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Animal-sourced foods are required for minimum-cost nutritionally adequate food patterns for the United States

Nature Food volume 1, pages 376–381 (2020)Cite this article

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Abstract

The amounts of animal-sourced foods required to achieve a least-cost nutritious diet depend on the food prices prevalent in each country. Using linear programming, we determine least-cost dietary patterns in the United States and the constituent amounts of animal-sourced foods. We considered local foods and prices from 2009–2010, and the average energy and nutrient requirements of adults. Nutrient-adequate food patterns were estimated at US$1.98 per day and included animal and plant products. Limiting nutrients were α-linolenic acid, potassium, choline, and vitamins C, D, E and K. The prices of animal-based foods had to be increased by 2–11.5 times to be excluded from the modelled food pattern, with the least cost of a plant-only diet at US$3.61. Given relative food prices in the United States, we show that animal-based foods are needed to secure adequate nutrition at the lowest cost, underscoring the role of price and market mechanisms in the choice of nutrient-adequate, sustainable diets.

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Fig. 1: Daily intake of the 15 foods included in food pattern modelling for linear programming analysis 1 and the 14 foods for linear programming analysis 3.

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Data availability

All data used and generated during the current study are available from an online resource (https://gitlab.com/thetasolutionsllc/naturefood-19100372).

Code availability

The computer code required to reproduce the findings of this study is available from an online resource (https://gitlab.com/thetasolutionsllc/naturefood-19100372).

References

  1. Biodiversity and Sustainable Diets: United Against Hunger (FAO, 2010).

  2. Drewnowski, A. in Sustainable Nutrition in a Changing World 25–34 (Springer, 2017).

  3. National Nutrient Database for Standard Reference Release 28 (USDA, 2016); http://www.ars.usda.gov/nea/bhnrc/mafcl.

  4. Rehm, C. D., Monsivais, F. & Drewnowski, A. Relation between diet cost and Healthy Eating Index 2010 scores among adults in the United States 2007–2010. Prev. Med. 73, 70–75 (2015).

    Article  Google Scholar 

  5. Darmon, N. & Drewnowski, A. Contribution of food prices and diet cost to socioeconomic disparities in diet quality and health: a systematic review and analysis. Nutr. Rev. 73, 643–660 (2015).

    Article  Google Scholar 

  6. Headey, D. D. & Alderman, H. H.The relative caloric prices of healthy and unhealthy foods differ systematically across income levels and continents. J. Nutr. 149, 2020–2033 (2019).

    Article  Google Scholar 

  7. Dantzig, G. B. Linear Programming and Extensions (Princeton Univ. Press, 1963).

  8. Van Dooren, C. A review of the use of linear programming to optimize diets, nutritiously, economically and environmentally. Front. Nutr. 5, 48 (2018).

    Article  Google Scholar 

  9. Darmon, N., Ferguson, E. L. & Briend, A. Impact of a cost constraint on nutritionally adequate food choices for French women: an analysis by linear programming. J. Nutr. Educ. Behav. 38, 82–90 (2006).

    Article  Google Scholar 

  10. Cleveland, L. E., Escobar, A. J., Lutz, S. M. & Welsh, S. O. Methods for identifying differences between existing food intake patterns and patterns that meet nutrition recommendations. J. Am. Diet. Assoc. 93, 556–560, 563 (1993).

  11. National Academies of Sciences, Engineering, and Medicine Dietary Reference Intakes for Sodium and Potassium (National Academies Press, 2019).

  12. Institute of Medicine Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids (National Academies Press, 2002).

  13. Institute of Medicine Dietary Reference Intakes: The Essential Guide to Nutrient Requirements (National Academies Press, 2006).

  14. Institute of Medicine Dietary Reference Intakes for Water, Potassium, Sodium, Chloride, and Sulfate (National Academies Press, 2005).

  15. Nicklas, T. A., O’Neil, C. E. & Fulgoni, V. L. III The role of dairy in meeting the recommendations for shortfall nutrients in the American diet. J. Am. Coll. Nutr. 28, 73–81 (2009).

  16. 2015–2020 Dietary Guidelines for Americans (USHHS, USDA, 2015).

  17. IPCC Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) (World Meteorological Organization, 2018).

  18. Willet, W. et al. Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems. Lancet 393, 447–492 (2019).

    Article  Google Scholar 

  19. Adesogan, A. T., Havelaar, A. H., McKune, S. L., Eilitta, M. & Dahl, G. E. Animal source foods: sustainability problem or malnutrition and sustainability solution? Perspective matters. Glob. Food Secur. https://doi.org/10.1016/j.gfs.2019.100325 (2019).

  20. Darmon, N., Ferguson, E. L. & Briend, A. Linear and nonlinear programming to optimize the nutrient density of a population’s diet: an example based on diets of preschool children in rural Malawi. Am. J. Clin. Nutr. 75, 245–253 (2002).

    Article  CAS  Google Scholar 

  21. Darmon, N., Lacroix, A., Muller, L. & Ruffieux, B. Food price policies improve diet quality while increasing socioeconomic inequalities in nutrition. Int. J. Behav. Nutr. Phys. Act. 11, 66 (2014).

    Article  Google Scholar 

  22. Briend, A. & Darmon, N. Determining limiting nutrients by linear programming: a new approach to predict insufficient intakes from complementary foods. Pediatrics 106, 1288–1289 (2000).

    CAS  PubMed  Google Scholar 

  23. Hirvonen, K., Bai, Y., Headey, D. & Masters, W. A. Affordability of the EAT–Lancet reference diet: a global analysis. Lancet Glob. Health 8, 59–66 (2020).

    Article  Google Scholar 

  24. Alston, J. M., Sumner, D. A. & Vosti, S. A. Farm subsidies and obesity in the United States: national evidence and international comparisons. Food Policy 33, 470–479 (2008).

    Article  Google Scholar 

  25. Poverty Thresholds (US Census Bureau, 2010); https://www.census.gov/topics/income-poverty/data/tables.2010.html.

  26. Moughan, P. J. Holistic properties of foods: a changing paradigm in human nutrition. J. Sci. Food Agric. https://doi.org/10.1002/jsfa.8997 (2018).

  27. Bezanson, J., Edelman, A., Karpinski, S. & Shah, V. B. Julia: a fresh approach to numerical computing. SIAM Rev. 59, 65–98 (2017).

    Article  MathSciNet  Google Scholar 

  28. Dunning, I., Huchette, J. & Lubin, M. JuMP: a modeling language for mathematical optimization. SIAM Rev. 59, 295–320 (2017).

    Article  MathSciNet  Google Scholar 

  29. Balintfy, J. L. Menu planning by computer. Commun. ACM 7, 255–259 (1964).

    Article  Google Scholar 

  30. Stigler, G. J. The cost of subsistence. J. Farm Econ. 27, 303–314 (1945).

    Article  Google Scholar 

  31. Buttris, J. L. et al. Diet modelling: how it can inform the development of dietary recommendations and public health policy. Nutr. Bull. 39, 115–125 (2014).

    Article  Google Scholar 

  32. Gazan, R. et al. Mathematical optimization to explore tomorrow’s sustainable diets: a narrative review. Adv. Nutr. 9, 602–616 (2018).

    Article  Google Scholar 

  33. Gephart, J. A. et al. The environmental cost of subsistence: optimizing diets to minimize footprints. Sci. Total Environ. 553, 120–127 (2016).

    Article  ADS  CAS  Google Scholar 

  34. Code of Federal Regulations: Title 21—Food and Drugs Vol. 2, Section 101.12 (US FDA, 2017); https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/cfrsearch.cfm?fr=101.12.

  35. Institute of Medicine Dietary Reference Intakes for Calcium, Phosphorus, Magnesium, Vitamin D and Fluoride (National Academies Press, 1997).

  36. Institute of Medicine Dietary Reference Intakes for Thiamine, Riboflavin, Niacin, Vitamin B6, Folate, Vitamin B12, Pantothenic Acid, Biotin, and Choline (National Academies Press, 1998).

  37. Institute of Medicine Dietary Reference Intakes for Vitamin C, Vitamin E, Selenium, and Carotenoids (National Academies Press, 2000).

  38. Institute of Medicine Dietary Reference Intakes for Vitamin A, Vitamin K, Arsenic, Boron, Chromium, Copper, Iodine, Iron, Manganese, Molybdenum, Nickel, Silicon, Vanadium, and Zinc (National Academies Press, 2001).

  39. Institute of Medicine Dietary Reference Intakes for Calcium and Vitamin D (National Academies Press, 2011).

  40. Haytowitz, D. B. et al. Key foods: setting priorities for nutrient analyses. J. Food Composit. Anal. 9, 331–364 (1996).

    Article  Google Scholar 

  41. Haytowitz, D. B., Pehrsson, P. R. & Holden, J. M. The identification of key foods for food composition research. J. Food Composit. Anal. 15, 183–194 (2002).

    Article  CAS  Google Scholar 

  42. Haytowitz, D. B. Updating USDA’s key foods list for what we eat in America, NHANES 2011–12. Procedia Food Sci. 4, 71–78 (2015).

    Article  Google Scholar 

  43. Kuczmarski, R. J. et al. 2000 CDC growth charts for the United States: methods and development. Vital Health Stat. 246, 1–190 (2002).

    Google Scholar 

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Acknowledgements

The work reported was supported in part through funds from the National Dairy Council and Global Dairy Platform.

Author information

Authors and Affiliations

  1. Riddet Institute, Massey University, Palmerston North, New Zealand

    Sylvia M. S. Chungchunlam & Paul J. Moughan

  2. Theta Solutions, Atascadero, CA, USA

    Daniel P. Garrick

  3. AL Rae Centre for Genetics and Breeding, School of Agriculture and Environment, Massey University, Hamilton, New Zealand

    Daniel P. Garrick

  4. Center for Public Health Nutrition, University of Washington, Washington, DC, USA

    Adam Drewnowski

Authors
  1. Sylvia M. S. Chungchunlam
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  2. Paul J. Moughan
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  3. Daniel P. Garrick
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  4. Adam Drewnowski
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Contributions

S.M.S.C. and P.J.M. were responsible for the design and analysis of the study. D.P.G. was responsible for the linear programming modelling and analysis. A.D. was responsible for the provision of databases and consulting on the linear programming models. S.M.S.C. prepared the first draft of the manuscript. P.J.M revised the first draft of the manuscript. All authors participated in interpretation of the results and have read and approved the final manuscript.

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Correspondence to Sylvia M. S. Chungchunlam.

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The authors declare no competing interests.

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Supplementary information

Supplementary Table 1

Sensitivity analysis, with the shadow prices for all constraints sitting at either minimum or maximum, for linear programming analysis 1 and linear programming analysis 3.

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Chungchunlam, S.M.S., Moughan, P.J., Garrick, D.P. et al. Animal-sourced foods are required for minimum-cost nutritionally adequate food patterns for the United States. Nat Food 1, 376–381 (2020). https://doi.org/10.1038/s43016-020-0096-8

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