the ASF foods. When more nutrients are included, meat and seafood have relatively higher nutrient density scores; additionally, when energy standardised, vegetables and fruits score relatively worse on an absolute basis. Despite the positive and high correlations demonstrating that these are similar in absolute terms, with respect to ranking shifts, grains, vegetarian ASF, and seafood move to more nutrient dense quintiles, on average, when more nutrients are included. It should be noted that these comparisons are not complete. We are missing many health promoting ingredients that fruits and vegetables confer like antioxidants. |
When energy standardised, there is a significant difference between nutritionally-invested environmental impacts on a capped (NR_H) and uncapped basis (NR_G) for all impact categories. Overall, it appears that the influence of “points” was less apparent for nutritionally-invested environmental impacts than for nutrient indices alone. Assessing trade-offs across nutritional and environmental dimensions can elucidate results imperative in the transition to a more sustainable food system by benefiting farmers, industry actors, policymakers, and consumers. | Future work should more closely examine differences within food groups and evaluate the influence of “points” with respect to validation; for example, is the application of energy standardisation in nutrient metrics important for health outcomes? Going forward, major areas to explore include the role of disqualifying nutrients, the selection of nutrients in certain contexts, the role of capping for particular nutrients based on population deficiencies or on fat versus water soluble nutrients, the role of food functionality, and finally, interpretation and data quality (e.g., uncertainty analyses). Food functionality includes aspects of interaction factors, bioavailability, and processing. More research into single nutrients versus ratios and DRI values reflective of anti-nutrients and overall bioavailability, as done with iron and zinc, can be useful. DRIs related to polyphenols and antioxidants can also be developed to better illustrate the health value of certain foods. Moreover, many metrics do not include the influence of low-quality processing (which is sometimes referred to as ultra-processing) on nutrients and the subsequent effects on health. Additionally, the role of fortification vehicles needs to be addressed (e.g., is it justified to fortify foods that are high in disqualifying nutrients? Does this result in burden shifting from one health issue to another?) Finally, selecting nutrients specific to the dietary context or population needs is imperative because large-scale solutions do not always scale down to regional or local levels. Recognising that populations have different challenges and solutions is the next step toward addressing the sustainability crisis. The most illustrative example of the need for contextual dependence is the case of animal meat; while environmentally detrimental (particularly ruminant meat) on a global scale, the production of animal meat is needed for certain subpopulations with limited access to protein-rich alternatives. Even in high-income countries, there are still massive disparities between low-income and minority populations compared to their wealthier counterparts in terms of food accessibility and associated diseases that arise with their consumption (e.g., obesity, cardiovascular complications, and nutrient deficiencies). However, such nuances are only visible if regionally explicit or non-aggregated data is available and used. Accordingly, we need metrics reflective of these nuances. N-LCA can be helpful for many actors, but it is still in need of further development. Future work should explore these “points” for various foods and in relation to other environmental impacts. |
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| 1131 | A. Green; T. Nemecek; S. Smetana; A. Mathys | Green, A., Nemecek, T., Smetana, S. and Mathys, A. (2021) 'Reconciling regionally-explicit nutritional needs with environmental protection by means of nutritional life cycle assessment', Journal of Cleaner Production, 312. | 2021 | Europe | meat, dairy, poultry | unspecified | METRIC, IMPACT CATEGORIES | GHG emissions, water use, eutrophi- cation, and land use. | For nutritional adequacy, we use metrics from the Nutrient Rich Food Index (NRF) family; namely, the regionally-explicit NRF21.2 and the NRFpro- tein-sub score. The NR is comprised of Protein, Calcium, Zinc, Folate, Vitamin C, Iron, Vitamin A, Carbohydrates, Potassium, Phosphorus, Copper, Fiber, Riboflavin, Vitamin B6, Thiamin, Niacin, Vitamin B12, Polyunsaturated fat, Choline, and Manganese, and Magnesium. The LIM is comprised of Sodium and Saturated fat. For nutrient adequacy metrics applied at the supply level, if quali- fying nutrient amounts exceed 100% of daily needs the metric is capped at 1 to ensure that countries do not receive higher scores for an excess of nutrients that do not provide additional health benefits (Drewnowski et al., 2018). At the food product level, we do not cap nutrient amounts because excess nutrients in one food item can compensate for a lack of nutrients in another (Green et al., 2020). Studies, however, should consider certain aspects when using uncapped NRF21.2food scores. Uncapped metrics can obscure nutrient density differences between food groups (i.e., an uncapped value over 100 does not indicate that a food group meets all nutrient requirements) and the dominance of one or two nutrients in a food item can affect the relative sustainability rankings. for meat products, poultry does the best on a capped basis because, on average, it has higher values for many nutrients. However, on an uncapped basis, bovine meat ranks highest but this results from its high vitamin B12 content because for most other nutrients, poultry has similar or higher values than bovine meat. This shows that food items with one or two nutrients present in large quantities can receive higher NRF scores despite being less nutrient dense than other foods. Here, the role of local context is very important. For example, if the nutrient in question is one for which severe nutrient deficiencies exist (e.g., calcium or vitamin A— as shown in Fig A4), then the higher score would be warranted. However, if the nutrient has an adequacy ratio of one or greater (e.g., carbohydrates, vitamin B6— as shown in Fig A4) then the higher NRF score would be misleading. Future studies should explore these options more in-depth. we developed the NRFprotein-sub score (Eqn. (4)) because metrics are needed in LCA to address questions specific to the debate of animal- and plant-based protein. | we illustrate how sustainably produced foods can alle- viate micronutrient deficiencies in an environmentally-responsible manner. Nutrient deficiencies that are common in most countries include calcium, vitamin A, potas- sium, and choline. Our adequacy values are based on food supply and ignores supplementation and bioavailability; the former does and can alleviate many deficiencies. On the other hand, minerals like zinc and iron would have much higher deficiency values if bioavailability were accounted for. As discussed, within the meat group, bovine meat receives the highest uncapped NRF21.2food score because of its vitamin B12 content (Fig A2), but poultry does better on a capped basis because on average (i.e., excluding B12) it is more micronutrient dense. Arguably, this higher score is highly relevant in countries where there are vitamin B12 de- ficiencies but perhaps less so in areas in which there is adequate vitamin B12. When only considering the dimensions of nutrition and environment, including disqualifying nu- trients is needed to avoid attributing more favorable environmental impacts to less nutrient-dense foods (e.g., OFS); however, when including the health dimension, disqualifying nutrients should be excluded from the FU and used in the impact assessment phase. the ‘most sustainable’ product can change based on data and methodological choice. This has implications for the communication of research results to policy makers and the public— and this will then determine how systems. | positive | When accounting for nutritionally-invested environmental impacts with n-LCA, we see changes in relative environmental footprint rankings. For example, on a kg basis, OFS has a lower environmental footprint than other food groups like meat; however, when nutrition is accounted for, OFS does the worst environmentally | Meat • GHG (kg CO₂eq): 1 (kg), 1 (NRFfood) • Water Use (L): 1 (kg), 1 (NRFfood) • Eutrophication (g PO₄³⁻ eq): 1 (kg), 1 (NRFfood) • Land Use (m²): 1 (kg), 1 (NRFfood) • Arable (m²): 1 (kg), 1 (NRFfood) • Pasture (m²): 1 (kg), 1 (NRFfood) • NRF scaled: 1.00 Dairy and Eggs • GHG (kg CO₂eq): 0.279 (kg), 0.371 (NRFfood) • Water Use (L): 1.651 (kg), 2.193 (NRFfood) • Eutrophication (g PO₄³⁻ eq): 0.355 (kg), 0.471 (NRFfood) • Land Use (m²): 0.405 (kg), 0.538 (NRFfood) • Arable (m²): 0.539 (kg), 0.716 (NRFfood) • Pasture (m²): 0.231 (kg), 0.307 (NRFfood) • NRF scaled: 0.75 Legumes, Nuts, and Seeds • GHG (kg CO₂eq): 0.09 (kg), 0.084 (NRFfood) • Water Use (L): 0.727 (kg), 0.677 (NRFfood) • Eutrophication (g PO₄³⁻ eq): 0.19 (kg), 0.176 (NRFfood) • Land Use (m²): 0.165 (kg), 0.153 (NRFfood) • Arable (m²): 1.149 (kg), 1.069 (NRFfood) • Pasture (m²): N/A • NRF scaled: 1.07 Oils, Fats, and Sugars • GHG (kg CO₂eq): 0.21 (kg), 1.866 (NRFfood) • Water Use (L): 0.834 (kg), 7.427 (NRFfood) • Eutrophication (g PO₄³⁻ eq): 0.317 (kg), 2.82 (NRFfood) • Land Use (m²): 0.178 (kg), 1.588 (NRFfood) • Arable (m²): 1.244 (kg), 11.075 (NRFfood) • Pasture (m²): N/A • NRF scaled: 0.11 |
new tradeoffs are revealed when measuring environmental impacts on a nutritional basis versus a mass basis. nutritional and environmental differences between pig, goat and sheep, poultry, and bovine meat. Overall, regional variations obscure differences between product groups, and groupings are not well defined. For the NRF21.2food of meat products, there are high regional variations for bovine, pig, and poultry meat. On average, bovine meat scores the highest followed by the goat and sheep group, however, this is a result of their high vitamin B12 content (Fig A2). Poultry meat scores the next highest and pig meat is the least nutrient dense. While bovine and goat and sheep product groups have higher nutritional profile scores, they also have higher footprints on average for all environmental categories. owever, cheese has higher envi- ronmental impacts than eggs and milk. Table 3 demonstrates that different tradeoffs are revealed between food groups when comparing impacts measured on a purely kg basis versus when they are measured on a nutritional basis. For example, for eutrophication, under a FU of 1 kg, RT have the lowest potentials, however, with a nutritional FU (n-FU) — in this case, the NRF21.2food— vegetables rank the lowest. For meat items in Table A2, the NRF21.2food FU has little influence on the relative sustainability rankings. For example, despite the higher nutrient density of bovine meat, it still has the highest GHG and eutrophication footprints. Overall, this table suggests that if meat consumption is needed to meet amino acid or other nutrient requirements, the better option might be poultry because it has the lowest nutritionally- invested environmental footprints for all categories excect arable land use. With respect to the nutritional dimension, animal- based foods are better sources of protein quality, vitamin B12, ribo- flavin, calcium, and iron quality; heme iron, predominately found in animals, is better absorbed by humans than nonheme iron which is common in plants | When accounting for nutritionally-invested environmental impacts with n-LCA, we see changes in relative environmental footprint rankings. For example, on a kg basis, OFS has a lower environmental footprint than other food groups like meat; however, when nutrition is accounted for, OFS does the worst environmentally (Table 3). | Currently, mass-based FUs are more common, but these do not reflect the nutritional benefits that foods provide for society. Integrating nutrition into the functional unit (FU) to estimate nutritionally-invested environmental impacts will help actors compare impacts in a less biased manner. In n-LCA, NRF metrics are the most commonly used type of nutrient index (Green et al., 2020), which is an established measure for ranking food items based on their nutrient content. From an LCA perspective, energy standardization is needed at the food product level because it increases the comparability of foods. Meats and fruits confer different outcomes on the human body because they have dissimilar nutritional compositions and consuming 100g of spinach is not the same as consuming 100g of pig. Therefore, energy standardization is needed to compare food products. Understanding the interconnectedness between nutritional and environmental dimensions of food production is crucial to the progress of sustainability initiatives as the impacts of climate change, environ- mental degradation, and hidden hunger become ever-present in our daily lives. Overall, this inter- connectedness and regional variability make optimizing ‘the global food system’ a difficult endeavor. Newer challenges to improving our agri-food production system Nutritional life cycle assessment integrates nutrition into environmental life cycle analysis to comprehensively account for agri-food sustainability challenges including micronutrient deficiencies, nutrient diversity, and environmental impacts like climate change or freshwater scarcity, when compared to traditional life cycle assessment. Newer challenges to improving our agri-food production system include increased recognition for producing nutritious foods as opposed to enough food. For such nutrition security analyses, actors need proper metrics to assess nutritional diversity and nutritional adequacy. When including disqualifying nutrients in nutrient indices, there is a risk the FU will be negative (Saarinen et al., 2017), and there is a much higher risk this will occur for energy dense foods such as oils, animal fats, and butters. In such instances, the environmental impacts will be negative, which implies an environmental benefit (Saarinen et al., 2017); this can be confused with environmental impacts that are actu- ally negative. However, the NRFprotein-sub metric does not include protein quality [e.g., Digestible Indispensable Amino Acid Score (DIAAS)], and its incorporation would provide even greater insights, by showing a greater stratification between foods, because, quite often, animal-based proteins have a better digestibility and are a more complete source of amino acids. |
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| 1274 | M. Herrmann; E. Mehner; L. Egger; R. Portmann; L. Hammer; T. Nemecek | Herrmann, M., Mehner, E., Egger, L., Portmann, R., Hammer, L. and Nemecek, T. (2024) 'A comparative nutritional life cycle assessment of processed and unprocessed soy-based meat and milk alternatives including protein quality adjustment', Frontiers in Sustainable Food Systems, 8. | 2024 | Swizerland | beef, poultry, dairy | cooked soybeans, tofu, soy drink, and a processed soy-based meat analogue (SBMA). chicken meat, beef, and cow milk. | cradle-to-gate | Land occupation, CED, EUTR-FW, WATER SCARCITY, GWP100 | (a) protein quality and (b) nutrient density. Digestible Indispensable Amino Acid Score (DIAAS). Nutrient Rich Food (NRF) index - adapted NRF score was used for nutrient density. The NRF score is calculated as the arithmetic difference between the positive and negative nutrient sub-scores and multiplied by 100 (Eq. 1). The positive sub-score is based on a variable number n of beneficial nutrients (NRn), whereas a maximum of three disqualifying nutrients (saturated fat, added sugar, and sodium) are considered in a second sub-score (LIMn), implying the need to limit their consumption. The NRn was adapted for protein-rich foods and included seven favourable nutrients: protein, fibre, and (mono-)unsaturated fatty acids, calcium (Ca), iron (Fe), zinc (Zn), and cobalamin (vitamin B12), as these are nutrients of concern in plant-based diets critical nutrients in the diet of the Swiss population. | positive | when considering protein functional unit rather than braoder.nutrient based, chicken enviornmental impact decreases whereas SMBA, Tofu, soybeans and soydrink increases. | GWP of beef and cow milk per unit of nutritional value. GWP of beef and cow milk per unit of NRprot7 Chicken meat 25% SBMA 6% Soydrink UHT 11% GWP of beef and cow milk per unit of qc-protein Chicken meat 19% SBMA 10% Soydrink UHT 23% |
The increased food intake of soy-based alternatives resulted in more calories, more saturated fatty acids, and more sodium, except for the sodium content of cooked soybeans and the total caloric intake in the case of soy drink. However, all of them were high in fibre, and the soy-based meat alternatives had higher levels of calcium and iron than the meat references (beef, minced). The zinc content was between chicken and beef. Soy drink was high in fibre, iron, and zinc, but not in calcium. All the soy-based alternatives lacked vitamin B12. In animal-based products, vitamin B12 was present in small amounts, and cow milk was high in calcium, whereas fibre was completely absent in meat and milk. Lower environmental impact came at the cost of higher caloric intake in the case of soy-based meat alternatives but not for soy drink. Despite higher food intake, soy drink was lower in both, environmental impact and calories, suggesting a win–win situation. Although soy drink may be lower in environmental impact, but unfortified, it was worse as a calcium source compared to cow milk. Soy-based meat alternatives were higher in calcium and lower in environmental impact compared to the animal-based references. Beef and chicken meat were lower in monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA) and lower in saturated fatty acids compared to the soy-based meat alternatives. Soy drink was favourable for saturated fat and PUFA but not for MUFA compared to the reference. Soy-based meat alternatives generally perform better than beef per gram of qc-protein but may have higher land occupation than chicken. Soy drink is favorable compared to cow milk in all environmental impact categories studied. Soybeans, potatoes, and rapeseeds significantly contribute to the environmental impact of soy-based meat alternatives (SBMA). Processing is more relevant than raw materials for certain impact categories. Amongst the soy-based products, SBMA, the most processed option, exceeded the CED, Water-scar, and Eutr-fw, compared to the minimally processed soybeans (cooked soybeans) and tofu. Compared to the reference (beef, minced), all soy-based meat alternatives performed better per gram of qc-protein. This was also true for soy drink. Apart from beef, chicken meat was presented as a meat reference with a lower environmental impact, which outperformed the soy-based products in terms of Land-occ but was worse than beef in terms of Water-scar potential. Contribution analysis showed that the environmental impact of chicken meat depends mainly on the feed composition (Wolff et al., 2016), which can change the result for the better (Water-scar) or even for the worse (Land-occ, GWP100, CED) when other feed sources are considered. In summary, the soy-based meat alternatives performed better than beef, but our modelled SBMA had higher Land-occ than chicken meat and a higher environmental impact compared to the less processed soy-based options. Soy drink was favourable compared to cow milk in all cases. | nutritional LCA (n-LCA) showed that the environmental impact of all soy-based meat alternatives was 4–20 times lower than that of beef, especially when locally sourced soy was used. The differences were smaller when compared to chicken meat. All soy-based products showed lower DIAAS compared to animal products, but the results from the combined n-LCA were always less favourable for animal products in this case study. comparisons within the soy-based alternatives revealed a lower environmental impact of the minimally processed products. The higher protein quality and quantity of the processed SBMA were not sufficient to offset its higher environmental impact in this case study. SBMA also contained highest level of sodium and saturated fatty acids, highlighting the need for careful food formulation. Soy-based meat alternatives require a higher food intake to supply 1g of qc-protein compared to animal products, resulting in more calories, saturated fatty acids, and sodium (except for cooked soybeans). However, they are also higher in fiber, calcium, and iron. Soy drink offers a win-win by being lower in environmental impact and calories, but is a worse source of calcium than cow's milk. All soy-based alternatives lack vitamin B12. Beef and chicken have lower levels of mono- and polyunsaturated fatty acids and saturated fatty acids. The SBMA has the highest disqualifying nutrient density score (LIM2) compared to beef, and soy drink has a higher score for beneficial nutrients (NRprot7) than cow milk. The meat reference, beef, had the highest beneficial sub-score, whilst for the milk reference, this was not the case (Figure 4). Additionally, soy drink was lower in sodium and saturated fatty acid content than cow milk, as described in the LIM2 sub-score. Amongst the plant- based meat alternatives, only tofu and cooked soybeans showed lower LIM2 scores than beef, although not lower than chicken meat. Whereas tofu and cooked soybeans were low in sodium and saturated fat compared to beef, SBMA was higher in these disqualifying nutrients. The higher density of disqualifying nutrients in SBMA should be taken into consideration when assessing the overall evaluation of this product. In this evaluation, soy-based products, including SBMA, emerged as more efficient in nutrient provision whilst minimising environmental impact compared to the references and chicken meat (Figure 5B). Amongst the soy-based meat alternatives, the less processed options held an advantage in the environmental impact categories Water-scar, Eutr-fw, and Acid-terr, compared to SBMA, and cooked soybeans demonstrated one of the lowest GWP100 (Figure 5A). Again, soy drink as an alternative to milk performed better in all environmental impact categories compared to cow milk. The cooked soybeans, tofu, and SBMA were less nutrient dense than beef but not chicken meat (Figure 4). The high protein content and protein quality in chicken meat did not compensate enough for the absence of other beneficial nutrients, such as dietary fibre and (poly-)unsaturated fatty acids. | ||||||||
| 1298 | D. A. Hobbs; C. Durrant; J. Elliott; D. I. Givens; J. A. Lovegrove | Hobbs, D. A., Durrant, C., Elliott, J., Givens, D. I. and Lovegrove, J. A. (2020) 'Diets containing the highest levels of dairy products are associated with greater eutrophication potential but higher nutrient intakes and lower financial cost in the United Kingdom', European Journal of Nutrition, 59(3), pp. 895-908. | 2020 | United Kingdom | dairy | milk, cheese, yogurt, dairy desserts | unspecified | greenhouse gas emissions (GHGE), eutrophication and acidification potentials | Alternative Healthy Eating Index (AHEI-2010) | blood pressure | factoring energy intake GHGE per unit nutrient = gCO2e per day/ ug, mg or g nutrient per day |
negative | Increased dairy intake has a negative impact on GHGE, eutrophication and acidification. | GHGE Kg CO2 eqv / g dairy/day Non-adjusted values show a progression from 3.7 (Q1) to 4.6 (Q4). The p-value (<0.0001) for non-adjusted values indicates a statistically significant difference in GHGE between the lowest (Q1) and highest (Q4) dairy consumption quartiles. Eutrophication g N eqv / g dairy/day Non-adjusted values range from 46.9 (Q1) to 65.3 (Q4). The p-value (<0.0001) indicates a statistically significant difference between Q1 and Q4. Acidification g SO2 eqv / g dairy/day Non-adjusted values go from 33.3 (Q1) to 40.0 (Q4). The p-value (<0.0001) for non-adjusted values shows a statistically significant difference between Q1 and Q4. |
When controlling for age, sex and total energy intake (kJ), there was a significant difference in eutrophication potential across increasing quartile of dairy intake (non-adjusted and adjusted values P < 0.0001) with the diets containing the highest amount of dairy (Q4) having significantly higher eutrophication potential (29%) (all P < 0.0001) compared with the diets containing the lowest amount of dairy (Q1, Table 4). For GHGE and acidification potential, there was a significant difference across dairy quartiles in the non-adjusted model only (both P < 0.0001) with the diets containing the highest amount of dairy (Q4) having significantly higher GHGE and acidification potential (both P < 0.0001) compared with the diets containing the lowest amount of dairy (Q1). However, the significance was lost when the analysis was adjusted for energy intake, age and gender (GHGE; P-trend = 1.00 and acidification potential; P-trend = 0.045, Table 4). Food groups contributing most to GHGEs in the total population were: Meat and meat products (24%) Vegetables and potatoes (16%) Dairy products (15%) Cereals and cereal products (14%) Alcohol (11%) _x000B_ Dairy products had the largest impact on GHGEs across quartiles, with the highest dairy consumption group (Q4) producing 376% more GHGEs from dairy than the lowest consumption group (Q1). Fruit consumption was also associated with higher GHGEs in Q4 compared to Q1. Meat and meat products, alcohol, and non-alcoholic beverages were associated with lower GHGEs in Q4 compared to Q1. Higher dairy intake (Q4) was associated with significantly higher intakes of essential nutrients, including energy, carbohydrates, protein, saturated fat, cis-MUFA, PUFA, calcium, magnesium, potassium, iodine, zinc, thiamine, riboflavin, vitamin B12, folate For the nutrients that were significantly different across dairy quartiles (vitamin B12, riboflavin, calcium, iodine, folate, zinc, magnesium, iron and potassium), the percentage of subjects below the LRNI was less in Q4 compared with Q1 Adults consuming between 274 and 1429 g/day dairy had significantly higher intakes of essential micronutrients including calcium, iodine, vitamin B12 and riboflavin, supporting previous studies Higher dairy diets (Q4) were associated with better overall diet quality, as measured by the Alternative Healthy Eating Index (AHEI-2010). The diets associated with higher dairy intake in the UK population contained more high-fibre breakfast cereals, vegetables, fruit, tea, coffee and water, and lower intakes of alcohol, chips, and soft drinks (not low calorie) compared with the lower dairy diet. Intakes of these foods are associated with a higher diet quality; however, other components of the higher dairy diets were associated with lower diet quality such as higher intakes of sugar, preserves and sweet spreads. Nutritional adequacy, particularly for protein, calcium and iodine (+ 18 g, + 533 mg,+95 g, respectively, all P < 0.0001) and AHEI-2010 (P < 0.0001) were significantly higher and systolic BP (− 2 mmHg, P = 0.019) was significantly lower for the higher-dairy diets (Q4, 274–1429 g/day dairy), compared with diets containing lower dairy (Q1, 0–96 g/ day dairy). After adjusting for age, sex, BMI, and energy intake, individuals in Q4 had significantly lower systolic blood pressure (SBP) compared to those in Q1 (2 mmHg lower, P = 0.028). Diastolic blood pressure (DBP) also showed significant differences across quartiles of dairy intake._x000B__x000B_An increasing number of population studies have also shown inverse associations between dairy product consumption and blood pressure, particularly in subjects with hypertension |
Diets in Q4 (high dairy) had lower financial costs (-19%, P < 0.0001) compared to Q1 (low diary). Q4 diets had the greatest eutrophication potential compared to Q1 (+29%, P < 0.0001) Environmental (GHGE) and financial costs per unit of several nutrients (riboflavin, zinc, iodine, magnesium, calcium, potassium) were lower in Q4 than Q1 Diets with the highest dairy content had higher nutrient composition, better diet quality, were associated with lower BP and financial cost, but with higher eutrophication potential. |
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| 1447 | R. Katz-Rosene; F. Ortenzi; G. A. McAuliffe; T. Beal | Katz-Rosene, R., Ortenzi, F., McAuliffe, G. A. and Beal, T. (2023) 'Levelling foods for priority micronutrient value can provide more meaningful environmental footprint comparisons', Communications Earth & Environment, 4(1). | 2023 | Europe | dairy, beef, poultry, lamb, mutton, pork | unspecified | mass, energy, and a functional unit developed using the PMV scoring system. PMV was chosen as an example to illustrate the importance of considering the con- tribution of nutrient-dense foods to global diet quality, and their essential role in reducing the global prevalence of micronutrient deficiencies, anemia, and child growth/underdevelopment | land use occupation (m2 × year), carbon footprints (kg CO2-eq), water scarcity (litres), acidification footprints (grams of sulphur dioxide equivalents; SO2-eq), and eutrophication footprints (grams of phosphate equivalents; PO43-eq),. land use, GWP100, water use, acidification potential, and eutrophication potential. | priority micronutrient value (PMV) | This presents a challenge for sustainable agri-food policy at both the population and individual levels, as the promotion of food substitution for the sake of environmental sustainability may come at the expense of greater nutritional risk, particularly for more vulnerable populations51. This is important for micronutrient deficiencies such as iron, zinc, and folate deficiency, which are surprisingly common worldwide, but especially in low- and middle-income countries and among women of reproductive age and other groups with increased nutrient requirements (e.g., infants and young children, pregnant and lactating women)51. Nevertheless, developing a functional unit based on PMV is useful in enabling a more meaningful comparison of the relative environmental footprints of different foods in contexts where deficiencies in those nutrients represent a notable public health burden. | exemplar functional unit to illustrate how the environ- mental footprints of a given food vary when considering priority micronutrient value (PMV) compared to a fixed quantity of kilograms, calories, or protein. iron, zinc, folate, calcium, vitamin A, and vitamin B12. PMV as a functional unit supports more geographically representative impact assessments of the environmental footprints of foods in nutritional contexts where priority micronutrients are particularly lacking. However, functional units deployed as mass, energy, or protein do not necessarily provide nutritionally relevant food comparisons1. target PMV (an average of one-third of recommended intakes of vitamin A, folate, vitamin B12, calcium, iron, and zinc for adults ≥25 years). | Positive | Introducing per 1000 kcal and priority micronutrient value rather than mass based (per kg) functional unit makes beef more favourable in terms of GHG emissions and land use. | priority micronutrient value (PMV) - target PMV (an average of one-third of recommended intakes of vitamin A, folate, vitamin B12, calcium, iron, and zinc for adults ≥25 years). GHG emissions Beef 163 kgCO2eq/kg Beef 60 kg CO2eq/1000kcal Beef 6.36 kgCO2eq/PMV Land use Beef 184.7 M2/year/1kg Beef 67.7 M2/year/1000kcal Beef 17.7 M2/year/PMV |
The implications are especially acute for guidance around the consumption of ASFs: on the one hand, there is strong evidence that moderating meat intake and encouraging minimally processed plant-rich diets globally would support climate change mitigation31,57, and could result in positive health outcomes at the population level1,32. On the other hand, nutrient-dense ASFs are an important source of high-quality protein, long-chain omega- 3 fatty acids, unique beneficial bioactive compounds, and bioavail- able micronutrients commonly lacking in diets globally, such as iron, zinc, vitamin B12, and calcium20,58. Thus, ASFs make an important contribution to improving diet quality and achieving nutrient adequacy worldwide, particularly in low- and middle- income countries. Land use - liver (which is highly micronutrient dense), goes from being the third and second highest land user per unit mass and energy, respectively, to being among the top 10 lowest land users per target PMV. Functional unit becomes contextualised by the priority micronutrient value of the food in question. When assessing environmental footprints based on PMV some ASFs become more comparable to their common plant- based protein alternatives. Eggs have a carbon footprint 48% higher than tofu per unit mass, and 19% higher per unit energy, but when assessed based on PMV, eggs have a carbon footprint 31% lower than tofu. Additionally, the divergence between common protein food substitutes is reduced when carbon footprints are assessed using the target PMV. For example, the global mean carbon footprint of cheese is about eight times larger than that of tofu per kg of retail weight, but only about 1.8 times larger once recalculated per target PMV. Similarly, the global mean carbon footprint for beef (averaged across dairy herds and beef-specific herds) is 21 times larger than tofu when based on mass yields; whereas, when computed per target PMV, the carbon footprint for beef is just five times larger. When calculated per target PMV, the carbon footprint for liver is comparable to some of the foods with the lowest carbon footprints (tree nuts and peas). For example, while beef has the highest mean carbon footprint amongst ASFs in this selection per PMV (at 6.36 kg CO2-eq), its best-in-class variant (at 2.51 kg CO2-eq) would outperform the average selection of most other ASFs, including farmed crustaceans (4.81 kg CO2-eq), poultry (4.54 kg CO2-eq), farmed fish (3.99 kg CO2-eq), lamb and mutton (3.98 kg CO2-eq), pork (3.37 kg CO2-eq), and a number of PSFs, including rice (3.52 kg CO2-eq), cassava (3.25 kg CO2-eq), and tomatoes (3 kg CO2-eq). This highlights the need for caution when basing food sustainability decisions on a comparison of globally averaged LCA results. For instance, nuts rank consistently as one of the least GHG-intensive foods regardless of which functional unit is used, but rank much less favourably when it comes to their water footprint (third highest per target PMV, at 1161.6 L)—about six times worse than beef (at 199.5 L). |
Any attempt to capture foods’ nutritional and environmental impacts by using a single-value score will be limited by its inevitable simplification of the food system’s multi-dimensionality. PMV—is still insufficient as a comprehensive nutritional metric for comparing food environmental footprints more broadly. While considering each food’s combined density in iron, zinc, calcium, folate, vitamin A, and vitamin B12 is important to address micronutrient malnutrition, it is important to note that PMV is just one aggregate indicator of nutritional value. Essential amino acids, essential fatty acids, other essential micronutrients, and non-essential but nevertheless beneficial compounds like fiber, phytonutrients, and bioactive compounds—as well as nutrient ratios and the type of processing of foods—also contribute to nutritional quality and play an important role in health and disease. | One food commodity may have a high GWP100 and a low eutrophication potential, whilst another may have the reverse, meaning a researcher needs to determine which is more problematic for the geographical boundary under investigation to provide regionally meaningful recommendations on which pollution potential, and primary sources thereof, require more urgent mitigation (e.g., reducing enteric CH4 may be the top priority in the case of ruminants, while NH3 may require more attention in the context of pig systems). | |||||
| 1458 | E. Kesse-Guyot; F. Berthy; J. Berlivet; E. Perraud; M. Touvier; S. Hercberg; B. Allès; D. Lairon; F. Mariotti; C. Couturier; H. Fouillet; P. Pointereau; J. Baudry | Kesse-Guyot, E., Berthy, F., Berlivet, J., Perraud, E., Touvier, M., Hercberg, S., Allès, B., Lairon, D., Mariotti, F., Couturier, C., Fouillet, H., Pointereau, P. and Baudry, J. (2024) 'Alignment between greenhouse gas emissions reduction and adherence the EAT-Lancet diet: A modeling study based on the NutriNet-Santé cohort', Science of the Total Environment, 951. | 2024 | France | dairy, red meat, processed meat | fruits and vegetables, nuts, legumes, whole-grain food, milk and dairy products, fish and seafood and added fat and six components refer to food cate- gories whose intakes should be limited: red meat, processed meat, sweet food, sweet-tasting beverages, alcoholic beverages. | LCA at farm level, conventional and organic farms. | Global Warming Potential (GWP) over a 100-year time horizon (GWP100) in kg of CO2 equivalents (CO2eq)), cumulative energy demand (MJ), and land occupation (m2) | The nutritional composition of each item was determined by combining the published NutriNet-Sant ́e food composition table (>3500 items) (Nutrinet-Sant ́e, 2013) with the FFQ-items as the weighted mean of the nutritional content of all corresponding foods. Weights were the frequencies of consumption in the overall NutriNet-Sant ́e population.We constructed an EAT-Lancet score based on the universal healthy diet definition (Willett et al., 2019) created in 2019. Supplemental Table 1 presents the components and cut-offs of the EAT-Lancet diet for 14 food groups, including wholegrain grains, vegetables, fruits, and dairy products, among others. PNNS-GS2 (Programme National Nutrition Sant ́e-Guidelines Score) - It is based on 13 components: seven refer to healthy foods: fruits and vegetables, nuts, legumes, whole-grain food, milk and dairy products, fish and seafood and added fat and six components refer to food cate- gories whose intakes should be limited: red meat, processed meat, sweet food, sweet-tasting beverages, alcoholic beverages. | negative | High compliance with the eat lancet diet indicated a lower intake of meat. Highest compliance with the Eat lancet diet correlates with the lowest CO2 emissions and land occupation scores. To reach full compliance with the eat lancet diet, and reduce GHGe as much as possible, iron and zinc constraints have to be relaxed suggesting a more environmentally friendly diet may not always be the most nutritonally fulfilling. | 4.34 KgCO2eq/d in observed situation 4.1 KgCO2eq/d when reducing GHGe and maximising the EAT Lancet by factor 1 2.89 KgCO2eq/d when reducing GHGe and maximising the EAT Lancet by factor 1.5 2.17 KgCO2eq/d when reducing GHGe and maximising the EAT Lancet by factor 2 1.74 KgCO2eq/d when reducing GHGe and maximising the EAT Lancet by factor 2.5 1.45 KgCO2eq/d when reducing GHGe and maximising the EAT Lancet by factor 3 1.24 KgCO2eq/d when reducing GHGe and maximising the EAT Lancet by factor 3.5 1.09 KgCO2eq/d when reducing GHGe and maximising the EAT Lancet by factor 4 20.93 Eat lancet score in observed situation 50.09 Eat lancet score when reducing GHGe and maximising the EAT Lancet by factor 1 49.75 Eat lancet score when reducing GHGe and maximising the EAT Lancet by factor 1.5 48.87 Eat lancet score when reducing GHGe and maximising the EAT Lancet by factor 2 47.72 Eat lancet score when reducing GHGe and maximising the EAT Lancet by factor 2.5 42.43 Eat lancet score when reducing GHGe and maximising the EAT Lancet by factor 3 50.51 Eat lancet score when reducing GHGe and maximising the EAT Lancet by factor 3.5 (iron and zinc constraints were relaxed) 50.34 Eat lancet score when reducing GHGe and maximising the EAT Lancet by factor 4 (iron and zinc constraints were relaxed) 11.36 Land occupation (m2/d) in observed situation 11.53 Land occupation (m2/d) when reducing GHGe and maximising the EAT Lancet by factor 1 8,63 Land occupation (m2/d) when reducing GHGe and maximising the EAT Lancet by factor 1.5 8.33 Land occupation (m2/d) when reducing GHGe and maximising the EAT Lancet by factor 2 7.93 Land occupation (m2/d) when reducing GHGe and maximising the EAT Lancet by factor 2.5 6.21 Land occupation (m2/d) when reducing GHGe and maximising the EAT Lancet by factor 3 5.70 Land occupation (m2/d) when reducing GHGe and maximising the EAT Lancet by factor 3.5 4.84 Land occupation (m2/d) when reducing GHGe and maximising the EAT Lancet by factor 4 |
Greenhouse gas emissions (GHGe) reductions from dietary changes ranged from 31% to 89%, depending on the constraints applied. _x000B_A 67% (from 4.34 in the observed diet to GHGe = 1.45 kgeqCO2/d) reduction in GHGe was achievable while improving the EAT score by 103% and using 91% organic food. The diet model with 67% GHGe reduction (G4) consisted mainly of dairy, milk, oil, pulses, sugared-sweetened beverages, soya-based food, vegetables, and wholegrain products, with small amounts of fish and sweet/fat products. It does not include any meat, eggs, fruit, potatoes, or snacks Further GHGe reduction (up to 83%) was possible by relaxing bioavailable iron and zinc constraints, with less dairy products and vegetables and more wholegrain products and fruit juice._x000B_The main limiting nutritional factors were bioavailable zinc, energy, sodium, linoleic to alpha-linolenic acid ratio, sugar, and bioavailable iron._x000B_ The EAT-lancet score gradually decreased in the models that required a reduction in GHGe. The EAT-Lancet score could be improved by 141% while reducing GHGe by 75%, but this required relaxing iron and zinc constraints. The gradual reduction in GHGe maximizing the EAT-Lancet (as objective function) score under nutritional and acceptability constraints are marked by no consumption of alcoholic beverages, animal fat, beef, eggs, offal, refined cereals, other beverages, other fat, pork, potatoes, poultry, energy-dense foods, and snack. Land occupation decreased along with GHGe reduction, from 11.53 to 4.84 m2/d (57%). The diet contained 94 % of organic foods. The PNNS-GS2 score (compliance with food-based dietary recommendations) was highest at a 1.5-factor reduction in GHGe (GHGe = 2.9 kgeqCO2/ d and PNNS-GS2 = 9.25/14.25). Low-emitting diets typically excluded meat, eggs, refined cereals, and energy-dense foods, while increasing dairy products, vegetable oil, soya-based foods, and wholegrain products.Low-emitting diets are typically meat-free but can include certain unhealthy products such as sugared-sweetened beverages and energy-dense foods. In the French study based on INCA3 data, reducing GHGe by 70 % or more would make it impossible to meet nutritional requirements. Achieving significant GHGe reductions requires a drastic shift from current dietary patterns, including substantial reduction in meat products and increased plant-based food consumption. Climate change might impact iron and zinc concentrations in food, and introducing novel foods or changing farming practices for less emitting ones could help achieve lower GHGe. |
while the carbon footprint of organic plant- based diets is reduced the cost of the diet may be higher than non- organic alternatives. We have shown here that a reduction in emissions from the diet alone can mathematically reach 75 % with high agreement with the EAT-Lancet diet, but all the low emitting diets are not necessarily healthy as showed by the models minimizing GHGe without constraints on healthy diet. Furthermore, climate change is expected to impact the nutritional values of our food, specifically resulting in decreased levels of protein, iron, and zinc. As a result, it is important to take this into account when planning for a healthy diet in the future. Our study suggests that, while dietary changes can help reduce emissions concomitantly to in- crease in health value, all low emitting diets are not necessarily healthy. This suggests the need to consider the health of humans and the planet together in order to limit side-effects. These results also illustrate that 80 % reduction in GHGe and even more net zero emissions require modification of dietary habits coupled with strong changes in the sector of “Agroforestery, Forestery and Other Land Use” in order to improve carbon stocks and reduce emissions. | ||||||||
| 1512 | I. Kovanen; V. Kyttä; A. Kårlund; A. M. Pajari; H. Tuomisto; M. Saarinen; M. Kolehmainen | Kovanen, I., Kyttä, V., Kårlund, A., Pajari, A. M., Tuomisto, H., Saarinen, M. and Kolehmainen, M. (2024) 'Advancing methods for comparative nutritional LCA of milk and plant-based milk substitutes', International Journal of Life Cycle Assessment. | 2024 | Finland | dairy | milk and plant‐based milk substitutes. Nutrient data was obtained for skimmed milk (n = 4); semi-skimmed milk (n = 6); full-fat milk (n = 5); and hazelnut (n = 1), cashew (n=1), coconut (n=1), oat (n=6), rice (n=5), almond (n = 2), and soy (n = 15)-based drinks. Nutritional composition information of both fortified and unfortified drinks was included when available. Nutritional content of assessed foods is presented in the supplementary material. oat-, almond-, rice- and soy-based drinks, as well as carrot and tomato juices. | unspecified | impact categories | climate impact (CO2 eq), water consumption (m3), land use (m2a), marine eutrophi- cation (N eq), and freshwater eutrophication (P eq). | The nutrients selected based on this criterion were protein, monounsaturated fatty acids (MUFAs), vitamin D, riboflavin, niacin, vitamin B12, iodine, phosphorus, calcium, selenium, zinc, and potassium. | The environmen- tal impacts were then assessed in relation to the nutrient densities of different drinks. Nutrient indices were used as a functional unit by dividing the environmental impact of 100 g of a product by the nutrient indices, which were also calculated per 100 g of product. Using the nutrient indices as a functional unit changed the ranking of the products in terms of environmental impacts. | positive | Considering nutrient index scores as the functional unit decreaes the climate impact of semi-skimmed milk. | Climate impact (kg CO2-eq) per 100 g of a product. Climate impact per unit of nutrient index score Cashew 0.438 kg CO2-eq/ 100g 0.036kg CO2-eq per / NR-FImilk, 0.003 kg CO2-eq / NR-FIpbd, 0.035 kg CO2-eq / NR- FImilk+pbd. Oat 0.05 kg CO2-eq/ 100g 0.042 kg CO2-eq per / NR-FImilk, 0.003 kg CO2-eq / NR-FIpbd, 0.036 kg CO2-eq / NR- FImilk+pbd. Coconut 0.082 kg CO2-eq/ 100g 0.018 kg CO2-eq per / NR-FImilk, 0.154 kg CO2-eq / NR-FIpbd, 0.027 kg CO2-eq / NR- FImilk+pbd. Semi-skimmed milk 0.135 kg CO2-eq/ 100g 0.016 kg CO2-eq per / NR-FImilk, 0.056 kg CO2-eq / NR-FIpbd, 0.022 kg CO2-eq / NR- FImilk+pbd. |
Across all impact categories, coconut drink was among the three drinks with the highest environmental impact and had the highest impact in land use (m2a eq/100 g), freshwater eutrophication (kg P eq/100 g), and water consumption (m3/100 g). Dairy milks had the highest climate impact (kg CO2 eq/100 g) and the second highest impact in land use (m2a eq/100 g). Oat drink had the highest marine eutrophication impact. Fortified and unfortified soy drinks had the low- est impact score across impact categories when using the NR-FIpbd index. With the NR-FImilk index as a FU, dairy milks had the lowest impacts in freshwater use (m3) and freshwater eutrophication (kg P eq), whereas almond and fortified soy drink had the lowest climate impact (kg CO2 eq), land use (m2a), and marine eutrophication (kg N eq). When using the NR-FImilk+pbd index, cashew and unforti- fied oat drink had relatively high environmental impacts across impact categories, whereas fortified soy drink con- sistently had low impact scores. (kg N eq/100 g). Rice and almond drinks had the lowest environmental impacts in land use and global warming but had the second and third highest impacts in water consump- tion. Soy drink had the lowest impacts in water use and both eutrophication categories (kg P eq/100 g, kg N eq/100 g). While in this study milk also has higher climate impact per 100 g than any PBD, in all the other environmental impact categories, one or more PBDs surpass the impacts of milk. This under- scores the importance of assessing multiple environmental indicators for a more thorough understanding of the overall impacts. Using the nutrient indices as a functional unit changed the ranking of the products in terms of environmental impacts. The results differed depending on the nutrient index used in the calculation. Across categories and indi- ces, fortified soy drink remained among the drinks with the lowest impact, whereas cashew, unfortified oat, and coco- nut drink were consistently among the drinks with higher impact. This nutrient index resulted in the highest scores for dairy milks and soy drinks, suggesting that these drinks could provide the most, although slightly different nutritional advantages to the diet considering the environmental impact. Nutrient fortifications considerably contribute to the nutri- tional content of PBDs. In this study, fortifications in PBDs resulted in higher NR-FImilk and NR-FImilk+pbd scores compared to unfortified drinks of the same base ingredi- ent. This, in turn, resulted in, e.g., unfortified oat and rice drinks having higher environmental impacts per nutrient index compared to those of fortified versions of the same drinks. Unfortified PBDs (cashew, oat and rice) included in this study were poor source of nutrients even on the NR-FIpbd index, raising the question whether these drinks provide any nutritional benefits to the diet. An exception to this was unfortified soy drink that received the highest NR-FIpbd scores among all drinks. However, unfortified soy drink received lower scores than fortified PBDs when measured using the NR-FImilk index, indicating that it would not be nutritionally adequate substitute for milk. |
In this study, the NR-FImilk index provides the most accurate information on assessing the nutritional value of PBDs as milk substitutes, focusing on key nutri- ents currently obtained from milk. Among PBDs examined, hazelnut, almond, and fortified soy drinks scored closest to dairy milks on the NR-FImilk index, indicating they are the most nutritionally comparable alternatives to dairy milk. When substituting dairy products with plant-based alterna- tives, the overall diet should be considered to make sure no deficiencies occur as a result. The index based on current consumption led to the highest nutrient index scores for cow’s milks and consequently lower environmental impacts when used as a nFU, whereas the index based on nutrients obtained from PBDs as nFU led to higher environmental impacts for milk and lower for PBDs. Cow’s milk had the highest climate impact when the impacts were allocated per unit of mass, but in nFU-based comparison, some PBDs had higher impacts than cow’s milk. The results showed notable difference between fortified and unfortified PBDs, as the environmental impacts of unfortified PBDs were higher than impacts of milk when the comparison was based on nutrient content, while the environmental impacts of fortified drinks were lower than those of milk. | On the other hand, fortification prac- tices raise questions for instance regarding the health effects of processed foods (Beal et al. 2023) and bioavailability of fortified nutrients (Bunge et al. 2024). While PBDs may be fortified with nutrients such as calcium, vitamin B12, and vitamin D, the contents of other nutrients, i.e., protein, vary based on the base ingredient. This should be considered especially when making recommendations for different population groups. For instance, the lower amount of protein in some PBDs would not necessarily risk the overall protein intake of the healthy adult population in Finland, whose protein intake is often sufficient or even above the recommended amount (Valsta et al. 2018), yet could have detrimental effects on the elderly population who are often at risk of under and malnutrition and protein deficiency. For example, PBDs included in this study on average included more iron compared to milk (Table 1), yet bioavailability of nutrients was not assessed, making it chal- lenging to draw conclusions on the actual nutritional benefit. The choice of nFU can also significantly impact the results of LCA. | |||||
| 1515 | G. F. Kramer; M. Tyszler; P. V. Veer; H. Blonk | Kramer, G. F., Tyszler, M., Veer, P. V. and Blonk, H. (2017) 'Decreasing the overall environmental impact of the Dutch diet: How to find healthy and sustainable diets with limited changes', Public Health Nutrition, 20(9), pp. 1699-1709. | 2017 | Netherlands | N/A | Beef, milk | N/A | Dutch men and women aged 9–69 years, divided into ten age–gender groups. The analysis included nutrient composition, a metric for popularity and life cycle assessments of 207 food products. Optimised diets were solutions that minimised changes to the current diet while satisfying all nutritional constraints, with stepwise reductions in environmental impact. | Greenhouse gas emissions, fossil energy use and land occupation (ReCiPe). | Nutrition Nutrient requirements (nutritionally optimised diet) used as restrictions in the model were compiled from national and international requirements for energy and macro- and micronutrients. We applied the Recommended Dietary Allowance or Adequate Intake as the lower limit and the Tolerable Upper Intake Level as the upper limit in the model | N/A | ‘nutritionally optimised’ with the ReCiPe value of the total diet and reduced/restricted it step by step, calculating a new optimised diet after each step until no solution was possible within the constraints. | Poisitve / negative | Public health | The proportion of the total environmental impact due to meat and meat products was 29–35 % in the current diet and 22–30 % in the ‘nutritionally optimised’ diet. | Quality | Up to the ‘critical point’, the preferred environmental savings come almost exclusively from consuming less meat, especially beef. This critical point is of high significance for particular groups, e.g. Fe (women of fertile age) and Ca (elderly women. Beyond the critical point, meat and eggs decreased, while bread, legumes and fish increased. Nutrients critical for the outcome were α-linoleic acid, retinol, Ca, Na, Se, dietary fibre, SFA, thiamin and Fe (women of childbearing age). Total protein, essential amino acids and carbohydrates were not critical. | |||||
| 1543 | V. Kyttä; A. Karlund; T. Pellinen; O. Pietiläinen; H. L. Tuomisto; M. Kolehmainen; A. M. Pajari; M. Saarinen | Kyttä, V., Karlund, A., Pellinen, T., Pietiläinen, O., Tuomisto, H. L., Kolehmainen, M., Pajari, A. M. and Saarinen, M. (2023) 'Product-group-specific nutrient index as a nutritional functional unit for the Life Cycle Assessment of protein-rich foods', International Journal of Life Cycle Assessment, 28(12), pp. 1672-1688. | 2023 | Finland | Because the index score is calculated for 100 g of cooked food product, the environmental impact was also first calculated for 100 g of cooked food product, and these results are compared with the results produced using nutrient indices as the nFU. | beef, pork, poultry | The studied foods were home-cooked patties and balls made with beef, pork, broiler, trout, perch, chick- pea, soya mince, or pulled oats (a protein-rich meat sub- stitute containing oats, peas, and faba beans) as the main ingredients. | cradle to plate, including emissions from primary production, post- farm processing of the raw materials, packaging, transport to a regional distribution centre and retail of the raw materi- als, and energy consumption of the cooking phase at home. Applying cradle-to-plate system boundaries is especially important when the comparison includes products that are ready to eat such as pulled oats and products that need to be cooked such as meats. In addition to cooking losses, for some food products, the cooking phase can cause the majority of the total emissions | climate impact | nutrient indices (baseline, scarce nutrients, dietary shift, and LIM index) to assess the nutritional value of various protein-rich foods. Baseline For the baseline nutrient index, we identified the nutrients provided by the typical sources of protein at a significant level in the diets of Finnish adults to capture the impacts of substituting the foods currently consumed as sources of protein. Specifically, the inclusion criterion was that meat, eggs and/or dairy products were the most or second most important source of the nutrient according to the National FinDiet Survey (Valsta et al. 2018; Kaartinen et al. 2020). Based on this, the nutrients included in the baseline nutrient index were protein, calcium (Ca), iron (Fe), selenium (Se), zinc (Zn), vitamin B6, vitamin B12, niacin, riboflavin, and thiamine. This second selection procedure resulted in the scarce nutrients index including protein, Fe, I, Se, folate, and thiamine. Scarce nutrients - The scarce nutrient index was based on the idea that the function was to provide nutrients that most promoted health in the context of the current public nutrition with the current nutrient intake of the Finnish population. This approach does not consider a possible risk of reduced intake of nutrients that are currently abundantly obtained from typical protein-source foods. Dietary shift Because a shift from animal-based products to more plant- dominant foods is desired for health and environmental reasons for the third approach, we focused on the nutrients whose intake would be further reduced in this anticipated dietary shift. Based on the Finnish nutrient intake survey (Valsta et al. 2018) and dietary scenarios (Springmann et al. 2018; Saarinen et al. 2019), the intake of the following nutrients was estimated to possibly reduce with dietary change: protein, Ca, Zn, vitamin B12, vitamin D, and riboflavin. These nutrients were included in the dietary shift index. LIM index The index that assesses the nutrients that should be limited (LIM index) included saturated fatty acids (SAFA) and sodium (Na). |
It has been estimated that improvements in diet quality could prevent one out of every five deaths from noncommunicable diseases world- wide (Afshin et al. 2019) and decrease the vulnerability to infections and shortens the duration of infections. Both reducing and preventing environmental impacts and improving nutrition to prevent adverse health effects are key global sustainability goals (UN 2022). We considered vulnerable population groups—children, adolescents, and elderly population—to study the impact of their special nutritional needs on the indices. These population groups may be at increased risk of decreasing availability of protein-source foods, as protein and beneficial composition of amino acids are very important for physical and cognitive growth and develpment. This implies that the environmental cost (impact) of providing the nutritional service (function) of a product for children is lower than for adults. Test calculations also imply that the environmental impact of beef- based complex food eaten by a child is much lower relatively than that eaten by an adult (when nutritional quality is considered in parallel). This is because these products are rich in nutrients that are particularly valuable for children. The nutritional recommendations for different population groups should therefore be considered in the interpretation and utilisation of results. Vitamin D is essential for bone health in the elderly (VRN 2014), and overall in the Nordic countries, special attention needs to be paid to vitamin D intake due to the limited availability of sunlight during the winter months (Kårlund et al. 2022). |
index score is calculated for 100 g of cooked food product, the environmental impact was also first calculated for 100 g of cooked food product, and these results are compared with the results produced using nutrient indices as the nFU. | positive | Considering unit of nutrient index rather than 100g of ASF product decreases the climate impact of beef, pork and broiler. Broiler has the same score as chickpeas and pork has a lower climate impact when considering nutrient index. | Climate impact (kg CO2 eq./100g) Beef 2.90 kg CO2 eq./100g Pork 0.61 kg CO2 eq./100g Broiler 0.54 kg CO2 eq./100g Chickpea 0.35 kg CO2 eq./100g Climate impact/nutrient index (kg CO2 eq./unit of nutrient index) Beef 0.108 kg CO2 eq./unit of nutrient index Pork 0.022 kg CO2 eq./unit of nutrient index Broiler 0.024 kg CO2 eq./unit of nutrient index Chickpea 0.024 kg CO2 eq./unit of nutrient index |
Patties and balls with fish as the main ingredients had the highest nutrient index scores when using the baseline nutrient index, while plant-based recipes had the lowest. Vitamin B12 in fish recipes contributed significantly to the scores, while plant-based recipes had no B12 contribution. Chickpea balls had the highest score when using the scarce nutrient index. The dietary shift index led to increased index scores for trout and perch, while scores for other foods decreased. Beef balls high in saturated fatty acids (SAFA) received the highest LIM index scores. Pulled oats and chickpea balls also scored highly due to NaCl content. Trout balls without added salt had the lowest LIM index. Beef patties had a considerably higher climate impact (kg CO2 eq./100 g) than other products. Even then, the climate impact of beef was the highest, affected by a notably higher climate impact per 100 g and the average nutrient index score compared to other foods. The relative difference between the beef-based and other recipes narrowed when the baseline nutrient index and the dietary shift index were used but widened when using the scarce nutrient index. The difference in climate impact between animal-source foods and plant-based foods generally decreased when using the nutrient index instead of mass-based functional units. Inclusion of dairy products in plant-based recipes increased both nutrient index scores and climate impact. The assessment of single ingredients led to larger differences in results between foods than the comparison of complex foods. Lower iron absorption from plant-based foods resulted in 16-25% lower indices for chickpea, pulled oats, and soya mince, increasing their climate impacts. The low climate impact per nutrient index does not necessarily indicate that the food will be healthy and sustainable, but the concentration of nutrients to limit (LIM index) should also be considered. | The baseline nFU introduced in the study is valuable in producing sustainability information to support the aspiration to a sustainable dietary shift. The index used as the nFU should be formatted based on the study goal and scope, and vulnerable groups must be considered when interpreting the results. n the baseline and dietary shift indices, meat-based products scored better than for the scarce nutrient index, which addressed nutrients relatively less abundant than in the current diet. The scarce nutrient index rather highlights products that contain nutrients that should be obtained more, while the baseline nutrient index and the dietary shift index focus on the maintenance of good nutrient intake from the main protein sources in the current diet. For the other nutrient indices, the contribution analysis reveals that complex foods with many kinds of main ingredient basis can contribute to the intake of scarce nutrients and nutrients that may become scarce in the dietary shift to more plant-based diets. The only significant exception to this is an intake of vitamins B12 and D from plant-based raw materials—plant-based foods do not contain these nutrients unless the foods are supplemented with these nutrients. The climate burden relative to the nutritional benefits of beef-based complex food eaten by a child is at the same level as plant-based complex foods eaten by adults, considered in the context of diets that are much more plant- based than the diets consumed today. Because the indices include different selection of nutrients, they have different implica- tions for example to human health. If the goal and scope is to provide a basis for information to help consumers’ deci- sion between products in the current situation, the baseline nutrient index may be the best choice. However, if the aim is to anticipate the possible future situation, the dietary shift index may be a better option. However, they seem largely to confer the same conclusions. The scarce nutrient index seems most appropriate in situations where a complemen- tary product is sought instead of substitutes, because it does not factor in the maintenance of an adequate intake of nutri- ents that are typical of current protein sources. |
The baseline nFU introduced in the study is valuable in producing sustainability information to support the aspiration to a sustainable dietary shift. The index used as the nFU should be formatted based on the study goal and scope, and vulnerable groups must be considered when interpreting the results. Sustainable product choices need to be supported by relevant information that integrates environmental and nutritional aspects, considering nutrition at a whole diet level. Usually not considered in LCA studies, the most fundamental reason for consuming food is to ensure an adequate intake of energy and nutrients to maintain bodily functions and health. The daily diet should provide adequate amounts of dietary energy and protein, essential fatty acids, carbohydrates, and micronutrients to support metabolic functions and well-being at all ages. Sources of dietary proteins are especially interesting because animal-origin foods are typically rich in many important nutrients such as proteins and micronutrients, e.g. vitamin B12. While shifting to more plant-based diets has sustainability benefits, it may also pose some nutritional risks compared with omnivorous mixed diets, especially in vulnerable population groups, if not planned and addressed carefully. Because the nFU expresses the environmental impact only in relation to a group of beneficial nutrients, the nutrients to limit should also be assessed separately when compar- ing products with the nLCA. More research is required into the inclusion of nutrient bioavailability in the indices, how to consider equality among a varied population, and how to consistently apply the nFUs in a wide range of nLCA studies. The selected strategies to format the nFU have a marked impact on the results especially for fish- and plant-based food. The results of each population group, especially children, also differ. The choice of nutrients in the index, the type of food assessed, and the system boundaries of assessment have a considerable impact on the results. The baseline nutrient index included the main nutrients provided by the protein-source foods in the current diet. Considering the context of LCA, this indicates that providing these nutrients is the primary nutritional function of protein-source food. This may ignore some nutrients that are or could be obtained from fish- or plant-based foods to a considerable extent. On the other hand, the other two nutrient indices addressed some of them, for example, Vitamin D. The comparison of three different indices should therefore have ensured that no major misleading conclusions were reached. Regarding children, the explanation is the same as in other nutrient indices; 100 g of any product represents a much larger proportion of children’s diet than that of adults. In other respects, when interpreting the LIM index results, it is important to note that the recipe greatly affects the LIM index scores. For example, the recipe for the trout balls con- tained no salt at all, which is strongly reflected in the low index scores. Furthermore, salt is typically added to complex food in the manufacturing or cooking phase, while saturated fatty acids (SAFA) are often inherently in the food item or ingredient (Valsta et al. 2018). Bioavailability issues may become important especially for vulnerable groups, including children and pregnant and lactating women with requirements for supporting active growth. The ability to digest proteins is impaired with age (Gilani et al. 2012), exposing the elderly to the risk of an inadequate nutrition status. No single index can therefore be used for all purposes, and the formation of the nFU index should always be explained with clear criteria and justification. |
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| 1596 | M. R. F. Lee; J. P. Domingues; G. A. McAuliffe; M. Tichit; F. Accatino; T. Takahashi | Lee, M. R. F., Domingues, J. P., McAuliffe, G. A., Tichit, M., Accatino, F. and Takahashi, T. (2021) 'Nutrient provision capacity of alternative livestock farming systems per area of arable farmland required', Scientific Reports, 11(1). | 2021 | United Kingdom and France | beef, lamb, poultry, pork, goat, dairy | Six meat production systems commonly observed in the country were included in the analysis: intensive beef (cereal based), extensive beef (forage based), lowland lamb (grazed on medium-quality soils), upland lamb (grazed on low-quality soils), chicken (indoor) and pork (indoor). Livestock pro- duction in each subregion comprised a combination of the following enterprises: intensive beef (cereal based), extensive beef (forage based), dairy cattle, sheep (dual purpose for meat and dairy), goats (dual purpose for meat and dairy), pork, poultry meat (combining chicken, turkey, duck and guineafowl) and laying chickens. | farm-scale data from the UK. | metric | The computation of NDS followed the UKprot10 protocol25. Designed specifically for commodities commonly consumed as protein sources, this index gives an equal weight to 10 essential nutrients typically expected from this food group and computes the average percentage of RDI satisfied per unit mass (usually 100 g) of food. The nutrients included in the formula are: protein, monounsaturated fatty acids, long-chain omega-3 polyunsaturated fatty acids, calcium, iron, riboflavin (vitamin B2), folate (B9), cobalamin (B12), selenium and zinc. The resultant scores represented the average percentage of RDI satisfied across all nutrients by 100 g of an uncooked product. | arable land use: ALU, GHG | per unit of nutrient density scores (NDS)21,22 - measure of the overall nutrient value supplied by a food product | metric of ALU per NDS, expressed in the unit of m2/%RDI. | positive | Positive impact on ASF environmental impact when considering nutrient density scores - kg CO₂e/ %RDI and m³/ %RDI | Arable Land Use per Nutrient Density Score (m³/ %RDI) • Beef (Cereal): Approximately 0.025 • Beef (Forage): Approximately 0.016 • Lamb (Lowland): Approximately 0.012 • Lamb (Upland): Approximately 0.017 • Chicken: Approximately 0.06 • Pork: Approximately 0.043 Panel (b): Arable Land Use per Mass of Product (m³/100g meat) • Beef (Cereal): Approximately 0.72 • Beef (Forage): Approximately 0.48 • Lamb (Lowland): Approximately 0.22 • Lamb (Upland): Approximately 0.31 • Chicken: Approximately 0.82 • Pork: Approximately 0.71 Panel (c): Carbon Footprint per Nutrient Density Score (kg CO₂e/ %RDI) • Beef (Cereal): Approximately 0.03 • Beef (Forage): Approximately 0.06 • Lamb (Lowland): Approximately 0.14 • Lamb (Upland): Approximately 0.17 • Chicken: Approximately 0.03 • Pork: Approximately 0.04 Panel (d): Carbon Footprint per Mass of Product (kg CO₂e/100g meat) • Beef (Cereal): Approximately 1.0 • Beef (Forage): Approximately 1.8 • Lamb (Lowland): Approximately 2.6 • Lamb (Upland): Approximately 3.1 • Chicken: Approximately 0.4 • Pork: Approximately 0.8 |
Across the six systems, ALU per NDS—the area (m2) required to synthesise 1% recommended daily intake (RDI) for 10 essential nutrients—ranged between 0.012 and 0.061. The smallest area of arable land was required to provide a unit of composite nutrient under lowland lamb, closely followed by forage beef, upland lamb and cereal beef. Upland lamb, which carries a better NDS than lowland lamb due to greater contents of nutritionally beneficial long-chain omega-3 polyunsaturated fatty acids, did not per- form as favourably as the lowland system because of the greater need for supplementation with “human-edible feed” per kg liveweight gain to compensate for the lower quality of forages. Nevertheless, the positive overall results for sheep systems are noteworthy in light of the heavy environmental burdens generally associated with the species. Pork and chicken systems were shown to occupy up to 3.6 and 5.1 times more arable land than ruminant systems, respectively. As part of the computational process to derive the above results, the ratio between ALU and NDS was also calculated individually for each component nutrient (Supplementary Table S2). An examination of these values revealed that, with the exception of selenium, of which content is generally lower in ruminant meat than monogastric meat in the UK due to the former’s reliance on pasture grown on low selenium soils26, the relative rankings amongst the six farming systems were largely consistent. This finding was further mirrored by the output from the sensitivity analysis using a common alternative NDS formulation with seven essential nutrients (Supplementary Figure S1a), indicating that the results are robust to the choice of nutrients to be included. | The current level of red meat consumption in the developed world is unwarranted and detrimental to both environment and human health35,36. As such, our finding that ruminant agriculture supplies more essential nutrients per area of arable farmland than monogastric agriculture does not necessarily mean that the sector should be expanded beyond today’s scale. On the other hand, forcing agricultural producers operating on marginal lands to shift away from ruminant production will likely result in forgone opportunities to supply essential nutrients without occupying fertile soils, leading to suboptimal use of global land resources endowed upon us. This may not be a prudent strategy at a time when the demand for livestock products is forecast to increase, and particularly so if we are to address malnutrition and undernourishment at the global scale37,38. A “happier medium” must be pursued to balance human nutrition, rural economy and climate change mitigation. Thus, under reduced consumption of animal source foods that is widely recommended by medical experts40, a com- bination of ALU saving and by-product utilising ruminant systems could form an integral part of the solution package to meet the demand for nutritionally dense food, especially in light of the strong consumer preference for on-farm practices to reduce environmental footprints41. Needless to say, the benefit of this approach must be carefully weighed against climate impacts of maintaining a certain number of ruminants on the planet. Then again, a recent consumer study reported a surprising result that the choice of diet may have little effect on carbon footprint once the issue of overconsumption is accounted for. Using arable land use and the resultant nutrient provision as a case exemplar, the evidence provided here has reiterated the fact that, at times, different metrics of “sustainability” can result in mutually irreconcilable policy implications that can only be resolved through a comprehensive multidimensional analysis43. We contend, therefore, that excessively climate-focused discussions contain a risk of unknowingly creating a suboptimal economy and society, and instead call for more multidimensional approaches of sustain- ability assessment to draw better-balanced policy packages. | Although climate impacts of ruminant agriculture are a major concern worldwide, using policy instruments to force grazing farms out of the livestock industry may diminish opportunities to produce nutritious food without exacerbating the food-feed competition for fertile and accessible land resources. The best available information in today’s scientific literature suggests that, when evaluated in carbon dioxide equivalent emitted per unit of food produced, ruminant systems generally emit higher levels of greenhouse gases (GHG) than monogastric livestock systems as well as systems that produce plant-based protein. Nonetheless, to use this evidence to advocate a global dietary shift away from ruminant products creates a curious paradox in light of the ever-growing human population and thus the need to produce more food with less resources. Meeting this demand requires optimal utilisation of farmlands, both cultivated and grazed, as it is unlikely that the former can feed future generations on its own. “the production of food of animal origin is a very complex process”, of which nuance cannot be understood solely from the GHG perspective. |
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| 1814 | R. Mazac; N. Järviö; H. L. Tuomisto | Mazac, R., Järviö, N. and Tuomisto, H. L. (2023) 'Environmental and nutritional Life Cycle Assessment of novel foods in meals as transformative food for the future', Science of the Total Environment, 876. | 2023 | Europe | The functional unit was one meal, which represented the sum of the environ- mental impacts of each individual ingredient making up the meal. | Beef, poultry, pork | The original recipe was a chickpea patty with roasted root vegetables and a (soy-based) cream sauce (Eustachio Colombo et al., 2020). From that recipe, we composed fourteen alternative meals by alter- ing the protein source of the patty in the original recipe with that of other PBPR alternatives (plant-based meat imitates and tofu), NFFs, or conven- tional ASFs (beef, chicken, pork sausage, and fish). NFFs in- cluded here are cultured meat, ovalbumin (produced using the fungus Trichoderma reesei), microbial protein (hydrogen-oxidizing bacteria), microalgae (Chlorella vulgaris), insect meal (Hermetia illucens), kelp (Saccharina latissima), and mycoprotein. | cradle to consumer and included cooking at consumer. | We sourced the original recipe for a nutritionally balanced, low-GHGE optimized meal from author correspondence with Eustachio Colombo et al. (2020). The original recipe was a chickpea patty with roasted root vegetables and a (soy-based) cream sauce (Eustachio Colombo et al., 2020). From that recipe, we composed fourteen alternative meals by alter- ing the protein source of the patty in the original recipe with that of other PBPR alternatives (plant-based meat imitates and tofu), NFFs, or conven- tional ASFs (beef, chicken, pork sausage, and fish). We sourced the original recipe for a nutritionally balanced, low-GHGE optimized meal from author correspondence with Eustachio Colombo et al. (2020). The original recipe was a chickpea patty with roasted root vegetables and a (soy-based) cream sauce (Eustachio Colombo et al., 2020). From that recipe, we composed fourteen alternative meals by alter- ing the protein source of the patty in the original recipe with that of other PBPR alternatives (plant-based meat imitates and tofu), NFFs, or conven- tional ASFs (beef, chicken, pork sausage, and fish). The ReCiPe 2016 Midpoint (H) method (Huijbregts et al., 2017) was used to calculate the GWP (kg CO2 equiva- lents), land use (m2 arable cropland equivalents), terrestrial acidification (kg SO2 equivalents), freshwater eutrophication (kg P equivalents), and ma- rine eutrophication (kg N equivalents). The AWARE method (Boulay et al., 2018) was used to calculate scarcity-weighted water use (m3) per gram of the food items. We selected these environmental impact categories as they are the most commonly used categories within assessments and com- parisons of environmental impact of food products. We calculated the Nutritional Footprint (NF) of each meal adapting the methods of Lukas et al. (2016) as the first nLCA method. The health and environment subtotals are calculated per meal with the relevant nutrition and environmental impact values for each ingredient in the meal. We calculated health subtotals (NFhealth) with the health indicators of total energy intake (kcal), sodium (g), dietary fiber (g), and saturates (g) of each meal. Environment subtotals (NFenvi) were calculated for each meal with environmental indicators of GWP, scarcity-weighted water use, land use, freshwater eutrophication, marine eutrophication, and terrestrial acidification. NFhealth and NFenvi were calcu- lated, respectively, adapted from Lukas et al. (2016). This step synthesized the health and environment indicators separately as to calculate the effect level for each and allowed for an equitable ranking of all indicators in relation to each other. We adapted the methods of Green et al.'s (2021) nLCA for individual food products to calculate the Nutrient Rich meal (NRmeal) score. NRmeal was calculated over 24 positive nutrients in the meals. We then calculated Green et al.'s (2021) Limiting nutrients (LIMmeal). This was calculated over 4 nutrients to limit in the meals—sodium and total polyunsaturated,monounsaturated, and saturated fatty acids. We then calculated the Nutrient Rich Food Index meal (NRF24.4meal), also adapted from Green et al. (2021), considering the multiple recommended and limiting nutrients in a single index with the single meal as the reference unit. Capping was not used for correcting the intake levels of nutrients at 100 % of recommended intake levels or levels to limit; it has been asserted that capping should not be used for analysing the nutritional quality of meals since dietary context must be included. Next, we calculated the Nutritionally Invested Environmental Impact meal (NIEImeal) value also adapted from Green et al.'s (2021) score for meals. We separately calculated a NIEI score for each environmental impact considering the total impact of each meal and using the NRF24.4meal as the denominator, yielding a NIEI for GWP (NIEI GWPmeal), scarcity-weighted water use (NIEI WUmeal), land use (NIEI LUmeal), terrestrial acidification (NIEI TAmeal), freshwater eutrophication (NIEI FEmeal), and marine eutro- phication (NIEI MEmeal).The ReCiPe 2016 Midpoint (H) method (Huijbregts et al., 2017) was used to calculate the GWP (kg CO2 equiva- lents), land use (m2 arable cropland equivalents), terrestrial acidification (kg SO2 equivalents), freshwater eutrophication (kg P equivalents), and ma- rine eutrophication (kg N equivalents). The AWARE method (Boulay et al., 2018) was used to calculate scarcity-weighted water use (m3) per gram of the food items. We selected these environmental impact categories as they are the most commonly used categories within assessments and com- parisons of environmental impact of food products. nLCA is a nascent method to integrate nutrient richness and environmental LCA factors and accounts for the fact that food serves a nutritional function as well as having direct environmental impacts (Saarinen et al., 2017; Weidema and Stylianou, 2020). The health and environment subtotals are calculated per meal with the relevant nutrition and environmental impact values for each ingredient in the meal. |
Environment subtotals (NFenvi) : Global Warming Potential (GWP), scarcity-weighted water use (WU), land use (LU), freshwater eutrophica- tion (FE), marine eutrophication (ME), and terrestrial acidification (TA). Nutritional footprint was calculated for each meal. | Amino acid profile of meal compared to 33% of daily recommended intake of essential amino acids in whole diet. | We calculated health subtotals (NFhealth) with the health indicators of total energy intake (kcal), sodium (g), dietary fiber (g), and saturates (g) of each meal. | We calculated a Nutritionally Invested Environmental Impact (NIEI) value per meal as a second nLCA (Green et al., 2021). The NIEI of Green et al. (2021) is a method which integrates environmental impacts with nutrient richness scores based on recommended daily allowances (RDAs) or adequate intakes (AI) of nutrients per person per day. In this way, the NIEI gives environmental impacts in terms of nutrient richness functional units. | Nutritionally Invested Environmental Impact indices (NIEI) NRF24.4meal/ GWPmeal (NIEI GWPmeal) (global warming potential) NRF24.4meal/ WUmeal (NIEI WUmeal) (scarcity weighted water use) NRF24.4meal/ LUmeal (NIEI LUmeal) (land use) NRF24.4meal/ FEmeal (NIEI FEmeal) (freshwater eutrophication) NRF24.4meal/ MEmeal (NIEI MEmeal) (marine eutrophication) NRF24.4meal/ TAmeal (NIEI TAmeal) (terrestrial acidification) NRF24.4meal /all 6 environmental impacts (NIEImeal). |
All meals with novel/future foods had up to 88 % less Global Warming Potential, 83 % less land use, 87 % less scarcity-weighted water use, 95 % less freshwater eutrophication, 78 % less marine eutrophication, and 92 % less terrestrial acidification impacts than similar meals with animal source foods, while still offering the same nutritional value as vegan and omnivore meals. The beef meal had the largest GWP, land use, marine eutrophication, and terrestrial acidification impacts and the second largest GWP. The fish meal had the largest scarcity- weighted water use and freshwater eutrophication impacts.All PBPR alternatives and NFF meals had 87–92 % less GWP than the beef meal. The other ASF meals, chicken, fish, and sausage, had 78–80 % less GWP than the beef meal. PBPR alternative and NFF meals had 66–85 % less impact from scarcity-weighted water use than the fish meal. Other ASF meals had 72–75 % less impact from scarcity-weighted water use than the fish meal. PBPR alternatives, NFFs, and ASF meals had 81–86 %, 79–86 %, and 73–80 % less land use than the beef meal. PBPR alternatives had 94–95 %, NFFs had 69–95 %, and the other ASFs had 88–92 % less freshwater eutrophication potential than the fish meal. PBPR alternatives, NFFs, and other ASF meals had 71–79 %, 56–78 %, and 62–71 % less marine eutrophication potential than the beef meal, respectively. PBPR alternatives, NFFs, and ASF meals had 93–94 %, 80–92 %, and 71–87 % less terrestrial acidification potential than the beef meal. All meals exceeded 33 % of the daily recommended amount of essential amino acids except for the kelp and fava meals, which were 0.03 g/day (13 %) and 0.06 g/day (26 %) short of the recommended amount of methionine, respectively. Most meals had low environmental (NFenvi) effect levels, with the ex- ception of microalgae, mycoprotein, fish, and beef meals, which had me- dium NFenvi effect levels. The microalgae and mycoprotein meals had a medium NFenvi effect level due to medium GWP, scarcity-weighted water use, freshwater eutrophication, and marine eutrophication effect levels. The chicken, fish, and sausage ASF meals had a low NFmeal effect level, and the beef meal had a medium NFmeal and medium NFenvi effect level, due to high GWP and land use values. The freshwater and marine eutrophication effects for all meals were in the medium range since the low threshold is a 100 % reduction in both eutrophication potentials. In terms of the Nutrient Rich food index (NRF24.4meal), microbial protein and mycoprotein meals had the highest NRF24.4meal values—higher values mean more nutritious meals—due to their high positive Nutrient Richness (NRmeal) and comparably few nutrients to limit (LIMmeal). The ov- albumin, sausage, and beef meals had the lowest NRF24.4meal values due to their low NRmeal compared to high LIMmeal. When the NRF24.4meal was used to compare NIEI by GWP (NIEI GWPmeal), the beef meal had the highest ratio of GWP to NRF24.4meal and the microbial protein meal the lowest. Lower ratios mean fewer environmental impacts and higher nutrient richness. The beef meal also had the highest land use to NRF24.4meal (NIEI LUmeal), marine eutrophication to NRF24.4meal (NIEI MEmeal), and terrestrial acidification to NRF24.4meal (NIEI TAmeal) ratios, and the microbial protein meal the lowest. In terms of scarcity-weighted water use to NRF24.4meal (NIEI WUmeal) and freshwater eutrophication to NRF24.4meal (NIEI FEmeal), the fish meal had the highest ratios and microbial protein the lowest. The aggregated environmental impact value (Agg Impactmeal) revealed that the beef and fish meals had the most and second most aggregated environmental impacts, while the fava bean and tofu meals had the fewest. However, when the overall NIEImeal value is calculated for each meal, which includes respective NRF24.4meal values, the beef and fish meals have the highest and second highest ratios while the microbial protein and insect meals have the lowest and second lowest ratios. The NIEImeal ratio is higher in all ASF meals than the NFFs and PBPR alternatives meals. |
The nLCA indices of most novel/future food meals are similar to protein-rich plant-based alternative meals and show fewer environmental impacts in terms of nutrient richness than most animal source meals. Substituting animal source foods with certain novel/future foods may provide for nutritious meals with substantial environmental benefits for sustainably transforming future food systems. Comparing the nLCA indices which combine the environment and health aspects of the meals, most meals converged on the low NFmeal and low NIEImeal (Fig. 4). The beef meal stands out as the meal with the highest NFmeal and NIEImeal values; the sausage and chicken meals had low NFmeal and but moderately higher NIEImeal values. The mycoprotein NFF meal stood out with a low but still comparatively higher NFmeal value due to their high environmental impacts. Though, none of the meals scored in the high NFmeal range, suggesting that there is a fairly large variance amongst the environmental impact values such that, when averaged, the tradeoffs amongst the different environmental impacts were masked. All ASF meals have the highest NIEImeal values, meaning they have highest environmental impacts and lower comparative nutritive values. Certain NFFs have the potential to act as substitutes for ASF in sample meals with up to 88 % lower GWP, 83 % fewer scarcity-weighted water use impacts, 85 % less land use, 95 % less freshwater eutrophication, 78 % less marine eutrophication, and 92 % less terrestrial acidification per meal. In general, meals with ASF protein patties ranked worse in terms of environmental impacts and NIEImeal score than NFF meals. Depending on the environmental impact, the mycoprotein, microalgae, and cultured meat meals ranked worse than some ASF. Though NFF meals generally performed better in terms of environmental impacts than the ASF meals, there was a large range of environmental impact discrepancies within the NFF meals protein type. Such tradeoffs reveal that not all environmental impacts are correlated amongst each other, suggesting that substitution of ASFs with certian NFFs would not yield consistent reductions in environmental impact across all impact cate- gories assessed. Substituting ASFs—here, beef in particular—with PBPR alternatives reduced all environmental impacts. For example, the fava bean meal has over 75 % less GWP, scarcity-weighted water use impacts, land use, freshwater eutrophication, marine eutrophication, and terrestrial acidification than the beef meal. Our results confirm previous findings that vegan and vegetarian meals have consistently fewer environmental impacts than those containing ASF. |
Employing nLCA, over simply eLCA, has the added advantage of considering nutrition as the functional unit in assessing the sustainability of foods, nutrition being a primary, if not the main, purpose of producing and consuming food. Integration of production and consumption, environmental impacts, and nutrient content of foods is an imperative and practical step in any further transformation of diets, meals, and food production for sustainable food systems. | |||||
| 1821 | G. A. McAuliffe; T. Takahashi; T. Beal; T. Huppertz; F. Leroy; J. Buttriss; A. L. Collins; A. Drewnowski; S. J. McLaren; F. Ortenzi; J. C. van der Pols; S. van Vliet; M. R. F. Lee | McAuliffe, G. A., Takahashi, T., Beal, T., Huppertz, T., Leroy, F., Buttriss, J., Collins, A. L., Drewnowski, A., McLaren, S. J., Ortenzi, F., van der Pols, J. C., van Vliet, S. and Lee, M. R. F. (2023) 'Protein quality as a complementary functional unit in life cycle assessment (LCA)', International Journal of Life Cycle Assessment, 28(2), pp. 146-155. | 2023 | United Kingdom | beef, dairy, poultry, pork | Beef, cheese, eggs, pork, nut, peas, tofu, wheat. | cradle to retail ready for purchasing. | global warming potential; GWP100), reported as2kg CO2-eq/100 g protein, and land use (LU), reported as m *year/100 g protein. | Digestible Indispensable Amino Acid Scores (DIAAS). | We adapted the methods of Green et al.'s (2021) nLCA for individual food products to calculate the Nutrient Rich meal (NRmeal) score. | positive | When factoring DIAAS, ASFs have decreased carbon emissions whereas plant souce foods have an increase. | kg CO2 eq/100g protein. M2/year per 100g protein. Considering DIAAS and not considerering Kg CO2 eq/ 100g protein / no DIAAS Beef 17.0 Pork 7.6 Nuts 0.3 Wheat 1.4 Kg CO2 eq/ 100g protein / Untruncated DIAAS Beef 11.9 Pork 4.6 Nuts 0.3 Wheat 3.2 M2*year/100g protein / no DIAAS Beef 22.0 Pork 11.0 Nuts 7.9 Wheat 3.4 M2*year/100g protein / Untruncated DIAAS Beef 15.4 Pork 6.7 Nuts 9.0 Wheat 7.8 |
Results uncorrected for quality via DIAAS demonstrate that animal-sourced products have the highest GWP (kg CO2-eq/100 g protein) (Fig. 1A) and LU (m2*year/100 g protein) (Fig. 1B) across all considered food items, except for eggs in the context of LU (where nuts are ranked fourth moving eggs to fifth; Fig. 1B). Untruncated DIAAS, par- ticularly for animal-based products which tend to have high DIAAS values compared to most plant-protein sources (Table 2), can be quite different from the protein content values (Fig. 1B). For example, dairy beef’s GWP and LU reduce from 17 kg to 11.9 CO2-eq/100 g protein and from 22 to 15.4 m2*year/100 g protein, respectively, when compar- ing the results for protein content with a quality corrected DIAAS nFU. The largest change across plant-based prod- ucts is wheat which, due to its low DIAAS score, results in a 57% increase in its GWP and LU impacts (Fig. 1B). Needless to say, all percentage changes in GWP and LU are driven by the DIAAS percentage reported in Table 2 as these were the coefficients used to transform the nFUs. | As Sonesson et al. (2017) showed the use of protein quantity as a nFU, whilst benefiting from simplicity and fewer data requirements, does not address the complexities of the composition and balance of amino acids and, subsequent digestion and absorp- tion in the human gut of each amino acid. In addition to the limitations of protein as an nFU, focus- ing on protein (or even composite nFUs for that matter) omit complexities such as anti-nutritional factors (ANFs), including but not limited, to phytates and oxalates that reduce protein digestibility. It is also important to reflect that amino acids sourced from proteins are only one compilation of vital nutrients contained within these food items (Leroy et al. 2022). Ide- ally, in future nLCAs, a wider nutrient density analysis (e.g., the NRF9.3 scoring system devised by Fulgoni et al. 2009) should be performed to more robustly align environmental impact(s) to the wider functionality of foods (i.e., to pro- vide complete nutrition; Lee et al. 2021a). Even then, food items are not consumed in isolation but as part of a diet and, perhaps more importantly in the current context, a meal due to reasons outlined in Section 1 (i.e., the rapid uptake and excretion of IAAs/proteins). Therefore, when analysed at the single commodity level, synergies between complementary dietary ingredients, even simple combinations thereof such as rice/veg/protein source, are ignored. This is a major flaw in many nLCA and could be rectified by exploring the food matrix using omics-based approaches (also referred to as food-omics). Furthermore, carbon footprints and LU per- taining to a commodity are just two of many sustainability metrics which need to be considered together to develop a better understanding of the holistic sustainability of alter- native products; other important impacts include—but are not limited to—eutrophication, acidification, direct and indi- rect land use change, animal welfare, social well-being and economic viability. We also contend that future nLCA studies should discuss the complementarity of amino acid balances at the meal-level, as a minimum, rather than the product level when assessing protein metabolic responses of consumers. Additionally, a broader set of nutrients should ideally be included when evaluating “protein-rich foods” which provide nutrients that extend beyond amino acids, which is of particular importance when exploring dietary-level nLCA. | |||||||
| 1822 | G. A. McAuliffe; T. Takahashi; M. R. F. Lee | McAuliffe, G. A., Takahashi, T. and Lee, M. R. F. (2018) 'Framework for life cycle assessment of livestock production systems to account for the nutritional quality of final products', Food and Energy Security, 7(3). | 2018 | United Kingdom | beef, lamb, poultry, pork | Seven “treatments” or combinations of species and production systems commonly observed in the UK were identified: intensive cattle, extensive cattle, upland lamb, lowland lamb, conventional chicken, free-range chicken, and conventional pork. | cradle-to-farm-gate | indicator, indicies, functional unit | While recent studies investigating the environmental impacts of alternative diets provide useful framework for assessing implications of different food consumption patterns on the whole, the LCA literature remains short of methodologies to account for quality differences between individual foodstuffs produced under contrasting on-farm practices. The results from the above case studies suggest that the application of nutrition-based functional units in the single-commodity setting has the potential to fill this research gap and offer better insight into economic-environmental trade-offs inherent by each production system and, by extension, on-farm practices that should be promoted. While the above approach offers a useful framework for LCA when the research question primarily concerns a single nutrient, these functional units do not necessarily represent the overall value of the product associated with human nutrition. One way to address this issue is through the use of a nutrient index, a scalar value to combine information on multiple nutrients, both beneficial and detrimental to human health. | GWP - global warming potential - based on a standard mass-based functional unit (kg deboned meat). | Omega 3 and 6 fatty acids // Protein MUFA (Monounsaturated Fatty Acids) EPA+DHA (Eicosapentaenoic Acid + Docosahexaenoic Acid) Ca (Calcium) Fe (Iron) Riboflavin (Vitamin B2) Folate Vitamin B12 Se (Selenium) Zn (Zinc) Na (Sodium) SFA (Saturated Fatty Acids) UKNIprot7 UKNIprot7-2 % UKNIprot10 % UKNIprot10-2 |
Differences when considering system type. Overall negative environemtal impact when consdiering quality based GWP. | mass based GWP (kg CO2-eq/kg meat), quality based GWP (kg CO2-eq/g Omega 3), Quality based GWP (kg CO2-eq/g EPA + DHA) | • Beef: o Concentrate: Mass-based GWP: 9.8 kg CO2-eq/kg meat Quality-based GWP: 48.0 kg CO2-eq/g omega-3 Quality-based GWP: 288.1 kg CO2-eq/g EPA + DHA o Forage: Mass-based GWP: 18.3 kg CO2-eq/kg meat Quality-based GWP: 18.5 kg CO2-eq/g omega-3 Quality-based GWP: 67.7 kg CO2-eq/g EPA + DHA • Lamb: o Lowland: Mass-based GWP: 26.1 kg CO2-eq/kg meat Quality-based GWP: 28.7 kg CO2-eq/g omega-3 Quality-based GWP: 99.2 kg CO2-eq/g EPA + DHA o Upland: Mass-based GWP: 30.9 kg CO2-eq/kg meat Quality-based GWP: 30.0 kg CO2-eq/g omega-3 Quality-based GWP: 98.9 kg CO2-eq/g EPA + DHA • Chicken: o Intensive: Mass-based GWP: 4.4 kg CO2-eq/kg meat Quality-based GWP: 1.2 kg CO2-eq/g omega-3 Quality-based GWP: 25.1 kg CO2-eq/g EPA + DHA o Free Range: Mass-based GWP: 5.1 kg CO2-eq/kg meat Quality-based GWP: 2.4 kg CO2-eq/g omega-3 Quality-based GWP: 34.7 kg CO2-eq/g EPA + DHA • Pork: o Intensive: Mass-based GWP: 7.4 kg CO2-eq/kg meat Quality-based GWP: 14.4 kg CO2-eq/g omega-3 Quality-based GWP: 50.3 kg CO2-eq/g EPA + DHA |
For the present analysis, four variants of the formulae originally developed by Saarinen, Fogelholm, Tahvonen, and Kurppa (2017) for protein-rich foods in Finland were adopted and applied to the same seven livestock systems as above: UKNIprot7 and UKNIprot10 based on FNIprot7, and UKNIprot7-2 and UKNIprot10-2 based on FNIprot7-2. The first group simply rewards foodstuffs with higher contents of desirable nutrients (protein, MUFA, EPA + DHA, calcium, iron, riboflavin, folate and, additionally for UKNIprot10, vitamin B12, selenium, zinc), while the second group also penalizes those with higher contents of undesirable nutrients (SFA and sodium). Only EPA and DHA were considered among PUFA, so as to ensure their bioavailability. Vitamin B12, selenium, and zinc, which did not form part of the original indices, were added to the alternative specifications as meat is particularly rich in these micronutrients (Castañé & Antón, 2017). All four indices are expressed as % RDI per 100 g, indicating the proportion of RDI satisfied across all nutrients, minus penalty where applicable, by the said amount of product.When the seven systems were compared by the absolute level of nutrient scores, beef produced from forage-fed cattle was shown to be the most favorable product under all four index specifications (Table 4). All other systems, apart from intensive pork, performed comparably under UKNIprot7, with pork scoring low due to lower contents of protein, MUFA and folate. Under UKNIprot7-2 that also considers the two nutrients to be limited, beef and lamb produced the highest scores, while pork overtook free-range chicken due to its low SFA and Na. When the three additional nutrients (vitamin B12, Se, and Zn) were further included (under UKNIprot10 and UKNIprot10-2), both beef production systems became notably more favorable than their counterparts from other species, owing to high concentrations of vitamin B12 and Zn. This finding is notable not only in the comparison between red meat and white meat but also between meat-based diets and plant-based diets, as vegan diets are often deficient in B12 and Zn, the latter more so among children. It was found that the low mass-based GWP of chicken systems directly translated to low environmental impacts under both UKNIprot7 and UKNIprot7-2 (Figure 1). The largely positive nutritional profiles of beef and, to a lesser extent, lamb, did not greatly alter the relative rankings under these index specifications. However, when vitamin B12, Se, and Zn were introduced as nutrients to be encouraged, notable reversals in rankings were observed for cattle systems (Figure 2). Concentrate beef generated the second lowest GWP only after intensive chicken under UKNIprot10, and the lowest under UKNIprot10-2. The performance of forage beef also improved, producing lower emissions than free-range chicken under UKNIprot10-2. On the other hand, lamb systems consistently generated the highest burdens regardless of the index specifications, due to the significantly high mass-based GWP that were robust to different functional units. Nonetheless, the overall findings of this analysis question the appropriateness of comparing environmental performances of products on a mass basis—in a similar vein to the first case study. | Global warming potential implications derived under the new functional units were profoundly different compared to the standard LCA results, particularly for beef and sheep systems. concentrate-fed cattle produced approximately half the emissions of pasture-fed cattle under the standard mass-based approach. When omega-3 content of meat is considered, however, these results reversed and the concentrate-based system produced more than double the emissions of the pasture-based beef system. This difference was further exacerbated when only the most bioactive omega-3 fatty acids (EPA and DHA) were included. Between the two lamb systems, while the upland system had a marginally higher GWP, it also produced meat with a marginally higher omega-3 content, resulting in a minimal difference when the novel functional units were applied. Differences between free-range and broiler chickens were less pronounced because neither GWP nor omega-3 contents differ as substantially as cattle and lamb systems. Nonetheless, the higher levels of total omega-3 and EPA + DHA contained in intensively reared chickens increased the GWP gap between the two systems.The table compares the Global Warming Potential (GWP) of various meat production systems across different species, using both mass-based and quality-based measurements. The GWP is expressed in kilograms of CO2 equivalent (kg CO2-eq) per unit of measurement. For beef production, two systems are compared: concentrate and forage. The concentrate system has a lower mass-based GWP at 9.8 kg CO2-eq per kg of meat, compared to the forage system at 18.3 kg CO2-eq per kg of meat. However, when considering quality-based measurements, the forage system performs better, with 18.5 kg CO2-eq per gram of omega-3 and 67.7 kg CO2-eq per gram of EPA + DHA, compared to the concentrate system's 48.0 and 288.1 kg CO2-eq, respectively. Lamb production is divided into lowland and upland systems. The lowland system has a slightly lower mass-based GWP at 26.1 kg CO2-eq per kg of meat, compared to the upland system at 30.9 kg CO2-eq per kg of meat. In terms of quality-based measurements, both systems have similar GWP values, with the lowland system slightly higher for omega-3 (28.7 vs. 30.0 kg CO2-eq/g) and slightly lower for EPA + DHA (99.2 vs. 98.9 kg CO2-eq/g). Chicken production is categorized into intensive and free-range systems. The intensive system has a lower GWP across all measurements, with 4.4 kg CO2-eq per kg of meat, 1.2 kg CO2-eq per gram of omega-3, and 25.1 kg CO2-eq per gram of EPA + DHA. The free-range system shows higher values at 5.1, 2.4, and 34.7 kg CO2-eq, respectively. For pork production, only the intensive system is presented, with a mass-based GWP of 7.4 kg CO2-eq per kg of meat, 14.4 kg CO2-eq per gram of omega-3, and 50.3 kg CO2-eq per gram of EPA + DHA. |
Across species, pig production was shown to be most affected when the functional unit was changed from mass-based to quality-based. While the new method did not alter the relative rankings between species, the discrepancy between red meat systems and white meat systems was considerably narrowed, challenging the view to stringently regulate ruminant production on the basis that it is far more harmful to society than monogastric production (Springmann et al., 2017). It could be argued that omega-3 should be sourced from alternative food groups such as oily fish and seafood, which are generally known to have higher contents of EPA and DHA than either white meat or red meat. Nonetheless, low consumption of these items in many societies suggests that, at least in short to medium terms, it is important to evaluate environmental impacts associated with production of all food types based on their nutritional values. More importantly, the current approach could be applied to any number of nutrients, so as to draw information not reflected when the mass of product is used as a sole reference to the value of food. Relative environmental performances among different agricultural systems reversed as new functional units were adopted, in particular between pasture-based and concentrate-based livestock systems, highlighting that the effect of farming methods on product quality should not be ignored in comparative studies. Nevertheless, improving nutritional values of meat (per GHG emissions) is only beneficial to the environment if it is accompanied by improved consumer awareness of differences in food quality (Coelho et al., 2016), which subsequently leads to reduction in consumption of lower quality products. To this end, there is a clear need for further interdisciplinary work, including a scope for consequential LCA to account for wider socioeconomic impacts of dietary transitions as well as for endpoint LCA to consider the ultimate impact of a product (and its quality) on human health. Even though a greater degree of uncertainty makes the latter a challenging task, work carried out by Stylianou et al. (2016), whereby endpoint impacts on health and environmental were concomitantly quantified, has paved the way to implement this concept. Finally, it should also be noted that GWP is one of many aspects of sustainability (Takahashi et al., 2018); in order to achieve a truly holistic comparison of livestock systems, a suite of metrics should collectively be considered, including those representing animal welfare (Edgar, Mullan, Pritchard, McFarlane, & Main, 2013), land use (Wilkinson & Lee, 2017), and water quality (Leip et al., 2015), to name a few. | |||||
| 1830 | L. C. McNicol; L. S. Perkins; J. Gibbons; N. D. Scollan; A. P. Nugent; E. M. Thomas; E. L. Swancott; C. McRoberts; A. White; S. Chambers; L. Farmer; A. P. Williams | McNicol, L. C., Perkins, L. S., Gibbons, J., Scollan, N. D., Nugent, A. P., Thomas, E. M., Swancott, E. L., McRoberts, C., White, A., Chambers, S., Farmer, L. and Williams, A. P. (2024) 'The nutritional value of meat should be considered when comparing the carbon footprint of lambs produced on different finishing diets', Frontiers in Sustainable Food Systems, 8. | 2024 | Wales | Lambs | cradle-to-farm-gate | metrics | carbon footprint, GHGs, mass (kg dwt) - deadweight. | omega-3 polyunsaturated fatty acid content (g omega-3) in 1 kg of fresh muscle as a functional unit. | Omega-3 PUFA is known to have a variety of health benefits such as reduced risk of cardiovascular disease and other inflammatory diseases | Grams of omega-3 in 1 kg of fresh muscle (kg CO2e/g-omega-3) was selected as a functional unit to express emissions on a nutritional basis | Differences when considering system type. | kg CO2e/g-omega-3. The semimembranosus muscle cut from the forage crops diet had the lowest average nutrition-based product emissions (19.2 kg CO2e/g omega-3); whereas the same muscle cut from lambs finished on the grass and concentrates diet had the highest nutrition-based product emissions (29.4 kg CO2e/g omega-3; p < 0.001). | The concentrates diet had the lowest average mass-based product emissions while the grass systems had the highest. Although lambs from the concentrates diet were on farm for longer and the bought-in feed would lead to greater embedded GHG emissions, concentrates have a lower fibre content which can result in lower CH4 production. Most notably, grass-based systems have been found to have higher levels of omega-3 PUFA than systems feeding concentrates (Fisher et al., 2000; Warren et al., 2008). Omega-3 PUFA is a functional unit of great importance due to its potential health benefits and nutraceutical properties in humans, e.g., reducing the risk of cardiovascular disease and other inflammatory diseases (Swanson et al., 2012). Consequently, omega-3 PUFA as a single nutrient functional unit has been explored to express emissions, particularly when comparing farming systems. Lambs from the concentrates diet had the lowest average mass-based product emissions (25.0 kg CO2e/kg dwt) while those from the grass systems had the highest (28.1 kg CO2e/kg dwt; Figure 1; p < 0.001). Further variation was seen when accounting for omega-3 content, with nutrition-based emissions ranging from 12.1–73.8 kg CO2e/g omega-3. Nutrition-based emissions were greater for longissimus dorsi than for semimembranosus across all diets other than for grass and concentrates, although this difference was not statistically significant (p > 0.05). Significant differences in nutrition-based product emissions between the two muscle cuts were only found in the forage crops diet (p < 0.01; data not shown). The semimembranosus cut of lambs from the forage crops diet had the lowest average nutrition-based product emissions (19.2 kg CO2e/g omega-3; Figure 1), whereas the semimembranosus cut of lambs from the grass and concentrates diet had the highest nutrition-based product emissions (29.4 kg CO2e/g omega-3; p < 0.001). The total omega-3 PUFA composition varied across the four diets, with the forage crops and grass diet having the highest amount and the lowest being reported in the concentrates diet for both muscle cuts. Studies in lamb have reported total omega-3 PUFA as 102 and 44 mg/100 g of meat (Fisher et al., 2000), and 78 and 67 mg/100 g of meat (Kitessa et al., 2010) in animals fed on grass and concentrate diets, respectively. This was supported by a study concluding that lambs reared on grass had significantly higher total omega-3 PUFA levels compared to lambs reared on a grass and concentrate and concentrate and hay diet (Boughalmi and Araba, 2016). | The concentrates diet had the lowest average mass-based product emissions [25.0 kg CO2e/kg deadweight (dwt)] while the grass systems had the highest (28.1 kg CO2e/kg dwt; p < 0.001). The semimembranosus muscle cut from the forage crops diet had the lowest average nutrition-based product emissions (19.2 kg CO2e/g omega-3); whereas the same muscle cut from lambs finished on the grass and concentrates diet had the highest nutrition-based product emissions (29.4 kg CO2e/g omega-3; p < 0.001). | While mass-based functional units can be useful for comparing efficiencies of different farming systems, they do not reflect how farming systems impact the nutritional differences of the final product. This study demonstrates the importance of considering nutrition when expressing and comparing the carbon footprints of nutrient-dense foods such as lamb. This approach could also help inform discussions around the optimal diets for lamb production systems from both a human nutrition and environmental sustainability perspective. | ||||||
| 1841 | T. Meier; S. Schade; F. Forner; U. Eberle | Meier, T., Schade, S., Forner, F. and Eberle, U. (2024) 'Bridging Nutritional and Environmental Sustainability Within Planetary Boundaries in Food Life Cycle Assessments: SWOT Review and Development of the Planet Health Conformity Index', Sustainability, 16(23). | 2024 | Germany | Meat, dairy, poultry, pork | Wheat, Rice, Potato, Sugar from beet, Beans, Peas, Almonds, Cashew nuts, Walnuts, Soybeans, Groundnuts, Sunflower oil, Palm oil, Olive oil, Tomato, Onion, Spinach, Orange, Peach, Banana, Apple, Grapes, Coffee, Wine, Beer, Meat, cattle Meat, dairy cow Meat, sheep Meat, pig Meat, pig Meat, chicken, Butter, Eggs, Cow milk, Cow milk | cradle-to-farmgate. | benchmark | 5 environmental impacts—Global Warming Potential (GWP), cropland use, freshwater use, nitrogen application (N- min) and phosphorus application (P-min). | Planet Health Conformity Index - The nutrients selected comprised micro- and macronutrients that are included in the NutriRECIPE Index due to their high public health relevance [26,29]. Whereas the nutriRECIPE Index comprises 19 nutrients (16 encouraging and 3 limiting) and the energy content of foods, the PHC was set up based on 18 nutrients and the energy content (Table 1). Sugar as a limiting nutrient has been excluded from this selection, as only a maximum value has been defined for its intake [27]. The remaining limiting nutrients salt and saturated fatty acids (SFAs) were included. The analysis compared mass-, energy- and multi-nutrient-based functional units. | In line with the goals of the study and following the framework proposed by Green et al. (2023) [10], a new environmental nFU—expressed as Nutrient-related Planetary Boundaries (NuPlaBos)—and, subsequently, the Planet Health Conformity (PHC) Index were developed. Furthermore, the results were compared to the environmentally adjusted NRF9.3 [12]. | Positive | Meat, cattle GWP * (Mass Based) g CO2e/100 g = 2821.3 Meat, cattle GWP * (kcal Based) g CO2e/100 kcal = 2027.7 Meat, cattle kg CO2e (100 kcal Based)/NRF9.3 = 6.2 |
In terms of the planetary boundary for GHG emissions (GWP) for eggs, conventionally produced eggs were mostly half as high as organically produced eggs, which means that conventional production respects the boundary for providing more nutrients than organic eggs. Similarly, organic egg production showed higher PHC factors regarding land use and blue water use. In terms of mineral N and P application, only conventional eggs showed a transgression of several nutrients (vitamins B1, B6, C and E; minerals NaCl, Ca, Mg and I), whereas the transgression for mineral P application was more strongly pronounced than for N. Due to the absence of mineral N and P application in organic production systems, here, the corresponding single N-min and P-min PHC Indices are within the safety zone. Milk production was mostly capable of providing all nutrients within the planetary boundaries for blue water use (excluding fiber) and mineral nitrogen and phosphorus fertilizer application. However, both conventional and organic milk production failed to provide almost any nutrients within the planetary boundaries for GHGs and land use. Overall, organic milk production resulted in higher PHC factors when it came to land use, while conventional milk production showed higher PHC factors concerning GHGs. The organic production of pork meat exceeded the planetary boundaries for GHGs and land use for most nutrients, while conventional production succeeded in providing protein, saturated fat and unsaturated fat within these boundaries in addition to vitamin B1 for GHGs and vitamins B1, B2 and B9, magnesium, iron and zinc for blue water use, which could be provided within the boundaries by both production methods. Regarding mineral fertilizer application, conventional meat production mostly surpassed the planetary boundaries for all nutrients. Due to the absence of mineral N and P application in organic production systems, here, the corresponding single N-min and P-min PHC Indices are within the safety zone. cereals (except rice), potatoes, legumes, nuts and seeds (excluding cashew nuts), cabbage, carrots, pumpkin, lettuce, spinach, oranges, bananas and eggs all were rated by the PHC Index as nutritious while still staying within the planetary boundary for GHGs. These products also emitted less than 0.12 kg CO2e/NRF 9.3. On the other end of the spectrum, products that could not meet nutritional demands without significantly exceeding the planetary boundary for climate change showed considerably higher GHG emissions per NRF9.3, too. This was the case for cashew nuts, vegetable oils, tomatoes, cucumbers, coffee, cocoa, wine, meat from cattle and sheep as well as cow milk, which ranged from 0.3 to 6.2 kg CO2e/NRF9.3. Additionally, the products excluded from the comparison due to their negative NRF9.3 values mostly had a PHC Index above 2.5 (with the exception of coconut and grapes). |
It was found that a considerable amount of food products were rated as preserving the planetary boundaries when a mass- or energy-based unit was applied. Including nutrients in the calculation significantly changed the results, with many of these products actually exceeding the planetary boundaries when nutrients were accounted for in the analysis. | Finally, it is worthwhile reiterating that, in addition to containing higher levels of omega-3, forage-based production systems are also associated with lower ω-6:ω-3 ratios (Table 2). Although quantifying this effect within the LCA framework is not straightforward, these systems are likely to result in further health benefits for humans than what is shown under the proposed functional units. | ||||||
| 1855 | E. Mertens; A. Kuijsten; J. M. Geleijnse; H. C. Boshuizen; E. J. M. Feskens; P. Van't Veer | Mertens, E., Kuijsten, A., Geleijnse, J. M., Boshuizen, H. C., Feskens, E. J. M. and Van't Veer, P. (2019) 'FFQ versus repeated 24-h recalls for estimating diet-related environmental impact', Nutrition journal, 18(1), pp. 2. | 2019 | Netherlands | dairy, red meat, processed meat | DHD15-index consists of fifteen food groups included the Dutch food-based dietary guidelines of 2015: vegetables, fruit, wholegrain products, legumes, nuts, dairy, fish, tea, fats and oils, filtered coffee, red meat, processed meat, sweetened beverages and fruit juices, alcohol, and salt. | cradle to grave | Purpose: To investigate the performance of a food frequency questionnaire (FFQ) for estimating the environmental impact of the diet as compared to independent 24-h recalls (24hR), and to study the association between environmental impact and dietary quality for the FFQ and 24hR. Methods: We analysed cross-sectional data from 1169 men and women, aged 20–76 years, who participated in the NQplus study, the Netherlands. They completed a 216-item FFQ and two replicates of web-based 24hR. Life cycle assessments of 207 food products were used to calculate greenhouse gas emissions, fossil energy and land use, summarised into an aggregated score, pReCiPe. Validity of the FFQ was evaluated against 24hRs using correlation coefficients and attenuation coefficients. Associations with dietary quality were based on Dutch Healthy Diet 15- index (DHD15-index) and Nutrient Rich Diet score (NRD9.3). The 24hR was a self-administered web-based highly-standardised version using the five-step multiple pass method, a validated technique to increase the ac- curacy of recalls. Daily energy and nutrient intakes were cal- culated by multiplying the intake of food items with their nutrient content using the Dutch food composition table of 2011 |
GHGE is greenhouse gas emissions in kilogram CO2 equivalents, FE fossil energy use in mega joules, LU land use in m2*year, | To illustrate the possible influence of the method of dietary assessment, we analysed the association between dietary quality and diet-related environmental impact by linear regression analyses with adjustments for age,gender, BMI, and energy intake. Dietary quality was assessed by the food-based DHD15-index and the nutrient-based NRD9.3 both based on the 24hR as the alleged gold standard reference. Dietary estimates of the 24hR were analysed for their dietary quality using a diet score based on food groups, i.e. the Dutch Healthy Diet Index 2015 (DHD15-index) [26], and one based on nutrients, i.e. the Nutrient Rich Diet score (NRD9.3) [10, 27]. DHD15-index consists of fifteen food groups included the Dutch food-based dietary guidelines of 2015: vegetables, fruit, wholegrain products, legumes, nuts, dairy, fish, tea, fats and oils, filtered coffee, red meat, processed meat, sweetened beverages and fruit juices, alcohol, and salt. A proportional score between 0 and 10 was assigned to all other food groups, and the final score was the mean of all food groups and ranged from 0 (minimal adherence) to 10 (maximal adherence). NRD9.3 was based on the principles of the Nutrient Rich Food Index, NRF9.3 [28, 29]. This NRF9.3 algorithm is the un- weighted sum of percentage daily values (DVs) for nine nutrients to encourage (protein, dietary fibre, calcium, iron, potassium, magnesium, and vitamin A, C and E) minus the sum of percentage maximum recommended values for three nutrients to limit (saturated fat, added sugar, and sodium), calculated per 100 kcal and capped at 100%DV. We expressed nutrient intakes relative to a daily energy intake of 2500 kcal for men and of 2000 kcal for women to obtain a daily nutrient density score. | Environmental impact of the diet was reported for each impact category individually (i.e. GHGE, FE and LU), and aggregated - weighing their relative importance - into a single measure of environmental impacts, i.e. pRe- CiPe based on the principles of the ReCiPe method. | Using different types of dietary recall methods changes the environmental impact of food groups | Contribution of food groups to daily intake and environmental impact in the NQplus study, using FFQ and 24 hr recall. Dairy • Cheese: o 24-h Recall: 1.2% g/d, 5.8% E%d, 8.7% GHGE, 4.7% FE, 5.6% LU, 6.6% pReCiPe o FFQ: 1.3% g/d, 4.8% E%d, 8.4% GHGE, 4.5% FE, 5.3% LU, 6.4% pReCiPe • Milk: o 24-h Recall: 6.1% g/d, 4.2% E%d, 5.9% GHGE, 4.9% FE, 4.0% LU, 4.9% pReCiPe o FFQ: 7.8% g/d, 4.1% E%d, 6.8% GHGE, 5.5% FE, 4.5% LU, 5.6% pReCiPe • Milk-based desserts: o 24-h Recall: 4.4% g/d, 4.7% E%d, 5.4% GHGE, 4.3% FE, 3.3% LU, 4.3% pReCiPe o FFQ: 5.4% g/d, 4.8% E%d, 5.8% GHGE, 4.7% FE, 3.5% LU, 4.6% pReCiPe Meat • Non-processed: o 24-h Recall: 1.4% g/d, 3.1% E%d, 15.7% GHGE, 9.4% FE, 16.9% LU, 15.0% pReCiPe o FFQ: 1.6% g/d, 2.8% E%d, 18.6% GHGE, 9.8% FE, 20.5% LU, 17.8% pReCiPe o • Processed: o 24-h Recall: 1.7% g/d, 5.5% E%d, 14.9% GHGE, 8.8% FE, 14.3% LU, 13.6% pReCiPe o FFQ: 1.45 g/d, 3.7% E%d, 9.5% GHGE, 6.2% FE, 8.8% LU, 8.6% pReCiPe Eggs • 24-h Recall: 0.5% g/d, 1.0% E%d, 1.3% GHGE, 1.5% FE, 1.6% LU, 1.5% pReCiPe • FFQ: 0.6% g/d, 0.9% E%d, 1.4% GHGE, 1.6% FE, 1.7% LU, 1.6% pReCiPe |
Meat, dairy, and beverage consumption contributed the most to the environmental impact, irrespective of the method of dietary assessment (meat 29% of total daily dietary pReCiPe, dairy 16% and beverages 15% according to 24hR, and with similar values for the FFQ) (Table 2). Impacts of type of meat, however, differed by method of dietary assessment with for the FFQ a higher contribution to pReCiPe and its components from non-processed meat and a lower contribution from processed meat (18% vs 9%) as compared to the 24hR (15% vs 14%); consistent with reported intake differences. In addition, reported in- takes of dairy and plant-based foods, like potatoes, bread, vegetables, legumes and fruit, were in general higher for the FFQ than for the 24hR. Contribution of the different food groups to daily diet-related environmental impact was dependent on the environmental impact measures for some food groups; meat had a higher share in total daily dietary GHGE and LU than in FE, while the opposite was seen for plant-based foods, fish and beverages. Our results show that quality of the food pattern (DHD15-index in our case) is similarly related to all environmental impact measures under study, and more environmentally-friendly diets (lower value) tend to score better on food-based dietary quality (hence a negative regression coefficient); this is irrespective of the environmental impact measures. However, when nutrient quality of the diet (NRD9.3 in our case) is considered, the results differ by environmen- tal impact measure and whether 24hR or FFQ was used as the method of dietary assessment. In the detail for NRD9.3, we showed that nutrient qual- ity tended to be positively associated with diet-related FE; but inversely with diet-related GHGE and LU. The positive association for diet-related FE with NRD9.3 is likely to be driven by food sources such as fish, bread, fruit and vegetables that have a higher contribution to total-diet related FE as compared to GHGE and LU (Table 2). Moreover, these foods have a high nutrient density contributing to high intakes of dietary fibre, potas- sium, magnesium, iron, vitamin C, E, and low intakes of sodium, added sugar and saturated fat. In contrast, the in- verse association for LU is likely to be driven by the low contribution of fruit and vegetables to diet-related LU as compared to GHGE and FE. This discrepancy between results for food-based scores and nutrient-based scores may be ex- plained by the different components included in the scores [41, 42]: food-based DHD15-index is conceptually related to food-based dietary guidelines and easily cap- tures intakes of nutrient-dense plant-based foods versus animal-based foods; while the nutrient-based NRD9.3 evaluates dietary quality based on nutrient intake relative to nutritional requirements irrespective of the food sources. A sole focus on food-based approaches to a healthy and environmentally-friendly diet may therefore not capture the full spectrum of nutritional risks and may incorrectly lump all sustainability indicators to- gether. |
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| 1856 | E. Mertens; A. Kuijsten; H. H. E. van Zanten; G. Kaptijn; M. Dofková; L. Mistura; L. D'Addezio; A. Turrini; C. Dubuisson; S. Havard; E. Trolle; J. M. Geleijnse; P. van't Veer | Mertens, E., Kuijsten, A., van Zanten, H. H. E., Kaptijn, G., Dofková, M., Mistura, L., D'Addezio, L., Turrini, A., Dubuisson, C., Havard, S., Trolle, E., Geleijnse, J. M. and van't Veer, P. (2019) 'Dietary choices and environmental impact in four European countries', Journal of Cleaner Production, 237. | 2019 | Denmark, Czech Republic, Italy, and France | unspecified | indicator | To estimate the environmental impact of the diets, we devel- oped the SHARP Indicators Database (SHARP-ID). This database contains GHGE and LU as indicators of the environmental impact and can be extended to other indicators. These two indicators relate to at least four of the planetary boundaries identified by Rockstro€m et al. (2009), i.e. biodiversity loss, nitrogen cycle disruption, carbon cycle disruption, and land use change, as discussed by Aiking (2014). | |||||||||||||||
| 1891 | L. Mogensen; J. E. Hermansen; E. Trolle | Mogensen, L., Hermansen, J. E. and Trolle, E. (2020) 'The Climate and Nutritional Impact of Beef in Different Dietary Patterns in Denmark', Foods, 9(9). | 2020 | Denmark | beef - In total, nine types of cattle were included in the present work, covering dairy systems and beef breed systems as well as calves and older animals. | nutritional impact of the different beef products ready to eat in different real-life dietary patterns. minced meat, roasted meat, steaks and dice/strips, - replacing beef with pork, poultry, fish, eggs, cheese or legumes, | slaughterhouse until the beef product is ready to eat | carbon footprint (CF) (ghg emissions) land use , kg CO2eq per day. | For most vitamins and minerals, the content was abundant (vitamin A, riboflavin, niacin and B12, calcium, phosphorus and iodine) or acceptable (vitamin E, thiamine, B6, folate and C and magnesium, zinc, selenium and potassium), low in vitamin D, however, and for some women of the fertile age also in iron [24]. Additionally, the contents of whole grain and dietary fibre were too low and saturated fatty acids were too high. | The recent update from the World Cancer Research Fund International and the American Institute for Cancer Research (2018) recommends, based on evidence for the risk of red meat causing different kinds of cancer, no more than 350–500 g (cooked weight) of red meat, such as beef, pork and lamb per week (on average 50–71 g per day) and only a small amount of, if any, processed meat [12]. Other studies including systematic reviews indicate positive associations between intake of red meat and processed meat and the risk of stroke, cardiovascular mortality and all-cause mortality [8–10,84] myocardial infarction [84] and diabetes type 2 [8,11,84]. Red and processed meat contribute with a high proportion of (≥30%) vitamins and minerals such as vitamin A, thiamine, niacin, B12, B6, zinc, selenium and protein of the average Danish diet. At the same time, red and processed meat, in particular, are major sources of saturated fat and sodium | ?? | The Green diet had a slightly higher GHG contribution from the foods than the Average diet, despite having the lowest intake of beef as well as of red meat in total. Compared with the Average diet, the Green diet daily saved 270 g of CO2eq from meat and 50 g of CO2eq from eggs and fat. However, this was counterbalanced by more CO2eq from fruit, vegetables, bread, milk and fish. Similar results were found by Vieux et al. [95], studying self-selected diets of French adults, showing that plant-based diets of high nutritional quality were not lower in GHG emissions. These estimations indicate that a reduction of beef intake in real-life dietary patterns can maintain the nutritional quality of the diets if the beef is exchanged with a combination of other protein-containing foods. However, the results also indicate that depending on the amount of beef and the percentages of reduction, the content of zinc and to some extent iron will need special attention, especially because substitution with pork was less relevant, since the content of pork before substitution, and thereby of red meat, was above or around the recommended maximum intake of 500 g per week, corresponding to on average 71 g per day according to the Danish FBDG. Comparing the High-beef diet, which was also highest in total red meat, with the Green diet, showed that the High-beef diet did not improve the nutritional profile as regards the nutrients of concern. On the contrary, the Green diet was lower in saturated fatty acids and higher in dietary fibre and whole grain, vitamins E, C and D, folate, potassium and magnesium, and smaller improvements were seen for iron and selenium (9%), thiamine (7%) and vitamin B6 (6%). In addition, the content of protein, added sugar and zinc was about the same. Besides the lower intake of beef and total red meat, the Green diet was characterised by a higher content of oat flakes, rye bread, vegetables and fruit and of dairy products, fish and eggs, and a lower content of beer, wine, sweet beverages and coffee than the High-beef diet. These changes were apparently sufficient to account for the lower content of red meat as regards the critical nutrients. The nutrient profile of the Traditional and Fast-food diets was close to the Average diet. However, the contents of folate and vitamin C were lower in the Traditional diet, and the Fast-food diet was higher in added sugar, and lower in dietary fibre, whole grain, potassium, vitamin D and iron (close to 10%). Thus, the Green diet was closest to the recommended intake compared to all other diets; since saturated fatty acids, dietary fibre and whole-grain were improved, added sugar either improved or stayed at the same level, and the contents of most micronutrients were improved while others were approximately alike. Using the substitutes in question here reduced the GHG emission by 4–12% and the land use by 5–14%. The largest impact on the GHG emission was obtained by using legumes or eggs as a substitute, whereas the largest impact on the land use, not surprisingly, was obtained by using fish—or eggs as the substitute. From a nutritional point of view, both positive and negative effects were observed, depending on the type of substitution. Focusing on the nutrients of concern, on the positive side, pork as a substitute increased thiamine in all dietary patterns (14–20%), eggs increased selenium in the Traditional and Fast-food diet (6–7%), fish increased vitamin D and selenium in all dietary patterns (35–66% and 9–15%, respectively), and legumes increased dietary fibre in all three dietary patterns (9–18%) and magnesium (5%) in the Traditional and Fast-food diet as well as folate and potassium (both 5%) in the Fast-food diet. On the negative side, all substitutes but pork reduced the content of zinc (7–10%) in all diets, except for cheese in the Traditional and Green diet. Poultry and fish also reduced the content of iron in the Fast-food diet (both 5%), and cheese also reduced the content of iron in both Traditional and Fast-food diets (6–7%). The content of vitamin D was reduced by legumes in the Traditional and Fast-food diets (6–7%) and by poultry and cheese in the Fast-food diet (both 5%). Cooked dry brown beans were used for the substitution of beef meat with legumes. Since the nutrient content of different types of legumes varies | The Traditional, Fast-food and Green dietary patterns showed almost the same GHG emission, whereas the High-beef diet showed a higher emission. The Green diet and the Fast-food diet had a low GHG emission from beverages, and therefore the GHGs of the total Green diet and the total Fast-food diet were slightly lower than the Traditional and the Average diet. Additionally, it can be noted that the contribution from all food of the High-beef diet, compared to the Average, more or less corresponds to the difference in the contribution from beef. The GHG emission from the Green diet was 4% lower than the Average diet, and the land use requirement was 8% less. The High-beef diet had 16–19% more GHG emission and required 20% more land than the Green and Fast-food diets. Scaled to a yearly basis, the High-beef diet resulted in 190 kg higher CO2eq emission (12%) than the Average diet. Of the different beef products—minced, roasted, steak and dice/strips—the roasted beef had the highest CF both as ready to eat and as slaughterhouse. Of the different beef products—minced, roasted, steak and dice/strips—the roasted beef had the highest CF both as ready to eat and as slaughterhouse. The CF of the Green diet or the Fast-food diet was around 16–19% lower than the CF of the High-beef diet. In the present study, beef products were responsible for from 9% (Green diet) to 20% (High beef diet) of the GHG emission of the total diet. Substitution of beef with the same weight of other animal-based food (pork, poultry, eggs, cheese) or substitution with the same amount of energy from legumes reduced the GHG emission by 4–12% and the land use by 5–14%. | |||||||||
| 1965 | J. Muñoz-Martínez; R. A. Elías; L. Batlle-Bayer; I. Cussó-Parcerisas; E. Carrillo-Alvarez | Muñoz-Martínez, J., Elías, R. A., Batlle-Bayer, L., Cussó-Parcerisas, I. and Carrillo-Alvarez, E. (2023) 'Optimizing sustainable, affordable and healthy diets and estimating the impact of plant-based substitutes to milk and meat: A case study in Spain', Journal of Cleaner Production, 424. | 2023 | Spain | beef, poultry, pork, dairy, processed meat | we explore the potential benefits of reducing animal meat and milk and replacing them with plant-based alternatives(PBA) given their increased consumption in Spain. This was accompanied by a sustainability performance exploration where milk and different types of meat(beef, chicken, pork, processed meat) were replaced by a calcium fortified soy-drink and a plant-based burger, respectively. fruits(fresh and dried), vegetables, starches (grains, cereals, and tubers), plant-based protein(PBP)(legumes -excluding soy-, tofu, nuts), meat, seafood, eggs, dairy(milk, yogurt, cheese, butter), plant-based dairy(plant-based drink and margarine), vegetable oils, sugar sources(sugar, sweets, pastries, desserts, and jam), beverages(soft drinks, juices, alcoholic drinks), dried tea and coffee, and residual(prepared meals, chocolate, sauces and other condiments). | These environmental data consider the impact of food along the whole food system - from primary production up to consumption, as well as the food losses and waste generated. | metric | Through multiobjective optimization we aimed to determine a sustainable and healthy diet(SHD) in Spain with the minimum cost and environmental impact (assessed through GHGe, land use and blue-water use) that deviate the least from current consumption. Additionally, this research also compares the optimised diet with the Spanish food-based dietary guidelines(FBDG), and explores the potential benefits of reducing animal meat and milk while replacing them with plant-based alternatives. Three indices were used to assess nutritional adequacy: the Nutrient-Rich-Diet 93(NRD93), 103(NRD103) and 103A(NRD103A). The former had been used by other authors(Batlle-Bayer et al., 2020) and is calculated using the Total-Nutrient-Rich 9(TNR9) minus the Total-Nutrient-Limiting 3 (TNL3) sub-scores. TNR9 equals the sum of positive percentages from encouraging nutrients(protein, fibre, vitamin A, C and E, minerals Ca, Fe, Mg, and K) whereas the TNL3 includes the negative percentages of limiting nutrients(saturated fats, salt, and total sugars). The NRD103 score was defined to also consider vitamin B12 as an encouraging nutrient, which has been identified to be insufficient in some sustainable diets due to the lower content of animal-based foods(Willett et al., 2019). Finally, NRD103A and NRD103 differ in the consideration of sugars: in the case of NRD103A, total sugars were replaced by added sugars, since the latter had been recognised to be responsible for dele- terious effects on health(WHO, 2018). | GHGe, land use and blue-water use. | NRD 93 NRD 103 NRD 103A Energy (kcal) Proteins (% from Kcal) Fats (% from Kcal) Carbohydrates (% from Kcal) Protein (g) Fibre (g) Calcium (mg) Iron (mg) Magnesium (mg) Potassium (mg) Vitamin A (μg) Vitamin C (mg) VitaminE(mg) VitaminB12(μg) Sodium (mg) Saturated fats (g) Added sugars (g). Food group contribution(in %) to daily energy requirements from the Spanish FBDG, the ANIBES adjusted diet, and the optimised diets(S2 and S3). |
Comparing meat with substitution with plant based hamburger and 4 types of meat are replaced with plant based hamburger GHGe (kgCO2eq) • ANIBES: 4.07 kgCO2eq • Meat 30% Subs.: 3.54 kgCO2eq • Meat 50% Subs.: 3.19 kgCO2eq • Meat 70% Subs.: 2.83 kgCO2eq • Meat 100% Subs.: 2.30 kgCO2eq • Beef Subs.: 3.10 kgCO2eq • Chicken Subs.: 3.81 kgCO2eq • Pork Subs.: 3.92 kgCO2eq • Processed Subs.: 3.67 kgCO2eq Land Use (m²) • ANIBES: 4.53 m² • Meat 30% Subs.: 4.36 m² • Meat 50% Subs.: 4.24 m² • Meat 70% Subs.: 4.12 m² • Meat 100% Subs.: 3.94 m² • Beef Subs.: 4.34 m² • Chicken Subs.: 4.47 m² • Pork Subs.: 4.46 m² • Processed Subs.: 4.27 m² Water Use (L) • ANIBES: 307 L • Meat 30% Subs.: 295 L • Meat 50% Subs.: 286 L • Meat 70% Subs.: 278 L • Meat 100% Subs.: 266 L • Beef Subs.: 295 L • Chicken Subs.: 300 L • Pork Subs.: 301 L • Processed Subs.: 291 L NRD 103A • ANIBES: 487 • Meat 30% Subs.: 512 • Meat 50% Subs.: 528 • Meat 70% Subs.: 544 • Meat 100% Subs.: 568 • Beef Subs.: 496 • Chicken Subs.: 519 • Pork Subs.: 502 • Processed Subs.: 518 Energy (kcal) • ANIBES: 1800 kcal • Meat 30% Subs.: 1785 kcal • Meat 50% Subs.: 1775 kcal • Meat 70% Subs.: 1765 kcal • Meat 100% Subs.: 1750 kcal • Beef Subs.: 1789 kcal • Chicken Subs.: 1825 kcal • Pork Subs.: 1792 kcal • Processed Subs.: 1746 kcal % Kcal Prot (Protein as % of total calories) • ANIBES: 16.4% • Meat 30% Subs.: 16.3% • Meat 50% Subs.: 16.3% • Meat 70% Subs.: 16.3% • Meat 100% Subs.: 16.5% • Beef Subs.: 16.5% • Chicken Subs.: 16.0% • Pork Subs.: 16.5% • Processed Subs.: 16.5% Protein (g) • ANIBES: 73.7 g • Meat 30% Subs.: 72.9 g • Meat 50% Subs.: 72.4 g • Meat 70% Subs.: 71.9 g • Meat 100% Subs.: 71.1 g • Beef Subs.: 73.8 g • Chicken Subs.: 72.9 g • Pork Subs.: 73.8 g • Processed Subs.: 71.9 g Iron (mg) • ANIBES: 10.7 mg • Meat 30% Subs.: 12 mg • Meat 50% Subs.: 12.8 mg • Meat 70% Subs.: 13.7 mg • Meat 100% Subs.: 15 mg • Beef Subs.: 11.4 mg • Chicken Subs.: 12.6 mg • Pork Subs.: 11.5 mg • Processed Subs.:11.5 mg Vitamin B12 (µg) • ANIBES: 5.2 µg • Meat 30% Subs.: 4.6 µg • Meat 50% Subs.: 4.2 µg • Meat 70% Subs.: 3.9 µg • Meat 100% Subs.: 3.3 µg • Beef Subs.: 4.5 µg • Chicken Subs.: 5.0 µg • Pork Subs.: 4.7 µg • Processed Subs.: 4.9 µg Comparing milk and plant-based drink (soy) substitution ANIBES • NRD 103A: 487 • Energy: 1800 kcal • %kcal prot: 16.4 • Protein: 73.7 g • Iron: 10.7 mg • Vitamin B12: 5.2 µg • GHGe: 4.07 kgCO2eq • Land use: 4.53 m² • Water use: 307 L Milk 50% subs. • NRD 103A: 488 • Energy: 1782 kcal • %kcal prot: 16.4 • Protein: 73.0 g • Iron: 11.0 mg • Vitamin B12: 4.9 µg • GHGe: 3.95 kgCO2eq • Land use: 4.37 m² • Water use: 300 L Milk 100% subs. • NRD 103A: 489 • Energy: 1764 kcal • %kcal prot: 16.4 • Protein: 72.4 g • Iron: 11.2 mg • Vitamin B12: 4.7 µg • GHGe: 3.84 kgCO2eq • Land use: 4.21 m² • Water use: 293 L |
Compared to current consumption, a Sustainable Healthy Diet (SHD) in Spain can be more nutritious and reduce cost, GHGe, land and blue-water use by 32%, 46%, 27%, and 41%, respectively. The Spanish intake displayed the worst nutritional assessment and the highest values for GHGe and land use. The Spanish food-based dietary guidelines (FBDG) showed the highest cost and blue-water usage. Further analysis revealed that plant-based meat alternatives are not necessary to achieve a nutritionally adequate diet at the minimum cost and environmental impact. Shifting to fortified plant-based milk alternatives may add additional environmental benefits. It has been proved that current food consumption has the most detrimental impact in all sustainability indicators except for blue-water and cost, for which the Spanish FBDG showed the greatest impact. By balancing the contribution of plant-based and animal-based products and limiting the uptake of low nutrient-dense foods, we propose a varied diet based on optimization that meets all nutrient requirements, that is 1.61 € cheaper than the typical Spanish food consumption pattern, that reduces GHGe by 2.33 kgCO2eq, land use by 1.5 m2 and blue-water use by 156L. In all scenarios, meat was the food group that was reduced to the maximum, resulting in a recommendation of four portions per week(64 g daily), one more than the Spanish FBDG but lower than the upper threshold from the EAT-Lancet report(86 g daily)(Willett et al., 2019). | our study showed that substituting meat with different PBMA can perform better than current diets from the nutritional point of view. However, it is important to highlight that we used a single PBMA and this is insufficient to reflect the wide variety of products available in the retail sector which some of them have been proven to be high in limiting nutrient(i.e. saturated fats,salt). The ANIBES intake displayed a carbon footprint (CF) of 5.03 kgCO2eq/day, similar to that reported in other Southern European countries(Mertens et al., 2019). According to the 2023 IPCC report, to avoid experiencing the detrimental consequences of climate change, CF should be halved by 2030(IPCC, 2023). The present study achieved almost 50% reduction of kgCO2eq with S3, which is a promising result. Concerning land use, optimization allowed to reduce pressure by 27%. The three main contributors in the ANIBES study were meat, dairy, and starches. The benefit of shifting towards less resource-intense diets (which means more plant-based) relies on the opportunity of restoring land through reforestation(Searchinger et al., 2019). This would imply a greater capacity for carbon sequestration and hence further GHGe mitigation would be achieved than that estimated in the present study. The Spanish FBDG showed the greatest BWF mainly due to its high content in fruits and vegetables. in Spain, a more sustainable and healthy diet that is affordable and culturally sensitive can be achieved by shifting towards more plant-based diets and limiting low-nutrient-dense foods. Plant-based meat alternatives have been proved unnecessary to achieve SHD, although fortified plant-based drinks are a suitable solution for milk replacement. | Given the high meat consumption in Spain, the fact that significant environmental pressure is reduced without eliminating meat is important to ease acceptance among the Spanish population. Disregarding detrimental(i.e., trans fatty acids) or beneficial(i.e., polyunsaturated fatty acids, phytochemicals) nutritional characteristics may have led the optimization procedure to underestimate low-energy nutrient-dense foods(i.e., fruits, vegetables, seafood) and enhance high-energy low-- nutrient dense foods (i.e., prepared meals, margarine). From the envi- ronmental perspective, although industrially produced foods may be moreenergy-efficientthanhomemadealternatives(Caldero ́netal., 2018; Saarinen et al., 2012; Sonesson et al., 2005), they can be a driver of biodiversity loss and land degradation due to the reliance on high-yielding crops which was not considered in our analysis. future research evaluating SHD should also consider nutrient bioavailability. For instance, it has been recognised that a greater amount of plant-based sources may imply an increased intake of anti-nutritional factors such as phytates or oxalates, which decrease the bioavailability of key nutrients such as protein or iron(Beal et al., 2023; McAuliffe et al., 2023). In our study, some nutrient re- quirements are met without leaving space for this variability, and therefore different results could have been obtained if bioavailability was considered. | |||||||
| 2122 | J. M. G. Paris; T. Falkenberg; U. Nothlings; C. Heinzel; C. Borgemeister; N. Escobar | Paris, J. M. G., Falkenberg, T., Nothlings, U., Heinzel, C., Borgemeister, C. and Escobar, N. (2022) 'Changing dietary patterns is necessary to improve the sustainability of Western diets from a One Health perspective', The Science of the total environment, 811, pp. 151437. | 2022 | Germany | Impacts on the environment, animal welfare and human health of alternative diets to the reference diets of both men and women in North-Rhine Westphalia (RD), namely recommended diet by the German Nutrition Society (DD); vegan diet (VD) and Mediterranean diet (MD) | meat, poultry, | Meatballs, meat based meals, meat stew, egg based meal, chicken egg | farm to fork | climate change; (b) fine particulate matter formation; (c) terrestrial acidification; (d) freshwater eutrophication; (e) marine eutrophication; (f) land occupation; (g) water use; (h) fossil resource scarcity. (i) Animal Life Years Suffered (ALYS), (j) loss of Animal Lives (AL); (k) loss of Morally-adjusted Animal Lives (MAL); | impacts on human health (DALYs). Nutrients contained in the respective food products in Optimeal® are based on the European Food Composition Database (EFSA, 2019). These data comprise 60 nutrients in total, including macronutrients and micronutrients, e.g., fiber and vitamin A, for over 2500 food prod- ucts, considering multiple preparation methods commonly applied in ten European countries (Broekema et al., 2019). Nutritional indices derived from food items consumed within the diets were qualified as die- tary risk factor exposure to estimate the underlying diseases affecting human health, using optimal levels of intake available in the GBD data- base. The optimal intake level and the reference diet intake values for both men and women are shown in Table 2 (see Table S10 in the ESM for further details). | DALYs attributed to dietary risk factors were considered to represent the disease burden associated with dietary choices. Impacts on human health as Disability-Adjusted Life Years (DALYs) caused by several non-communicable diseases (NCDs) attributed to dietary risk factors by gender, due to reference diets of both men and women in North Rhine-Westphalia. CVD: cardiovascular diseases; IHD: ischemic heart disease; HHI: hypertensive heart disease; STR: stroke; D + CKD: diabetes and chronic kidney diseases; T1D: type I diabetes; T2D: type II diabetes; NE: neoplasms; CRC: colon and rectum cancer; SC: stomach cancer; EC: esophageal cancer; BC: breast cancer; TBLC: tracheal, bronchial, and lung cancer. | no quantitative data | It is particularly noteworthy that the RD in NRW is more detrimental to human health than the proposed alternative dietary scenarios. Two main factors contribute to diabetes and cardiovascular diseases: the high intake of animal-based and energy-dense foods, combined with the low intake of plant-based foods. Several studies show the relation between red meat intake and a higher risk of metabolic syndrome, obe- sity and diet-related NCDs, including coronary heart disease, stroke, and diabetes mellitus (Azadbakht and Esmaillzadeh, 2009; Micha et al., 2010; Rouhani et al., 2014). The use of dietary risk factors is a good mea- sure of human health impacts, in which vegetarian meals present a lower disease burden than meals containing meat (Weidema and Stylianou, 2020). As an additional finding, women's diet turned out to be more aligned with healthier standards than men's, corroborating re- sults from earlier German studies. Dietary risk factors exposure per FU is higher in men than in women and delivers a greater loss of potential healthy years. The prevalent NCDs in both men and women's diets are cardiovascular diseases, spe- cially ischemic heart disease. A large proportion of DALYs arises from the low intake of legumes and whole grains and the high intake of sodium and trans fatty acids. The latter is mainly associated with the consumption of bread and butter/margarine, pastries, ready-to-eat meals and proc- essed meat (i.e. sausages). Specifically, dietary risk factors pose health risks of 0.802 and 0.666 DALYs for ischemic heart diseases for men and women, respectively; while 0.503 and 0.348 DALYs are linked to all cardiovascular diseases. Likewise, the total burden of diabetes type I and type II (higher in men's diet) ranges between 0.271 and 0.463 DALYs for both genders, attributed to the high intake of processed meat and red meat. Stroke is associated with >0.25 DALYs due to the high intake of red meat and sodium in both RDs. DALYs related to colon and rectum cancer are also significant for both genders (be- tween 0.438 and 0.464), mainly due to the low intake of whole grains and milk. | The reduction in animal-based products consumption contributes greatly to lower environmental impact values for most indicators in RD, MD and VD. These results are aligned with many LCA studies evalu- ating the contribution of animal-based products to environmental im- pacts such as climate change (Batlle-Bayer et al., 2020; Bruno et al., 2019; Heller et al., 2018). According to Sandström et al. (2018), the share of animal-based products within a diet is a good measure of its environmental footprint. This study also shows that typical Western diets cause greater impacts than vegetarian options (Chapa et al., 2020; Goldstein et al., 2016). Within the EU context, reducing meat (especially beef) and dairy products could remarkably reduce several consumption-based environmental impacts and improve human nutri- tion (Beylot et al., 2019; Chaudhary et al., 2018; Sala and Castellani, 2019; Sandström et al., 2018). Moreover, this study reveals that an in- creased consumption of other animal-based products such as fish and honey can have negative animal welfare implications, based on the indi- cators from Scherer et al. (2018). In this sense, normalization and weighting among OH dimensions could help identify more sustainable diets, but this requires arbitrary choices and remains an open challenge in LCA (Hélias and Servien, 2021; Roesch et al., 2020). . The three scenarios deliver sustainability gains rela- tive to the RD, although trade-offs arise. On the one hand, replacing animal-based with plant-based protein sources can increase water scar- city. On the other hand, an increased consumption of animal-based products such as fish, seafood and honey has negative implications for animal welfare, given the larger number of animals that suffer. This highlights the role that the choice of animal-based products plays in the overall sustainability of Western diets from a OH perspective. Re- gardless of the choice of animal-based protein sources, the larger the share of plant-based foods – such as fruits, vegetables, legumes and whole grains – in a diet, the greater the associated human health bene- fits. Moreover, reducing consumption of ready-to-eat meals and highly processed foods is clearly recommended to improve the health of humans, animals and the environment at the same time. | ||||||||
| 2376 | E. Röös; G. Carlsson; F. Ferawati; M. Hefni; A. Stephan; P. Tidåker; C. Witthöft | Röös, E., Carlsson, G., Ferawati, F., Hefni, M., Stephan, A., Tidåker, P. and Witthöft, C. (2020) 'Less meat, more legumes: prospects and challenges in the transition toward sustainable diets in Sweden', Renewable Agriculture and Food Systems, 35(2), pp. 192-205. | 2020 | Sweden | pork, poultry, red meat, offal | In our scenario, we assumed an equal reduction in meat across the main livestock species and across different animal parts (muscles and offal). We took data on meat consumption from the latest national food consumption survey Riksmaten (NFA, 2012), which reports an average daily per capita intake of meat products of 110 g, divided among different products as follows: red meat 63 g, chicken 22 g, sausage 21 g, offal 3 g and blood 1 g (NFA, 2012). Hence, a 50% reduction means a reduction in meat products of 55 g. In our scenario, this meat is replaced by 55 g of cooked grain legumes daily, corresponding to approximately 20 g dried legumes. After accounting for total postharvest losses of 11% (FAO 2011), the amount of grain legumes required for the transition scenario corresponds to an annual total of 75,000 tons for the Swedish population (10 million people). Replacement based on edible weight rather than energy or protein content is justified because the energy and protein content in the Swedish diet on a population level is well within the recommended range (NFA, 2012), so it is not necessary on a population level to replace all energy and protein provided by meat. Moreover, we assumed that, when shopping for foods, consumers base their purchase decisions on the amount of food, rather than the energy and protein content. | unspecified | To analyze the prospects and challenges of reducing meat consumption in favor of legumes, we selected the case of Sweden and an explorative scenario in which meat consumption is reduced by 50%. There were four reasons for this level of reduction. First, it would keep consumption by high-meat consumers well below the level recommended by the World Cancer Research Fund (max. 500 g of cooked red meat per week) to reduce the risk of some cancer forms, which is also the maximum red meat consumption level stated in dietary advice from the Swedish National Food Agency (NFA, 2015). | Climate impact and land use and eutrophication | kg protein | negative | Approx. Average Kg CO2 eq per kg protein Legume and pulses - 10 Egg - 30 Milk - 40 Cheese - 48 Chicken - 20 Pork - 30 Lamb - 145 Beef - 148 |
The per capita climate impact and land use related to food consumption would be reduced by 20 and 23%, to 1.5 tons CO2e and 0.26 ha, respectively, by a 50% reduction in meat consumption and addition of 55 g cooked grain legumes per day (Fig. 4a and b). A 20% reduction in the climate impact of food consumption is a considerable decrease. An additional 20–30% is likely to be achievable through improvements on the production side. In the scenario, approximately 5100 tons less mineral N would be needed in Swedish agriculture due to reduced need for cereals and oilseed crops for animal feed. Furthermore, if 25 kg less N fertilizer were applied per ha to non-legume crops grown after a grain legume. As the diet after transition contains less protein (6%) and hence less N, excretion of N will be lower, which in turn will affect wastewater composition. In addition, the reduction in chicken and pig production means that less manure is produced, which also reduces the risk of eutrophication. After the proposed transition, the estimated average daily intake for energy, fat, protein, vitamin B12, zinc and total iron is still within the recommended range, even before adding the grain legumes to the diet. (No data are shown for the other vitamins and minerals that are above recommendations in both scenarios.) However, calculations for iron based on the average requirements for men and post-menopausal women mask the fact that, for women of childbearing age and during pregnancy, the diet does not meet the dietary recommendations either before or after the transition. The most beneficial aspect increasing the legume consumption is the increased intake of fiber and folate. The current average fiber intake in the Swedish population is far below the recommended level (Fig. 3), amounting to 20 g day−1. In the transition scenario, the fiber intake increases by 25% through incorporation of grain legumes (Fig. A1), to 25 g day−1, which is at the lower limit of the recommendation. Average folate intake is also improved after the transition, due to the incorporation of grain legumes. This is of particular importance for women of childbearing age and during pregnancy and lactation. Reducing Swedish meat consumption by 50% and replacing it with a daily per capita consumption of 55 g domestically grown cooked grain legumes would bring many benefits. It would reduce the climate impact (−20%) and land use (−23%) associated with the Swedish diet, reduce the need for N fertilizer and the N load from wastewater plants, greatly increase fiber intake and improve folate intake from diets, and bring many agronomic benefits to Swedish cropping systems. However, achieving a large increase in the production of domestic grain legumes to supply the necessary legumes involves several challenges, such as lack of suitable varieties and difficulties controlling weeds, pests and diseases. | |||||||||
| 2434 | M. Saarinen; M. Fogelholm; R. Tahvonen; S. Kurppa | Saarinen, M., Fogelholm, M., Tahvonen, R. and Kurppa, S. (2017) 'Taking nutrition into account within the life cycle assessment of food products', Journal of Cleaner Production, 149, pp. 828-844. | 2017 | Finland | N/A | Beef, pork, chicken, milk | N/A | a methodology to combine nutritional and environmental aspects within the food life cycle assessment (LCA). There are two approaches in the paper: The first considers individual nutrients separately and uses mass-based functional units (FU), and the second one considers multiple recommended nutrients at the same time by using a nutrient index as the FU, and considers nutrients to be limited as a separate measure. | GWP. KgCO2e | Protein in g PUFA in g MUFAc cis in g Fe mg Ca mg A general nutrient content, unit of NR9a g |
N/A | GWP | NR9; NRF9-3, FINprot7-2, NRF9, FINprot7, LIM2 and LIM3 | Positive | Public health | Changing FU from a mass unit to a nutrient unit affect the results. According to the results, beef has the highest climate impact per 100g (1.921 KgCO2e) together with mutton, but only the fourth highest per unit of NR9 (0.158 KgCO2e) and FINprot7 (0.137 KgCO2e). | Quantity / quality | The best source of protein is beef, and the best source of Ca is cheese. Eggs and semi-hard cheese are in turn the best sources of B2 vitamin. Climate impacts of these animal-based foods are, in general, higher than plant-based foods both per kg of product and a mass unit of most individual nutrients. But because of low RA of some nutrients, they might have a role in an optimized diet. Special attention has to be paid to vitamin B12. It is a critical nutrient for vegans, as it exists only in animal-based foods. | There can be found groups of “sustainable products” and “unsustainable products” based on GWP/NR9 and GWP/FNIprot7 scores and corresponding LIM3 per RF(NR9) and LIM2 per RF(FNIprot7) scores. Beef falls within a sustainable product. As a conclusion, even an inclusion of several nutrients at the same time does not explain the climate impacts of the product. It is thus relevant and important to include a general nutritional function separately to food LCA as a FU (instead of mass, e.g. 100 g) as low climate impact and high nutritional quality are both desirable qualities, and climate impact does not reflect the general nutritional quality. |
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| 2450 | S. Saget; M. Costa; C. S. Santos; M. W. Vasconcelos; J. Gibbons; D. Styles; M. Williams | Saget, S., Costa, M., Santos, C. S., Vasconcelos, M. W., Gibbons, J., Styles, D. and Williams, M. (2021) 'Substitution of beef with pea protein reduces the environmental footprint of meat balls whilst supporting health and climate stabilisation goals', Journal of Cleaner Production, 297. | 2021 | Ireland and (Brazil) | meal | beef | We performed an attributional life cycle assessment (LCA) of a 100 g serving of cooked protein balls (PPBs) made from peas (Pisum sativum), and Swedish-style beef meatballs (MBs) made from Irish or Brazilian beef. | cradle to fork | In terms of 100 g cooked balls, the PPBs have the lowest environmental burdens across all impact categories. In terms of climate change, land use, and eutrophication, the impact of MBs (IE) is between 4 and 34 times that of PPBs. | Global warming, acidification, and land use. acidification, climate change, marine and terrestrial eutrophication, land use, photochemical ozone formation, resource use energy carriers and minerals and metals, and respiratory inorganics categories. | The Nutrient Density Unit (NDU) FU was applied. where: EFA is the amount of essential fatty acids in 100 g of product, expressed in grams. Protein is the amount of protein in 100 g of product, expressed in grams. Fibre is the amount of fibre in 100 g of product, expressed in grams. DVEFA is the recommended daily value intake of essential fatty acids, expressed in grams. DVprot is the recommended daily value intake of protein, expressed in grams. DVfibre is the recommended daily value intake of fibre, expressed in grams. Si is the amount of kilocalories in 100 g of product, expressed in kilocalories. |
Positive | Using NDU decreases environmental impact compared to when per 100g cooked product | Impact per Serving of meatballs • Acidification ter. & freshwater: 0.070 mol H+ eq • Cancer human health: 5.0E-08 CTUh • Climate change (w/o COC): 3.3 kg CO2 eq • Climate change + COC: 13.4 kg CO2 eq • Ecotoxicity freshwater: 5.7 CTUe • Eutrophication freshwater: 0.0012 kg P eq • Eutrophication marine: 0.029 kg N eq • Eutrophication terrestrial: 0.30 mol N eq • Ionising radiation, HH: 0.30 kBq U235 eq • Land use: 354 Points • Non-cancer human health: 2.3E-06 CTUh • Ozone depletion: 9.1E-08 kg CFC-11 eq • Photochem. ozone form.: 0.0076 kg NMVOC eq • Resource use, energy carriers: 19.8 MJ • Resource use mins. & metals: 2.9E-07 kg Sb eq • Respiratory inorganics: 5.0E-07 disease inc. • Water scarcity: 1.03 m³ depriv. Impact per NDU • Acidification ter. & freshwater: 0.052 mol H+ eq • Cancer human health: 3.7E-08 CTUh • Climate change (w/o COC): 2.5 kg CO2 eq • Climate change + COC: 10.1 kg CO2 eq • Ecotoxicity freshwater: 4.3 CTUe • Eutrophication freshwater: 0.0009 kg P eq • Eutrophication marine: 0.021 kg N eq • Eutrophication terrestrial: 0.22 mol N eq • Ionising radiation, HH: 0.23 kBq U235 eq • Land use: 266.3 Points • Non-cancer human health: 1.8E-06 CTUh • Ozone depletion: 6.8E-08 kg CFC-11 eq • Photochem. ozone form.: 0.0057 kg NMVOC eq • Resource use, energy carriers: 14.9 MJ • Resource use mins. & metals: 2.2E-07 kg Sb eq • Respiratory inorganics: 3.7E-07 disease inc. • Water scarcity: 0.78 m³ depriv. |
The working hypothesis that “a serving of PPB has a significantly overall lower environmental impact than a serving of MB (IE or BR) per unit of nutrition” was validated. The results showing that the environmental burdens of a serving of a vegetarian alternative are lower than those of a meat product are coherent with those from other studies. | The simplicity of the NDU is a major advantage, requiring few nutritional analyses when compared with more extensive FUs, such as the Nutrient Rich Foods index 11.3 (Fulgoni et al., 2009), while still correlating with them (Saget et al., 2020). ALSO CONSIDERS BRAZIL BUT NOT ACCOUNT FOR IN RESULTS AND DISCUSSION. | ||||||
| 2587 | X. Simon; D. Copena; D. Pérez-Neira | Simon, X., Copena, D. and Pérez-Neira, D. (2023) 'Assessment of the diet-environment-health-cost quadrilemma in public school canteens. an LCA case study in Galicia (Spain)', Environment Development and Sustainability, 25(11), pp. 12543-12567. | 2023 | Spain | meat, poultry, dairy | Oil Meat Cereals Fruits Eggs Dairy products Legumes Fish Vegetables Water and the rest |
cradle-to-grave approach | functional unit , impact categories | study considers the following indicators: a) those obtained from an energy and carbon life cycle assessment of the school menus (cradle-to-grave approach), mainly the cumulative energy demand (CED) and the carbon footprint (CF), complemented by some energy efficiency indicators. abiotic depletion (fossil fuels) and IPCC global warming potential (100y). In particular, we used three impact indicators: a) the cumu- lative energy demand (CED); b) the carbon footprint (CF) expressed in different functional units (meal, kilograms of food, kilograms of protein); and c) the energy return on investment (EROI). Three indicators are used to assess both abiotic depletion (fossil fuels) and the IPCC global warming potential: CED and CF, expressed in different functional units (meal, kilograms of food, and kilograms of protein), and EROI. total carbon footprint (kg CO2-eq). CED or CFper fu = cumulative energy demand or carbon footprint per functional unit (meal, kg of food, or kg of protein); N = number of meals (No.), kilograms of food or kilograms of protein served during one year.An average meal was also chosen as the functional unit. | we estimated the kilocalorie, protein, carbohy- drate and fat intake per meal for each of the main food groups. We estimated the NRD 9.3 index assuming that a school canteen menu is equivalent to 2,000 kcal per person and day to homogenize the results for comparative purposes. | the carbon footprint (CF) expressed in different functional units (meal, kilograms of food, kilograms of protein). | A 30% reduction of salt consumption in the meals could advance the score to 381, a clear improvement. From a nutritional viewpoint, 72.1% of the kilocalories supplied in the meals were accounted for by oil (23.2%), cereals (22.4%), vegetables (including potatoes) (14.1%), and meat (12.4%). On the other hand, 61.1% of the proteins were concentrated in the consumption of animal products, especially fish (26.0%) and meat (20.3%), while cereals, vegetables and leg- umes accounted for 16.2%, 13.2% and 6.3%, respectively. Animal products represented 64.4% of the CED, 73.4% of the CF, and 57.0% of the cost of food for the school meals, thus revealing a positive correlation between the economic and the environmental cost of food. The monetary cost of vegetables (15.6%) and fruits (12.0%) is worth highlighting, although their environmental impact is relatively low: 10.7% and 4.6% of the CF, respec- tively. On the other hand, legumes only account for 1.2% of the cost, 1.3% of the CED and 0.9% of the CF. the substitution of organic prod- ucts for 30% or 60% of their conventional equivalents would allow for an 8.8% (S1a) or 16.4% (S1b) reduction of emissions as compared to the baseline scenario. Increasing the plant-based proportion of the diet by 30% or 60% would, in turn, allow for a larger reduction of the CF (by up to 33%). Although reducing the consumption of animal products would result in a lower intake of proteins (by up to 28.1%), this dietary change would actually increase the NRD 9.3 index score. When the diet combines a decrease in the consumption of ani- mal products and the introduction of organic foodstuffs, the reduction in the environmental impact is at its highest (emissions decrease by up to 45%). a 45% reduction in the consumption of animal products with a 60% substitution of organic products for conventional food would make it possible to reach a monetary balance (S4) and obtain important environmental and nutri- tional benefits.The consumption of animal products and labor (for food preparation) are identified, respectively, as the main environmental impact and economic cost of the menus. Our analysis of the diet-environment-health-cost quadrilemma ren- ders results demonstrating that introducing organic products reduces the environmental impact of school meals (up to 16.4% of the CF); yet it increases their price (up to 4.8% of the TC).This trade-off between environmental improvement and increased cost disappears when dietary changes also include the reduction of animal protein intake and their replacement by vegetable products. In this case, a higher consumption of vegetable products, in addition to increasing nutritional quality as measured by the NRD 9.3 index, may cut the cost by up to 6.4%. However, when more vegetarian and more organic menus are designed, the effect on the price is diluted and allows for an improvement in the four dimensions of the quadrilemma. In both situations, the reduction of energy consumption and GHG emissions could reach values between 4.4% and 29.0%; and 8.8% and 44%, respectively. Introducing more vegetarian dishes would reduce the monetary and environmen- tal cost of school meals, as well as enhance their nutritional quality according to the NRD 9.3 index. A 30% reduc- tion of salt consumption in the meals could advance the score to 381, a clear improvement. From a nutritional viewpoint, 72.1% of the kilocalories supplied in the meals were accounted for by oil (23.2%), cereals (22.4%), vegetables (including potatoes) (14.1%), and meat (12.4%). On the other hand, 61.1% of the proteins were concentrated in the consumption of ani- mal products, especially fish (26.0%) and meat (20.3%), while cereals, vegetables and leg- umes accounted for 16.2%, 13.2% and 6.3%, respectively. Animal products represented 64.4% of the CED, 73.4% of the CF, and 57.0% of the cost of food for the school meals, thus revealing a positive correlation between the economic and the environmental cost of food. The monetary cost of vegetables (15.6%) and fruits (12.0%) is worth highlighting, although their environmental impact is relatively low: 10.7% and 4.6% of the CF, respec- tively. On the other hand, legumes only account for 1.2% of the cost, 1.3% of the CED and 0.9% of the CF. the substitution of organic prod- ucts for 30% or 60% of their conventional equivalents would allow for an 8.8% (S1a) or 16.4% (S1b) reduction of emissions as compared to the baseline scenario. Increasing the plant-based proportion of the diet by 30% or 60% would, in turn, allow for a larger reduction of the CF (by up to 33%). Although reducing the consumption of animal products would result in a lower intake of proteins (by up to 28.1%), this dietary change would actually increase the NRD 9.3 index score. When the diet combines a decrease in the consumption of ani- mal products and the introduction of organic foodstuffs, the reduction in the environmental impact is at its highest (emissions decrease by up to 45%). a 45% reduction in the consumption of animal products with a 60% substitution of organic products for conventional food would make it possible to reach a monetary balance (S4) and obtain important environmental and nutri- tional benefits. |
products of animal origin have greater impacts than do those of plant origin when said impact is expressed in kilograms, but the difference decreases when the chosen functional unit is protein. The phase having the largest impact both in terms of energy and emissions is food pro- duction (also in Jungbluth et al. 2016; Martínez et al. 2020). More specifically, the pro- duction/consumption of meat and sea products is the main source of proteins, but it also contributes to the highest GHG emissions and makes highest energy demand. 60% of the CF of the average diet in Galicia is linked to animal products. An excessive intake of veal is one of the main hotspots in the school can- teens under analysis, followed by the consumption of other foodstuffs with high emission intensities, such as lamb, cheese, butter, pork or fish. replacing 30% or 60% of animal products with vegetable products (vegetables, legumes, fruits and cereals) leads to positive results in relation to the food quadrilemma: reducing the consumption of animal products, decreases GHG emissions and improves the nutritional quality of the menu, and leads to a significant drop in the TC of school canteen meals (and even results in improved efficiency in the case of other scenarios). | |||||||||
| 2597 | C. M. Singh-Povel; M. P. van Gool; A. P. G. Rojas; M. C. E. Bragt; A. J. Kleinnijenhuis; K. A. Hettinga | Singh-Povel, C. M., van Gool, M. P., Rojas, A. P. G., Bragt, M. C. E., Kleinnijenhuis, A. J. and Hettinga, K. A. (2022) 'Nutritional content, protein quantity, protein quality and carbon footprint of plant-based drinks and semi-skimmed milk in the Netherlands and Europe', Public Health Nutrition, 25(5), pp. 1416-1426. | 2022 | Netherlands, Belgium, Germany, Spain, Italy and Sweden | dairy | plant-based drinks and semi-skimmed milk. semi-skimmed milk, soy, oat, almond, coconut and rice drink | cradle to grave | in order to consume at least 24 % of WHO requirements for each essential amino acid, representative for 1 glass of semi-skimmed milk, consumption of 1·7 (soy drink) to 246·3 (rice drink) glasses of plant-based drinks are required. Semi-skimmed bovine milk provided the lowest amount of energy and required the least amount of money to provide at least 24 % of WHO requirements for each of the essential amino acids. Soy drink scored best on carbon footprint and required 160 g CO2-equivalents to provide at least 24 % of WHO requirements for each essential amino acid. For semi-skimmed bovine milk, this was 312 g CO2-equivalents and for oat drink 474 g CO2-equivalents. For the other plant-based drinks, greenhouse gas emission was above 5000 g CO2-equivalents when meeting essential amino acids requirements. Semi-skimmed bovine milk contained ∼3·3 g protein/100 g and soy drink ∼3·2 g protein/100 g. For all other plant-based drinks, the protein content was on average below 1 g/100 g. The key nutritional differentiator between bovine milk and fortified plant-based drinks is milk’s high-quality protein. As in addition protein is also the main determinant of carbon footprint, it is important to consider the balance between protein quality and carbon footprint. One glass of semi-skimmed bovine milk has a carbon footprint of 312 g CO2-equivalents. In order to provide a similar protein quality one would need to drink so many glasses of almond, rice or coconut drink, that their accumulative carbon footprint would be above 5000 g CO2-equivalents (Table 5). Therefore, for those drinks, the nutrition v. climate change balance is so far off, that a significant place in a sustainable diet cannot be justified. For soy and oat drink, it was shown that 1·7 glasses of soy drink (142 g CO2-equivalents) or 7·9 glasses of oat drink (476 g CO2-equivalents) are required to provide a similar protein quality as milk. Fortified soy drink scores best on the nutrition to climate change balance, and semi-skimmed milk scores second best. The latter conclusion is in line with the study of Tessari et al. (Reference Tessari, Lante and Mosca36), which compared milk with soy beans. |
Carbon footprint was calculated for 1 UHT drink per regular plant-based type and for 1 UHT semi-skimmed bovine milk. | protein quantity, protein quality, amino acids. B2, B12 and Ca. | Saturated fatty acid content also differed between bovine milk and plant-based drinks. SFA were highest in coconut drink (1·4 g/100 g), while for semi-skimmed bovine milk they were 1·0 g/100 g. For other plant-based drinks, saturated fatty acid content was at or below 0·4 g/100 g. SFA have been shown to increase LDL cholesterol levels. ccording to WHO, free sugars are defined as added sugar, as well sugars formed during the production process(19). Free sugars, particularly in the form of sugar-sweetened beverages, are associated with a higher body weight(19). Furthermore, free sugar is associated with dental caries(19). On the other hand, regarding sugars intrinsically present in milk, such as lactose, WHO states that there is no reported evidence of adverse effects(19). Plain semi-skimmed, bovine milk does not contain any free sugar. All sugars in the plant-based drinks are either added or formed during the production process, and thus considered by the WHO definition as free sugars. The regular varieties of plant-based drinks contained on average 2·1 (soy drink) to 5·9 (rice drink) g free sugar/100 g. This is lower than average sugar level in for example juice or soda, which all contain around 10 g free sugar/100 g.Milk naturally contains many micronutrients such as Ca, I, vitamin B2 and vitamin B12, all in a highly bioavailable delivery matrix(Reference Zhang, Hughes and Grafenauer33). Data in the current study showed that for regular plant-based drinks, roughly 50 % of the products is fortified with Ca and roughly 40 % is additionally fortified with 1 or more other micronutrients. For the organic plant-based drinks, hardly any is fortified. unfortified drinks carries the risk of suboptimal nutrient intake and deficiencies for Ca and B vitamins. The impact of such deficiency on bone health and other health outcomes, would be particularly apparent in sensitive groups such as children, elderly and vegans | Positive | Soy drink is the only PBMA that has lower carbon emissions than semi-skimmed bovine milk whilst meeting at least 24% of WHO requirements for essential amino acids. | g CO2-equivalents to provide at least 24 % of WHO requirements for each essential amino acid. Semi- skimmed bovine milk - 312 Soy drink - 149 Oat drink - 476 Almond drink - 5436 Coconut drink - 7159 Rice drink - 36797 |
To compare the nutritional composition of bovine milk and several plant-based drinks with a focus on protein and essential amino acid content and to determine the ratio of essential amino acids to greenhouse gas emission. A Life Cycle Assessment (LCA) with system boundaries from cradle to grave was conducted to calculate carbon footprint. Protein quality was determined by calculating the contribution to the WHO essential amino acids requirements. The protein content of the products was determined by Kjeldahl(20,Reference Kjeldahl21) . The protein content is calculated using the nitrogen conversion factor, depending on the protein’s origin. The amino acids cystine/cysteine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine, tyrosine and valine were quantified using ion chromatography, post-column derivatisation with ninhydrin and detection using UV-VIS absorption, after (oxidation and) hydrolysis. The applied amino acid analyzer was a Hitachi L-8900 (Hitachi, Tokyo, Japan). After oxidation, both cysteine and cystine are converted to cysteic acid. The results are expressed as cystine. The amino acid tryptophan was quantified using ultra-performance liquid chromatography and fluorescence detection (Waters Acquity), after hydrolysis. If the concentration of an essential amino acid was below the detection limit, the detection limit was used in further calculations, thereby potentially overestimating the result. | Protein content was highest in semi-skimmed bovine milk. For essential amino acid content, the difference with plant-based drinks was even larger, as in these analyses not only protein quantity, but also protein quality was accounted for. The difference became even larger, if in addition the WHO amino acid requirements were accounted for. This means that bovine milk contains more protein, more essential amino acids and has better ratio among the different essential amino acids. One glass of bovine milk (200 ml) contained at least 24 % of the WHO requirements for each of the essential amino acids. For the plant-based drinks the contribution to the required level was significantly lower: 14·2 % for soy drink, 3·1 % for oat drink, 0·4 % for almond drink, 0·3 % for coconut drink and only 0·1 % for rice drink. Of all drinks, bovine milk was the cheapest product. Carbon footprint was lowest for plant-based drinks when not considering nutritional value. Among the plant-based drinks, oat drink had the lowest carbon footprint. | ||||||
| 2610 | A. Smedman; H. Lindmark-Månsson; A. Drewnowski; A. K. M. Edman | Smedman, A., Lindmark-Månsson, H., Drewnowski, A. and Edman, A. K. M. (2010) 'Nutrient density of beverages in relation to climate impact', Food & Nutrition Research, 54. | 2010 | sweden | Cattle | milk | N/A | Estimating, in a life cycle perspective, the GHG emissions resulting from the production of milk, a soft drink, orange juice, beer, wine, bottled carbonated water, soy drink, and oat drink. The nutrient density of the beverages was based on calculations including protein, carbohydrates, fat and 18 vitamins, and minerals. The nutrient density of each beverage was then combined with the GHG emissions to create the novel Nutrient Density to Climate Impact (NDCI) index. | grams of CO2-equivalents | nutrient density, expressed as percentage of Nordic Nutrition Recommendations (NNR) (protein, carbohydrates, fat, retinol equivalents, vitamin D, vitamin E, thiamin, riboflavin, ascorbic acid, niacin equivalents, vitamin B6, vitamin B12, folate, phosphorus, iron, potassium, calcium, magnesium, selenium, zinc, and iodine.) | Nutrient Density to Climate Impact (NDCI) index | Positive | Environment-public health | Due to low-nutrient density, the NDCI index was 0 for carbonated water, soft drink, and beer and below 0.1 for red wine and oat drink. The NDCI index was similar for orange juice (0.28) and soy drink (0.25). Due to a very high-nutrient density, the NDCI index for milk was substantially higher (0.54) than for the other beverages. | Nutrient density (quality) | The NDCI index for milk was substantially higher than for the other beverages studied. This can be explained by a very high nutrient density value, both with regard to the number of nutrients and their amount relative to recommendations. protein quality must also be taken into consideration. Milk proteins had a more favorable amino acid composition than soy proteins | ||||||
| 2636 | U. Sonesson; J. Davis; A. Flysjö; J. Gustavsson; C. Witthöft | Sonesson, U., Davis, J., Flysjö, A., Gustavsson, J. and Witthöft, C. (2017) 'Protein quality as functional unit – A methodological framework for inclusion in life cycle assessment of food', Journal of Cleaner Production, 140, pp. 470-478. | 2017 | sweden | N/A | bread, chicken fillet, minced pork, minced beef, milk and pea soup | N/A | Developed a method to determine the nutritional value, measured in terms of both quality and quantity of proteins. We used the content and quality of proteins as a basis, and included dietary context as part of our method, since the nutritional value of a nutrient depends on the total dietary intake. Our method uses the digestible intake of the nine essential amino acids in the product and relates these values to the equivalent total dietary intake of the same amino acids. | GWP; LU; freshwater ecotoxicity | g protein g digestible protein; kg PQI (protein quality index-weighted food). | N/A | GWP/kg; GWP/(g protein); GWP/(g digestible protein); GWP/kg PQI (protein quality index-weighted food). | Positive / negative | Public health | Chicken, pork, beef, milk and pea soup has 293, 567, 2187, 107 and 13% GWP relative to bread respectively when GWP/kg is used. When GWP/(g protein) is used the corresponding values are 99, 189, 750, 263 and 27% respectively. 194% reduction for chicken; 378% pork; 1437% for beef; but milk increased 156%. But …. For PQI … The most pronounced difference is that when using “kg protein” as the FU, milk scores 9.7 times higher than pea soup, but when “kg food/PQI” (regardless of dietary context) is used as the FU, milk scores 4.9 times higher than pea soup. For chicken, the corresponding figures are 3.7 and 2.6, and for pork they are 7.0 and 4.4. | Quantity / quality | This is a result of the higher digestibility and more beneficial amino acid profile of animal products, given the dietary contexts.. Using the simplest approximation of the nutritional function of protein, such as g protein, improves the understanding of environmental impact related to the most important function of food, nutrition, significantly, but systematically under-values products of animal origin because of their higher protein quality. Adding a determinant of protein quality, namely protein digestibility, to the FU gram protein improves the results slightly, but the systematic error of under-valuing animal proteins is still relevant, although to a lesser extent. The PQI-based FU captures the nutritional quality of the proteins in foods in a much more accurate way. However, it is very data-demanding and could be difficult to apply in practice. | |||||
| 2637 | U. Sonesson; J. Davis; E. Hallström; A. Woodhouse | Sonesson, U., Davis, J., Hallström, E. and Woodhouse, A. (2019) 'Dietary-dependent nutrient quality indexes as a complementary functional unit in LCA: A feasible option?', Journal of Cleaner Production, 211, pp. 620-627. | 2019 | Sweden | dairy, poultry | bread, apples, tomatoes, milk, hard cheese, spread and chicken fillets. | unspecified | The results, calculated using bread as the reference, indicated that in both dietary contexts apples, tomatoes, and hard cheese had lower NQI adjusted GWPs compared to when GWPs were calculated using mass as the functional unit. Milk's NQI-adjusted and mass-calculated GWPs differed little, while the chicken fillet GWPs were the same in the unhealthy diet and performed better in the average diet. The NRF9.3-adjusted GWPs differed from the NQI-adjusted ones for all analysed foods. The main conclusions were: 1) considering nutritional value in the LCA of foods improves our understanding of how the environmental impacts and nutritional functions of food are related; 2) the environmental performance of different products varies with dietary context; and 3) application of the NQI could help industry, authorities, and consumers improve products and diets.Looking at the results for NQI-adjusted GWP/ kg (GWP/kg divided with the NQI-value for the product) in the AD context, it can be observed that apples, tomatoes, hard cheese, and chicken fillets have lower NQI-adjusted GWP/kg values compared to bread than when using GWP/kg as the FU. This is because these products provide more nutritional value (i.e. higher NQI values) than does bread in this dietary context (AD). For apples and to- matoes, this is reinforced by the lack of disqualifying nutrients. The results for the NRF9.3-adjusted GWP differ relatively little from the NQI-adjusted GWP results for apples, tomatoes, milk, and chicken fillets. | Global warming potential | The proposed functional unit expresses the nutrient content of individual foods in relation to the nutritional supply of the complete diet, to create a single score reflecting the nutrient quality in a given dietary context. | Public health authorities can use the method to provide tailor-made dietary advice for population sub-groups. On a more detailed level, dietary interventions can use the NQI method to accurately choose what foods to increase and decrease in a diet, maximizing the health impact while reducing the environmental impact. | (GWP) between single products differed when using as functional unit either the mass of the food product, a nutrient quality index not considering the dietary context (the Nutrient Rich Foods Index 9.3, NRF9.3) and the new dietary dependent nutrient quality index (NQI) proposed. Two dietary scenarios were explored, an average Swedish diet and a typical unhealthy diet. | Positive | introducing NRF.3 when considering GWP per kg improves the environmental impact of chicken fillets, hard cheese and milk. | GWP/kg rel. values, bread = 100 Chicken fillets 625 Hard cheese 1484 Milk 156 NRF9.3-adjusted GWP/kg. rel. values, bread = 100 Chicken fillets 183.2 Hard cheese 815.3 Milk 82.1 NQI-adjusted GWP/Kg. rel. values Average Swedish Diet, bread = 100 Chicken fillets 264 Hard cheese 790 Milk 177 NQI-adjusted GWP/kg. rel. values Unhealthy Diet, bread = 100 Chicken fillets 592 Hard cheese 633 Milk 171 |
The complementary FU was based on available methods from nutritional science, but was developed to incorporate the dietary context and to constitute a dietary dependent nutrient quality in- dex (NQI). The two dietary contexts used in applying and evaluating the approach were Scandinavian and the products tested were foods consumed in Scandinavia. The diets were: 1) the average Swedish diet (AD) and 2) a typical “unhealthy” diet (UD). The environmental impacts were captured in terms of global warming potential (GWP), this narrow scope being chosen because the main objective was to evaluate the dietary dependent nutrition-based complementary FU. No new LCA results were generated; rather, previously published data were used. To evaluate the NQI-based FU, seven food products were chosen to represent products with different nutrient profiles, giving a basis for analysing and discus- sing the usability of the NQI. Available dietary quality scores were screened in a literature review (Hallstro€m et al., 2018). Based on an evaluation of completeness (i.e., coverage of different nutrients) and on data availability, the Nutrient Rich Foods Index, 9.3 (NRF9.3) was chosen. The method was presented by Drewnowski et al. (2009). NRF9.3 evaluates dietary quality based on the content of nine qualifying nutrients (i.e., nutrients positive for health) and three disqualifying nutrients (i.e., nutrients whose intakes should be limited). Development of the dietary dependent nutrient quality index based on NRF9.3 The NQI is quantified using an approach like that of NRF9.3, including the same nine qualifying nutrients and the three disqualifying nutrients. However, the qualifying nutrients are not capped, because the baseline is the actual and not the recommended dietary intake. This choice leads to some complexities, partly connected to the general challenges in nutrient quality models presented above (Nicklas et al., 2014). A product with a high content of a single nutrient whose dietary intake is low and simultaneously high levels of several disqualifying nutrients might still have a high NQI. |
The environmental performance of single food products can strongly be affected by the dietary contexts when using a dietary dependent nutrient quality index as functional unit. Including nutritional value in the LCA of foods improves our understanding of how the environmental impacts and nutritional functions of food are related to the broader aspects of sustain- ability. However, the complexity of the approach makes it difficult to use in direct product comparisons. | |||||
| 2684 | A. Strid; E. Hallström; U. Sonesson; J. Sjons; A. Winkvist; M. Bianchi | Strid, A., Hallström, E., Sonesson, U., Sjons, J., Winkvist, A. and Bianchi, M. (2021) 'Sustainability Indicators for Foods Benefiting Climate and Health', Sustainability, 13(7). | 2021 | Sweden | beef, pork, lamb, venison | Venison, red meat from ruminants (beef and lamb) minced meat (beef and pork) | production system | indicator | Even though food groups represented in Q5 differed to a certain extent among the three rankings, all three corresponded well with present dietary guidelines in terms of foods we should limit our consumption of. food subgroups with negative synergies between nutrition and climate performance (i.e., nutrient density below median and climate impact above median of included food subgroups) could easily be identified. These were mostly animal-based foods, and products with high fat and/or sugar content, e.g., red meat from ruminants (beef and lamb) and pork, minced meat (beef and pork), processed meat (sausage and cold cuts), cheese, and other high-fat dairy products, vegetable oils, snacks, sweets, and pastries (see Figure 2). The selection of foods represented in this quadrant also showed a high level of coherence with the dietary guidelines (i.e., including only foods that should be limited), with the exception of vegetable oil that is considered a healthier alternative to solid fat in the dietary guidelines. Foods with relatively higher nutrient density but also higher climate impact included animal-based foods such as liver paste, eggs, crustaceans, some fish species, and venison (deer bred in captivity), as well as seeds, dried fruit, and nuts (see Figure 2). Some differences in the categorization were found when climate impact was expressed per kcal instead of per kg of food subgroup; see Figure 3. For the food subgroups catego- rized as having high nutrient density, those with low-energy content, such as vegetables growing above ground, berries and citrus fruit, as well as drinks, e.g., juice and milk, were categorized as having a high instead of a low climate impact when calculated per kcal instead of per kg. Food subgroups with high-energy content, such as dried fruit, seeds, nuts, and liver paste were categorized as having a low instead of high climate impact when calculated per kcal instead of per kg. For the food subgroups categorized as having low nutrient density, the change of functional unit resulted in only few sub- groups changing categorizations from lower to higher climate impact (rice and alcoholic drinks). More food subgroups changed categorization from higher to lower climate impact, including high-fat food products, such as vegetable oils and margarine, and high-fat sugar- sweetened products, such as sweets, pastries, and ice cream. When ranked by the integrated climate-nutrient score, only plant-based food groups, such as vegetables, legumes, fruit, berries, wholegrain bread, enriched plant-based drinks, and juice were found in Q1. When ranked solely by nutrient density or solely by climate impact, many plant-based foods reoccurred in Q1. An important difference between rankings was the larger representation of foods with relatively lower nutrient density (soft drinks and plant-based cooking cream) in Q1 when food subgroups were ranked solely on climate impact, compared to the integrated climate-nutrient score. Top performing food subgroups in Q1 included more animal-based foods (e.g., liver paste, egg, and pelagic fish) when ranking was based on solely nutrient density, compared to the integrated climate- nutrient score. Since Q1 based on the integrated climate-nutrient score contained a larger proportion of foods which we should increase our consumption of according to dietary guidelines, and a lower proportion of foods which we should limit our consumption of (e.g., only juice), it corresponded more closely to the dietary guidelines than Q1 based on solely climate impact or nutrient density. When ranked by the integrated climate-nutrient score, high-fat dairy products, pro- cessed meat (sausage and cold cuts), minced meat (beef and pork), red meat from ruminants (beef and lamb), high-fat sweets, and pastries were found in Q5. Differences in outcome among the three rankings were the addition of crustaceans, pork, snacks, and low-fat cheese and the withdrawal of sugar-sweetened foods (ice cream, biscuits, cakes, chocolate, and candies) in Q5 when food subgroups were ranked solely based on climate impact compared to the integrated climate-nutrient score. When the ranking was based on solely nutrient density compared to the integrated climate-nutrient score, an addition of low-fat sugar- sweetened foods and drinks, such as honey, jams, and soft drinks, as well as a withdrawal of red meat from ruminants could be found in Q5. |
climate impact, GHGE, biodiversity loss, freshwater use, and land use change. Climate impact is expressed as kg carbon dioxide equivalents (CO2e) per kg food product. | NRF11.3 assigns a nutrient density score based on 11 nutrients (protein, dietary fiber, iron, folate, vitamins A, C, D, E, magnesium, calcium, potassium) to be encouraged (qualitative nutrients) and three nutrients (saturated fat, added sugar, sodium) to be limited (disqualitative nutrients). | A suboptimal diet is a strong, but preventable, risk factor for non-communicable disease morbidity and mortality [7], underscoring the need for improving diets globally. Identifying dietary patterns benefiting both health and environment is therefore crucial. | kgCO2eq/kg food // kgCO2eq/100 kcal food. No quantitative data. | Expressing climate impact per kg was shown to give advantage to foods with lower energy content and often high water content, whereas climate impact per kcal was shown to benefit foods with higher energy content. Since food LCA usually employs the functional unit mass, using kg instead of kcal to express climate impact in combined analyses with nutrient density was considered to simplify the interpretation of the categorization of the food subgroups. The integrated indicator showed better coherence with dietary guidelines than indica- tors based solely on nutrient density or solely on climate impact, and it was considered useful as an alternative method to incorporate nutritional aspects when comparing en- vironmental impacts of foods. | To evaluate nutrient density and climate impact of 118 foods commonly consumed in Sweden, To study implications of using parallel or integrated assessments when evaluating nutrient density and climate impact. To study implications of different reference units for calculating nutrient density and different functional units for calculating climate impact in these assessments. To discuss the usability and suitability of the parallel and integrated assessments in relation to the Swedish dietary guidelines and as tools in industry food product development and communication towards consumers. For the main analysis, climate impact was expressed by the functional unit kg of food; however, a complementary analysis using the functional unit kcal of food also was performed. For the integrated score, the ratio of climate impact to nutrient density was calculated by dividing kg CO2e per kg food product by NRF11.3 per reference unit of food product. | |||||||
| 2685 | A. Strid; I. Johansson; M. Bianchi; U. Sonesson; E. Hallström; B. Lindahl; A. Winkvist | Strid, A., Johansson, I., Bianchi, M., Sonesson, U., Hallström, E., Lindahl, B. and Winkvist, A. (2021) 'Diets benefiting health and climate relate to longevity in northern Sweden', American Journal of Clinical Nutrition, 114(2), pp. 515-529. | 2021 | Sweden | poultry, red meat, dairy | Food groups (g/day): Fast food, alcoholic drinks, sweet drinks, sugar, honey, jan, sweets and snacks, low fibre vegetables, high fibre vegetables, berries and fruits, fish, poultry, red meat, processed meat, potato, pasta, rice, white bread, low-fibre cereals, wholegrain bread, high fibre cereals, porridge, low-fat cheese, high-fat cheese, low-fat dairy products, high-fat dairy products, oil. butter, high fat margarine. | primary production up to and including the raw materials processing in the industry | Climate impact was expressed as kg carbon dioxide equivalents (CO2e) per kg edible food product (e.g., meat without bones) | The quality of the participants’ diets was scored using 3 variants of the NRF index and 5 versions thereof. The 3 variants were 1) the validated NRF9.3 (23); 2) NRF9.3 plus vitamin D and folate, to account for nutrients at risk of low intake in the Swedish population (yielding NRF11.3); and 3) an NRF index based on most nutrients specified in NNR2012 (1) yielding NRF21.3. Qualitative nutrients Protein, g Fiber, g Vitamin A, retinol equivalents Vitamin C, mg Vitamin E, mg Calcium, mg Iron, mg Potassium, g Magnesium, mg Vitamin D, μg Folate, μg Thiamin, mg Riboflavin, mg Omega-3 fatty acids, g Niacin, niacin equivalents Vitamin B-6, mg Vitamin B-12, μg Phosphorus, mg Iodine, μg Selenium, μg Zinc, mg Disqualitative nutrients Saturated fat, g Added sugars, g Sodium, g. Thereafter, women and men were ranked by age group into 4 groups, respectively, based on their diet quality as captured by the selected nutrient density index and dietary climate impact (see Figure 1): HNutr/LClim: higher nutrient density and lower climate impact HNutr/HClim: higher nutrient density and higher climate impact LNutr/LClim: lower nutrient density and lower climate impact LNutr/HClim: lower nutrient density and higher climate impact |
Dietary habits affect both human health (1–3) and global planetary health (4–7). A nutritionally adequate diet is crucial to prevent and treat noncommunicable diseases such as obesity, type 2 diabetes, and cardiovascular diseases. However, dietary patterns with a lower climate impact will not necessarily improve nutrient density or health outcomes (21), and dietary interventions based on nutrition recommendations have moreover shown that changes toward healthier dietary patterns in practice may not lead to decreased climate impact (22). In short, choosing diets beneficial for both health and climate is not obvious for consumers, and it is also not obvious how policy and dietary guidelines should be designed to benefit both perspectives. In addition, positive long-term health effects of such diets need to be verified. The results indicated that women with a diet of higher quality, no matter whether combined with higher or lower dietary climate impact, had a statistically significantly lower risk of total mortality than had the reference group with a diet of lower quality and higher dietary climate impact. Surprisingly, for men none of the groups with a diet of higher quality showed a lower risk of total mortality than the reference group. The EAT– Lancet Commission proposed a universal healthy reference diet from a sustainable food system (45). Our results and previous results (17) demonstrate that the Swedish population is far from such a diet and that strategies for making people shift their diet toward more sustainable options are acutely needed. Importantly, women and men with higher diet quality had a higher reported intake of vegetables, fruits, and berries, as well as high-fiber cereal products and low-fat dairy products, than had those with lower diet quality. The women and men with lower diet quality instead had a higher reported intake of sugar sweetened drinks and food products and high-fat dairy products, compared with those with higher diet quality. The 2 groups with higher dietary climate impact had a higher reported intake of red and processed meat, fish, and poultry than had the groups with lower dietary climate impact. The results demonstrated the usefulness of nutrient density indexes for predicting total mortality of diets, and that diets benefiting both health and climate are feasible and associated with lower mortality among women. The results also showed that diets with low climate impact may have either a positive or a negative impact on health, depending on the diet quality. In the evaluation of different nutrient density indexes, NRF11.3 with capping was identified as the diet quality index best predicting total mortality in the study population. Here, when examining the effect of diet quality irrespective of that of dietary climate impact, our results demonstrated an association between higher diet quality and lower mortality for both women and men, in line with other studies using various indexes for diet quality (40). In sum, our results suggest that nutrient density indexes are valid to predict risk of total mortality in general, including the specific NRF11.3 variant used here for the Swedish population. Nevertheless, men with lower diet quality and lower climate impact exhibited statistically significantly higher mortality risk (∼10% higher) than the reference group of lower diet quality and higher dietary climate impact. The same risk increase was found among women aged 35–44 y (∼50% higher). In addition, men aged 45–54 y with higher diet quality and lower climate impact exhibited statistically significantly higher mortality risk. the results indicate that dietary patterns with lower climate impact may affect the total mortality risk either positively or negatively, and both dietary climate impact and diet quality should be jointly accounted for. | Nutr (nutrient quality) /Clim (kgCO2eq) - no quantitative data | Dietary data from 49,124 women and 47,651 men aged 35–65 y in the population-based prospective study Västerbotten Intervention Programme (Sweden) were used. Greenhouse gas emissions (GHGEs) were estimated using data from life cycle assessments. Fifteen variants of nutrient density indexes were evaluated and the index that best predicted mortality was used to estimate participants’ nutrient density. GHGEs and nutrient density were adjusted for energy intakes. Total mortality risk was estimated by Cox proportional hazards models for 4 groups of women and men, respectively, i.e., higher nutrient density, lower climate impact (HNutr/LClim); higher nutrient density, higher climate impact (HNutr/HClim); lower nutrient density, lower climate impact (LNutr/LClim); and lower nutrient density, higher climate impact (LNutr/HClim—reference group). | When combined with dietary climate impact, women with higher diet quality and either a higher or a lower climate impact had a lower risk of total mortality, suggesting that a diet benefiting both health and climate is possible. The same conclusion could not be reached for men. This advocates further studies of how men can transition into more climate-sustainable and healthy diets. Among men and the younger group of women, a diet of lower diet quality and lower climate impact was associated with higher mortality than was a diet of lower diet quality and higher climate impact, highlighting that dietary patterns with lower climate impact can have either a positive or a negative impact on risk of total mortality depending on diet quality. | |||||||||
| 2767 | P. Tessari; A. Lante; G. Mosca | Tessari, P., Lante, A. and Mosca, G. (2016) 'Essential amino acids: master regulators of nutrition and environmental footprint?', Scientific Reports, 6. | 2016 | Italy | N/A | Beef, milk, pork, chicken | Parameter | the aim of this study was to re-assess the environmental footprint, expressed both as the land surface required for production, and as GHGE, of selected foods of either animal or vegetable sources, in respect to their EAAs content and daily requirements for humans. Following an extensive survey of scientific literature, we retrieved from published reports and databases, the land surface and GHGE estimates for the production of a limited number of “sample”, popular foods, of both animal and vegetal origin. We retrieved also the data about their edible fractions and amino acid composition. These data were comprehensively analysed to provide estimates of the environmental footprint associated to the production of specific amounts of these sample foods. |
land use for production and as Green House Gas Emission (GHGE) | EAA; The amino acid composition of most foods were derived from the database of the Italian National Institute for Research in Food and Nutrition (INRAN); The RDA values for the EAAs, referred to a 70-kg man, were those of the WHO/FAO/UNU 2002 report | N/A | GHGe LU | EAA/RDA EAA | Positive / negative | Environment-public health | When comparing GHGe per Kg, per EAA and per RDA EAA, there were minimal (sometimes nothing) differences for all ASF … approx. increase of 1gCO2e for Beef to reach RDA EAA. Exponential increase in vegetal foods… The estimated GHGE for food amounts satisfying the RDA of each EAA (beans, peas, wheat, rice and cauliflowers) actually became approximately equal to that of beef and sea bass, for peas and rice, ~40% greater for cauliflowers, while the gap between beef or fish, and beans, peas, wheat and potato was reduced The same for LU approx. increase of 1.6gCO2e for Beef to reach RDA EAA. Exponential increase in vegetal foods to reach same – with beans, peas, wheat, maize and rice and cauliflowers becoming equal to (beans more than) to beef. Food combinations: Only the combination including soy beans showed an environmental footprint markedly lower than that of beef. Note also the great amounts of rice and peas, as well as of pasta and beans, required to satisfy the EAA RDAs. |
Quantity / Quality | Previous investigators used a variety of approaches and parameters to estimate the “nutritional quality” of foods, also called “nutrient profile”, that were then implemented in different models6,8. The list of previously-used parameters, variably combined, include: 1) the nutrient content per 100 g of edible portion; 2) the daily recommended values for nutrients, with proteins considered as a whole; 3) the number of nutrients contained in a specific food; 4) the so-called “nutrient adequacy scores”; 5) the “nutrient density score”; 6) the energy density of foods (kcal/g); 7) the “limited nutrient score”; 8) the “maximum recommended values”, or, simply: 9) the caloric content6,8. By employing either of these models, estimates of the environmental footprint associated to nutrient consumption had been calculated6,8. The use of either of these terms and concepts doesn’t have only a semantic relevance, but it essential when transferring the nutritional parameters of food quantity and quality, to the environmental footprint associated to their production. |
The main conclusion of the study is that, under this perspective, the theoretical advantage of producing vegetal rather than animal proteins, is either markedly blunted, abolished or even reverted, with the notable exceptions of soybeans (still requiring ≈85% less land and producing ≈90% less GHGE, than those associated to beef meat). Also the production of other vegetal products (wheat, maize, cauliflowers and quinoa, Fig. 2a) required less land, and resulted in a lower GHGE (maize, beans, wheat and potato, Fig. 2b) than beef. However, large amounts of vegetables were required to comply with the RDA of all the EAA (with the exception of soybeans), as compared to animal proteins (Table 4). Production of high-quality animal proteins, in amounts sufficient to match the Recommended Daily Allowances of all the EAAs, would require a land use and a GHGE approximately equal, greater o smaller (by only ±1-fold), than that necessary to produce vegetal proteins, except for soybeans, that exhibited the smallest footprint. This new analysis downsizes the common concept of a large advantage, in respect to environmental footprint, of crops vs. animal foods production, when human requirements of EAAs are used for reference. |
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| 2834 | M. Tyszler; G. Kramer; H. Blonk | Tyszler, M., Kramer, G. and Blonk, H. (2016) 'Just eating healthier is not enough: studying the environmental impact of different diet scenarios for Dutch women (31–50 years old) by linear programming', International Journal of Life Cycle Assessment, 21(5), pp. 701-709. | 2016 | Netherlands | N/A | Beef, milk, pork, chicken | N/A | linear programming to find solutions that are as close as possible to the current diet of an average woman with age 31–50, first without any food groups’ constraints and later by imposing constraints on meat, fish, dairy, and eggs. Finally, we use a similar technique to search for the closest diet that achieves the same environmental reduction as the most restricted option (no meat, fish, dairy, or eggs), without restrictions on products We studied six dietary scenarios. average Dutch diet (Current diet), Closest healthy diet, a Vegetarian M diet, which excludes meat products; a Vegetarian MF diet, which excludes meat and fish; and a Vegan Footnote4 diet, which excludes meat, fish, dairy, and egg products. These diets were found by adding constraints on meat-based products or all animal-based products and then using the optimization tool to find the solutions closest to the current diet. Finally, we looked at a diet with 30 % less environmental impact (30 % less), which, instead of imposing constraints on food groups, includes only a constraint on the environmental impact. We choose this target, because it was the largest reduction achieved by the other preselected diets, which was in fact the vegan diet. |
GHGe | EPA + DHA—Eicosapentaenoic acid + Docosahexaenoic acid | N/A | Results are projected scenarios … there is no absolute values | Positive | Environment-public health | Removing meat and fish from the diet reduces the environmental impact by about 21 %. A healthy vegan diet reaches 30 % environmental impact reduction, but leads to a diet with many changes in comparison to a typical Dutch diet and without meeting one of the health constraints (EPA + DHA—Eicosapentaenoic acid + Docosahexaenoic acid). the closer a diet is to the frontier line, the more similar it is to the current diet, while being healthy. The Closest healthy and the 30 % less are, by construction, on the frontier. Notice how much further the Vegetarian and Vegan diets are from the frontier. This does not indicate per se that a Vegetarian or Vegan options are not valid, but it does indicate that, if the goal is simply to reduce the environmental impact, there are many other options possible to reach the same environmental goal with less changes |
Quality | Just eating healthier is not enough in order to reduce environmental impact. However, designing a diet that meets dietary requirements must be a prerequisite for sustainable diets. Simply removing products from a diet can have as consequence that other products have to be added to compensate for the nutritional imbalances. We show, by using linear programming, that it is possible to reach 30 % reduction in the environmental impact with a diet which is relatively similar to the current one and could be more likely to be accepted | |||||
| 2875 | K. van de Locht; I. Perrar; J. M. G. Paris; M. E. Schnermann; K. Oluwagbemigun; U. Alexy; U. Nothlings | van de Locht, K., Perrar, I., Paris, J. M. G., Schnermann, M. E., Oluwagbemigun, K., Alexy, U. and Nothlings, U. (2024) 'Environmental sustainability of diets among children and adolescents in the German DONALD cohort study: age and time trends, and nutrient adequacy', The American journal of clinical nutrition, 120(1), pp. 92-101. | 2024 | Germany | Meat, dairy, poultry | https://ars.els-cdn.com/content/image/1-s2.0-S0002916524004490-mmc1.pdfMeat products Dairy products Egg products Fish products Animal fats Vegetable oils Composite dishes and sauces Grain products Pulses, nuts, and seeds Potato products Vegetables and fruits Vegetarian/vegan products Non-alcoholic beverages Others |
unspecified | indicator | 3dWR in the highest tertiles of GHGE, LU, and WU per 1000 kcal had higher food amounts, intakes of total protein, animal protein, and PR, and lower intakes of added sugar. Across tertiles of GHGE and LU per 1000 kcal, intakes of carbohydrates, fiber, and plant protein decreased, and intakes of fat, saturated fat, and monounsaturated fat increased. Across WU tertiles, the opposite was true. For all 3 indicators, the MAR and the MARR were the highest in the second tertile and the lowest in the first tertile. IN ALL CASES GHGE/1000KCAL, LU/1000KCAL AND WU/1000KCAL - ANIMAL PROTEIN G/1000KCAL WAS HIGHER THAN PLANT PROTEIN G/1000G | GHGE/d (greenhouse gas emission [kgCO2eq]), LU/d (land use [m2 _x0002_ y]), and WU/d (water use [L]) . GHGE, LU, and WU per food item were converted to the reported amount consumed, and then the mean values of the 3 record days were calculated, resulting in kgCO2eq/day, m2 _x0002_ y/d, and L/d. In addition, GHGE, LU, and WU were each standardized per 1000 kcal/d total energy intake. | As an indicator for nutrient adequacy, the MAR [22] and the mean adequacy risk ratio (MARR) were calculated in each 3dWR | To identify the main determinants of GHGE, LU, and WU per day, the contribution of food groups to the 3 ecologic indicators was calculated by the mean value of GHGE, LU, and WU per food group (%) of all 3dWR. | kgCO2eq/1000 kcal/d | The overall aim of this study was to examine the effects of diets varying in nutrient density and climate impact on total mortality within a population-based prospective study in Sweden. As an indicator for nutrient adequacy, the MAR [22] and the mean adequacy risk ratio (MARR) were calculated in each 3dWR. The recommended nutrient intake was based on German reference values [23]. Each NAR included in the calculation of MAR was truncated at 100% if necessary to avoid reporting the overintake of a nutrient and compensation in the summation with the other NARs [22]. The number of nutrients included was 16 (Supplemental Table 1). The same calculation was used for the MARR as for the MAR. However, only NARs of the 7 most critical micronutrients (vitamin E, niacin, pantothenic acid, calcium, magnesium, iron, and zinc) in this study sample were included (supplemental Table 1). In the 3dWR, all foods and beverages consumed by the participants were weighted and recorded by the parents or by the older participants themselves for 3 consecutive days following the same protocols. The continuously updated inhouse nutrient database “LEB- ensmittelTABelle” (food table, LEBTAB) included nutrient data for staple foods based on the “Bundeslebensmittelschlüssel” (BLS, version 3.02) [17] as well as brand-specific foods estimated by recipe simu- lation using labeled ingredients and nutrient content including fortifi- cation [16]. All food items (9731) have been coded according to FoodEx2 [18], enabling linkage to ecologic indicator databases [19–21]. Energy and nutrient intake, and the consumption weight were calculated as the mean of the 3 record days. Carbohydrates, fat, protein, and added sugars were converted to percentage of energy intake; all other nutrients were expressed as per 1000 kcal. Additionally, an ani- mal protein-to-plant protein ratio (PR) in each 3dWR was calculated on a grams/day basis. | The 3 highest contributors to GHGE and LU per day (Figure 2) were meat products (GHGE: 25.6%; LU: 32.8%), dairy products (22.2%; 17.7%), and sweets and pastries (14.0%; 14.3%); followed by nonalcoholic beverages (12.0%) for GHGE/d and for LU/d by grain products (11.2%). The major contributors to WU/d were nonalcoholic beverages (24.3%), meat products (18.9%), vegetables and fruits (17.7%), and grain products (10.7%). | |||||||
| 2896 | K. Van Mierlo; L. Baert; E. Bracquené; J. De Tavernier; A. Geeraerd | Van Mierlo, K., Baert, L., Bracquené, E., De Tavernier, J. and Geeraerd, A. (2022) 'Moving from pork to soy-based meat substitutes: Evaluating environmental impacts in relation to nutritional values', Future Foods, 5. | 2022 | Belgium | pork | pork schnitzel and two soy-based schnitzels | cradle-to- gate production steps up to the point that the products are ready to be packed. | indicator | For a functional unit of 1 kg of product, the pork schnitzel induces the largest environmental impact for most environmental impact indicators. For functional units considering protein contents and protein quality, the impact of the soy schnitzels is higher than that of the pork schnitzel for multiple environmental impact indicators. The vegan soy schnitzel shows a lower impact than the vegetarian one, especially when the protein quality is considered. The largest contributor to the environmen- tal impact of the pork schnitzel is pig feed and energy use during slaughtering and meat processing. The largest contributors to the environmental impact of the soy schnitzels are soy protein concentrate, sunflower oil and energy, and chicken egg protein for the vegetarian soy schnitzel. In sum, it is environmentally and nutritionally more beneficial to replace the pork schnitzel with the vegan soy schnitzel than the vegetarian soy schnitzel. | climate change (kg CO2 eq.), ozone depletion (kg CFC-11 eq.), human toxicity (non-cancer and cancer effects, CTUh), particulate matter (kg PM2.5 eq.), ionizing radiation (human health (kBq U235 eq.) and ecosystem effects (CTUe)), photochemical ozone formation (kg NMVOC eq.), acid- ification (molc H+ eq.), eutrophication (terrestrial (molc N eq.), fresh- water (kg P eq.) and marine (kg N eq.)), freshwater ecotoxicity (CTUe), land use (kg C deficit), water resource depletion (m3 water eq.) and mineral, fossil & renewable resource depletion (kg Sb eq.). | functional units considering protein contents and protein quality (DIAAS) | Positive | (A) 1 kg of product (B) 1 kg of protein and (C) 1 kg protein•DIAAS. When considering environmental impacts with FU of 1kg product. Pork schnitzel preforms worst in all categories apart from human toxicity cancer effects, photochemical ozone formation and freshwater ecotoxicity. When considering environmental impacts with FU of 1kg protein, pork schnitzel preforms better than vegetarian soy schnitzel in land use, human toxicity cancer effects, photochemical ozone formation and freshwater ecotoxicity. Pork schnitzel also outperforms vegan soy schnitzel for freshwater ecotoxicity. When considering environmental impacts with FU of 1kg DIAAS; pork schnitzel preforms better than vegetarian soy schnitzel in terrestrial eutrophication, particulate matter, acidification, freshwater eutrophication, climate change, water resource depletion, land use, human toxicity cancer effects, photochemical ozone formation and freshwater ecotoxicity. Pork schnitzel preforms better than vegan soy schnitzel in human toxicity cancer effects, photochemical ozone formation and freshwater ecotoxicity. |
The protein contents of the products were retrieved from nutritional tables. The DIAAS of the schnitzels were calculated following the calculation methods recommended by the FAO (2013), based on the amino acid composition of the protein ingredients of the schnitzels (Norton et al., 2012; USDA, 2021) and the true ileal digestibility of the amino acids (Bailey et al., 2019; Kashyap et al., 2018; Moughan et al., | ||||||||
| 3016 | B. P. Weidema; K. S. Stylianou | Weidema, B. P. and Stylianou, K. S. (2020) 'Nutrition in the life cycle assessment of foods-function or impact?', International Journal of Life Cycle Assessment, 25(7), pp. 1210-1216. | 2020 | Unspecified | beef | burritos in the US diet. beef and a bean burrito | unspecified | Functional unit, impct pathway | Satiety is proposed as a central attribute for comparisons of food products, while weighted measures of nutrient content are suggested to be largely misplaced as part of the functional unit. In contrast, nutritional measures have a large role to play in assessing the human health impacts of the marginal ingestion of specific food products. Such measures should enable a direct quantification of human health effect and benefits and should take advantage of robust epidemiological evidence. Nutritional measures enter into both the functional unit in the form of satiety measures and into the calculation of impacts in the form of the marginal influence of the specific food item on the human health impact of the overall diet. To enhance the differentiation of health impacts at the level of individual food items, it is recommended to combine the nutrient balance indicator with the DALY Nutritional Index (DANI) in each specific dietary context. | |||||||||||||
| 3022 | L. B. Werner; A. Flysjö; T. Tholstrup | Werner, L. B., Flysjö, A. and Tholstrup, T. (2014) 'Greenhouse gas emissions of realistic dietary choices in Denmark: The carbon footprint and nutritional value of dairy products', Food and Nutrition Research, 58. | 2014 | Denmark | N/A | Beef, milk, pork, chicken | N/A | Created eight dietary scenarios with different quantity of dairy products using data from the Danish National Dietary Survey (1995–2006). Nutrient composition and GHGE data for 71 highly consumed foods were used to estimate GHGE and nutritional status for each dietary scenario. An index was used to estimate nutrient density in relation to nutritional recommendation and climate impact for solid food items; high index values were those with the highest nutrient density scores in relation to the GHGE. | GWP/KgCO2e | The 21 nutrients included in the present study were the ones specified by the NNR 2004 (protein, carbohydrates, fat, vitamin A, vitamin D, vitamin E, vitamin C, vitamin B12, niacin, thiamin, riboflavin, vitamin B6, folate, magnesium, iron, zinc, phosphorus, potassium, calcium, selenium, iodine) (see tables 4 and 5) (Citation64). The nutritional value for the food intake patterns were compared with the NNR for women aged 31–60 | N/A | Nutrient density to climate impact index (NDCI=nutrient density/GHGE); nutrient density=percentage of NNR in 100 g of product×number of nutrients ≥15% NNR/ 21; GHGE: greenhouse gas emission (gram CO2e per 100 g food item). | Positive | Environment-public health | 28 kg CO2e per kg Beef; Beef NCDI = 0.06 (gram CO2e per 100 g food item) (the lowest of all foods). 99 kg CO2e per kg cheese; Cheese NCDI = ~0.17 (gram CO2e per 100 g food item) 6 kg CO2e per kg pork; Pork NCDI = ~0.18 (gram CO2e per 100 g food item) 5 kg CO2e per kg chicken; Chicken NCDI = 0.1 (gram CO2e per 100 g food item) |
Quantity / quality | N/A | Excluding dairy products from our diet does not necessarily mitigate climate change; however, it may have nutritional consequences. This study shows that reducing consumption of food items with high or relative high GHGE is not necessarily the best approach to decreasing diet-related GHGE. If a product is replaced by food with lower energy density, the quantity needed to compensate for the caloric loss is greater than the quantity removed. This may result in a higher diet-related GHGE despite the lower GHGE per kg of the substituted product. In conclusion, this study shows that excluding dairy products from our diet does not necessary mitigate climate change but in contrast may have diametrical nutritional consequences. In addition, when optimizing a diet with regard to sustainability it is crucial to account for the nutritional value and not solely focus on impacts per kg products. | ||||
| 3177 | M. Zhang; H. Li; S. Chen; Y. Liu; S. Li | Zhang, M., Li, H., Chen, S., Liu, Y. and Li, S. (2023) 'Interrogating greenhouse gas emissions of different dietary structures by using a new food equivalent incorporated in life cycle assessment method', Environmental Impact Assessment Review, 103. | 2023 | United Kingdom | beef, dairy, poultry, pork, lamb | grain, non greenhouse/ greenhouse vegetable, non greenhouse/ greenhouse fruit, legume, nut, egg, chicken, milk, pork, lamb, beef, fish, shellfish and shrimp | unspecified | raw materials to regional distri- bution centers | GHG emissions from 15 food products based on either same mass or FE measured and compared by LCA showed that legumes, grains and nuts are low-carbon food product, whereas beef can provide the highest carbon emission. The GHG emission is depending on the type of food production. GHG emissions for grain are 2.19 kg CO2-eq, for legumes are 0.94 kg CO2-eq and for beef are 32.28 kg CO2-eq (Zhang et al., 2021). The GHG emissions of omnivorous diets are 3.24–3.92 kg CO2-eq/day/capita, whereas the GHG emissions of vegan diets are 2.61–3.13 kg CO2-eq/day/capita. Grains, legumes, nuts and chicken have a higher nutritional value the intake of anti-seasonal vegetables and anti-seasonal fruits should be reduced while more seasonal foods should be consumed. At same mass, non-greenhouse vegetable and fruit, grain, legume and nut were reported as ‘environmentally friendly’ foods that exhibited the lowest GHG emission, while lamb and beef showed high greenhouse impacts. The high emission of methane produced from the ruminant metabolic processes of cattle and sheep was the main contributor to increase greenhouse effects of their relevant foods. Compared to carbon dioxide that can be easily converted into oxygen by plant photosyn- thesis, while methane is difficult to be degraded and removed once released into the air. At same nutritional value, grain, legume and nut replaced the lowest GHG emission position of non-greenhouse vegetables and fruits. Nuts and grains contain more calories, protein and fat, while vegetables only provide vitamins and calories. It is reported that the average calorie per kilogram provided by grain (1.39 × 107 J) was ~4 times higher than that by vegetable (3.17 × 106 J) (Table S1, Table S2). The level of protein in grain (1015 g /kg) is ten times than that of fruit (108 g /kg) and twice for vegetables. The enhanced GHG emissions from greenhouse vegetables and fruits were attributed to the great amount of energy consumed in temperature maintenance for growths, making them less environmen- tally friendly foods. FE not only involves the nutritional information, but address the energy consumption details. Legume, grain and nut were studied as three most ‘green’ foods with limited GHG emission value lower than 0.06 kg CO2-eq and rich nutri- ents. Consistent with previous studies, GHG emission value of 0.094 kg CO2-eq for fruits and 0.075 kg CO2-eq for vegetables proved their limited effects on global warming. It is worth noting that vegetable and fruit in greenhouse have a much higher GHG emission than those in non- greenhouses due to the energy consumption from greenhouse building and temperature maintain. Shrimp and fish were highly GHG emission due to cargo ships which catch them use heavy oil. GHG emissions of ruminants (lamb and beef) meats were greatly higher than those of other food products. Therefore, to have a healthy and low-carbon diet, the proportion of anti-seasonal vegetables and fruits should be reduced, the large quantity of lamb and beef should be replaced by chicken and fish, and increase the consumption of grain, legume and nuts. |
GHG emissions | In this study, protein, vitamin and fiber were selected as nutrient substances to assess the nutritional level of food products. Based on that, nutrient score is the ratio of nutrients per kilogram of the food to the daily requirement of humans. To normalize the food product in FE-LCA, the unit of foods was adjusted to kg/week. | new food equivalent (FE) unit incorporated in LCA (FE-LCA) to investigate the greenhouse gas (GHG) emission and nutritional level (FEC) of different food and dietary structure. | positive | GHG References emission (kgCO2-eq/kg) Legume: 0.51 Beef: 26.61 % Difference: 192.48% GHG emission at FE=1 (kgCO2- eq) Legume: 0.032 Beef: 1.078 % Difference: 188.47% |
Mass | Mediterranean, New Nordic and Chinese diet were healthier and greener dietary structures. In these three diets, the low diary intake and food quality resulted in small FEC of Chinese diet. From Fig. 4 (B) Mediterranean diet showed reasonable compositions of foods with high proportion of vegetables and dairy products, and moderate intake of nuts and legumes. Therefore, by decreasing the consumption of beef and enhancing the supply of legumes (Harwatt et al., 2017), GHG emissions could be successfully reduced. Argentine diet presented the highest carbon emission due to extensive beef intake. The lowest GHG emission referred to Vegan diet but has a low FEC of 75.90 cannot supply the nutritional needs of human health. New Nordic Diet, Mediterranean Diet, Chinese Diet and Dutch Diet with reasonable GHG emission were recommended. They were characterized by a more balanced consumption of various food groups without a clear preference for a particular food group. In conclusion, the FE-LCA method is the most suitable method when evaluating food production. The GHG emission values indicate the environmental friendliness of the diet and the FEC values indicate the nutritional value of the diet. The high FEC of Argentine diet indicated its rich nutrients including beef and chicken, but the remarkable GHG emission value attributed to the excessive consumption of meat showed its strongest global warming effects. In contrary to Argentine diet, vegan diet that only involves vegetables and fruits exhibited the lowest FEC and GHG emission value, indicating its limited contribution to global warming, but inadequate nutrients supply for human body. GHG emission values of Dutch, Dutch healthy, Chinese, Mediterranean and New Nordic diets were at similar level of ~15, but significantly different in nutritional values. FEC of Dutch diet and Dutch healthy diet were different because meat and milk and dairy descend by 10.5% and 13.5% respectively, legume, fruit, nut, aquatic product and vegetable rising respectively 866.7%, 60.9%, 60%, 55.2% and 44.3% after improving diet structure. Though it had been widely accepted that Vegetarian and Traditional vegetarian diets were low-carbon dietary habits, for vegan and vegetarian diets, lacking of necessary nutrients especially for proteins (Colley et al., 2019) caused the small FEC, the Argentina diet difference in the average GHG emission showed it weak assistance to decrease the trend of global warming compared to Chinese, Mediterranean and New Nordic diets. Consequently, from the results of our study, Mediterranean, New Nordic and Chinese diet were healthier and greener dietary structures. In these three diets, the low diary intake and food quality resulted in small FEC of Chinese diet. From Fig. 4 (B) Mediterranean diet showed reasonable compositions of foods with high proportion of vegetables and dairy products, and moderate intake of nuts and legumes. Therefore, by decreasing the consumption of beef and enhancing the supply of legumes (Harwatt et al., 2017), GHG emissions could be successfully reduced. |
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| Paper number | Author | Reference | Year | Location / country(s) | Consideration of product or diet | Livestock type | Product type | system boundary | Terminology of indicator | (indicator) Impact summary | Environmental indicator(s) | Nutritional Indicator (s) | Public Health indicator (s) | combined indicator | Positive / negative impact on using combined indicator for livestock | Combined indicator outcome | impact actor - What is the impact on? | Co Efficient / n-lca output | Fus mass, protein quantity or protein quality | impact actor - What is the impact on? | Study methodology | Study outcome summary |