a research in nutrition

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• Published: 15 September 2023

Optimizing clinical nutrition research: the role of adaptive and pragmatic trials

• Camila E. Orsso   ORCID: orcid.org/0000-0001-5989-0528 1 ,
• Katherine L. Ford   ORCID: orcid.org/0000-0002-8620-9360 1 , 2 ,
• Nicole Kiss   ORCID: orcid.org/0000-0002-6476-9834 3 ,
• Elaine B. Trujillo   ORCID: orcid.org/0000-0002-8480-2427 4 ,
• Colleen K. Spees 5 ,
• Jill M. Hamilton-Reeves 6 , 7 &
• Carla M. Prado   ORCID: orcid.org/0000-0002-3609-5641 1  

European Journal of Clinical Nutrition volume  77 ,  pages 1130–1142 ( 2023 ) Cite this article

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• Clinical trials
• Randomized controlled trials

Evidence-based nutritional recommendations address the health impact of suboptimal nutritional status. Efficacy randomized controlled trials (RCTs) have traditionally been the preferred method for determining the effects of nutritional interventions on health outcomes. Nevertheless, obtaining a holistic understanding of intervention efficacy and effectiveness in real-world settings is stymied by inherent constraints of efficacy RCTs. These limitations are further compounded by the complexity of nutritional interventions and the intricacies of the clinical context. Herein, we explore the advantages and limitations of alternative study designs (e.g., adaptive and pragmatic trials), which can be incorporated into RCTs to optimize the efficacy or effectiveness of interventions in clinical nutrition research. Efficacy RCTs often lack external validity due to their fixed design and restrictive eligibility criteria, leading to efficacy-effectiveness and evidence-practice gaps. Adaptive trials improve the evaluation of nutritional intervention efficacy through planned study modifications, such as recalculating sample sizes or discontinuing a study arm. Pragmatic trials are embedded within clinical practice or conducted in settings that resemble standard of care, enabling a more comprehensive assessment of intervention effectiveness. Pragmatic trials often rely on patient-oriented primary outcomes, acquire outcome data from electronic health records, and employ broader eligibility criteria. Consequently, adaptive and pragmatic trials facilitate the prompt implementation of evidence-based nutritional recommendations into clinical practice. Recognizing the limitations of efficacy RCTs and the potential advantages of alternative trial designs is essential for bridging efficacy-effectiveness and evidence-practice gaps. Ultimately, this awareness will lead to a greater number of patients benefiting from evidence-based nutritional recommendations.

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Micha R, Peñalvo JL, Cudhea F, Imamura F, Rehm CD, Mozaffarian D. Association between dietary factors and mortality from heart disease, stroke, and type 2 diabetes in the United States. JAMA. 2017;317:912–24.

Article   PubMed   PubMed Central   Google Scholar  

Vinke PC, Navis G, Kromhout D, Corpeleijn E. Associations of diet quality and all-cause mortality across levels of cardiometabolic health and disease: A 7.6-year prospective analysis from the Dutch Lifelines Cohort. Diabetes Care. 2021;44:1228–35.

Article   CAS   PubMed   Google Scholar  

World Cancer Research Fund/American Institute for Cancer Research. Diet, Nutrition, Physical Activity and Cancer: A Global Perspective. Continuous Update Project Expert Report, 2018. https://www.wcrf.org/diet-activity-and-cancer/ . Accessed 17 Aug 2023.

Cederholm T, Jensen GL, Correia MITD, Gonzalez MC, Fukushima R, Higashiguchi T, et al. GLIM criteria for the diagnosis of malnutrition – A consensus report from the global clinical nutrition community. Clin Nutr. 2019;38:1–9.

Jensen GL, Cederholm T, Correia MITD, Gonzalez MC, Fukushima R, Higashiguchi T, et al. GLIM Criteria for the Diagnosis of Malnutrition: A Consensus Report From the Global Clinical Nutrition Community. J Parenter Enter Nutr. 2019;43:32–40.

Article   Google Scholar  

Prado C, Purcell S, Alish C, Pereira S, Deutz N, Heyland D, et al. Implications of low muscle mass across the continuum of care: A narrative review. Ann Med. 2018;50:675–93.

Article   PubMed   Google Scholar  

Gielen E, Beckwée D, Delaere A, De Breucker S, Vandewoude M, Bautmans I, et al. Nutritional interventions to improve muscle mass, muscle strength, and physical performance in older people: An umbrella review of systematic reviews and meta-analyses. Nutr Rev. 2021;79:121–47.

Bhat S, Coyle DH, Trieu K, Neal B, Mozaffarian D, Marklund M, et al. Healthy food prescription programs and their impact on dietary behavior and cardiometabolic risk factors: A systematic review and meta-analysis. Adv Nutr. 2021;12:1944–56.

Sempos CT, Liu K, Ernst ND. Food and nutrient exposures: What to consider when evaluating epidemiologic evidence. Am J Clin Nutr. 1999;69:1330S–1338S.

Thorpe KE, Zwarenstein M, Oxman AD, Treweek S, Furberg CD, Altman DG, et al. A pragmatic-explanatory continuum indicator summary (PRECIS): A tool to help trial designers. J Clin Epidemiol. 2009;62:464–75.

Courneya KS. Efficacy, effectiveness, and behavior change trials in exercise research. Int J Behav Nutr Phys Act. 2010;7:81.

Loudon K, Treweek S, Sullivan F, Donnan P, Thorpe KE, Zwarenstein M. The PRECIS-2 tool: Designing trials that are fit for purpose. BMJ. 2015;350:h2147.

Hébert JR, Frongillo EA, Adams SA, Turner-McGrievy GM, Hurley TG, Miller DR, et al. Perspective: Randomized controlled trials are not a panacea for diet-related research. Adv Nutr. 2016;7:423–32.

Lichtenstein AH, Petersen K, Barger K, Hansen KE, Anderson CAM, Baer DJ, et al. Perspective: Design and conduct of human nutrition randomized controlled trials. Adv Nutr. 2021;12:4–20.

Flay BR, Biglan A, Boruch RF, Castro FG, Gottfredson D, Kellam S, et al. Standards of evidence: Criteria for efficacy, effectiveness and dissemination. Prev Sci. 2005;6:151–75.

Weaver CM, Miller JW. Challenges in conducting clinical nutrition research. Nutr Rev. 2017;75:491–9.

Ford KL, Sawyer MB, Trottier CF, Ghosh S, Deutz NEP, Siervo M, et al. Protein Recommendation to Increase Muscle (PRIMe): Study protocol for a randomized controlled pilot trial investigating the feasibility of a high protein diet to halt loss of muscle mass in patients with colorectal cancer. Clin Nutr ESPEN. 2021;41:175–85.

Boushey CJ, Harris J, Bruemmer B, Archer SL. Publishing nutrition research: A review of sampling, sample size, statistical analysis, and other key elements of manuscript preparation, part 2. J Am Diet Assoc. 2008;108:679–88.

Lam CN, Watt AE, Isenring EA, de van der Schueren MAE, van der Meij BS. The effect of oral omega-3 polyunsaturated fatty acid supplementation on muscle maintenance and quality of life in patients with cancer: A systematic review and meta-analysis. Clin Nutr. 2021;40:3815–26.

Lambell KJ, King SJ, Forsyth AK, Tierney AC. Association of energy and protein delivery on skeletal muscle mass changes in critically ill adults: A systematic review. J Parenter Enter Nutr. 2018;42:1112–22.

Findlay M, Bauer JD, Dhaliwal R, de van der Schueren M, Laviano A, Widaman A, et al. Translating evidence-based guidelines into practice—are we getting it right? A multi-centre prospective international audit of nutrition care in patients with foregut tumors (INFORM). Nutrients. 2020;12:3808.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Laur C, Johnsen JT, Bradfield J, Eden T, Mitra S, Ray S. Closing the gap: Data-based decisions in food, nutrition and health systems: Proceedings of the Fifth International Summit on Medical and Public Health Nutrition Education and Research. BMJ Nutr Prev Heal. 2020;3:397–402.

Groenwold RHH The efficacy-effectiveness gap. In: Girman CJ, Ritchey ME (eds). Pragmatic randomized clinical trials: Using primary data collection and electronic health records . London: Academic Press; 2021. pp 9–19.

Fiaccadori E, Sabatino A, Barazzoni R, Carrero JJ, Cupisti A, De Waele E, et al. ESPEN guideline on clinical nutrition in hospitalized patients with acute or chronic kidney disease. Clin Nutr. 2021;40:1644–68.

Arends J, Bachmann P, Baracos V, Barthelemy N, Bertz H, Bozzetti F, et al. ESPEN guidelines on nutrition in cancer patients. Clin Nutr. 2017;36:11–48.

Muscaritoli M, Arends J, Bachmann P, Baracos V, Barthelemy N, Bertz H, et al. ESPEN practical guideline: Clinical Nutrition in cancer. Clin Nutr. 2021;40:2898–913.

Clinton SK, Giovannucci EL, Hursting SD. The World Cancer Research Fund/American Institute for Cancer Research Third Expert Report on Diet, Nutrition, Physical Activity, and Cancer: Impact and future directions. J Nutr. 2020;150:663–71.

Dimairo M, Pallmann P, Wason J, Todd S, Jaki T, Julious SA, et al. The Adaptive designs CONSORT Extension (ACE) statement: A checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design. BMJ. 2020;369:m115.

Hiremath S, Fergusson D, Knoll G, Ramsay T, Kong J, Ruzicka M. Diet or additional supplement to increase potassium intake: Protocol for an adaptive clinical trial. Trials. 2022;23:147.

Pallmann P, Bedding AW, Choodari-Oskooei B, Dimairo M, Flight L, Hampson LV, et al. Adaptive designs in clinical trials: Why use them, and how to run and report them. BMC Med. 2018;16:29.

Schuetz P, Fehr R, Baechli V, Geiser M, Deiss M, Gomes F, et al. Individualised nutritional support in medical inpatients at nutritional risk: A randomised clinical trial. Lancet. 2019;393:2312–21.

Califf RM, Sugarman J. Exploring the ethical and regulatory issues in pragmatic clinical trials. Clin Trials. 2015;12:436.

Zwarenstein M, Treweek S, Gagnier JJ, Altman DG, Tunis S, Haynes B, et al. Improving the reporting of pragmatic trials: An extension of the CONSORT statement. BMJ. 2008;337:1223–6.

Pan A, Lin X, Hemler E, Hu FB. Diet and cardiovascular disease: Advances and challenges in population-based studies. Cell Metab. 2018;27:489–96.

Friedman LM, Furberg CD, DeMets DL, Reboussin DM, Granger CB. Fundamentals of clinical trials. 5 th ed. Switzerland: Springer International Publishing; 2015.

Kernan WN, Viscoli CM, Makuch RW, Brass LM, Horwitz RI. Stratified randomization for clinical trials. J Clin Epidemiol. 1999;52:19–26.

Vorland CJ, Brown AW, Dawson JA, Dickinson SL, Golzarri-Arroyo L, Hannon BA, et al. Errors in the implementation, analysis, and reporting of randomization within obesity and nutrition research: A guide to their avoidance. Int J Obes. 2021;45:2335–46.

Most MM, Ershow AG, Clevidence BA. An overview of methodologies, proficiencies, and training resources for controlled feeding studies. J Am Diet Assoc. 2003;103:729–35.

Tiwari U, Cummins E. Factors influencing levels of phytochemicals in selected fruit and vegetables during pre- and post-harvest food processing operations. Food Res Int. 2013;50:497–506.

Article   CAS   Google Scholar  

Sorkin BC, Kuszak AJ, Williamson JS, Hopp DC, Betz JM. The challenge of reproducibility and accuracy in nutrition research: Resources and pitfalls. Adv Nutr. 2016;7:383–9.

Staudacher HM, Irving PM, Lomer MCE, Whelan K. The challenges of control groups, placebos and blinding in clinical trials of dietary interventions. Proc Nutr Soc. 2017;76:203–12.

Jenab M, Slimani N, Bictash M, Ferrari P, Bingham SA. Biomarkers in nutritional epidemiology: Applications, needs and new horizons. Hum Genet. 2009;125:507–25.

Berk L, James J, Schwartz A, Hug E, Mahadevan A, Samuels M, et al. A randomized, double-blind, placebo-controlled trial of a β-hydroxyl β-methyl butyrate, glutamine, and arginine mixture for the treatment of cancer cachexia (RTOG 0122). Support Care Cancer. 2008;16:1179–88.

Yang J, Zhang X, Li K, Zhou Y, Hu Y, Chen X, et al. Effects of EN combined with PN enriched with n-3 polyunsaturated fatty acids on immune related indicators and early rehabilitation of patients with gastric cancer: A randomized controlled trial. Clin Nutr. 2022;41:1163–70.

Hanai N, Terada H, Hirakawa H, Suzuki H, Nishikawa D, Beppu S, et al. Prospective randomized investigation implementing immunonutritional therapy using a nutritional supplement with a high blend ratio of ω-3 fatty acids during the perioperative period for head and neck carcinomas. Jpn J Clin Oncol. 2018;48:356–61.

Sousa IM, Gonzalez MC, Bielemann RM, Rocha IMG, Barbalho ER, Carvalho ALM, et al. Agreement between muscle mass assessments by computed tomography and calf circumference in patients with cancer: A cross-sectional study. Clin Nutr ESPEN. 2022;47:183–8.

Orkin AM, Gill PJ, Ghersi D, Campbell L, Sugarman J, Emsley R, et al. Guidelines for reporting trial protocols and completed trials modified due to the COVID-19 pandemic and other extenuating circumstances: The CONSERVE 2021 Statement. JAMA. 2021;326:257–65.

Hui D, Glitza I, Chisholm G, Yennu S, Bruera E. Attrition rates, reasons, and predictive factors in supportive care and palliative oncology clinical trials. Cancer. 2013;119:1098–105.

Upadhaya S, Yu JX, Oliva C, Hooton M, Hodge J, Hubbard-Lucey VM. Impact of COVID-19 on oncology clinical trials. Nat Rev Drug Discov. 2020;19:376–7.

Edbrooke L, Khaw P, Freimund A, Carpenter D, McNally O, Joubert L, et al. ENhAncing Lifestyle Behaviors in EndometriaL CancEr (ENABLE): A pilot randomized controlled trial. Integr Cancer Ther. 2022;21:153473542110698.

Thomas EA, Zaman A, Sloggett KJ, Steinke S, Grau L, Catenacci VA, et al. Early time-restricted eating compared with daily caloric restriction: A randomized trial in adults with. Obes Obes. 2022;30:1027–38.

CAS   Google Scholar  

Mavridis D, White IR. Dealing with missing outcome data in meta-analysis. Res Synth Methods. 2020;11:2–13.

Mekanna AN, Panchal SK, Li L. Beyond lockdowns: A systematic review of the impacts of COVID-19 lockdowns on dietary pattern, physical activity, body weight, and food security. Nutr Rev. 2023;81:790–803.

Park JJH, Mogg R, Smith GE, Nakimuli-Mpungu E, Jehan F, Rayner CR, et al. How COVID-19 has fundamentally changed clinical research in global health. Lancet Glob Heal. 2021;9:e711–e720.

Glasziou P, Scott AM, Chalmers I, Kolstoe SE, Davies HT. Improving research ethics review and governance can improve human health. J R Soc Med. 2021;114:556–62.

Almeida-Magana R, Maroof H, Grierson J, Clow R, Dinneen E, Al-Hammouri T, et al. E-Consent—a guide to maintain recruitment in clinical trials during the COVID-19 pandemic. Trials. 2022;23:388.

Strujo E, Sanders M, Fiscella K, Thomas M, Johnson B, Deets A, et al. COVID-19 impact on multi-site recruitment and enrollment. Clin Trials. 2020;17:501–4.

Hoenemeyer TW, Cole WW, Oster RA, Pekmezi DW, Pye A, Demark-Wahnefried W. Test/retest reliability and validity of remote vs. in-person anthropometric and physical performance assessments in cancer survivors and supportive partners. Cancers. 2022;14:1075.

O’Shea AMJ, Baum A, Haraldsson B, Shahnazi A, Augustine MR, Mulligan K, et al. Association of adequacy of broadband internet service with access to primary care in the Veterans Health Administration before and during the COVID-19 pandemic. JAMA Netw Open. 2022;5:e2236524.

De Guzman KR, Caffery LJ, Smith AC, Snoswell CL. Specialist consultation activity and costs in Australia: Before and after the introduction of COVID-19 telehealth funding. J Telemed Telecare. 2021;27:609–14.

Burnett T, Mozgunov P, Pallmann P, Villar SS, Wheeler GM, Jaki T. Adding flexibility to clinical trial designs: An example-based guide to the practical use of adaptive designs. BMC Med. 2020;18:352.

Giovagnoli A. The bayesian design of adaptive clinical trials. Int J Environ Res Public Health. 2021;18:530.

Gallo P. Confidentiality and trial integrity issues for adaptive designs. Drug Inf J. 2006;40:445–9.

Sepehrvand N, Alemayehu W, Das D, Gupta AK, Gouda P, Ghimire A, et al. Trends in the explanatory or pragmatic nature of cardiovascular clinical trials over 2 decades. JAMA Cardiol. 2019;4:1122–8.

Godwin M, Ruhland L, Casson I, MacDonald S, Delva D, Birtwhistle R, et al. Pragmatic controlled clinical trials in primary care: The struggle between external and internal validity. BMC Med Res Methodol. 2003;3:28.

Appel LJ, Michos ED, Mitchell CM, Blackford AL, Sternberg AL, Miller ER, et al. The effects of four doses of vitamin D supplements on falls in older adults a response-adaptive, randomized clinical trial. Ann Intern Med. 2021;174:145–56.

de van der Schueren MAE, Laviano A, Blanchard H, Jourdan M, Arends J, Baracos VE. Systematic review and meta-analysis of the evidence for oral nutritional intervention on nutritional and clinical outcomes during chemo(radio)therapy: Current evidence and guidance for design of future trials. Ann Oncol. 2018;29:1141–53.

Chaitman BR, Pepine CJ, Parker JO, Skopal J, Chumakova G, Kuch J, et al. Effects of ranolazine with atenolol, amlodipine, or diltiazem on exercise tolerance and angina frequency in patients with severe chronic angina: A randomized controlled trial. JAMA. 2004;291:309–16.

Zajicek JP, Hobart JC, Slade A, Barnes D, Mattison PG. Multiple sclerosis and extract of cannabis: Results of the MUSEC trial. J Neurol Neurosurg Psychiatry. 2012;83:1125–32.

Miller E, Gallo P, He W, Kammerman LA, Koury K, Maca J, et al. DIA’s Adaptive Design Scientific Working Group (ADSWG): Best Practices Case Studies for ‘Less Well-understood’ Adaptive Designs. Ther Innov Regul Sci. 2017;51:77–88.

Marquis-Gravel G, Faulkner M, Merritt G, Farrehi P, Zemon N, Robertson HR, et al. Importance of patient engagement in the conduct of pragmatic multicenter randomized controlled trials: The ADAPTABLE experience. Clin Trials. 2022;20:31–5.

Slattery P, Saeri AK, Bragge P. Research co-design in health: A rapid overview of reviews. Heal Res Policy Syst. 2020;18:17.

Pfaff E, Lee A, Bradford R, Pae J, Potter C, Blue P, et al. Recruiting for a pragmatic trial using the electronic health record and patient portal: Successes and lessons learned. J Am Med Inform Assoc. 2019;26:44–9.

Weinfurt KP, Hernandez AF, Coronado GD, DeBar LL, Dember LM, Green BB, et al. Pragmatic clinical trials embedded in healthcare systems: Generalizable lessons from the NIH Collaboratory. BMC Med Res Methodol. 2017;17:1–10.

Coffey CS, Levin B, Clark C, Timmerman C, Wittes J, Gilbert P, et al. Overview, hurdles, and future work in adaptive designs: Perspectives from a National Institutes of Health-funded workshop. Clin Trials. 2012;9:671–80.

Trujillo EB, Claghorn K, Dixon SW, Hill EB, Braun A, Lipinski E, et al. Inadequate nutrition coverage in outpatient cancer centers: Results of a national survey. J Oncol. 2019;2019:7462940.

Subar AF, Freedman LS, Tooze JA, Kirkpatrick SI, Boushey C, Neuhouser ML, et al. Addressing current criticism regarding the value of self-report dietary data. J Nutr. 2015;145:2639–45.

Reijnierse EM, De Van Der Schueren MAE, Trappenburg MC, Doves M, Meskers CGM, Maier AB. Lack of knowledge and availability of diagnostic equipment could hinder the diagnosis of sarcopenia and its management. PLoS One. 2017;12:e0185837.

Prado CM, Landi F, Chew ST, Atherton PJ, Molinger J, Ruck T, et al. Advances in muscle health and nutrition: A toolkit for healthcare professionals. Clin Nutr. 2022;41:2244–63.

Cuzick J, Edwards R, Segnan N. Adjusting for non-compliance and contamination in randomized clinical trials. Stat Med. 1997;16:1017–29.

Ford I, Norrie J. Pragmatic trials. N. Engl J Med. 2016;375:454–63.

Lund LH, Oldgren J, James S. Registry-based pragmatic trials in heart failure: Current experience and future directions. Curr Heart Fail Rep. 2017;14:59–70.

Palmer JA, Parker VA, Barre LR, Mor V, Volandes AE, Belanger E, et al. Understanding implementation fidelity in a pragmatic randomized clinical trial in the nursing home setting: A mixed-methods examination. Trials. 2019;20:656.

Roeland EJ, Bohlke K, Baracos VE, Bruera E, Del Fabbro E, Dixon S, et al. Management of cancer cachexia: ASCO guideline. J Clin Oncol. 2020;38:2438–53.

Arends J, Strasser F, Gonella S, Solheim TS, Madeddu C, Ravasco P, et al. Cancer cachexia in adult patients: ESMO Clinical Practice Guidelines. ESMO Open. 2021;6:100092.

Laviano A, Medicine P. Current guidelines for nutrition therapy in cancer: The arrival of a long journey or the starting point? JPNEN J Parenter Enter Nutr. 2021;45:12–15.

Google Scholar  

Hiatt RA, Clayton MF, Collins KK, Gold HT, Laiyemo AO, Parker Truesdale K, et al. The Pathways to Prevention (P2P) Program: Nutrition as Prevention for Improved Cancer Outcomes. J Natl Cancer Inst. 2023;115:886–95.

Ravasco P. Nutrition in cancer patients. J Clin Med. 2019;8:1211.

Trujillo EB, Hays C, Regan K, Ross S, Seifried H. Nutrition research funding trends and focus areas at the US National Cancer Institute. JNCI Cancer Spectr. 2022;6:pkac064.

Khorasanchi A, Nemani S, Pandey S, Del Fabbro E. Managing nutrition impact symptoms in cancer cachexia: A case series and mini review. Front Nutr. 2022;9:831934.

Nipp RD, Yao NA, Lowenstein LM, Buckner JC, Parker IR, Gajra A, et al. Pragmatic study designs for older adults with cancer: Report from the U13 conference. J Geriatr Oncol. 2016;7:234–41.

Parks RM, Holmes HM, Cheung KL. Current challenges faced by cancer clinical trials in addressing the problem of under-representation of older adults: a narrative review. Oncol Ther. 2021;9:55–67.

Nipp RD, Hong K, Paskett ED. Overcoming barriers to clinical trial enrollment. Am Soc Clin Oncol Educ B. 2019;39:105–14.

Saunders D, Liu M, Vandermeer L, Alzahrani MJ, Hutton B, Clemons M. The Rethinking Clinical Trials (REaCT) program. A Canadian-led pragmatic trials program: Strategies for integrating knowledge users into trial design. Curr Oncol. 2021;28:3959–77.

Carlson SE, Gajewski BJ, Valentine CJ, Kerling EH, Weiner CP, Cackovic M, et al. Higher dose docosahexaenoic acid supplementation during pregnancy and early preterm birth: a randomised, double-blind, adaptive-design superiority trial. EClinicalMedicine. 2021;36:100905.

Salchow J, Mann J, Koch B, Von Grundherr J, Jensen W, Elmers S, et al. Comprehensive assessments and related interventions to enhance the long-term outcomes of child, adolescent and young adult cancer survivors - Presentation of the CARE for CAYA-Program study protocol and associated literature review. BMC Cancer. 2020;20:16.

Downs DS, Savage JS, Rivera DE, Smyth JM, Rolls BJ, Hohman EE, et al. Individually tailored, adaptive intervention to manage gestational weight gain: Protocol for a randomized controlled trial in women with overweight and obesity. JMIR Res Protoc. 2018;7:e150.

Al Wattar HB, Dodds J, Placzek A, Beresford L, Spyreli E, Moore A, et al. Mediterranean-style diet in pregnant women with metabolic risk factors (ESTEEM): A pragmatic multicentre randomised trial. PLoS Med. 2019;16:e1002857.

Fortin M, Stewart M, Ngangue P, Almirall J, Bélanger M, Brown JB, et al. Scaling up patient-centered interdisciplinary care for multimorbidity: A pragmatic mixed-methods randomized controlled trial. Ann Fam Med. 2021;19:126–34.

Colin-Ramirez E, Ezekowitz JA. Rationale and design of the Study of Dietary Intervention Under 100 MMOL in Heart Failure (SODIUM-HF). Am Heart J. 2018;205:87–96.

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This research received no specific grant from any funding agency, commercial or not-for-profit sectors. CMP was funded by as a Campus Alberta Innovation Program Chair in Nutrition, Food, and Health. Support for time for JHR was provided by National Institutes of Health MERIT award (R37CA218118) and by the Nutrition Shared Resource through the National Cancer Institute Cancer Center support grant (P30 CA16852); the contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.

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Camila E. Orsso, Katherine L. Ford & Carla M. Prado

Department of Kinesiology & Health Sciences, University of Waterloo, Waterloo, ON, Canada

• Katherine L. Ford

Institute for Physical Activity and Nutrition, Deakin University, Geelong, VIC, Australia

Nicole Kiss

Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Rockville, MD, USA

Elaine B. Trujillo

Divison of Medical Dietetics, School of Health and Rehabilitation Sciences, The Ohio State University College of Medicine, Columbus, OH, USA

Colleen K. Spees

Department of Urology, University of Kansas Medical Center, Kansas City, KS, USA

Jill M. Hamilton-Reeves

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CEO and CMP designed research; CEO and KLF conducted literature search; CEO, KLF, and CMP contributed to writing—original draft preparation; CEO, KLF, NK, EBT, CKS, JHR, and CMP contributed to writing—review and editing. All authors have read and approved the final manuscript.

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Correspondence to Carla M. Prado .

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CEO has received honoraria from Abbott Nutrition. CMP has previously received honoraria and/or paid consultancy from Abbott Nutrition, Nutricia, Nestlé Health Science, Fresenius Kabi, AMRA Medical, and Pfizer. NK has received honoraria and/or paid consultancy from Abbott Australasia. KLF, EBT, CKS, JHR—no conflicts of interest.

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Orsso, C.E., Ford, K.L., Kiss, N. et al. Optimizing clinical nutrition research: the role of adaptive and pragmatic trials. Eur J Clin Nutr 77 , 1130–1142 (2023). https://doi.org/10.1038/s41430-023-01330-7

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Received : 19 May 2023

Revised : 08 August 2023

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Published : 15 September 2023

Issue Date : December 2023

DOI : https://doi.org/10.1038/s41430-023-01330-7

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• Cherie Russell   ORCID: orcid.org/0000-0003-1251-4810 1 ,
• Jillian Whelan   ORCID: orcid.org/0000-0001-9434-109X 2 &
• Penelope Love   ORCID: orcid.org/0000-0002-1244-3947 1 , 3  

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Purpose of Review

Poor diets are a leading risk factor for chronic disease globally. Research suggests healthy foods are often harder to access, more expensive, and of a lower quality in rural/remote or low-income/high minority areas. Food pricing studies are frequently undertaken to explore food affordability. We aimed to capture and summarise food environment costing methodologies used in both urban and rural settings.

Recent Findings

Our systematic review of high-income countries between 2006 and 2021 found 100 relevant food pricing studies. Most were conducted in the USA ( n  = 47) and Australia ( n  = 24), predominantly in urban areas ( n  = 74) and cross-sectional in design ( n  = 76). All described a data collection methodology, with just over half ( n  = 57) using a named instrument. The main purpose for studies was to monitor food pricing, predominantly using the ‘food basket’, followed by the Nutrition Environment Measures Survey for Stores (NEMS-S). Comparatively, the Healthy Diets Australian Standardised Affordability and Price (ASAP) instrument supplied data on relative affordability to household incomes.

Future research would benefit from a universal instrument reflecting geographic and socio-cultural context and collecting longitudinal data to inform and evaluate initiatives targeting food affordability, availability, and accessibility.

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Introduction

Poor diets, described as those low in fruits, vegetables, and whole grains, and high in red and processed meats and ultra-processed foods, are a leading risk factor for chronic disease globally [ 1 ]. In most high-income countries (HIC), poor diets disproportionally affect lower socioeconomic populations, Indigenous Peoples, and those living in rural and/or remote areas [ 2 , 3 , 4 , 5 ]. Rather than solely a consequence of individual behaviours, poor diets are critically informed by broad contextual factors, including social, commercial, environmental, and cultural influences [ 6 , 7 ]. Crucially, the consumption of a healthy diet is constrained by the range, affordability, and acceptability of foods available for sale [ 8 ]. Research suggests that healthy foods are often harder to access, more expensive, and often of a lower quality in rural, remote, or low-income/high minority areas, than in metropolitan or high-income areas [ 9 , 10 , 11 , 12 ]. Such food environments contribute to higher rates of diet-related non-communicable diseases and food insecurity [ 13 , 14 ]. In order to improve population diets, all aspects of the food environment must be addressed to ensure healthy foods are affordable, available, and of adequate nutritional quality [ 15 ].

Price is a primary factor impacting food choice, diet quality, and food security, therefore having affordable, acceptable, healthy food should be a political and social priority [ 8 , 15 , 16 ]. Some research suggests that healthy diets are associated with greater total spending [ 17 , 18 , 19 ], while other studies report that adherence to a healthy diet is less expensive than current or ‘unhealthy’ diets [ 9 , 20 , 21 ]. Regardless, the cost of a healthy diet is a proportionately large household expense (> 30% of household income) and may therefore be considered ‘unaffordable’ [ 22 ]. Additionally, public perception that healthy diets are expensive is high, which itself may be a barrier to the purchase of healthy foods [ 23 ]. Therefore, improving the affordability of healthy food could improve population diets, regardless of context [ 24 ].

To address the issue of food affordability and inform appropriate attenuating policy and intervention strategies, food pricing studies are frequently undertaken. Food pricing, however, is not a universal construct and is highly influenced by country and context. Numerous methods have been developed to measure food pricing, with data therefore not always comparable or replicable, and of limited value to inform appropriate policy [ 25 ]. Most studies that collect food pricing data conclude that food prices are rising, making healthy eating unaffordable for many populations. However, few studies to date have used this data to suggest strategies to improve affordability. Our systematic review aims to capture and summarise food environment costing methodologies used in HIC, in both urban and rural settings, between 2006 and 2021. In addressing this aim, we answer the following questions: (i) What is the stated purpose of collecting data on food prices, including whether the data is used to inform or advocate for interventions? (ii) Which instruments are being used to measure food pricing? (iii) What are the strengths and limitations of each instrument as reported by study authors?

To address the research aim, we undertook a systematic review of the literature, following the Preferred Reported Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 26 ]. We followed four steps: (i) systematic search for relevant literature; (ii) selection of studies, (iii) data extraction, and (iv) analysis and synthesis of results.

Systematic Search Strategy

After consultation with a research liaison librarian, databases used included EBSCOHOST (Academic Search Complete, CINAHL Complete, GlobalHealth, Medline Complete, and PsychINFO) and Informit. We chose these databases for their comprehensiveness and conventional use in the public health nutrition discipline. We identified search terms using a scoping review and key words used in previous food pricing reviews [ 15 , 23 , 27 , 28 ]. We searched both article abstracts and titles using the following search string: ‘food affordability’ OR ‘food cost’ OR ‘food price*’ OR ‘food promotion*’. We completed an initial search for studies published 2016–2021 in October 2021, followed by a search for studies published 2006–2015 in December 2021.

Selection of Studies

Studies were included if they were English, peer-reviewed journal articles presenting original research, monitored food prices in a high-income country/s, and were published between 2006 and 2021. The article by Glanz (2006) [ 15 ] is considered a seminal paper in food pricing research and was therefore chosen as the starting date for our search. Studies prior to this date were considered unlikely to be relevant to the research question and were thus excluded. Review articles, opinion pieces, posters, perspectives, study protocols, viewpoints, editorials, and commentaries were excluded, as well as those assessing middle- or low-income countries.

Study screening involved an initial review of all titles and removal of duplicates by A1 using online Covidence software [ 29 ], followed by abstract screening (A1), and then full text screening of remaining studies (A1). A second reviewer independently screened all articles by abstract and full text to minimise bias (A2 and A3). Disagreements were resolved through discussion between researchers; where no agreement was reached, a third party acted as an arbiter (A2 and A3). Limited hand searching was conducted given the volume of papers identified. Online Resource 1 presents a PRISMA flow chart of the study selection process.

Data Extraction

Included studies were uploaded to an Endnote (V. X9) [ 30 ] library. We systematically extracted details of each study to Microsoft Excel (V. 2112), including the author/s, year published, article title, aim, pricing instrument used (if specified), country and geographical context (e.g. urban or rural), type of data collected, number and type of locations assessed, number and type of food items captured, population (if the study used sales receipts to estimate food prices), time period of study, strengths, limitations, and conclusions.

Data Analysis and Synthesis

The coded data were used to identify major themes that were then synthesised in the results. We used an inductive thematic approach for our analysis, with the results discussed between the research team to limit researcher subjectivity [ 31 ]. We used Microsoft Excel to calculate descriptive statistics and graphical outputs.

Overview of Studies

Database searching identified 2737 studies, with 1882 studies remaining after removal of duplicates. After abstract screening, a total of 287 were identified for full-text screening, with 187 excluded, and a total of 100 studies included in this systematic review (Online Resource 1).

We observed an increasing number of studies each year, with peaks in 2013, 2014, and 2018 (Fig.  1 ).

Frequency of studies published assessing food prices between 2006 and 2021

Most studies measured food prices in the USA ( n  = 47), followed by Australia ( n  = 25). Urban food environments were assessed more frequently ( n  = 74) than rural ( n  = 33). Most studies were cross-sectional ( n  = 77). Most studies included instore price audits ( n  = 59), followed by online price audits (supermarket websites, n  = 13), or electronic point of sale data (consumer receipts, register sales, or electronic scanning of food prices in the home, n  = 12), and a combination of these ( n  = 17). Most studies collected food price data from more than 20 food retail outlets ( n  = 34) (Table 1 ).

Details of all included studies, grouped according to data source used (instore price audits, online price audits, electronic point of sale, and combinations of these), are shown in Tables 2 , 3 , and 4 . Details include instrument used (if applicable), purpose of data collection, country, context, study type (e.g. cross-sectional, longitudinal), healthiness comparisons (between healthy and unhealthy products or diets), study author, and year. The use of a named instrument was captured to identify commonalities in usage of instruments, and not as an indication of study quality. When assessing differentials in ‘healthiness’, studies either presented a comparison of a ‘healthy diet’ with an ‘unhealthy or currently consumed diet’ or a comparison of the cost of ‘healthy’ and ‘unhealthy’ foods or product categories.

Study Purpose for Collecting Data on Food Prices

The studies included in this review had a multitude of aims (Tables 2 , 3 , and 4 ). While most studies were conducted solely to monitor food prices in a specific location/s [ 33 , 39 , 42 , 46 , 47 , 52 , 54 , 56 , 57 , 59 , 64 , 67 , 71 , 75 , 80 , 81 , 88 , 89 , 104 , 106 , 108 , 109 , 114 ], others aimed to monitor food price changes over time [ 53 , 63 , 74 , 83 , 93 , 97 , 111 , 127 ], assess food prices as a function of income, socioeconomic status, or welfare assistance [ 9 , 19 , 20 , 33 , 36 , 37 , 38 , 40 , 41 , 66 , 69 , 70 , 77 , 84 , 85 , 86 , 90 , 91 , 92 , 94 , 100 , 110 , 115 , 116 , 117 , 122 ]; assess food price in relation to geographic distance [ 19 , 77 , 91 , 92 , 94 , 98 ]; compare perceptions of food price with actual food prices [ 68 , 101 , 107 ]; and relate food price with a health outcome [ 34 , 35 , 37 , 40 , 47 , 58 , 70 , 72 , 78 , 105 , 116 , 117 , 124 , 125 ], compare the price of healthy or unhealthy foods/diets [ 9 , 20 , 34 , 43 , 50 , 51 , 55 , 60 , 61 , 62 , 63 , 64 , 65 , 76 , 85 , 86 , 93 , 94 , 95 , 96 , 99 , 102 , 110 , 111 , 112 , 120 , 121 , 123 , 124 , 126 ], assess diet costs for a specific population [ 82 , 118 ], compare food prices between brands [ 79 ], compare approaches for estimating dietary costs [ 32 ], or understand how prices impact consumption [ 44 ]. Only seven studies specifically aimed to collect data to inform policy strategies and/or community interventions to improve population health [ 10 , 11 , 49 , 80 , 87 , 103 , 113 ]. However, 26 studies did discuss their study findings on food price in relation to potential further action to improve food environments [ 9 , 19 , 20 , 33 , 36 , 37 , 40 , 43 , 47 , 49 , 50 , 54 , 55 , 59 , 63 , 64 , 81 , 85 , 86 , 87 , 88 , 103 , 104 , 105 , 110 ]. Specific suggested strategies included those targeting individuals, such as education campaigns to promote healthy and more affordable food choices [ 9 , 36 , 43 , 45 , 49 , 50 , 55 ], and those targeting environmental changes, such as taxes on ‘unhealthy’ foods [ 33 , 49 , 85 , 104 , 110 ], subsidies and exemptions for ‘healthy’ foods [ 9 , 20 , 45 , 62 , 63 , 85 , 104 , 110 ], vouchers for farmer’s markets [ 43 ], establishing more food stores [ 33 , 45 , 48 , 104 ], better public transportation for consumers to access food stores [ 59 ], generating savings at the manufacturer/wholesaler level that can be passed on to customers [ 81 ], establishing community-led food supply options [ 9 ], and increasing welfare support proportionate to food prices and geographic distances to food stores [ 37 , 40 , 50 , 73 , 85 ].

Overview of Instruments Used to Measure Food Prices

Of the 100 included studies, 57 used a named instrument to measure food prices, as described below. The remaining 43 studies did not name a pre-existing data collection instrument; instead, the authors described the data collection methodology used, for example, in store, online, or via electronic sales data.

Food Basket Instruments

The majority ( n  = 30) of studies used a variation of a ‘food basket’ to estimate food prices. Food baskets capture the prices of a pre-defined list of foods, often in quantities representative of the total diet of reference families over a defined timeframe [ 9 ], and is a longstanding methodology used to investigate the availability and affordability of food. Food basket studies were mainly conducted in the USA ( n  = 14) and Australia ( n  = 12) [ 19 , 20 , 80 , 81 , 83 , 87 , 88 , 89 , 90 , 91 , 92 ]. Food basket studies using named instruments were conducted in the USA—using the Thrifty Food Plan Market Basket ( n  = 5), the Fred Hutchinson Cancer Research Center Market Basket ( n  = 3), the University of Washington’s Center for Public Health Nutrition Market Basket ( n  = 3), and the USDA Market Basket ( n  = 2); in Australia—using the Victorian Healthy Food Basket ( n  = 4), the Food Basket informed by the INFORMAS framework ( n  = 2), the Adelaide Healthy Food Basket ( n  = 2), the Illawarra Healthy Food Basket ( n  = 2), the Queensland Healthy Food Access Basket Survey ( n  = 1), and the Northern Territory Market Basket ( n  = 1); and in Canada—using the Ontario Nutritious food basket ( n  = 1), the Revised Northern Food Basket ( n  = 1), and an unspecified market basket ( n  = 1). Food basket studies were conducted in both rural ( n  = 13) [ 19 , 37 , 49 , 50 , 52 , 81 , 83 , 87 , 88 , 90 , 91 , 103 , 110 ] and urban contexts ( n  = 25) [ 19 , 20 , 37 , 38 , 40 , 46 , 49 , 50 , 51 , 52 , 62 , 63 , 64 , 66 , 67 , 70 , 80 , 81 , 83 , 88 , 89 , 92 , 104 , 105 , 111 ].

All but two [ 37 , 40 ] food basket studies collected prices from physical instore locations [ 19 , 20 , 38 , 43 , 46 , 49 , 50 , 51 , 52 , 55 , 62 , 63 , 64 , 66 , 67 , 70 , 73 , 80 , 81 , 83 , 87 , 88 , 89 , 90 , 91 , 92 , 103 , 104 , 105 , 110 ], with four of these studies supplementing the data with online supermarket prices [ 62 , 63 , 64 , 81 ]. Additionally, three instruments compared the cost of a ‘healthy diet’ to either an ‘unhealthy or currently consumed diet’ [ 20 , 88 , 110 ], 13 instruments compared the cost of ‘healthy’ and ‘unhealthy’ individual foods or product categories [ 19 , 38 , 51 , 62 , 63 , 66 , 83 , 87 , 89 , 90 , 103 ], and 14 instruments did not present a comparison [ 37 , 40 , 46 , 49 , 50 , 52 , 64 , 67 , 70 , 80 , 81 , 91 , 92 , 104 , 105 ]. ‘Current’ diets were defined using national survey data [ 20 , 110 ]. Level of healthiness was defined using various benchmarks, namely the NOVA food processing classification system [ 38 ], nutrient composition and energy density [ 38 , 51 , 62 , 63 , 66 , 80 , 83 , 90 ], national Dietary Guidelines [ 19 , 43 , 70 , 87 , 88 , 89 , 90 ], and the Dietary Approaches to Stop Hypertension (DASH) dietary pattern [ 43 ]. Food affordability was benchmarked using household income [ 20 , 49 , 50 , 90 , 91 , 92 , 103 , 105 , 110 ], government subsidies [ 37 , 40 , 87 , 89 , 91 ], and minimum wage [ 38 , 66 , 70 ]; however, most studies ( n  = 13) did not determine relative affordability in their analysis [ 43 , 51 , 52 , 55 , 62 , 63 , 64 , 67 , 73 , 80 , 81 , 83 , 88 ].

Healthy Diets Australian Standardised Affordability and Price (ASAP) Instrument

Following critiques of existing food baskets, the previously described INFORMAS instrument was refined to assess and compare the price and affordability of healthy and current diets in Australia, leading to the development of the Healthy Diets Australian Standardised Affordability and Price (ASAP). This instrument assesses the cost of a ‘recommended’ Australian diet (defined by the Australian Dietary Guidelines and Australian Guide to Healthy Eating) and the cost of the ‘current’ Australian diet (as reported in the 2011–12 Australian Health Survey) using the reference household of two parents and two children (boy aged 14 years; girl aged 8 years) [ 128 ]. Thus, all studies using this instrument present a comparison of the cost of a ‘healthy’ and ‘unhealthy’ diet in their analysis. Intrinsic to the instrument, the relative affordability of a healthy diet is measured against household incomes. The ASAP instrument was used by four studies to collect food price data in physical instore locations [ 9 , 85 , 86 ] or from online supermarkets [ 94 ]. Studies were conducted in both rural ( n  = 2) [ 9 , 85 , 94 ] and urban ( n  = 2) [ 85 , 86 , 94 ] contexts.

Nutrition Environment Measures Survey for Stores (NEMS-S) Instrument

The Nutrition Environment Measures Survey for Stores (NEMS-S) and its variants were also frequently used throughout food pricing studies ( n  = 15). These included NEMS-S-Rev (Nutrition Environment Measures Survey for Stores Revised), TxNEAS (Texas Nutrition Environment Assessment), NEMS-S-NL (Nutrition Environment Measures Survey for Stores Newfoundland and Labrador), and The Bridging the Gap Food Store Observation Form. This instrument was used mostly in the USA ( n  = 11) [ 11 , 33 , 36 , 44 , 47 , 48 , 54 , 57 , 68 , 71 , 107 ]. Studies were conducted in both rural ( n  = 4) [ 10 , 11 , 56 , 106 ] and urban ( n  = 11) [ 33 , 36 , 44 , 47 , 48 , 54 , 57 , 68 , 71 , 107 , 108 ] contexts. Compared to the food basket methodology, the NEMS-S instrument compares products in the same category that are considered ‘healthy’ or ‘unhealthy’ based on American Dietetic Association (ADA) recommended dietary guidelines, focusing on availability, price, and quality. All studies using the NEMS-S instrument collected food price data in physical instore locations. While the instrument itself does not include a calculation of relative affordability, approximately half the NEMS-S studies included this step in their methods [ 33 , 36 , 44 , 47 , 48 , 54 , 57 ], while all others did not [ 10 , 11 , 56 , 68 , 71 , 106 , 107 , 108 ].

Other Instruments

Several other named instruments were identified, used in single studies. These included the Diet and Nutrition Tool for Evaluation (DANTE) [ 101 ], the Flint Store Food Assessment Instrument [ 60 ], the Food Label Trial registry tool [ 76 ], the New Zealand Food Price Index [ 111 ], the USDA Food Store Survey Instrument [ 73 ], USDA Low-cost food plan [ 55 ] and audit forms developed by the Yale Rudd Center [ 39 ], the Hartford Advisory Commission on Food Policy [ 59 ], and the USDA Authorized Food Retailers’ Characteristics and Access Study [ 43 ]. Only three instruments compared healthy and unhealthy products [ 43 , 76 , 111 ] and none analysed the relative affordability of food.

Instrument Strengths and Limitations

The strengths and limitations of instruments commonly used across studies, as identified by study authors, are presented in Online Resource 2 . Commonly cited limitations, regardless of instrument used, included that actual purchasing behaviours were not captured (unless electronic point of sales data was utilised); culturally important and region-specific products were often not captured; tools were cross-sectional in nature, thus seasonality or changes overtime were not considered; and out-shopping, described as food purchases undertaken outside the local residential geography, including internet orders or foods purchased during travel to other communities, could not be accounted for. While some food basket studies and those using the ASAP instrument did contextualise the relative affordability of healthy foods and/or diets, this was not a part of the methodology for NEMS-S. Other limitations specific to NEMS-S included the length of the survey, and a low convergence between NEMS-S results and consumer perceptions of affordability. Specific limitations for food basket studies included results being constrained by the reference family used and the assumption that food is shared equally among household members. Additionally, most instruments did not capture geographical information regarding access to food retail outlets or availability of foods within food retail outlets.

Authors less commonly described instrument strengths. For NEMS-S, cited strengths included the ability to compare food prices between healthy and unhealthy options, that it has strong inter-rater and test-re-test reliability, and that it has been validated in multiple countries. ASAP studies, and some food basket studies, included a comparison between healthy and current (‘unhealthy’) diets (based on actual consumption) and included alcohol in the survey.

Our systematic review details the key purposes, and methodologies used, for measuring food prices in HIC between 2006 and 2021. While most studies were conducted solely to monitor food prices in specific locations, some sought to report price changes over time, and others collected data to assess comparability of food costs to healthier alternatives, average earnings, welfare payments, rurality, and socioeconomic position. Most studies measured food prices in urban areas, using instore food price audits, with an emerging use of online data collection evident. The most frequently used instruments were ‘food baskets’, used predominantly to monitor food prices; the NEMS-S instrument, used to provide data on relative cost and availability; and the ASAP instrument, use to provide data on relative affordability.

Our review differs from previous reviews of food price and affordability instruments [ 23 , 28 ] by taking a broadened focus on food pricing measures used in HIC globally and including new technology that is affording opportunities for electronic food pricing data collection. While a previous review critiqued food pricing measures for relevance specific to a rural context, our review includes both rural and urban contexts [ 28 ]. Another review [ 23 ] also describes the components of individual instruments, such as the identification of differently sized ‘food baskets’, ranging between 30 and 200 food items. Such critique was beyond the scope of our research questions.

Despite emerging options for electronic methodologies, the predominance of in person, instore data collection continues, notwithstanding the time-consuming and resource-intensive nature of this method. Studies indicate that these instore instruments can be targeted and applied within multiple contexts, such as rural [ 9 , 10 , 11 , 12 ], Indigenous [ 129 , 130 ], and low socioeconomic areas [ 85 ]. Perhaps researchers consider instore data collection as providing real-world insights at a community and population health level. Our review identified that food pricing instruments were mostly used to monitor food prices at a single point in time (cross-sectional) rather than changes at different time points (longitudinal). Instruments that enable the comparison of food prices in terms of a healthy diet (as recommended by dietary guidelines) compared with current dietary patterns (as reported through population health surveys) [ 128 ], and relative affordability for families, appear to provide data of greater practice and policy relevance with regard to community strategies, taxes, and subsidies that have potential to enhance food affordability, availability, and accessibility.

Technological innovations are an emerging alternative to in person data collection, facilitating the acquisition of online supermarket prices, a less labour-intensive method for capturing food prices [ 131 ]. To date, this method has been used within major chain-supermarkets, with a recent study reporting similar results when comparing pricing data obtained instore versus online [ 94 ]. This method therefore holds potential where an online supermarket presence exists, which was increasingly the case during the COVID-19 pandemic [ 53 ], providing rapid feedback to inform price promotions. However, for smaller and/or independent food retail outlets, frequently located in rural areas, online data collection does not appear to capture the contextual nuances of instore price promotions.

Our review found an over-representation of food pricing studies within urban areas. This is consistent with multiple studies that reflect inequities experienced within rural environments [ 132 ], and rural food environments are no exception [ 133 ]. The predominance of research within urban areas may also reflect a pragmatic researcher response to the physical proximity of stores (ease of measurement) and larger population reach (potential for greater population impact). Previous research shows significant differences in income-based variables, food environments, and the affordability of healthy food between urban and rural settings [ 134 ]. There is therefore a need for rural-specific food pricing studies, using appropriate instruments, to evaluate and inform rural-specific food environment initiatives [ 28 ].

During the period covered by this review, high level experts from the World Health Organization [ 135 ], the Lancet Commission [ 136 ], and the Food and Agricultural Organisation of the United Nations [ 137 ] have identified the potential benefits that initiatives located within food retail environments can provide in nudging dietary choices towards healthier options through instore food pricing and promotion, with the overall aim of improving population level diets [ 14 ]. Measures of food pricing, and the relative affordability of a healthy diet, are important to both inform and measure the effectiveness of such initiatives. However, few studies in our review explicitly aimed to inform initiatives or strategies, either at the community or policy level. Assessment of author-reported strengths and limitations of food pricing instruments and methodologies also identified a need for a universal instrument that reflects contextual geographic and socio-cultural information; is intended to be used repeatedly over time; and is adaptable to different country/cultural/contextual settings [ 17 , 23 ]. Future research would benefit from linking the purpose of undertaking food pricing data collection more explicitly to potential initiatives. Our review supports this call and suggests that the instrument selected should suit the context and collect longitudinal data to provide greater insights into the design and effectiveness of initiatives that make healthy food not only affordable but also available and accessible.

Strengths and Limitations

This systematic review provides a current and comprehensive overview of international food pricing studies across HIC. We acknowledge that while food prices are an important factor influencing food choice, it is only one component of the food environment; however, analysing instruments that assess food acceptability, availability, and accessibility was beyond the scope of this review. This review focused on HIC and a similar review on food pricing studies in low- and middle-income countries would be informative. This review may have missed additional relevant data as it only included English language studies and did not include grey literature or hand searching of reference lists.

Food security has come under heightened scrutiny given the food supply interruptions experienced worldwide during the COVID-19 pandemic. While studies providing a snapshot of food prices can be useful to identify areas impacted by rising food prices, much of this cross-sectional data is known. This review raises questions regarding the purpose of collecting food price data, and how this data can best be used to inform change through practice and policy strategies. We suggest that longitudinal studies using a consistent methodology, which acknowledges contextual nuances and demonstrates temporal changes in food pricing, are needed to inform and to evaluate community-based or legislative strategies to improve the relative affordability of a healthy diet.

Murray CJL, Aravkin AY, Zheng P, Abbafati C, Abbas KM, Abbasi-Kangevari M, Abd-Allah F, Abdelalim A, Abdollahi M, Abdollahpour I, et al. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396:1223–49.

Article   Google Scholar  

Australian Institute of Health and Welfare. Australia’s Health 2022: Burden of Disease. Canberra: AIHW; 2020.

Google Scholar  

Sloane DC, Diamant AL, Lewis LB, Yancey AK, Flynn G, Nascimento LM, Mc Carthy WJ, Guinyard JJ, Cousineau MR. Improving the nutritional resource environment for healthy living through community-based participatory research. J Gen Intern Med. 2003;18:568–75.

Swinburn BA, Sacks G, Hall KD, McPherson K, Finegood DT, Moodie ML, Gortmaker SL. The global obesity pandemic: shaped by global drivers and local environments. Lancet. 2011;378:804–14.

Darmon N, Drewnowski A. Does social class predict diet quality? Am J Clin Nutr. 2008;87:1107–17.

Article   CAS   Google Scholar  

Kickbusch I, Allen L, Franz C. The commercial determinants of health. Lancet Glob Health. 2016;4:e895–6.

Wilkinson RG, Marmot M. Social determinants of health: the solid facts, (World Health Organization). 2003.

Lee JH, Ralston RA, Truby H. Influence of food cost on diet quality and risk factors for chronic disease: a systematic review. Nutr Diet. 2011;68:248–61.

Love P, Whelan J, Bell C, Grainger F, Russell C, Lewis M, Lee A. Healthy diets in rural Victoria-cheaper than unhealthy alternatives, yet unaffordable. Int J Environ Res Public Health. 2018;15.

Whelan J, Millar L, Bell C, Russell C, Grainger F, Allender S, Love P. You can’t find healthy food in the bush: poor accessibility, availability and adequacy of food in rural Australia. Int J Environ Res Public Health. 2018;15:2316.

Pereira RF, Sidebottom AC, Boucher JL, Lindberg R, Werner R. Peer Reviewed: Assessing the Food Environment of a Rural Community: Baseline Findings From the Heart of New Ulm Project, Minnesota, 2010–2011. Prev Chronic Dis. 2014;11.

Vilaro MJ, Barnett TE. The rural food environment: a survey of food price, availability, and quality in a rural Florida community. Food Public Health. 2013;3:111–8.

Garasky S, Morton LW, Greder KA. The effects of the local food environment and social support on rural food insecurity. J Hunger Environ Nutr. 2006;1:83–103.

Swinburn B, Sacks G, Vandevijvere S, Kumanyika S, Lobstein T, Neal B, Barquera S, Friel S, Hawkes C, Kelly B. INFORMAS (I nternational N etwork for F ood and O besity/non-communicable diseases R esearch, M onitoring and A ction S upport): overview and key principles. Obes Rev. 2013;14:1–12.

Glanz K, Johnson L, Yaroch AL, Phillips M, Ayala GX, Davis EL. Measures of retail food store environments and sales: review and implications for healthy eating initiatives. J Nutr Educ Behav. 2016;48(280–288): e281.

Begemann F. Ecogeographic differentiation of bambarra groundnut (Vigna subterranea) in the collection of the International Institute of Tropical Agriculture (IITA, (Wissenschaftlicher Fachverlag). 1988.

Lee A, Mhurchu CN, Sacks G, Swinburn B, Snowdon W, Vandevijvere S, Hawkes C, L’Abbé M, Rayner M, Sanders D. Monitoring the price and affordability of foods and diets globally. Obes Rev. 2013;14:82–95.

Rao M, Afshin A, Singh G, Mozaffarian D. Do healthier foods and diet patterns cost more than less healthy options? A systematic review and meta-analysis. BMJ Open. 2013;3: e004277.

Palermo C, McCartan J, Kleve S, Sinha K, Shiell A. A longitudinal study of the cost of food in Victoria influenced by geography and nutritional quality. Aust N Z J Public Health. 2016;40:270–3.

Lee AJ, Kane S, Ramsey R, Good E, Dick M. Testing the price and affordability of healthy and current (unhealthy) diets and the potential impacts of policy change in Australia. BMC Public Health. 2016;16:1–22.

Clark P, Mendoza-Gutiérrez CF, Montiel-Ojeda D, Denova-Gutiérrez E, López-González D, Moreno-Altamirano L, Reyes A. A healthy diet is not more expensive than less healthy options: cost-analysis of different dietary patterns in Mexican children and adolescents. Nutrients. 2021;13:3871.

Burns C, Friel S. It’s time to determine the cost of a healthy diet in Australia. Aust N Z J Public Health. 2007;31:363–5.

Lewis M, Lee A. Costing ‘healthy’food baskets in Australia–a systematic review of food price and affordability monitoring tools, protocols and methods. Public Health Nutr. 2016;19:2872–86.

Moayyed H, Kelly B, Feng X, Flood V. Is living near healthier food stores associated with better food intake in regional Australia? Int J Environ Res Public Health. 2017;14:884.

Seal J. Monitoring the price and availability of healthy food–time for a national approach? Nutr Diet. 2004;61:197–200.

Moher D, Liberati A, Tetzlaff J, Altman D. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151:264–9.

Caspi CE, Sorensen G, Subramanian S, Kawachi I. The local food environment and diet: a systematic review. Health Place. 2012;18:1172–87.

Love P, Whelan J, Bell C, McCracken J. Measuring rural food environments for local action in Australia: a systematic critical synthesis review. Int J Environ Res Public Health. 2019;16:2416.

Covidence systematic review software. Volume 2022. (Melbourne, Australia: Veritas Health Innovation).

The Endnote Team. Endnote. Endnote. X9 ed. Philadelphia, PA: Clarivate; 2013.

Braun V, Clarke V. Reflecting on reflexive thematic analysis. Qual Res Sport Exerc Health. 2019;11:589–97.

Aaron GJ, Keim NL, Drewnowski A, Townsend MS. Estimating dietary costs of low-income women in California: a comparison of 2 approaches. Am J Clin Nutr. 2013;97:835–41.

Andreyeva T, Blumenthal DM, Schwartz MB, Long MW, Brownell KD. Availability and prices of foods across stores and neighborhoods: the case of New Haven, Connecticut. Health affairs (Project Hope). 2008;27:1381–8.

Anekwe TD, Rahkovsky I. The association between food prices and the blood glucose level of US adults with type 2 diabetes. Am J Public Health. 2014;104:678–85.

Bernstein AM, Bloom DE, Rosner BA, Franz M, Willett WC. Relation of food cost to healthfulness of diet among US women. Am J Clin Nutr. 2010;92:1197–203.

Borja K, Dieringer S. Availability of affordable healthy food in Hillsborough County, Florida. J Public Aff (14723891). 2019;19. N.PAG-N.PAG.

Bronchetti ET, Christensen G, Hoynes HW. Local food prices, SNAP purchasing power, and child health. J Health Econ. 2019;68: 102231.

Buszkiewicz J, House C, Anju A, Long M, Drewnowski A, Otten JJ. The impact of a city-level minimum wage policy on supermarket food prices by food quality metrics: a two-year follow up study. Int J Environ Res Public Health. 2019;16:102.

Caspi CE, Pelletier JE, Harnack LJ, Erickson DJ, Lenk K, Laska MN. Pricing of staple foods at supermarkets versus small food stores. Int J Environ Res Public Health. 2017;14.

Christensen G, Bronchetti ET. Local food prices and the purchasing power of SNAP benefits. Food Policy. 2020;95. N.PAG-N.PAG.

Colabianchi N, Antonakos CL, Coulton CJ, Kaestner R, Lauria M, Porter DE. The role of the built environment, food prices and neighborhood poverty in fruit and vegetable consumption: an instrumental variable analysis of the moving to opportunity experiment. Health Place. 2021;67: 102491.

Cole S, Filomena S, Morland K. Analysis of fruit and vegetable cost and quality among racially segregated neighborhoods in Brooklyn. New York J Hunger Environ Nutr. 2010;5:202–15.

Connell CL, Zoellner JM, Yadrick MK, Chekuri SC, Crook LB, Bogle ML. Energy density, nutrient adequacy, and cost per serving can provide insight into food choices in the lower Mississippi Delta. J Nutr Educ Behav. 2012;44:148–53.

DiSantis KI, Grier SA, Oakes JM, Kumanyika SK. Food prices and food shopping decisions of black women. Appetite. 2014;77:106–14.

Fan L, Canales E, Fountain B, Buys D. An assessment of the food retail environment in counties with high obesity rates in Mississippi. J Hunger Environ Nutr. 2021;16:571–93.

Franzen L, Smith C. Food system access, shopping behavior, and influences on purchasing groceries in adult Hmong living in Minnesota. Am J Health Promot. 2010;24:396–409.

Ghosh-Dastidar B, Cohen D, Hunter G, Zenk SN, Huang C, Beckman R, Dubowitz T. Distance to store, food prices, and obesity in urban food deserts. Am J Prev Med. 2014;47:587–95.

Ghosh-Dastidar M, Hunter G, Collins RL, Zenk SN, Cummins S, Beckman R, Nugroho AK, Sloan JC, Wagner LV, Dubowitz T, et al. Does opening a supermarket in a food desert change the food environment? Health Place. 2017;46:249–56.

Greenberg JA, Luick B, Alfred JM, Barber LR Jr, Bersamin A, Coleman P, Esquivel M, Fleming T, Guerrero RTL, Hollyer J, et al. The affordability of a thrifty food plan-based market basket in the United States-affiliated Pacific Region. Hawaii J Med Public Health. 2020;79:217–23.

Hardin-Fanning F, Rayens MK. Food cost disparities in rural communities. Health Promot Pract. 2015;16:383–91.

Hardin-Fanning F, Wiggins AT. Food costs are higher in counties with poor health rankings. J Cardiovasc Nurs. 2017;32:93–8.

Hilbert N, Evans-Cowley J, Reece J, Rogers C, Ake W, Hoy C. Mapping the cost of a balanced diet, as a function of travel time and food price. Journal of Agriculture, Food Systems and Community Development. 2014;5:105–27.

Hillen J. Online food prices during the COVID-19 pandemic. Agribusiness (New York). 2021;37:91–107.

Jin H, Lu Y. Evaluating consumer nutrition environment in food deserts and food swamps. Int J Environ Res Public Health. 2021;18.

Karp RJ, Wong G, Orsi M. Demonstrating nutrient cost gradients: a Brooklyn case study. Int J Vitam Nutr Res. 2014;84:244–51.

Ko LK, Enzler C, Perry CK, Rodriguez E, Mariscal N, Linde S, Duggan C. Food availability and food access in rural agricultural communities: use of mixed methods. BMC Public Health. 2018;18. N.PAG-N.PAG.

Lee Smith M, Sunil TS, Salazar CI, Rafique S, Ory MG. Disparities of food availability and affordability within convenience stores in Bexar County. Texas J Environ Public Health. 2013;2013:1–7.

Lipsky LM. Are energy-dense foods really cheaper? Reexamining the relation between food price and energy density. Am J Clin Nutr. 2009;90:1397–401.

Martin KS, Ghosh D, Page M, Wolff M, McMinimee K, Zhang M. What role do local grocery stores play in urban food environments? A case study of Hartford-Connecticut. PLoS ONE. 2014;9: e94033.

Mayfield KE, Hession SL, Weatherspoon L, Hoerr SL. A cross-sectional analysis exploring differences between food availability, food price, food quality and store size and store location in Flint Michigan. J Hunger Environ Nutr. 2020;15:643–57.

Meyerhoefer CD, Leibtag ES. A spoonful of sugar helps the medicine go down: the relationship between food prices and medical expenditures on diabetes. Am J Agr Econ. 2010;92:1271–82.

Monsivais P, Drewnowski A. The rising cost of low-energy-density foods. J Am Diet Assoc. 2007;107:2071–6.

Monsivais P, McLain J, Drewnowski A. The rising disparity in the price of healthful foods: 2004–2008. Food Policy. 2010;35:514–20.

Monsivais P, Perrigue MM, Adams SL, Drewnowski A. Measuring diet cost at the individual level: a comparison of three methods. Eur J Clin Nutr. 2013;67:1220–5.

Nansel TR, Lipsky LM, Eisenberg MH, Liu A, Mehta SN, Laffel LMB. Can families eat better without spending more? Improving diet quality does not increase diet cost in a randomized clinical trial among youth with type 1 diabetes and their parents. J Acad Nutr Diet. 2016;116:1751.

Otten JJ, Buszkiewicz J, Tang W, Anju A, Long M, Vigdor J, Drewnowski A. The impact of a city-level minimum-wage policy on supermarket food prices in Seattle-King County. Int J Environ Res Public Health. 2017;14:1039.

Richards R, Smith C. Shelter environment and placement in community affects lifestyle factors among homeless families in Minnesota. Am J Health Promot. 2006;21:36–44.

Shen Y, Clarke P, Gomez-Lopez IN, Hill AB, Romero DM, Goodspeed R, Berrocal VJ, Vydiswaran VV, Veinot TC. Using social media to assess the consumer nutrition environment: comparing Yelp reviews with a direct observation audit instrument for grocery stores. Public Health Nutr. 2019;22:257–64.

Smith C, Butterfass J, Richards R. Environment influences food access and resulting shopping and dietary behaviors among homeless Minnesotans living in food deserts. Agric Hum Values. 2010;27:141–61.

Spoden AL, Buszkiewicz JH, Drewnowski A, Long MC, Otten JJ. Seattle’s minimum wage ordinance did not affect supermarket food prices by food processing category. Public Health Nutr. 2018;21:1762–70.

Stroebele-Benschop N, Wolf K, Palmer K, Kelley CJ, Jilcott Pitts SB. Comparison of food and beverage products’ availability, variety, price and quality in German and US supermarkets. Public Health Nutr. 2020;23:3387–93.

Townsend MS, Aaron GJ, Monsivais P, Keim NL, Drewnowski A. Less-energy-dense diets of low-income women in California are associated with higher energy-adjusted diet costs. Am J Clin Nutr. 2009;89:1220–6.

Wright L, Palak G, Yoshihara K. Accessibility and affordability of healthy foods in food deserts in Florida: policy and practice implications. Florida Public Health Review. 2018;15:98–103.

Yang Y, Leung P. Price premium or price discount for locally produced food products? A temporal analysis for Hawaii. J Asian Pac Econ. 2020;25:591–610.

Zenk SN, Grigsby-Toussaint DS, Curry SJ, Berbaum M, Schneider L. Short-term temporal stability in observed retail food characteristics. J Nutr Educ Behav. 2010;42:26–32.

Abreu MD, Charlton K, Probst Y, Li N, Crino M, Wu JHY. Nutrient profiling and food prices: what is the cost of choosing healthier products? J Hum Nutr Diet. 2019;32:432–42.

Ball K, Timperio A, Crawford D. Neighbourhood socioeconomic inequalities in food access and affordability. Health Place. 2009;15:578–85.

Brimblecombe J, Ferguson M, Liberato SC, O’Dea K, Riley M. Optimisation modelling to assess cost of dietary improvement in remote aboriginal Australia. PLoS ONE. 2013;8: e83587.

Chapman K, Innes-Hughes C, Goldsbury D, Kelly B, Bauman A, Allman-Farinelli M. A comparison of the cost of generic and branded food products in Australian supermarkets. Public Health Nutr. 2013;16:894–900.

Cuttler R, Evans R, McClusky E, Purser L, Klassen KM, Palermo C. An investigation of the cost of food in the Geelong region of rural Victoria: essential data to support planning to improve access to nutritious food. Health Promot J Austr. 2019;30:124–7.

Ferguson M, O’Dea K, Chatfield M, Moodie M, Altman J, Brimblecombe J. The comparative cost of food and beverages at remote Indigenous communities, Northern Territory, Australia. Aust N Z J Public Health. 2016;40(Suppl 1):S21–6.

Ferguson M, O’Dea K, Holden S, Miles E, Brimblecombe J. Food and beverage price discounts to improve health in remote Aboriginal communities: mixed method evaluation of a natural experiment. Aust N Z J Public Health. 2017;41:32–7.

Harrison MS, Coyne T, Lee AJ, Leonard D, Lowson S, Groos A, Ashton BA. The increasing cost of the basic foods required to promote health in Queensland. Med J Aust. 2007;186:9–14.

Kettings C, Sinclair AJ, Voevodin M. A healthy diet consistent with Australian health recommendations is too expensive for welfare-dependent families. Aust N Z J Public Health. 2009;33:566–72.

Lee A, Patay D, Herron L-M, Parnell Harrison E, Lewis M. Affordability of current, and healthy, more equitable, sustainable diets by area of socioeconomic disadvantage and remoteness in Queensland: insights into food choice. Int J Equity Health. 2021;20:1–17.

Lee AJ, Kane S, Herron L-M, Matsuyama M, Lewis M. A tale of two cities: the cost, price-differential and affordability of current and healthy diets in Sydney and Canberra, Australia. Int J Behav Nutr Phys Act. 2020;17:1–13.

Palermo CE, Walker KZ, Hill P, McDonald J. The cost of healthy food in rural Victoria. Rural Remote Health. 2008;8. (1 December 2008).

Pollard CM, Landrigan TJ, Ellies PL, Kerr DA, Lester MLU, Goodchild SE. Geographic factors as determinants of food security: a Western Australian food pricing and quality study. Asia Pac J Clin Nutr. 2014;23:703–13.

Tsang A, Ndung’u MW, Coveney J, O’Dwyer L. Adelaide Healthy Food Basket: a survey on food cost, availability and affordability in five local government areas in metropolitan Adelaide, South Australia. Nutr Diet. 2007;64:241–7.

Walton K, do Rosario V, Kucherik M, Frean P, Richardson K, Turner M, Mahoney J, Charlton K, Andre do Rosario V. Identifying trends over time in food affordability: the Illawarra Healthy Food Basket survey, 2011–2019. Health Promot J Austr. 2021;1–1.

Ward PR, Coveney J, Verity F, Carter P, Schilling M. Cost and affordability of healthy food in rural South Australia. Rural Remote Health 2012;12. Article No. 1938.

Wong K, Coveney J, Ward P, Muller R, Carter P, Verity F, Tsourtos G. Availability, affordability and quality of a healthy food basket in Adelaide, South Australia. Nutr Diet. 2011;68:8–14.

Burns C, Sacks G, Gold L. Longitudinal study of Consumer Price Index (CPI) trends in core and non-core foods in Australia. Aust N Z J Public Health. 2008;32:450–3.

Zorbas C, Lee A, Peeters A, Lewis M, Landrigan T, Backholer K. Streamlined data-gathering techniques to estimate the price and affordability of healthy and unhealthy diets under different pricing scenarios. Public Health Nutr. 2021;24:1–11.

Conklin AI, Monsivais P, Khaw K, Wareham NJ, Forouhi NG. Dietary diversity, diet cost, and incidence of type 2 diabetes in the United Kingdom: a prospective cohort study. PLoS Med. 2016;13: e1002085.

Jones NRV, Tong TYN, Monsivais P. Meeting UK dietary recommendations is associated with higher estimated consumer food costs: an analysis using the National Diet and Nutrition Survey and consumer expenditure data, 2008–2012. Public Health Nutr. 2018;21:948–56.

Lan H, Lloyd T, Morgan W, Dobson PW. Are food price promotions predictable? The hazard function of supermarket discounts. J Agric Econ. 2021;1.

Mackenbach JD, Burgoine T, Lakerveld J, Forouhi NG, Griffin SJ, Wareham NJ, Monsivais P. Accessibility and affordability of supermarkets: associations with the DASH diet. Am J Prev Med. 2017;53:55–62.

Monsivais P, Scarborough P, Lloyd T, Mizdrak A, Luben R, Mulligan AA, Wareham NJ, Woodcock J. Greater accordance with the Dietary Approaches to Stop Hypertension dietary pattern is associated with lower diet-related greenhouse gas production but higher dietary costs in the United Kingdom. Am J Clin Nutr. 2015;102:138–45.

Timmins KA, Hulme C, Cade JE. The monetary value of diets consumed by British adults: an exploration into sociodemographic differences in individual-level diet costs. Public Health Nutr. 2015;18:151–9.

Timmins KA, Morris MA, Hulme C, Edwards KL, Clarke GP, Cade JE. Comparability of methods assigning monetary costs to diets: derivation from household till receipts versus cost database estimation using 4-day food diaries. Eur J Clin Nutr. 2013;67:1072–6.

Vogel C, Abbott G, Ntani G, Barker M, Cooper C, Moon G, Ball K, Baird J. Examination of how food environment and psychological factors interact in their relationship with dietary behaviours: test of a cross-sectional model. Int J Behav Nutr Phys Act. 2019;16. N.PAG-N.PAG.

Kenny T-A, Fillion M, MacLean J, Wesche SD, Chan HM. Calories are cheap, nutrients are expensive – the challenge of healthy living in Arctic communities. Food Policy. 2018;80:39–54.

Latham J, Moffat T. Determinants of variation in food cost and availability in two socioeconomically contrasting neighbourhoods of Hamilton, Ontario, Canada. Health Place. 2007;13:273–87.

Lear SA, Gasevic D, Schuurman N. Association of supermarket characteristics with the body mass index of their shoppers. Nutr J. 2013;12. (13 August 2013).

Mah CL. Taylor N. Store patterns of availability and price of food and beverage products across a rural region of Newfoundland and Labrador. Canadian journal of public health = Revue canadienne de sante publique. 2020;111:247–256.

Minaker LM, Raine KD, Wild TC, Nykiforuk CIJ, Thompson ME, Frank LD. Objective food environments and health outcomes. Am J Prev Med. 2013;45:289–96.

Minaker LM, Raine KD, Wild TC, Nykiforuk CIJ, Thompson ME, Frank LD. Construct validation of 4 food-environment assessment methods: adapting a multitrait-multimethod matrix approach for environmental measures. Am J Epidemiol. 2014;179:519–28.

Pakseresht M, Lang R, Rittmueller S, Roache C, Sheehy T, Batal M, Corriveau A, Sangita S. Food expenditure patterns in the Canadian Arctic show cause for concern for obesity and chronic disease. Int J Behav Nutr Phys Act. 2014;11. (17 April 2014).

Mackay S, Buch T, Vandevijvere S, Goodwin R, Korohina E, Funaki-Tahifote M, Lee A, Swinburn B. Cost and affordability of diets modelled on current eating patterns and on dietary guidelines, for New Zealand total population, Māori and Pacific households. Int J Environ Res Public Health. 2018;15.

Mackay S, Vandevijvere S, Lee A. Ten-year trends in the price differential between healthier and less healthy foods in New Zealand. Nutrition & dietetics: the journal of the Dietitians Association of Australia. 2019;76:271–6.

Vandevijvere S, Young N, Mackay S, Swinburn B, Gahegan M. Modelling the cost differential between healthy and current diets: the New Zealand case study. Int J Behav Nutr Phys Act. 2018;15:1–1.

Wilson N, Nghiem N, Mhurchu CN, Eyles H, Baker MG, Blakely T. Foods and dietary patterns that are healthy, low-cost, and environmentally sustainable: a case study of optimization modeling for New Zealand. PLoS ONE. 2013;8: e59648.

Alexy U, Bolzenius K, Köpper A, Clausen K, Kersting M. Diet costs and energy density in the diet of German children and adolescents. Eur J Clin Nutr. 2012;66:1362–3.

Stroebele N, Dietze P, Tinnemann P, Willich SN. Assessing the variety and pricing of selected foods in socioeconomically disparate districts of Berlin, Germany. J Public Health. 2011;19:23–8.

Albuquerque G, Moreira P, Rosário R, Araújo A, Teixeira VH, Lopes O, Moreira A, Padrão P. Adherence to the Mediterranean diet in children: Is it associated with economic cost? Porto biomedical journal. 2017;2:115–9.

Alves R, Lopes C, Rodrigues S, Perelman J. Adhering to a Mediterranean diet in a Mediterranean country: an excess cost for families? Br J Nutr. 2021;1–24.

Faria AP, Albuquerque G, Moreira P, Rosário R, Araújo A, Teixeira V, Barros R, Lopes Ó, Moreira A, Padrão P. Association between energy density and diet cost in children. Porto Biomed J. 2016;1:106–11.

Mackenbach JD, Dijkstra SC, Beulens JWJ, Seidell JC, Snijder MB, Stronks K, Monsivais P, Nicolaou M. Socioeconomic and ethnic differences in the relation between dietary costs and dietary quality: the HELIUS study. Nutr J. 2019;18. N.PAG-N.PAG.

Waterlander WE, de Haas WE, van Amstel I, Schuit AJ, Twisk JWR, Visser M, Seidell JC, Steenhuis IHM. Energy density, energy costs and income - how are they related? Public Health Nutr. 2010;13:1599–608.

Rydén P, Mattsson Sydner Y, Hagfors L. Counting the cost of healthy eating: a Swedish comparison of Mediterranean-style and ordinary diets. Int J Consum Stud. 2008;32:138–46.

Rydén PJ, Hagfors L. Diet cost, diet quality and socio-economic position: how are they related and what contributes to differences in diet costs? Public Health Nutr. 2011;14:1680–92.

Keiko S, Kentaro M, Hitomi O, Livingstone MBE, Satomi K, Hitomi S, Satoshi S. Nutritional correlates of monetary diet cost in young, middle-aged and older Japanese women. J Nutr Sci. 2017;6:1–11.

Bolarić M, Šatalić Z. The relation between food price, energy density and diet quality. Croatian Journal of Food Science and Technology. 2013;5:39–45.

Parlesak A, Tetens I, Jensen JD, Smed S, Blenkuš MG, Rayner M, Darmon N, Robertson A. Use of linear programming to develop cost-minimized nutritionally adequate health promoting food baskets. PLoS ONE. 2016;11: e0163411.

Marty L, Dubois C, Gaubard MS, Maidon A, Lesturgeon A, Gaigi H, Darmon N. Higher nutritional quality at no additional cost among low-income households: insights from food purchases of “positive deviants.” Am J Clin Nutr. 2015;102:190–8.

Ng SW, Slining MM, Popkin BM. Turning point for US diets? Recessionary effects or behavioral shifts in foods purchased and consumed. Am J Clin Nutr. 2014;99:609–16.

Lee AJ, Kane S, Lewis M, Good E, Pollard CM, Landrigan TJ, Dick M. Healthy diets ASAP–Australian standardised affordability and pricing methods protocol. Nutr J. 2018;17:1–14.

Lee A, Lewis M. Testing the price of healthy and current diets in remote Aboriginal communities to improve food security: development of the Aboriginal and Torres Strait Islander Healthy Diets ASAP (Australian Standardised Affordability and Pricing) methods. Int J Environ Res Public Health. 2018;15:2912.

Ferguson M, O’Dea K, Chatfield M, Moodie M, Altman J, Brimblecombe J. The comparative cost of food and beverages at remote Indigenous communities, Northern Territory, Australia. Aust N Z J Public Health. 2016;40:S21–6.

Zorbas C, Gilham B, Boelsen-Robinson T, Blake MR, Peeters A, Cameron AJ, Wu JH, Backholer K. The frequency and magnitude of price-promoted beverages available for sale in Australian supermarkets. Aust N Z J Public Health. 2019;43:346–51.

Bourke L, Humphreys JS, Wakerman J, Taylor J. Understanding rural and remote health: a framework for analysis in Australia. Health Place. 2012;18:496–503.

Alston LV, Bolton KA, Whelan J, Reeve E, Shee AW, Browne J, Walker T, Versace VL, Allender S, Nichols M. Retail initiatives to improve the healthiness of food environments in rural, regional and remote communities. Med J Aust. 2020;213:S5.

Cafer AM, Kaiser ML. An analysis of differences in predictors of food affordability between rural and urban counties. J Poverty. 2016;20:34–55.

Drysdale C, Sykes E, Honeysett C. WHO urges governments to promote healthy food in public facilities. 2021;2022.

Willet W. Summary report of the EAT-Lancet Commission on healthy diets from sustainable food systems. E.-L. Commission, ed. (Eat-Lancet Commission ). 2019.

Food and Organization A. The State of Food Security and Nutrition in the World 2021. (Food and Agriculture Organization Rome). 2021.

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Open Access funding enabled and organized by CAUL and its Member Institutions CR is supported by an Australian Government Research Training Scholarship. This funder had no involvement in any aspect of the study. JW is funded by a Deakin University Dean’s Postdoctoral Research Fellowship. JW is also supported by the National Health and Medical Research Council (NHMRC) funded Centre of Research Excellence in Food Retail Environments for Health (RE-FRESH) (APP1152968). The opinions, analysis, and conclusions in this paper are those of the authors and should not be attributed to the NHMRC.

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Russell, C., Whelan, J. & Love, P. Assessing the Cost of Healthy and Unhealthy Diets: A Systematic Review of Methods. Curr Nutr Rep 11 , 600–617 (2022). https://doi.org/10.1007/s13668-022-00428-x

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Clinically researched mitochondrial support

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[1] Sinha R, Sinha I, Calcagnotto A, et al. Oral supplementation with liposomal glutathione elevates body stores of glutathione and markers of immune function.  Eur J Clin Nutr . 2018;72(1):105-111. doi:10.1038/ejcn.2017.132

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The Power of Carrots: Samford Student Presents Research at NUTRITION 2024 Conference

Mary Harper Simmons, a Master of Science in Nutrition student at Samford University, recently presented her research on the consumption of baby carrots and their impact on skin carotenoid levels at NUTRITION 2024, the annual meeting of the American Society for Nutrition held June 29-July 2 in Chicago.  

Simmons' research revealed that consuming baby carrots three times a week significantly increased skin carotenoids in young adults. These phytonutrients were further enhanced when paired with a multivitamin containing the carotenoid beta carotene.  

"Previous studies have demonstrated that skin carotenoid levels can be increased by consuming three times the recommended serving of fruits and vegetables every day for three weeks," said Simmons. "Our findings suggest that a small, simple dietary modification—incorporating baby carrots as a snack—can significantly increase skin carotenoid accumulation."  

Under the supervision of Suresh Mathews, chair of the Department of Nutrition and Dietetics in Samford’s School of Public Health, Simmons and her research team studied 60 young adults over a four-week period with various interventions. The randomly assigned groups consumed Granny Smith apple slices (control), a half cup (100 grams) of baby carrots, a multivitamin supplement containing beta carotene, or a combination of baby carrots and the supplement.  

The team utilized a noninvasive research-grade spectroscopy instrument called a VeggieMeter to detect and measure the skin carotenoids of the participants before and after the study. The results showed that skin carotenoid scores increased by 10.8% in the group receiving the baby carrots and 21.6% in the group receiving the carrots and supplement combination. The groups receiving the supplement only and the apple slices did not have any notable change in skin carotenoid levels.  

"I am extremely proud of the research work conducted by Harper and colleagues. She was able to present these findings at Nutrition 2024, the premier scientific meeting in the field of nutrition, and receive widespread media attention for her research," Mathews said. Along with the carotenoid impact, he explained that consuming baby carrots a few times a week “can contribute to overall health and lower the risk for chronic diseases."  

The fact that the group receiving only the supplement did not experience increased skin carotenoid levels suggests differences in absorption between food and supplements. Simmons intends to further study the mechanism behind these findings and explore the effects of other carotenoid-rich foods, such as sweet potatoes or green leafy vegetables.  

A committee of industry experts selected Simmons to present her study at this year’s conference. Numerous media outlets including Fox News, CNN and BBC have featured Simmons’ study, highlighting the research being done in Samford’s School of Public Health.  

For more stories like this, follow us on Facebook and see interprofessional education in action on Instagram .

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Strengthening national nutrition research: rationale and options for a new coordinated federal research effort and authority

Sheila e fleischhacker.

Fly Health, LLC and Georgetown University Law Center, Washington, DC, USA

Catherine E Woteki

University of Virginia Biocomplexity Institute and Initiative, Arlington, VA, USA

Paul M Coates

Retired, National Institutes of Health, Bethesda, MD, USA

Van S Hubbard

Grace e flaherty.

Gerald J and Dorothy R Friedman School of Nutrition Science and Policy at Tufts University, Boston, MA, USA

Daniel R Glickman

The Aspen Institute, Washington, DC, USA

Thomas R Harkin

Retired US Senator, Des Moines, IA, USA

David Kessler

Former Food and Drug Administration Commissioner, College Park, MD, USA

William W Li

The Angiogenesis Foundation, Cambridge, MA, USA

Joseph Loscalzo

Department of Medicine at Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA

Anand Parekh

Bipartisan Policy Center, Washington, DC, USA

Sylvia Rowe

SR Strategy, Washington, DC, USA

Patrick J Stover

Texas A&M AgriLife, Texas A&M College of Agriculture and Life Sciences, and Texas A&M AgriLife Research, College Station, TX, USA

Angie Tagtow

Äkta Strategies LLC, Des Moines, IA, USA

Anthony Joon Yun

Yun Family Foundation, San Mateo, CA, USA

Dariush Mozaffarian

Associated data.

• HHS Centers for Medicare & Medicaid Services. National health expenditure data: historical 2018. [cited 2020 Oct 14] [Internet]. Available from: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/NationalHealthAccountsHistorical.html .

The US faces remarkable food and nutrition challenges. A new federal effort to strengthen and coordinate nutrition research could rapidly generate the evidence base needed to address these multiple national challenges. However, the relevant characteristics of such an effort have been uncertain.

Our aim was to provide an objective, informative summary of 1 ) the mounting diet-related health burdens facing our nation and corresponding economic, health equity, national security, and sustainability implications; 2 ) the current federal nutrition research landscape and existing mechanisms for its coordination; 3 ) the opportunities for and potential impact of new fundamental, clinical, public health, food and agricultural, and translational scientific discoveries; and 4 ) the various options for further strengthening and coordinating federal nutrition research, including corresponding advantages, disadvantages, and potential executive and legislative considerations.

We reviewed government and other published documents on federal nutrition research; held various discussions with expert groups, advocacy organizations, and scientific societies; and held in-person or phone meetings with >50 federal staff in executive and legislative roles, as well as with a variety of other stakeholders in academic, industry, and nongovernment organizations.

Stark national nutrition challenges were identified. More Americans are sick than are healthy, largely from rising diet-related illnesses. These conditions create tremendous strains on productivity, health care costs, health disparities, government budgets, US economic competitiveness, and military readiness. The coronavirus disease 2019 (COVID-19) outbreak has further laid bare these strains, including food insecurity, major diet-related comorbidities for poor outcomes from COVID-19 such as diabetes, hypertension, and obesity, and insufficient surveillance on and coordination of our food system. More than 10 federal departments and agencies currently invest in critical nutrition research, yet with relatively flat investments over several decades. Coordination also remains suboptimal, documented by multiple governmental reports over 50 years. Greater harmonization and expansion of federal investment in nutrition science, not a silo-ing or rearrangement of existing investments, has tremendous potential to generate new discoveries to improve and sustain the health of all Americans. Two identified key strategies to achieve this were as follows: 1 ) a new authority for robust cross-governmental coordination of nutrition research and other nutrition-related policy and 2 ) strengthened authority, investment, and coordination for nutrition research within the NIH. These strategies were found to be complementary, together catalyzing important new science, partnerships, coordination, and returns on investment. Additional complementary actions to accelerate federal nutrition research were identified at the USDA.

Conclusions

The need and opportunities for strengthened federal nutrition research are clear, with specific identified options to help create the new leadership, strategic planning, coordination, and investment the nation requires to address the multiple nutrition-related challenges and grasp the opportunities before us.

Executive Summary

This white paper aims to evaluate key issues relevant to federal nutrition research, including the following:

• The mounting diet-related health burdens and corresponding economic, health equity, national security, and sustainability implications;
• The current diverse federal nutrition research landscape and existing mechanisms for its coordination;
• The opportunities for new nutrition-related discoveries in fundamental, clinical, public health, food and agricultural, and translational scientific research; and
• The best strategies to further strengthen and coordinate federal nutrition research, including advantages, disadvantages, and potential paths forward.

This effort, informed by extensive background research and interviews, is intended to invite comment and discussion from all key stakeholders and help lay the foundation for accelerated scientific advances in nutrition to improve and sustain the health of all Americans.

Diet-related illnesses are the leading source of poor health in the US. Nearly 3 in 4 American adults are overweight or obese, and 1 in 2 have diabetes or prediabetes—and these rates continue to rise. Poor nutrition further contributes to cardiovascular diseases, several cancers, poor gut health, and many other disorders. Beyond effects on health, these diet-related diseases create enormous strains on productivity, health care spending, health disparities, and military readiness ( Figure 1 ). Our food system also strains our natural resources, a crucial new area of intersecting science and policy.

Examples of identified diet-related burdens that could be addressed by more coordinated and strengthened federal nutrition research. COVID-19, coronavirus disease 2019. Graphic design support courtesy of Ink&Pixel Agency.

Profound disparities in both diet-related chronic diseases and food insecurity, for example, are experienced by low-income, rural, minority, and other underserved populations. Nearly 3 in 4 young Americans do not qualify for military service, with obesity being the leading medical disqualifier. Obesity and other diet-related chronic diseases are endemic among veterans, while obesity and food insecurity coexist in many active-duty military families. Over just 50 y, federal health care spending has risen from 5% to 28% of the federal budget, while US business (inflation-adjusted) spending on health care has increased from $79 billion to $1180 billion. Approximately 85% of current health care spending is related to management of diet-related chronic diseases. Estimated US government expenditures on direct medical care for diabetes alone (∼$160 billion/y) exceeds the annual budgets of many individual federal departments and agencies, including, among others, the Departments of Education (DoE), Homeland Security (DHS), and Justice (DoJ) and the NIH, CDC, Environmental Protection Agency (EPA), and FDA.

These strains have been further exposed and exacerbated by coronavirus disease 2019 (COVID-19). This includes, for example, challenges related to hunger and food insecurity, major diet-related comorbidities for poor outcomes from COVID-19, insufficient evidence on optimal population resilience through better nutrition, and inadequate surveillance and coordination of our food system.

Addressing each of these issues requires a better understanding of their multilevel, interrelated biological, individual, social, and environmental determinants, and the corresponding translational solutions. However, the current scope and pace of nutritional knowledge and discovery are insufficient to address the fundamental nutrition-related challenges facing the nation.

The current landscape

More than 10 federal departments and agencies currently invest in critical nutrition research. Their relative investments in nutrition research have remained flat or declined over several decades—even as diet-related conditions and their societal burdens have climbed. The NIH is the largest funder, with nutrition research investments estimated at $1.9 billion annually (∼5% of total NIH funding) for fiscal year 2019. Approximately 25% of this funding (1.3% of total NIH funding) focuses on diet for the prevention or treatment of disease in humans. This NIH nutrition research is conducted and supported across nearly all of the 27 current NIH institutes and centers. Coordination of these efforts has been challenged by successively smaller NIH coordinating offices with decreasing stature, staff, and resources. The USDA is the second-largest funder of US nutrition research, with an estimated annual budget of ∼$0.17 billion for fiscal year 2019 across several institutes and services. The USDA works to provide Americans with safe, nutritious, and wholesome food and works to ensure the foods and beverages our nation produces optimally benefits human and animal health and to address food insecurity through the administration of 15 federal nutrition assistance programs. Several structures work to improve research coordination within the USDA, although a recent USDA workshop and Government Accountability Office (GAO) report identified gaps and opportunities in nutrition research coordination. Multiple other federal departments and agencies invest in nutrition research, including the CDC, FDA, Department of Defense (DoD), US Agency for International Development (USAID), Department of Veterans Affairs (VA), National Aeronautics and Space Administration (NASA), and others.

Consistent with this fragmented infrastructure, multiple major reports over 50 y have called for greater coordination of federal nutrition research. Current coordination efforts include the Interagency Committee on Human Nutrition Research (ICHNR), which currently meets about twice a year to work on the following activities, among others: food and nutrition monitoring and surveillance, the joint USDA–Department of Health and Human Services (-HHS) activity to produce the Dietary Guidelines for Americans (DGAs) and certain regulatory, communication, and educational activities. However, no concrete authority has been created to successfully harmonize and leverage the federal investments in nutrition research.

Overall, this white paper and several prior reports found these efforts to be important but insufficient to address current and rising diet-related disease burdens, food insecurity, health disparities, health care costs, challenges to military readiness, and intersections with food and agricultural production, supply chains, and sustainability.

The opportunity

Several specific priority areas in nutrition research have been identified by various federal and nongovernmental organizations. However, most have not been adequately addressed. Greater federal coordination and investment in nutrition research could accelerate discoveries across these critical areas ( Figure 2 ).

Opportunities for enhanced federal nutrition research coordination and investment. DGAs, Dietary Guidelines for Americans ; DoD, Department of Defense; NASA, National Aeronautics and Space Administration; SNAP-Ed, USDA Supplemental Nutrition Assistance Program Education; USAID, US Agency for International Development; VA, Department of Veterans Affairs. Graphic design support courtesy of Ink&Pixel Agency.

Several lines of evidence support a strong return on investment (ROI) for an expanded and coordinated nutrition research effort. As stated by the FDA Commissioner in 2018 at the National Food Policy Conference, “Improvements in diet and nutrition offer us one of our greatest opportunities to have a profound and generational impact on human health .… The public health gains of such efforts would almost certainly dwarf any single medical innovation or intervention we could discover.”

The options

Any new federal nutrition research investment and coordination structure must leverage, harmonize, and catalyze the existing efforts being led across multiple federal departments and agencies. Two major complementary strategies were identified: 1 ) a new authority for robust cross-governmental coordination of nutrition research and other nutrition-related policy and 2 ) strengthened authority, investment, and coordination for nutrition research within the NIH.

Specific promising options to advance these 2 strategies were identified ( Box 1 ); and for each option, potential advantages and disadvantages, executive and legislative considerations, and paths forward are discussed. Improved coordination between federal departments and agencies conducting nutrition research was identified as having tremendous potential for accelerating essential basic, clinical, public health, and translational discoveries. Increased authority, coordination, and funding for nutrition science within NIH was also identified as being essential for accelerating needed discoveries. Appropriate efforts should leverage and amplify, not replace, compete with, or isolate existing nutrition research efforts across NIH, USDA, or other departments and agencies. The cross-government strategy and within-NIH strategy were identified as complementary, with benefits accruing independently and further synergies to be gained by joint implementation.

Promising cross-governmental and NIH options to strengthen and accelerate national nutrition research 1

Further complementary actions to accelerate federal nutrition research were identified at USDA. First, to increase investment in nutrition research for the Agricultural Research Service (ARS) including its network of Human Nutrition Research Centers, the National Institute of Food and Agriculture (NIFA) extramural research programs, and the Economic Research Service (ERS) programs, which assesses demographic, social, informational, and economic determinants of dietary consumption and associated health outcomes. Second, to expand USDA research that evaluates and improves major ongoing efforts for public guidance and education on nutrition. And third, to build the robust evidence base and collaborations needed to strengthen the positive impacts of the ∼$100 billion/y federal investments in nutrition assistance programs.

This white paper identified many stark and growing national challenges related to nutrition. Our research further documented a diversity of federal investments in nutrition research across departments and agencies, but with flat or declining funding and with suboptimal coordination authority. The opportunities to be gained by greater coordination and investment in federal nutrition research are clear, with potential for large and rapid ROI. This white paper identified and described 2 priority strategies, including 1 ) a new authority for cross-governmental coordination and 2 ) strengthened authority, investment, and coordination within NIH. Additional important strategies were also identified at USDA. All these strategies were found to be complementary, providing independent as well as synergistic benefits. The identified specific options would help create the new leadership, strategic planning, coordination, and investment the nation requires to address the multiple nutrition-related challenges before us, and grasp the corresponding opportunities.

Introduction

The US faces remarkable food and nutrition challenges. More Americans are sick than are healthy, with diet-related illnesses playing a major role including obesity, type 2 diabetes, cardiovascular diseases, cancers, food allergies, and more ( 1 ). The incidence and prevalence of many of these conditions have increased dramatically in recent decades. In addition to burdens on health and productivity, these diet-related diseases are creating tremendous strains on health care spending, health disparities, government budgets, economic competitiveness of American businesses, and military readiness. Innovations in food and nutrition should improve human health while also preserving our natural resources, a crucial new area of intersecting science and policy.

Many of these strains in food and nutrition have been further exposed and exacerbated by COVID-19 ( 2 ). This includes, for example, challenges related to hunger and food insecurity; major diet-related comorbidities for hospitalization and death from COVID-19 such as diabetes, obesity, and hypertension; insufficient evidence on optimal population resilience through better nutrition; and the need to further improve the surveillance on and coordination of food production and supply chains ( 3–9 ).

While advancing nutrition research has provided evidence to describe the general contours of healthy eating patterns, it has also highlighted many critical new, unanswered questions on food and nutrition and the national challenges we face ( 10 ). Important nutrition research is currently being supported by >10 federal departments and agencies ( 11 ). Yet, as diet-related conditions and their societal burdens have climbed in recent decades, funding for such research has remained flat ( 12 ). In addition, no concrete action has emerged to successfully harmonize and leverage nutrition research across the government, despite consistent recommendations over at least 5 decades for a robust coordinating federal entity ( 13 ). A major, new federal effort to strengthen and coordinate nutrition research could rapidly generate the necessary evidence base to address multiple national challenges, providing major benefits and ROI.

The aim of this white paper is to evaluate key issues relevant to such a scientific effort, including the following:

• The mounting diet-related health burdens facing our nation and the corresponding economic, health equity, national security, and sustainability implications;
• The current federal nutrition research landscape and existing mechanisms for its coordination among the diverse departments and agencies working to address these challenges;
• The opportunities for and potential impact of new fundamental, clinical, public health, food and agricultural, and translational scientific discoveries related to nutrition; and
• The best strategies to further strengthen and coordinate federal nutrition research, including relevant advantages, disadvantages, and potential executive and legislative considerations for a path forward.

This white paper is intended to invite comment and discussion from all stakeholders who care about strengthening nutrition research, whether to improve health, lower public and private health care spending, reduce disparities, promote business innovation, reinvigorate rural communities, preserve our national resources, or strengthen national security. Key audiences for this white paper include the following:

• Elected and appointed federal officials in both executive and legislative branches;
• Federal science agency leaders and program and policy staff;
• Federal military leadership;
• The academic community;
• Clinical and scientific professional organizations;
• Nonprofit advocacy groups;
• Allied health professional organizations;
• US businesses whose efforts, employees, and competitiveness can be benefited by federally supported nutrition discoveries;
• The media, who communicate key nutrition-related messages; and
• The public who rely on and desperately need advances in federally supported nutrition research to help improve and sustain their health and communities.

This white paper was informed by extensive background research and stakeholder conversations. This research included a review of government and other published documents on federal nutrition research; discussions with expert groups, advocacy organizations, and scientific societies; and in-person or phone meetings with >50 federal staff in executive and legislative roles, as well as with a variety of extramural researchers in academic and nongovernmental organizations. The writing group reached out to all 10 departments and agencies participating in the ICHNR, particularly for assistance in estimating their relevant budget for nutrition research. The legislative history for the NIH was independently collected by 2 team members with high agreement. Legal experts at the Center for Health Law and Policy Innovation at Harvard Law School reviewed this white paper with special attention to the section on Options and the corresponding legislative and executive considerations. We also reviewed feedback received through the American Society for Nutrition (ASN) request for member input regarding the concept of a National Institute of Nutrition and through a related panel session and Q&A at the ASN Nutrition 2019 annual scientific conference. We also sought input from members of the Nutrition Action Alliance (NAA), a coalition of organizations working to advance federal nutrition research, nutrition education, and nutrition monitoring and surveillance, among other activities, and which includes ASN, Academy of Nutrition and Dietetics, American Society for Parenteral and Enteral Nutrition, Association of Nutrition Departments and Programs, Institute of Food Technologists, National Board of Physician Nutrition Specialists, Society for Nutrition Education and Behavior, and The Obesity Society. The writing group used these document reviews, one-on-one conversations, stakeholder interviews, and additional discussions to maximize candid, confidential reflections following Chatham House Rules on the past and present state of federal nutrition research, the challenges and opportunities, and the best available strategies for moving forward.

We hope this white paper provides an objective, informative summary of the 1 ) burdens, 2 ) current federal nutrition research landscape, 3 ) opportunities, and 4 ) options for strengthening national nutrition research. Ultimately, we hope it helps lay the foundation for accelerated advances in nutrition research to help improve and sustain the health of all children, adults, families, and communities.

Poor nutrition is contributing to major increases in diet-related obesity and type 2 diabetes, as well as continuing high rates of other chronic diet-related diseases such as cardiovascular diseases, cancers, and other conditions ( 1 ). Since the 1970s, Americans’ diets have changed significantly. For example, both portion sizes and frequency of snacking have increased, with each linked to greater calorie intake ( 14 , 15 ). Among US children, substantial increases in daily calories since the 1970s are entirely attributable to increased foods eaten outside from home, mostly from fast food ( 16 ). Consistent with prior health messaging to reduce total fat, the percentage of energy from carbohydrates increased from 42% to 48% of calories in men and 45% to 51% in women between 1971 and 2004, primarily due to higher consumption of starches, grains, and caloric beverages ( 17 , 18 ). Between 1977 and 1994, intake of processed breakfast cereals increased by 60%, intake of pizza by 115%, and intakes of snack foods like crackers, popcorn, pretzels, and corn chips by 200% ( 19 ). Between 1965 and 2002, the intake of caloric beverages increased from 12% to 21% of all calories, representing an average increase of 222 calories/d per person ( 20 ). This change was due to increased intake of sweetened fruit drinks, alcohol, and especially soda. Over this time, the average portion size of a sugar-sweetened beverage increased by >50% ( 21 ).

In more recent years, with growing public awareness of the critical role of nutrition in overall health, some aspects of US diet quality have modestly improved, such as reductions in soda and small increases in whole grains, fruits, and nuts/seeds ( 22 , 23 ). Nevertheless, intakes of these and other healthful components remain far below dietary guidelines, with 45.6% of adults and 56.1% of children continuing to have poor-quality diets overall, and most of the remainder having intermediate-quality diets, with very few Americans having ideal diets ( 22 , 23 ). While less well documented by national surveillance data, the levels and types of food processing have substantially changed in the past 50 y. Ultra-processed foods now contribute ∼60% of all calories in the US food supply ( 24 ). These changes in our nutrition and corresponding diet-related illnesses are associated with rising health care costs, widening diet-related health disparities, and weakened national security and military readiness ( 25 ).

Between 1980 and 2018, the percentage of US children with obesity increased from 5.5% to 19.3%, whereas the percentage of adults with obesity increased from 15% to 42.4% ( 26–30 ). Nearly 3 in 4 American adults are now either overweight or obese ( 26 , 31 , 32 ). Across all preventable risk factors for disease in the US, poor diet is now the leading cause of poor health, associated with more than half a million deaths per year—or more than 40,000 deaths each month ( 1 ). Along with suboptimal diet, adiposity and physical inactivity are shared risk factors for illness and death ( 33–37 ). Over the last 20 y, the number of adults with diabetes has more than doubled ( 38 ), and today, >100 million Americans—nearly half of all adults—suffer from diabetes or prediabetes ( 39 ). Cardiovascular disease afflicts ∼122 million Americans and causes ∼840,000 deaths each year ( 40 ). Many of these diseases disproportionately affect older Americans, and as our nation's demographics shift toward an aging population, the burden of diet-related ailments on society will accelerate ( 41 , 42 ). In short, more Americans are sick or suffer from major medical conditions than are healthy, and much of this is related to diet-related illness.

Although the general contours of healthy eating patterns have been outlined by important advances in nutrition science, many questions remain unanswered ( 10 ). Modern nutrition science is still evolving, with a rapidly growing but still relatively nascent repertoire of research methods, foundational science, and large-scale interventions to investigate and address diet-related diseases. For most of the 20th century, the focus of nutrition research was on isolated vitamins and minerals and their role in clinical nutrient deficiency diseases. This effort led to major accomplishments, such as documenting the role of individual nutrients in diseases such as pellagra (vitamin B-3 deficiency), rickets (vitamin D deficiency), and scurvy (vitamin C deficiency), among others, and then quickly mobilizing innovative technology such as fortification of staple foods, along with well-coordinated policy and programmatic responses, to address these conditions. In comparison, the shift of nutrition science to focus more meaningfully on diet-related chronic diseases, such as heart disease, strokes, cancer, diabetes, obesity, brain health, and autoimmune and inflammatory diseases, is much more recent, largely begun only since the 1980s. In this short period, important knowledge has been gained. Yet, the investment and pace of progress have been insufficient to address the burgeoning rates of diet-related illness and the associated societal and economic consequences.

For example, in detailed reviews of available research by the 2015 Dietary Guidelines Advisory Committee (DGAC), numerous areas were identified as having only moderate, limited, or insufficient (not assignable) scientific evidence for making dietary recommendations ( Supplemental Table 1 ). These include, for instance, evidence that healthier dietary patterns favorably influence body weight or obesity in adults (moderate evidence) or children or adolescents (limited); reduce the risk of type 2 diabetes in adults (limited) or children (not assignable); or are associated with lower risk of colorectal (moderate), breast (moderate to limited), lung (limited), or prostate (not assignable) cancer; age-related cognitive impairment, dementia, or Alzheimer disease (limited); depression in adults (limited) or children, adolescents, or postpartum mothers (not assignable); or bone health in adults (limited) or children and adolescents (not assignable). Considering specific individual foods and nutrients, the 2015 DGAC concluded that evidence is only moderate that coffee consumption is associated with reduced risk of type 2 diabetes, cardiovascular disease, or certain cancers and is limited for caffeine intake and lower risk of cognitive decline and Alzheimer disease or increased risk of miscarriage, stillbirth, or low birth weight. The 2015 DGAC found limited evidence to address additives, such as aspartame and risk of cancers or preterm delivery. Evidence was considered moderate for any specific sodium target (e.g., 2400 mg/d) for blood pressure control or risk of cardiovascular outcomes; limited or not assignable for potassium intake and these outcomes; moderate or limited for low-calorie sweeteners and body weight or diabetes; and limited for replacing saturated fat with monounsaturated fat for reducing cardiovascular risk.

The 2015 DGAC identified multiple specific areas of research needs ( Supplemental Table 2 ). Examples include the need to conduct research on 1 ) the dietary needs and intakes of older adults, whether polypharmacy plays a role in nutritional adequacy, and whether comorbidities, such as poor dentition, musculoskeletal difficulties, arthralgias, vision loss, and other age-related symptoms, affect their ability to establish and maintain proper nutritional status; 2 ) nutrition transitions from early childhood to adolescence to identify how and why diets change so rapidly during this period, the driving forces behind these changes, and effective programs to maintain positive nutrition habits established in young children; 3 ) the validity, reliability, and reproducibility of new biomarkers of nutritional status; 4 ) the effects of fortification strategies and supplement use on consumer behaviors and diets related to calcium, vitamin D, potassium, iron, and fiber; and 5 ) design approaches to quantify diets in large population-based studies.

Overall, advances in science have identified numerous new opportunities for research and pressing scientific questions that must be addressed ( Figure 2 ). These topics, discussed further in “The Opportunity” section below, include fundamental questions about foods and diet quality in relation to obesity, insulin resistance, diabetes, cancers, and other conditions; the interactions between diet, physical activity, the microbiome, and immunity and other key health defenses; and the health effects of various forms of food processing, additives, fermentation, and probiotics. Other topics include personalization of nutrition based on each person's background, habits, genes, microbiome, medications, and existing diseases; how hunger and food security influence wellness and key approaches to address this interaction; the intersections of plant and animal breeding and farming practices with nutrition and sustainability; and many other questions. Thus, we have learned much, but the present state of science remains far from offering a sufficient understanding of many crucial facets of food and nutrition fundamental to human health ( 43–47 ). Scientific progress is being made, but at the current pace it may take many decades to meaningfully understand and reduce the prevalence and impact of the broad range of diet-related chronic diseases that we face.

The economic costs of nutrition-related diseases are staggering and ever rising. As a share of our economy, total US health care expenditures have nearly tripled since 1970, from 6.9% to 17.9% of Gross Domestic Product (GDP) ( 48 , 49 ). These increases are harming government budgets, competitiveness of US businesses, workers’ wages, and livelihoods of families. Federal health care spending has increased from 5% of the total federal budget in 1970 to 28% in 2018, reducing available funds for other priorities. Similarly, average state government spending on health care has increased from 11.3% of state budgets in 1989 to 28.7% in 2016. For US businesses, health care expenditures have increased 15-fold in 50 y, from $79 billion in 1970 to $1180 billion in 2017 (in constant 2017 dollars) ( 49 ). Over this same period, annual per capita health care spending in the US has increased from $1797 to $10,739 (in constant 2017 dollars) ( 49 ). And, ∼85% of total US health care expenditures are related to management of diet-related chronic diseases ( 50 ). For example, the total direct health care and indirect economic costs of cardiovascular diseases are estimated at $316 billion/y; of diabetes, at $327 billion/y; and of all obesity-related conditions, at $1.72 trillion/y ( 51 , 52 ). These economic costs exceed the annual budget appropriations of most federal departments and agencies, such as (for fiscal year 2020) the budgets of the USDA ($150 billion) ( 53 ), DoE ($72 billion) ( 54 ), DHS ($51 billion) ( 55 ), DoJ ($33 billion) ( 56 ), NIH ($42 billion) ( 57 ), CDC ($12.7 billion) ( 58 ), EPA ($9.5 billion) ( 59 ), and FDA ($5.9 billion) ( 59 ).

Rising health care expenditures are straining government budgets and private business growth; limiting the ability to support other national, state, and business priorities; contributing to stagnating wages; and bankrupting individuals, families, and small businesses ( 60 , 61 ). Improving what Americans eat would have a significant impact on reducing diet-related chronic diseases, lowering health care spending, and creating new opportunities for innovation and jobs. Although advancing science has elucidated the broad outlines of healthy eating patterns for making many general dietary and policy recommendations, numerous critical questions remain unanswered, with corresponding scientific debate and public confusion. There is a large and growing appetite among American citizens for credible, rigorous nutritional science information, both for general health but also for treating many specific diseases and ailments. Consumers are inundated with often conflicting information from multiple sources, including the internet, social media, television, marketing, and food and menu labeling, among others, making it difficult to discern trusted information for making informed choices ( 62 ). Many American adults remain unaware of foundational federal guidance on nutrition ( 63 , 64 ), and use the internet or other sources for seeking guidance on what to eat ( 65 ).

Poor nutrition also contributes to profound disparities. Prior to COVID-19, food insecurity was a significant challenge for 1 in 8 Americans ( 66 , 67 ), and is expected to more than double this year. A total of 37 million Americans, including 11 million children, experienced food insecurity in 2018 ( 68 , 69 ). The dramatic increase in unemployment with COVID-19 is expected to cause food insecurity for an additional 18 million US children, bringing the total to 40% of all US youth ( 70 ). Americans are also experiencing ever-widening disparities in diet quality and diet-related chronic diseases by race/ethnicity, education, and income ( 22 , 71–75 ). While social and economic factors such as lower education, poverty, bias, and reduced opportunities are major contributors to population disparities, they are likewise major barriers to healthy food access and proper nutrition. Poor diets lead to a harsh cycle of lower academic achievement in school, lost productivity at work, increased chronic disease risk, increased out-of-pocket health costs, and poverty for the most vulnerable Americans ( 76 ). Addressing these profound diet-related disparities experienced by rural, low-income, and minority populations requires a better understanding of their multilevel and interrelated individual, social, and environmental determinants, and corresponding translational solutions ( 77 , –80 ). As one example, the 2015 DGAC concluded that the current body of evidence on the links between access to retail food outlets and dietary intake was limited and inconsistent ( 81 ).

Our national nutrition challenges also diminish military readiness ( 82 ). For much of human history, governments have prioritized nutrition to enable a high-performing, able military. During World War II, for example, recognition of the national security threat of undernutrition produced strong federal actions, such as creation of the first RDAs by President Franklin D Roosevelt in 1941 and of the National School Lunch Program by Congress in 1945 ( 83 ). Today, we face very different nutritional challenges: 71% of young people between the ages of 17 and 24 do not qualify for military service, with obesity being the leading medical disqualifier ( 25 ). Since 2010, Mission: Readiness—a group of >750 retired US generals, admirals and other top military leaders—has produced several reports documenting the national security threat of childhood obesity ( 25 , 84 , 85 ). In addition, obesity and other diet-related chronic diseases are common among veterans, with more than one-third of veterans seen at the Veterans Health Administration (VHA) being obese ( 86 ). Food insecurity is common among veterans seen at the VHA and is associated with suboptimal control of medical conditions ( 87–89 ). Both obesity and food insecurity are common and often coexist in active-duty military families ( 90 , 91 ). Overall, diet-related illnesses are harming the readiness of US military forces and the budgets of the DoD and VA ( 86 , 92 , 93 ). A more robust understanding of nutrition is a top DoD priority to maximize the performance of active-duty forces and their recovery from physical and psychologic injuries ( 11 ).

Our food systems are creating challenges to our climate and natural resources with widespread related health consequences ( 94 ). Emerging science is advancing the understanding of how nutrition security—access to affordable, sufficient, safe, and nutritious food—is interrelated with challenges and opportunities in use of natural resources ( 11 , 94 ). While federal nutrition research and coordination is the focus of this white paper, we recognize that nutrition research and agricultural and food systems research are mutually interdependent ( 95 ). Ongoing market forces, food production, and consumption patterns, among other factors, are creating not only poor health but large and unsustainable environmental impacts ( 96 ). On a global scale, one-quarter of greenhouse gases, 70% of water use, and 90% of tropical deforestation are related to food production. Climate change is warming the planet, contributing to lower crop yields and new economic risks for farmers. These issues and corresponding potential solutions are complex: for example, greenhouse gas emissions have global impact, while water use has more regional impact ( 97–101 ). Food waste worsens resource losses, with at least one-third of food produced in the US wasted during post-harvest, and consumer losses ( 102 ). The future productivity of US agriculture faces additional growing environmental challenges such as resource scarcity, loss of biodiversity, and soil degradation ( 96 ). These sustainability issues have direct relevance for human health, increasing the risk of infectious diseases, respiratory illness, allergies, cardiovascular diseases, food- and waterborne illness, undernutrition, and mental illness ( 103 , 104 ).

Addressing all of these nutrition-related health, equity, societal, and economic burdens requires advancing science to better understand their biological, individual, social, and environmental drivers. Current scientific knowledge, however, remains insufficient to address the mechanistic determinants and solutions of these complex challenges.

The Current Federal Nutrition Research Landscape

The federal government is the largest supporter of US nutrition research, with a diverse federal nutrition research infrastructure that generates critically important research and surveillance across a range of areas. A new federal research investment and coordination structure must leverage, harmonize, and catalyze—not diminish or replace—these efforts being led across multiple federal departments and agencies.

No current or complete accounting of all federal nutrition research funding is available ( 12 , 105 ). For this work, we obtained and collated information on the largest departments and agencies focused on nutrition research, and their current estimated spending on nutrition research. These findings are presented in  Table 1 , and summarized further below. The NIH and USDA are by far the 2 largest funders of federal nutrition research. As recently described ( 12 ), NIH and USDA negotiated how to share priorities for nutrition science after the 1978 Congressional report on Nutrition Research Alternatives ( 106 , 107 ). The Secretaries of HHS and USDA agreed that NIH would take the lead on research related to the biomedical aspects of nutrition (e.g., diagnosing and treating diseases), while USDA would be responsible for research on healthy diets for the general population. In addition to NIH and USDA, many other departments and agencies conduct or utilize nutrition research ( 11 ), as described in further detail below.

Current federal nutrition research agencies and departments participating in the US ICHNR 1

In 2003, the Director of the White House Office of Science and Technology Policy (OSTP) estimated that federal investment for food-related (beyond nutrition alone) research and development was $2.5 billion/y ( 105 ). A 2015 USDA report estimated that overall federal investment in nutrition research was $1.6 billion/y in 2009, increased from ∼$0.8 billion/y in 1985 (in constant 2007 dollars) ( Figure 3 ) ( 108 ). The increase occurred primarily at NIH, while nutrition funding at USDA declined in real dollars during this period. However, total NIH research funding also doubled between fiscal year 1994 and 2003 (constant dollars) ( 109 ). Thus, as a share of overall research expenditures, federal nutrition research spending remained generally flat, despite the dramatic increase in diet-related illnesses such as obesity and diabetes from 1980 to the present ( 12 ). A limitation of all such estimates is the reliance on keyword searches of grant projects, which may incorporate funding only peripherally related to nutrition. For example, funding for research identified as related to “obesity” increased nearly 4-fold between 1985 and 2009, and was counted as “nutrition” research ( 108 ).

Estimated overall federal expenditures for nutrition research, 1985–2009 (top panel) ( 108 ); and within NIH for fiscal year 2019 (bottom panel) ( 110 ). The top panel is based on information provided by the DHHS (NIH, FDA, CDC), USDA, VA, USAID, DoD, DoC, NSF, and NASA using data from the NIH Human Nutrition Research Information Management system and the Biomedical Research and Development Price Index. The bottom panel is based on data from all NIH institutes, centers, and offices ( x axis) that provided funding for nutrition research in fiscal year 2019, listed in alphabetical order. DHHS, Department of Health and Human Services; DoC, Department of Commerce; DoD, Department of Defense; FIC, Fogarty International Center; FY, fiscal year; NASA, National Aeronautics and Space Administration; NCATS, National Center for Advancing Translational Sciences; NCCIH, National Center for Complementary and Integrative Health; NCI, National Cancer Institute; NEI, National Eye Institute; NHGRI, National Human Genome Research Institute; NHLBI, National Heart, Lung, and Blood Institute; NIA, National Institute of Aging; NIAAA, National Institute on Alcohol Abuse and Alcoholism; NIAID, National Institute of Allergy and Infectious Diseases; NIAMS, National Institute of Arthritis and Musculoskeletal and Skin Diseases; NIBIB, National Institute of Biomedical Imaging and Bioengineering; NICHD, Eunice Kennedy Shriver National Institute of Child Health and Human Development; NIDA, National Institute on Drug Abuse; NIDCD, National Institute on Deafness and Other Communication Disorders; NIDDK, National Institute of Diabetes and Digestive and Kidney Diseases; NIEHS, National Institute of Environmental Health Sciences; NIGMS, National Institute of General Medical Sciences; NIMH, National Institute of Mental Health; NIMHD, National Institute on Minority Health and Health Disparities; NINDS, National Institute of Neurological Disorders and Stroke; NINR, National Institute of Nursing Research; NLM, National Library of Medicine; NSF, National Science Foundation; OD, Office of the Director; USAID, US Agency for International Development; VA, Department of Veterans Affairs. Reprinted with permission from the USDA Economic Research Service and NIDDK Office of Nutrition Research.

The NIH is the largest biomedical research agency in the world and largest funder of US nutrition research ( 110 ). Important intramural and extramural nutrition research occurs across multiple institutes, centers, and offices, in particular the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK); National Heart, Lung, and Blood Institute (NHLBI); National Cancer Institute (NCI); National Institute of Aging (NIA); Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD); and NIH Office of the Director ( 110 ). These institutes focus on diseases or specific subsets of the population, rather than food and nutrition. For example, NIDDK research efforts include diabetes and other endocrine and metabolic diseases; liver disease and other digestive diseases and conditions; nutritional disorders, such as inborn errors of metabolism; obesity; kidney diseases, such as polycystic kidney disease and glomerular disease; urologic diseases and conditions; and blood diseases ( 111 ). The NHLBI aims to promote the prevention and treatment of heart, lung, and blood diseases, which includes strategic priorities around dietary assessment methodologies that combine objective dietary measures and biomarkers to help identify dietary patterns and food constituents that contribute to weight maintenance and to inform intervention strategies to lower cardiometabolic risks ( 112 ). The NCI leads, conducts, and supports cancer research to advance scientific knowledge and help all people live longer, healthier lives, which includes efforts to advance dietary assessment methodology ( 113 ). The NIA leads a broad scientific effort to understand the nature of aging and to extend the healthy, active years of life, including building the understanding of the roles of nutrition, obesity, sleep, and metabolic status ( 114 ). The NICHD aims to investigate human development through the entire life process, including the role of nutrition ( 115 ).

Within the NIH Office of the Director, as one example of several offices relevant to nutrition, the NIH Office of Dietary Supplements works to promote the scientific study of the benefits of dietary supplements in maintaining health and preventing chronic disease and other health-related conditions ( 116 ).

For fiscal year 2019, total NIH expenditures for nutrition research were estimated at $1.9 billion, supporting a total of ∼4600 active projects across at least 25 of the 27 NIH institutes, centers, and offices ( Figure 3 ) ( 110 ). NIH's investment in nutrition research has been estimated at 5% of total funding, a percentage that “has remained largely flat for at least three decades, and pales in comparison to many other areas of research” ( Figure 4 ) ( 12 ). A separate analysis of NIH-supported research grants and cooperative research projects between 2012 and 2017 found that only 16.7% of projects and 22.6% of funding supported investigations focused on primary prevention or secondary prevention (treatment) of disease in humans ( 117 ). And, among this subset, only 7.8% included a focus on diet ( 118 ). Thus, this careful analysis suggests that only 1.3% of all research projects supported by NIH in recent years focused on the role of diet in the prevention or treatment of disease in humans ( 119 ). Another recent NIH analysis evaluated the leading risk factors and causes of death and disability in the US, compared with NIH funding on these factors, and concluded that large mismatches exist between the top causes of poor health versus research funding to address them, with the largest gap being for nutrition ( 120 ).

Trends in NIH investments in total nutrition research based on data from the NIH, Hathi Trust, and the Government Publishing Office ( 12 ) (top panel) and the 2020 NIH analysis of the percentage of NIH's prevention research projects focused on leading risk factors for death in the US compared with the percentage of deaths caused by these leading risk factors in the US ( 120 ) (bottom panel). Top panel adapted from POLITICO Pro Datapoint ( 12 ), with graphic design support courtesy of Ink&Pixel Agency.

Over the years, NIH has aimed to coordinate the diverse nutrition science research being conducted or supported across the agency through a range of initiatives, including recent efforts to help accelerate the science of obesity research ( Supplemental Table 3 ) ( 121 ). In 1975, the NIH Nutrition Coordinating Committee (NCC) was established within the NIH Office of the Director to improve nutrition research coordination and communications within NIH and across the federal government ( 122 ). In 1993, NCC was moved from the Office of the Director, the highest level of leadership within NIH, into one of the institutes, NIDDK, where NIH Division of Nutrition Research Coordination (DNRC) was established ( 123 ). The DNRC comprised ∼10 full-time employees, more than half with PhDs. In 2015, DNRC was disbanded and transitioned from an NIDDK Division into an NIDDK Office, the Office of Nutrition Research (ONR) ( 123 ) [within NIDDK, a lower organizational stature and size than a division ( 124 )]. The ONR now comprises 2 PhD-level scientists and 3 other staffers ( 125 ). The ONR hosts the renamed and slightly restructured NIH Nutrition Research Coordinating Committee (NRCC) ( 122 ). In 2016, one of the main tasks of ONR was to develop the first overall NIH strategic plan to expand mission-specific nutrition research ( 123 ). The NIH Nutrition Research Task Force was established later in 2016 to guide the development and implementation of the first NIH-wide strategic plan for nutrition research for the next 10 y ( 126 ). A draft plan was released for public comment in the Fall of 2018—the original date the final plan was to be made public ( 127 , 128 ).

The final 2020–2030 Strategic Plan for NIH Nutrition Research was released in May 2020. Including several themes from the 2016 National Nutrition Research Roadmap ( 11 ) (see “ICHNR” section below), this first-of-its-kind NIH plan is organized around 4 strategic goals ( 129 ):

• Spur discovery and innovation through foundational research: What do we eat and how does it affect us?
• Investigate the role of dietary patterns and behaviors in optimal health: What and when should we eat?
• Define the role of nutrition across the lifespan: How does what we eat promote health across the lifespan?
• Reduce the burden of disease in clinical settings: How can we improve the use of food as medicine?

The NIH plan includes 5 cross-cutting areas: minority health and health disparities; health of women; rigor and reproducibility; data science, systems science, and artificial intelligence; and training the nutrition scientific workforce ( 130 ). Examples of priority objectives in the 4 strategic areas include to investigate bioinformatic gaps in nutrition-related genes and pathways, diet-host-microbiome interrelationships, new tools for microbiome and precision nutrition research, mechanisms of interindividual variability in responses to food-based dietary patterns, influence of diet on infant developmental and health outcomes, the role of nutrition in older adults to promote healthy aging, and interactions between drugs, diseases, and nutrition to improve clinical care and outcomes, among others. How new NIH funding streams, leadership, coordination structures, or other implementation strategies may help achieve these important goals were not detailed. Also in May 2020, the trans-NIH Precision Nutrition Working Group of the NIH Common Fund, in collaboration with the NIH Nutrition Research Task Force, published a request for information on the challenges and opportunities in precision nutrition research ( 130 ). The NIH Common Fund is planning a potential program in Precision Nutrition for fiscal year 2021 ( 131 ), potentially similar to other Common Fund–supported endeavors such as the All of US Research Program and the NIH Human Microbiome Project (see “Options” section below).

Starting in 1895, Dr. Wilbur Atwater's pioneering work at USDA laid much of the groundwork for modern nutrition science in the US as well as many current USDA nutrition research programs ( 132 ). The USDA is the second largest federal funder of nutrition-relevant research, with activities across multiple agencies ( Table 1 ) ( 133 ). The Farm Bill requires the Secretary of USDA to establish and support food and human nutrition research as a distinct mission of the Department, including coordinating nutrition research within the Department and with agencies across the federal government, as well as using formalized mechanisms for external input. The USDA also has a major focus on implementing federal nutrition programs to segments of the public, which constitute the majority of USDA's budget. The importance of the nutrition assistance and associated nutrition education programs for improving food security and health and preventing disease in low-income populations creates a particularly important need to integrate and connect nutrition research from within and outside USDA to inform and guide policy development for these programs.

The agencies in USDA's Research, Education, and Economics (REE) mission area work to integrate research, analysis, and education to create a safe, sustainable, competitive US food and agricultural system and strong, healthy communities, families, and youth ( 134 ). REE science agencies include the ARS, NIFA, ERS, and National Agricultural Statistics Service ( 135 ). The ARS’ Human Nutrition Program emphasizes food-based approaches for health, including a core network of 6 internationally recognized Human Nutrition Research Centers with scientists, equipment, and facilities for long-term, multidisciplinary, translational research ( 136 , 137 ). NIFA supports postsecondary education at 113 land-grant colleges and universities (Public Law 37–130), as well as 21 historically black colleges and universities (Public Law 51–841) and 37 tribal colleges and universities (Public Law 89–329) ( 138–141 ). While federal funding for these schools initially focused on agricultural research and extension, over time these schools have increasingly focused on human nutrition and food research and extension nutrition education, although the recent growth in research is largely through additional competitive grant mechanisms rather than direct NIFA support to the Agricultural Experiment Station. NIFA further supports extramural nutrition research, often with a focus on integrating agricultural considerations with promotion of health and decreasing health disparities; this work includes funding projects aiming to identify environmental and behavioral factors that act as barriers to consumption of a high-quality diet, while identifying factors that promote healthy eating behaviors (e.g., increasing home access and availability of fruits and vegetables) ( 142 ). The ERS’ food and nutrition research aims to study demographic, social, economic, and informational determinants of adequacy and healthfulness of the American diet, related health outcomes, and corresponding health care expenditures ( 11 , 143 ). This research includes examining interactions among consumers, food industry, and government as they relate to the food supply, markets, and access; food choice and its impact on diet quality; federal regulations and other aspects of food policy; and the USDA's nutrition assistance programs in meeting public policy and nutrition goals.

The Food and Nutrition Service (FNS) is the only agency of the Food, Nutrition, and Consumer Services mission area. The FNS administers 15 domestic nutrition assistance programs, conducts some limited research, and makes use of nutrition research sponsored by other federal agencies to help assess and improve these programs. And, as discussed in the cross-governmental section below, the USDA FNS Center for Nutrition Policy and Promotion (CNPP) conducts the evidence analysis for the DGAs, including nutrition evidence systematic reviews, data analysis, and food pattern modeling, and develops the corresponding consumer-facing education tools (e.g., MyPlate) ( 144 , 145 ).

USDA investments in research and statistics, including nutrition, have fallen below 1980s levels in constant dollars ( Figure 3 ) ( 12 , 146 ). Indeed, as a percentage of GDP, public investment in agrifood (agriculture and food combined) research and development (4.2%) and particularly food research and development (1%) was lower in 2018 than pharmaceutical research and development (4.9%) ( 147 ). The US fell behind China in public agricultural research in 2009, and now only invests half the amount as China ( 148 ). US public sector funding for agricultural research and development is also lower than India, Western Europe, and the Asia-Pacific region including Canada, using constant 2011 purchasing-power parity ( 148 ). Yet, growth in productivity in the farm sector has come almost exclusively from science-based innovations ( 146 ). Declines in US public funding for food and agriculture research and development “risks national competitiveness, long-term cutting-edge scientific discovery, and the next generation talent pipeline” ( 147 ). Specific to nutrition, as one example, the ARS budget for human nutrition research and monitoring, including funding for 6 important extramural and intramural Human Nutrition Centers nationally, has been flat since 1980 in constant dollars ( Figure 5 ) ( 132 ). In addition, 2 USDA research and statistical agencies that include nutrition research—ERS and NIFA—were relocated to Kansas City, Missouri, at the start of fiscal year 2020 and lost 50% (ERS) and 71% (NIFA) of their workforce ( 149 ). A recent Congressional Research Service analysis reported the leadership positions at NIFA and ERS have been staffed primarily by acting officials since the relocation and indicated that Congress may be interested in how NIFA and ERS are meeting their responsibilities with reduced workforces and as new staff are potentially hired ( 150 ). These trends demonstrate declining investments in science to advance US food and agriculture to increase health, sustain our natural resources, and stimulate rural economic development.

Trends in USDA ARS investments for total nutrition research based on data from the USDA, Hathi Trust, and the Government Publishing Office ( 12 ) (top panel) and for human nutrition research and monitoring for fiscal years 1978–2010 based on data from the USDA ( 132 ) (bottom panel). In the bottom panel, shaded bars represent absolute yearly funding (millions of dollars) and open bars represent funding adjusted to 1978 dollars ( https://data.bls.gov/cgi-bin/cpicalc.pl ). ARS, Agricultural Research Service; FY, fiscal year. Top panel adapted from POLITICO Pro Datapoint ( 12 ), with graphic design support courtesy of Ink&Pixel Agency.

The USDA has aimed to coordinate nutrition research within and outside the department in many different ways ( Supplemental Table 4 ) ( 132 ). The Food Security Act of 1985 (Public Law 99–198) required the Secretary of Agriculture to submit to Congress “a comprehensive plan for implementing a national nutrition research program, including recommendations relating to research directions, educational activities, and funding levels necessary to carry out such a plan.” This plan was submitted to Congress in 1986, but no new legislative mandates or change in mission resulted from this report ( 132 , 151 , 152 ). In 1993, USDA revised its human nutrition program coordination structure and developed a Human Nutrition Policy Committee that reported to the Secretary's Policy Coordination Council and a USDA Human Nutrition Coordinating Committee (HNCC) that reported to the Policy Committee. The Human Nutrition Policy Committee has not been active since the late 1990s. HNCC is chaired by an ARS representative and vice-chaired by an FNS representative and includes members from a variety of USDA agencies with additional liaisons from HHS. Over the last 2 decades, HNCC has generally met quarterly. Each March, HNCC coordinates National Nutrition Month activities at USDA and functions as the steering committee for the website Nutrition.gov ( 153 ). USDA Office of the Chief Scientist (OCS) was established by Congress in 2008 (Public Law 110–234) “to provide strategic coordination of the science that informs USDA's and the federal government's decisions, policies, and regulations that impact all aspects of US food and agriculture and related landscapes and communities.” ( 154 ) The OCS advises USDA's Chief Scientist and the Secretary of Agriculture in multiple areas, including the following: Agricultural Systems and Technology; Animal Health and Production, and Animal Products; Plant Health and Production, and Plant Products; Renewable Energy, Natural Resources, and Environment; Food Safety, Nutrition, and Health; and Agricultural Economics and Rural Communities. By statute, OCS is primarily staffed by detailed staff from other departments and agencies across the government for potentially up to 3 years. In 2017, OCS hosted the first-of-its-kind USDA Intra-Departmental Nutrition Workshop Series and identified major gaps and needs to strengthen coordination of USDA nutrition research. These gaps and needs included the following: assessing existing and potential new means of coordination and collaboration; developing new interdepartmental working groups and interest groups; identifying new and improved ways to enhance coordination with USDA food safety efforts; better utilizing the HNCC; and hosting overviews of USDA nutrition relevant databases and related data science trainings and resources. The chair of this workshop series was detailed to OCS for 1 y and completed the detail a few months after this workshop. A 2019 GAO report noted there are currently no plans for another intradepartmental meeting on nutrition ( 155 ).

In 2020, USDA put forth a new Science Blueprint for the next 5 y to help promote synergy across the department for prioritized objectives and strategies ( 156 ). This Blueprint includes specific objectives in nutrition and health promotion, such as to develop and update the current evidence base to promote proper macro- and micronutrient intake among critical age groups or life stages, such as women who are pregnant or lactating, infants, children, adolescents, working-age adults, tribal members, and seniors; provide guidance and incentives to promote healthier eating patterns so that the US can reduce incidence of, and morbidity from, obesity and diet-related chronic diseases; promote food systems that reduce the prevalence and severity of food insecurity; and expand understanding about the impacts of USDA nutrition assistance programs on human health, communities, and the economy. The USDA Science Blueprint has objectives related to infrastructure, innovation, and well-being: to develop and evaluate methods to increase access to low-cost and nutritious food as well as sustain efficient agriculture and bioeconomy systems in rural communities; and to evaluate alternative systems that may improve the quality, resiliency, and sustainability of food, fiber, forest, and fuel supplies. The USDA also set forth objectives to work toward being a “beacon for science”: to encourage a global conversation and facilitate such discussion within decision-making bodies about literacy in agriculture, food, forestry, health, and science; advocate globally for the development of science-based, international and domestic standards, regulatory approaches, and policies, including those guiding the development of new and emerging technologies; develop an effective and diverse US agriculture workforce that contributes to safer, healthier, vibrant, sustainable, and innovative communities; enhance the capacities of USDA and other institutions in workforce development, with attention towards developing scientists and practitioners familiar with developing technologies and innovative practices; and develop and expand degree, certificate, curriculum, and youth programs that integrate science, technology, engineering, and mathematics (STEM) into instruction, considering real-world challenges relevant to agriculture and food science. How new federal funding streams, leadership, or coordination structures may help achieve these laudable goals were not addressed in the report. On 20 February 2020, the Secretary of Agriculture put forth a new Agriculture Innovation Agenda, a department-wide initiative to align resources, programs, and research to position American agriculture to better meet future global demands. Benchmarks of success included reducing US food loss and waste by 50% by the year 2030 and reducing US nutrient loss in water by 30% by 2050 ( 157 ).

Nutrition research in other federal departments and agencies

In addition to NIH and USDA, many other departments and agencies conduct or utilize nutrition research ( Table 1 ). This section highlights summaries provided by 8 departments and agencies in the Topics of Interest section of the 2016 National Nutrition Research Roadmap, as well as any major developments since then ( 11 ). The Roadmap explained each of the participating ICHNR department and agency's missions, roles and responsibilities, and mechanisms for supporting and/or using nutrition research; many include histories and contemporary overviews of research needs and interests.

The DoD, for example, focuses on nutrition's role in human performance and resilience. At the US Army Natick Soldier Systems Center, DoD supports scientists and technologists conducting innovative research to develop foods and combat rations that are nutritious, palatable, and nonperishable ( 158 ). In Natick, the Combat Feeding Directorate, a part of the Combat Capabilities Development Command of the US Army Futures Command, provides DoD with a joint-service program responsible for research, development, testing, and integration and engineering for materiel solutions such as combat rations, food service equipment technology, and combat feeding systems. The Military Nutrition Division (MND) of the US Army Research Institute of Environmental Medicine, a part of the US Army Medical Research and Materiel Development Command, also of the US Army Futures Command is co-located in Natick with the Combat Feeding Directorate. The MND conducts research that provides the biomedical science basis for warfighter nutritional requirements utilized for the development of rations, menus, policies and programs that enable warfighter health and performance, evaluates warfighter nutritional status, and examines interactions between nutrition, health, performance and the operational environment. The Consortium for Health and Military Performance (CHAMP) at the Uniformed Services University of the Health Sciences (DoD's health sciences university) conducts various nutrition-related research on the nutrition environment (Go For Green and the Military Nutrition Environment Assessment Tool) and tests strategies to mitigate the consequences of environmental and/or physiological stressors and sustain physical and cognitive performance. CHAMP is also extensively involved in dietary supplement research—from beneficial ingredients to those that could compromise force readiness. Both MND and CHAMP collaborate on projects whenever possible to maximize efficiencies and effectiveness.

NASA conducts nutrition research to understand the dietary requirements of space travelers and the role of nutrition in human adaptation to microgravity, each critical to crew safety and mission success. The CDC addresses population nutrition through surveillance, intramural and extramural research, and translation of research into program implementation. The FDA is responsible for protecting the public health by ensuring the safety of our nation's food supply, among other activities ( 159 ). The FDA works to foster an environment to promote healthy and safe food choices through several actions. This includes providing and supporting accurate and useful nutrition information and education to customers, monitoring and assessing emerging nutrition science and changes in the composition of foods in the marketplace in relation to the health status of Americans, and encouraging and facilitating new products and product reformulation to promote a healthier food supply. To achieve this mission, FDA depends heavily on federal nutrition research from other departments and agencies and also conducts its own research activities, such as consumer studies to support nutrition labeling and claims, assessments of constituents of the food supply, development of methods for analyzing food constituents, surveys on health, analyses of dietary intake, monitoring of adverse events from dietary foods and supplements, and cost–benefit analyses of various nutrition regulatory activities. The VA is home to the largest integrated health care system in the US. Known as the VHA, this system includes ∼150 medical centers and 1400 community-based outpatient clinics, community living centers, Vet Centers, and domiciles. The VHA Office of Research and Development supports a range of projects that relate to nutrition including The Million Veteran Program, which aims to build one of the largest databases of genetic, military exposure, lifestyle, and health information. USAID adopts, adapts, modifies, and increases the information, evidence, practices, and technologies of US institutions in human nutrition to be applicable to USAID target populations in developing countries as a key plank of US diplomacy and security. Demonstrating its increased prioritization of nutrition, USAID recently hired its first Chief Nutritionist, who aims to galvanize support for the December 2020 Nutrition for Growth Summit and secure commitments from partner countries, private sectors, and nongovernmental organizations to accelerate progress on improving nutrition worldwide ( 160 ).

There are a variety of other federal departments and agencies that are not a member of ICHNR that engage with and leverage nutrition research, such as, but not limited to, HHS Centers for Medicare and Medicaid Services (CMS), HHS Center for Medicare and Medicaid Innovation (CMMI), HHS Office of the Surgeon General, Federal Emergency Management Agency (FEMA), and Departments of Veterans Affairs, Education, Energy, Transportation, Labor, Homeland Security, Housing and Urban Development, Interior, and Justice.

Current Efforts for Cross-Governmental Nutrition Research Coordination

Given the diverse investments in nutrition research across separate federal departments and agencies, several initiatives have aimed to better coordinate these efforts. Major initiatives are summarized below.

In 1977, Congress recognized the need and called for improved coordination of human nutrition research (Public Law 95–113) ( Supplemental Text 1 ). Congress further requested its Office of Technology Assessment to review existing federal human nutrition research, with findings published in the 1978 report Nutrition Research Alternatives ( 106 ). This report found that federal nutrition research programs had failed to deal with the changing health problems of the American people. In response, Congress chartered the Joint Subcommittee on Human Nutrition Research (JSHNR), under the aegis of OSTP, who, in a 1980 report, recommended an improved planning system to coordinate federal nutrition research ( 161 ). In 1982, the GAO was also asked to review federal nutrition research and concluded that the government had no overall federal nutrition plan with specific goals or unified and coordinated strategies, while acknowledging the ongoing work of USDA, HHS, and OSTP to develop a coordinated planning system ( 162 ).

In 1983, JSHNR completed its review and recommendations, leading to the formation of the ICHNR. The aim of ICHNR was to fill the identified gaps of insufficient planning and coordination and achieve “the pursuit of new knowledge to improve the understanding of nutrition as it relates to human health and disease … in 5 major areas: biomedical and behavioral sciences, food sciences, nutrition monitoring and surveillance, nutrition education, and impact on nutrition of intervention programs and socioeconomic factors” ( 161 ). ICHNR co-chairs are the HHS Assistant Secretary for Health and USDA Undersecretary for Research, Education, and Economics (who is also USDA Chief Scientist)—positions filled by Presidential appointment with Senate confirmation. ICHNR includes representatives from multiple federal departments and agencies ( Table 1 ).

After some early collaborative successes, ICHNR had a ≥10-y hiatus ( Supplemental Table 5 ). Reassembled in 2013, ICHNR recognized the need for a new effort to coordinate federal nutrition research. This resulted in a new strategic plan, the National Nutrition Research Roadmap 2016–2021: Advancing Nutrition Research to Improve and Sustain Health ( 11 ). The Roadmap was framed around 3 questions:

• How can we better understand and define eating patterns to improve and sustain health?
• What can be done to help people choose healthy eating patterns?
• How can we develop and engage innovative methods and systems to accelerate discoveries in human nutrition?

Across these 3 questions, 11 topical areas were identified based on population impact, feasibility given current technological capacities, and emerging scientific opportunities ( Supplemental Figure 1 ) within which 120 short- and long-term research and resource initiatives were defined. Each of the participating ICHNR departments or agencies also briefly described their own interests in the Roadmap's 11 topical areas ( Supplemental Figure 2 ). The Roadmap also identified gaps in the US nutrition research workforce and put forth recommendations for developing a diverse, interdisciplinary workforce able to advance nutritional sciences research.

Notably, the Roadmap did not include any data, findings, or recommendations on current or new nutrition research investment levels, leadership, or structures ( 11 ). Thus, the Roadmap lacked any prioritization between the 120 identified initiatives, due to variable and nonharmonized funding criteria, priorities, and capacities across federal, nonprofit, and private-sector research agencies in the US and globally. This may be why a 2017 analysis found only early signs of implementation of the Roadmap among ICHNR member departments and agencies ( 163 ). ICHNR recognized that further engagement with the extramural scientific community and leveraging existing or new public–private partnerships would be important to achieving the Roadmap's goals ( 163 ). Currently, ICHNR has a narrower focus, meeting about twice per year to discuss the DGAs, DRIs, and a potential new federal database of nutrition research projects. There are few other indicators of current use or monitoring of the Roadmap's aims or progress ( 164 ). Although ICHNR is the current major entity charged with improving coordination among federal departments and agencies engaged in nutrition research ( 164 ), several structural challenges have limited its impact. These include lack of any strong or consistent connection to the White House, no specific budget appropriations, no mechanism for reporting to Congress, and absence of any well-supported infrastructure for external advisory input on cross-governmental strategies for nutrition research.

National food and nutrition monitoring and surveillance

National monitoring and surveillance are integral to nutrition research and translation. Several CDC and other federal collaborations ( Supplemental Table 6 ) and USDA efforts ( Supplemental Table 4 ) focus on food and nutrition monitoring and surveillance surveys and related research ( Supplemental Table 7 ). These federal efforts began with an international focus to lend expertise and capacity to developing nations to help them develop nutritional assessment and data-informed food and nutrition policy and programmatic responses, such as food fortification and research and training in nutritional sciences ( 165 ). For example, in 1955, the Interdepartmental Committee on Nutrition for National Defense was formed after malnutrition was identified to be common among the troops of Korea and China ( 166 , 167 ). After initial emphasis on surveillance of nutrition programs among military personnel, this Committee expanded focus to civilians in countries of “special interest,” ultimately conducting surveys in 33 developing countries ( 165 ). In 1967, this international surveillance program was reorganized in response to Congressional amendments to focus on domestic hunger and malnutrition. In 1968, the Ten State Nutrition Survey identified severe malnutrition in several low-income US states ( 168 ), stimulating Congressional hearings regarding hunger and the formation of the US Senate Select Committee on Nutrition and Related Needs. In 1969, President Nixon commissioned the first and still only White House Conference on Food, Nutrition, and Health, which put numerous concrete recommendations that led to expansion and standardization of school lunch and Food Stamps, and the creation of school breakfast and the USDA Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) ( 13 , 169 ).

In 1990, Congress (Public Law 101–445) created the National Nutrition Monitoring and Related Research Program (NNMRRP), with aims to produce a comprehensive, coordinated program for nutrition monitoring and related research to improve assessment of the US population's health and nutrition. Congress required this program to achieve coordination of federal monitoring efforts within 10 y, guided by a new Interagency Board for Nutrition Monitoring and Related Research (IBNMRR) and a 9-member National Nutrition Monitoring Advisory Council. The IBNMRR convened between 1991 and 2002, co-chaired by HHS Assistant Secretary for Health and USDA Undersecretary for Research, Education, and Economics, and was charged with designing and implementing a 10-y comprehensive plan for planning and coordinating the activities of 22 federal agencies that conduct nutrition monitoring and surveillance or related research or are major users of nutrition monitoring data ( 170 ). The IBNMRR published its 10-y plan in 1993, and summarized ongoing federal nutrition monitoring in its Directory of Federal and State Nutrition Monitoring Activities in 1989, 1992, 1998, and 2000 ( 171 , 172 ). The impact of this plan is difficult to quantify, although in its first 5 y, 97 proposed and final regulations citing NNMRRP data were published in the Federal Register ( 173 ). When this program ended in 2002, federal nutrition monitoring efforts returned to being decentralized, without explicit coordination ( 11 , 174–176 ). Current national nutrition monitoring and surveillance systems face fiscal, infrastructure, and coordination challenges that limit their capacity to respond to evolving data needs, technological advances, and demographic shifts (e.g., barriers to provide sufficient national data for the Congressional mandate in the 2020–2025 DGAs to include infants and women who are pregnant or lactating) ( 177 , 178 ).

A key cross-departmental nutrition-related activity is the DGAs, the cornerstone for many federal nutrition programs and policies ( Supplemental Table 8 ) ( 179 ). The National Nutrition Monitoring and Related Research Act of 1990 (Public Law 101–445) requires the DGAs be reviewed by the Secretaries of both USDA and HHS. Since 1995, a memorandum of understanding between the 2 departments provides a framework for this joint USDA–HHS endeavor, with each department alternating in leading each 5-y edition ( 180 ). Regardless of departmental lead, the USDA CNPP conducts the evidence analysis and develops the corresponding consumer-facing education tools ( 144 , 145 ). The HHS Office of Disease Prevention and Health Promotion (ODPHP) aims to provide technical expertise and develop DGA-related resources for health professionals.

Both agencies’ efforts are constrained by limited funding and staff dedicated to the DGAs ( 144 ). In mandating the DGAs, Congress (Public Law 101–445) did not authorize or appropriate any regular funding for the DGA process nor, importantly, for the fundamental research, monitoring, and surveillance processes necessary for developing and translating dietary guidance, among other national needs. For example, there is no consistent funding source to develop the nation's DRIs, which are foundational to the DGAs, nor to ensure sufficient research to develop the necessary evidence base for updates of either the DGAs or DRIs. Successive DGACs from the 1980 edition onwards have documented persistent, major research gaps for setting evidence-based guidelines ( 181 ). Consistent funding also does not exist to review the impact of the DGAs on the public's understanding of nutrition, food choices, or health, or on the impact on other stakeholders ( 181–183 ).

In response to concerns that the DGA process may require updated processes and coordination, in 2016 Congress instructed the National Academies of Sciences, Engineering, and Medicine (NASEM) to review and make recommendations to the process for updating the DGAs (Public Law 114–113). First, in February 2017, NASEM released “Optimizing the Process for Establishing the Dietary Guidelines for Americans: The Selection Process” ( 184 ). This report provided recommendations for how the advisory committee process can be improved to provide more transparency, eliminate bias, and include committee members with a range of viewpoints. The second report released in September 2017 was entitled “Redesigning the Process for Establishing the Dietary Guidelines for Americans” ( 182 ). This report identified the following specific opportunities for improvement in the DGA process: more consistent interpretation of purpose and target audiences of the DGA, greater transparency of the overall process, and more rigorous methodological approaches to the evaluation of the evidence. The USDA-HHS responded to NASEM recommendations in September 2018 indicating changes they will be making in the development of the 2020–2025 DGAs, such as asking for public comments on the topics and scientific questions to be examined in the review of the evidence supporting the development of the next edition ( 185 ).

In part to respond to these recommendations, the FY2019 appropriations bill provided a one-time allocation of $12.3 million to CNPP, divided over 3 y, to support the 2020–2025 DGAs ( 186 ). These one-time funds are supporting a limited set of systematic reviews of published evidence, but not any new research to address critical knowledge gaps. As previously noted, only ∼1.3% of NIH-supported research focuses on diet for the prevention or treatment of disease in humans, and furthermore, among these, only about half of the projects relate to key research gaps identified by the 2015 DGAC ( 117–119 ). In addition, while the 2014 Farm Bill (Public Law 113–79) mandated that the DGAs include, for the first time, food-based nutrition guidance for infants and toddlers aged 0–24 mo and women who are pregnant or lactating (prior DGAs did not include or consider these critical populations), no funding was authorized or appropriated to support this new mandate. Given the first-ever focus of the 2020–2025 DGAs on these important populations, it is expected that the 2020 DGAC will identify even more knowledge gaps for setting national dietary guidance than prior editions ( 187 ).

In 1990, Congress specified that the DGAs focus on the general public, not on specific nutritional recommendations for individuals suffering from diet-related conditions (Public Law 101–445). However, highlighting the scale and scope of diet-related illness, only 12% of US adults are metabolically healthy (as defined by blood glucose, cholesterol, blood pressure, and waist circumference). Thus, the DGAs’ general focus may exclude the specific dietary needs of the great majority of the US population. Until 2014, the NIH supported the development of evidence reviews and dietary guidance for patients with health issues such as overweight and obesity, high blood pressure, and high blood cholesterol, among others ( 188 , 189 ). These reviews were used by DGACs with input and endorsement from >25 professional groups. The NIH ceased these reports in 2014, in part because the CDC's mandate deals with disease prevention activities and the mandate of the HHS Agency for Healthcare Research and Quality (AHRQ) includes development of systematic evidence reviews to inform clinical practice guidelines ( 189–191 ). Certain nongovernmental professional and clinical organizations provide nutrition guidance for populations with or at risk for various chronic conditions, but these various recommendations are not coordinated ( 192 , 193 ). The current 2020 DGAC process excludes—for the first time—the use of existing high-quality nongovernmental systematic reviews and meta-analyses conducted by peer-reviewed researchers and major professional organizations. Little work has been done to understand the short- or long-term implications of NIH's shift in 2014 away from dietary guidance for populations with disease conditions, or whether CDC and AHRQ efforts are addressing this gap. Thus, currently no federal entity takes the lead on the development of evidence reviews or dietary guidance for patients with diet-related health conditions. Several organizations, including AND, the National Association for the Advancement of Colored People, and the National Hispanic Medical Association, recently formed the Food4Health Alliance to advocate for additional federal nutrition guidelines tailored to the needs of tens of millions of Americans who have diet-related diseases such as hypertension, obesity, and type 2 diabetes—conditions that also disproportionately affect minorities and underserved communities ( 194 ).

In addition to the lack of consistent funding and staff for the evidence reviews, fundamental research, monitoring, and surveillance processes needed to develop and translate dietary guidance, concerns have been raised that the process of updating the DGAs every 5 y is not protected from political or external influences (e.g., political appointees, Congress, food and beverage industries, agribusiness interests, advocacy groups) ( 182 , 184 , 195 ). A coordinated federal approach and authority for nutrition research could help strengthen the process for objective and independent development, review, and dissemination of the best science evidence to the American public in the DGAs for both healthy individuals and those with major diet-related illnesses, as well as for the evaluation of corresponding intended and unintended impacts of these guidelines and needed changes to improve these impacts.

DRIs provide specific targets for intakes of relevant nutrients for the general population ( 196 ). The first DRIs were created by Presidential mandate in 1941 when President Franklin D. Roosevelt commissioned scientists to generate new minimum dietary requirements for the population to be prepared for World War II ( 197 ). In 1943, the first RDAs (a type of DRI) were published, providing science-based guidelines for target intakes of total calories, protein, calcium, phosphorus, iron, and a few vitamins ( 198 ). Although DRIs are foundational to DGAs, the Nutrition Facts label, and other federal policies, there is no dedicated funding stream or statutory requirement for updating DRIs. Since the 1940s, DRIs have been updated sporadically dependent on available funding support provided by Congress to federal agencies (e.g., NIH and CDC) and, since the 1990s, additional contributions by the Canadian government ( 199 ). NASEM leads the updating of any DRI when requested by the federal government or instructed by Congress. Recently, a NASEM Consensus Study Report determined that crucial research gaps for setting DRIs remain largely unaddressed ( 200 ). Another challenge is there is no generally accepted process for deriving dietary reference values, which has led to several-fold differences in international recommendations and decreases their credibility ( 201 , 202 ). The ICHNR DRI Subcommittee recommended that $2 million annually be placed and held in an agency's budget (e.g., ARS, CDC, and/or NIH) to establish a consistent funding stream for setting and updating of DRIs ( 203 ); this recommendation has not been implemented.

Food and nutrition regulatory activities

Nutrition research is foundational for diverse federal, tribal, state, and local food and nutrition regulatory activities including labeling, health claims, food marketing, and oversight of food additives and other constituents ( 204 ). For example, Congress in 1990 (Public Law 101–535) authorized the Secretary of HHS to provide consumers with accurate nutrition information on food labels, giving rise to the Nutrition Facts panel. In 1994, the GAO recommended that USDA and FDA work together to perform laboratory analyses to independently verify the accuracy of nutrition labels; review labels for compliance with formatting requirements, nutrient content claims, and health claims; work with companies to correct identified inaccuracies; and where appropriate, pursue legal action against products with inappropriate labels ( 205 ). Since that time, USDA and FDA, among other federal departments and agencies, have needed to work together on these topics. Examples include the determination that partially hydrogenated oils (high in industrial trans fat) were no longer Generally Recognized As Safe (GRAS), for which NIH- and USDA-funded research, CDC surveillance data, and HHS regulatory reviews supported the FDA determination ( 206 ); and FDA's amendment of the food additive regulations to change the standard of identity of enriched flour and corn masa flour ( 207 ) to allow folic acid fortification to help prevent neural tube defects in developing infants, which required similar inputs from diverse federal research, surveillance, and regulatory efforts. Another example is the 2016 Nutrition Facts updates (e.g., requiring labeling of added sugar) based on new scientific research, updated DGAs, consensus reports, and national survey data, along with input obtained through proposed rulemaking processes ( 208 , 209 ).

In 2018, FDA announced their Nutrition Innovation Strategy that outlined key activities to take a “fresh look” at what can be done to reduce diet-related chronic diseases ( 210 ). Key elements included the following: modernizing claims such as “healthy,” modernizing ingredient labels and standards of identity, implementing the Nutrition Facts Label and Menu Labeling, reducing sodium, and expanding nutrition education (e.g., launching a new Nutrition Facts label education campaign). For example, FDA agreed with a petition that its definition of “healthy,” central for marketing regulations, was scientifically outdated and inconsistent with the DGAs and advancing research ( 211 ). Insufficient scientific evidence on dietary supplement contents, health effects, and potential risks limits the FDA's ability to provide oversight for this $40 billon/y industry ( 212–214 ). As another example, there is no DRI or listing on Nutrition Facts for many compounds that appear relevant for health such as omega-3 fatty acids, phenolics, and other phytonutrients ( 212 , 215 ). Further, many processing methods and additives banned in the European Union are permitted in the US, based on insufficient science for a definitive determination by FDA ( 216 ).

The Federal Trade Commission (FTC) has not been able to engage in any research on the impacts of food marketing to children in nearly 10 y ( 11 ). Congress prohibited FTC from completing their joint study with FDA, CDC, and USDA on nutrition standards for food marketing to children, even though this Interagency Working Group on Food Marketed to Children was established by the 2009 Omnibus Appropriations Act (Public Law 111–8) ( 11 ). Taken together, these FDA and FTC examples, among others, illustrate the crucial role of robust and coordinated federal nutrition research for numerous regulatory decisions and activities.

Federal nutrition education and promotion

Congress requires federal departments and agencies to coordinate review processes to ensure that nutrition education materials produced by the federal government are consistent with the latest DGAs (Public Law 101–445). This process is facilitated by a Dietary Guidance Review Committee, co-chaired by USDA CNPP and HHS ODPHP. More recently, DoD worked with USDA and HHS to integrate DGAs into their Go for Green® joint-service performance-nutrition initiative that aims to improve the food environment where military service members live and work ( 217 ). There is no direct, consistent Congressional investment in nutrition education for the general public, except for limited support of CNPP's dietary guidance translation activities and of USDA Food and Nutrition Service's nutrition education and promotion materials associated with the federal nutrition assistance programs. Over the years, various efforts have examined the impacts of USDA investments in nutrition education and promotion with mixed success ( 218 ). A 2019 GAO evaluation found that USDA administers 5 key programs that provide nutrition education but does not have formal coordination mechanisms for its nutrition education efforts and does not fully leverage the department's nutrition expertise ( 155 ). The GAO recommended that USDA develop a formal mechanism for coordinating nutrition education, improve the information it gathers on Supplemental Nutrition Assistance Program Education (SNAP-Ed), and take steps to fully leverage the department's expertise for nutrition education efforts.

National nutrition research database

There is no dedicated, consistent funding to identify and track federal investments in nutrition research. In 1981, Congress authorized the Human Nutrition Research and Information Management (HNRIM) system to track funding of nutrition research projects across the federal government (Public Law 97–98). From 1985 to 2015, HNRIM was maintained by NIH and, at its peak, included ≥100,000 records on federal nutrition research and training expenditures. HNRIM was a staff-curated database, with projects identified and classified by expert staff including the proportion of each project actually addressing nutrition. NIH shifted to the more automated NIH Research Portfolio Online Reporting Tools Expenditures and Results (RePORTER) system, which is based on NIH's Research, Condition, and Disease Categorization (RCDC) system to define and categorize research projects across >200 Congressionally mandated categories (Public Law 109–482). RCDC uses automated text data mining to match federal research projects to spending categories. The RePORTER system then assigns the total dollar amount of any research project that may be related to nutrition to the category of “nutrition research.” Most research projects meet criteria for and are counted across multiple categories. For instance, a single project and its total dollars may be counted as 100% nutrition, obesity, cardiovascular disease, diabetes, and prevention, among others. Besides NIH systems, a variety of other websites and databases aim to capture federal investments in human nutrition research, each using different methods with uncertain accuracy ( Supplemental Table 9 ).

Current landscape: summary

Significant efforts are occurring across diverse federal departments and agencies to leverage existing personnel and funding and coordinate existing activities to advance nutrition research. However, these efforts are not sufficiently coordinated or expansive enough to address the current and future diet-related disease burdens, or the corresponding health care spending, food insecurity and health disparities; strains on government budgets and American businesses; challenges to military readiness; and intersections with supply chains and sustainability. Many new opportunities exist to be seized, as reviewed next.

The Opportunity

A strengthening of federal nutrition research has significant potential to generate new discoveries to improve and sustain the health of all Americans. We identified and collated multiple specific priority areas that have been set forth by various federal and nongovernmental organizations ( Table 2 , Figure 2 ), and most of these have not been adequately addressed ( 11 , 81 , 147 , 196 , 219–226 ).

Opportunities for enhanced federal nutrition research coordination and investment 1

Cross-governmental strategic planning and prioritization

An expanded, coordinated federal nutrition research effort could more effectively plan and prioritize scientific discoveries across critical areas. In addition to existing priorities, such an effort would create capacity to quickly identify and address timely new scientific challenges and opportunities as they arise. Improved cross-governmental coordination would also facilitate interdisciplinary research and its societal impact. This would include accelerated translation of scientific findings into practice—for example, relevant for USDA nutrition assistance programs, FDA regulatory activities, CMS health care improvements, CDC public health efforts, DoD and VA priorities for active-duty forces and veterans, USDA agricultural priorities, and additional interests of communities, schools, and worksites. Cross-governmental coordination would also provide leadership to help develop effective public–private partnerships. A coordinated federal nutrition research authority would also facilitate appropriate expertise on review panels to identify meritorious projects and multidisciplinary investigative teams to achieve project goals and foster the development and application of high standards for scientific rigor, reproducibility, and transparency ( 11 , 227 ).

Greater science for dietary guidance to the public

While current science permits broad recommendations on healthy eating patterns, significant scientific debate and public confusion remain on many topics. As reviewed earlier, the 2015 DGAC identified numerous critical areas for national dietary guidance that require greater scientific evidence ( Supplemental Table 2 ). A 2020 DGAC member described their continuing inability to draw many conclusions from an inadequate evidence base in 2 words: “It's disheartening” ( 228 ). Similar opportunities exist for greater scientific investments to allow regular DRI updates ( 200 ). Additional areas for accelerated research include major food groups for which health effects are currently poorly understood, and the interrelationships between nutrition and the gut microbiome, immunity, epigenetics, vascular health, food allergies, and other physiological systems—all with tremendous implications for human health ( 229–232 ). The complex effects of nutrition on health, the often provocative messages from the media and other influencers, and the many real unanswered and emerging questions in nutrition science have created significant public confusion ( 233 ). As a result, the public is awash with insufficient and conflicting information on many topics, such as on popular diets for weight loss, the effects of caloric restriction or intermittent fasting, and many other topics, with limited rigorous science to provide confident guidance. A broadly expanded and coordinated effort to generate and disseminate scientifically sound nutrition research is an essential need for the American people.

Leverage new technologies and data science

Exponential growth has occurred in technology, genomics, proteomics, and metabolomics platforms; personalized and environmental sensors; and other big-data resources. Yet, the implications of these advances for a new era of nutrition research have not been realized. Strategic planning across the federal government would help mobilize limited resources for maximizing this high-cost area of research. As one example, while diverse federal departments and agencies [e.g., NIH, USDA, DoD, FDA, National Science Foundation (NSF), VA] have expressed great interest in personalized or precision nutrition ( 234 ), inadequate funding and coordination have hampered the nation's ability to fully leverage and harness the potential of the powerful, expensive ’omics platforms and related data science advances to develop personalized recommendations ( 235 ). The untapped potential of new technology and data science approaches extends far beyond precision nutrition, with promise for additional basic, clinical, environmental, and public health research on food and nutrition ( 236 ).

Foundational basic science and discovery

Fundamental research in nutrition is essential to accelerate progress but is hampered by the absence of any federal home for its investment and coordination. For example, little is known about the molecular basis of varying nutritional needs across continua from birth to older age, health to disease, or inactive to active lifestyles ( 11 ). Pathways of nutritional influences during the first 1000 days of life, when critical metabolic programming can alter lifelong and possibly epigenerational disease risk, remain critically understudied ( 237 ). Food allergies have exploded among US children, yet with little understanding of their underlying determinants or effective preventive measures ( 238 ). The molecular and metabolic influences of food on aging—including frailty, suppressed immune responses, brain function, sarcopenia, macular degeneration, renal decline, and functional decline—are essential areas of research for an aging population ( 11 ). Thousands of poorly characterized bioactive compounds in foods, such as flavanols and other phenolics, require basic research to elucidate their biochemical and physiologic effects. Accelerated basic research is also essential to assess the molecular and health impacts of other factors such as food additives, gluten, FODMAPS (fermentable oligo-, di-, mono-saccharides and polyols), low-calorie sweeteners, and other food components of public health interest.

Diet-related health disparities

Many health disparities are closely linked to nutritional disparities ( 71–73 , 239 ). Hunger and food insecurity remain pervasive in the US, with great costs for society and our health care system ( 76 , 218 , 240 , 241 ). Yet, while it is now evident that calories alone are an insufficient solution, scientific understanding remains limited on the causal intersections of food insecurity and risk of diet-related chronic diseases, and on the optimal nutritional and other translational approaches to address these challenges ( 78 , 80 , 240 , 242 ). As noted earlier, nutrition-related health disparities experienced by low-income, rural, and minority populations are influenced by a complex and insufficiently understood intersection of individual, sociocultural, and environmental determinants ( 77 , –80 ). Community-based participatory research holds promise as an approach to better understand and address community priorities around nutrition ( 243 , 244 ). Research priorities for greater investment and cross-agency coordination include the influence of context on food-related decisions and behaviors across diverse retail food environments, including but not limited to the influence of price and marketing, food access and availability, transportation options and use, perceptions of neighborhood and traffic safety, rapidly growing online purchasing including with federal nutrition programs, the short- and long-term impacts of the Public Charge Rule on federal nutrition assistance participation, and the influences of past and current discriminatory policies and practices impacting employment opportunities, homeownership, and community development ( 218 , 245–256 ).

Translational and implementation science

Major research initiatives are needed to better understand how eating behaviors can be positively influenced in diverse populations. Translational research must identify optimal strategies to leverage the food environment, including retail settings, schools, worksites, health care systems, nursing homes and assisted-living facilities, and federal nutrition assistance programs for better nutrition ( 257 , 258 ). In the 2015 DGAC report, for example, the scientific evidence was considered limited or not assignable for many crucial translational questions, such as whether food insecurity affects body weight; whether acculturation influences diet, body weight, or cardiovascular risk factors; whether menu calorie labels influence food selection or consumption; or whether access to farmers’ markets, supermarkets, grocery stores, or convenience/corner stores influences dietary intakes, diet quality, or body weight ( Supplemental Table 1 ).

Implementation research is also crucial to assess and optimize intended benefits of the numerous federal policies and investments around public communication and education, including the DGAs, food labeling, health claims, menu labeling, and SNAP-Ed. This should include coordinated research efforts on evidence-based nutrition education and promotion strategies for healthy populations (the current focus of the DGAs), those with specific diet-related illnesses (the majority of the US population, but not included in the DGAs), and those with resource limitations and food insecurity ( 194 , 259 , 260 ). Understanding how and why effectiveness of communication channels may vary, such as according to print or health literacy, numeracy, culture, income, or neighborhood (e.g., food access), is critical. Effective approaches to increase nutrition science literacy can be assessed through new and enhanced research collaborations, such as between the DoE, USDA, NIH, and CDC. As one example, enhanced collaborations with DoE could include efforts to study potential improvements to food-, nutrition-, and health education–related curricula, testing, school environments, and teacher preparation. In addition, more research is needed across the policy development and dissemination spectrum to advance our understanding of efficacy, cost-effectiveness, equity, and feasibility of policy, systems changes, and environmental supports that promote healthy eating ( 241 , 261– 263 ). Coordinated interagency research is also needed on the effects and appropriateness of food marketing to children (e.g., between the FTC, CDC, FDA, and USDA). Together, such research can inform both current and alternative federal approaches for disseminating evidence-based information to inform choice and reduce confusion among a public hungering for scientifically sound guidance.

Translational research is also needed to leverage allied health professionals and the health care infrastructure to reduce diet-related illnesses. Innovative translational and implementation science research has tremendous potential to strengthen medical nutrition therapy led by registered dietitian nutritionists for an array of acute and chronic diseases and conditions ( 11 , 264–267 ). Many other promising strategies warrant significant research, including the following: expanding the integration of food security and diet quality assessments into electronic medical records or Fast Healthcare Interoperability Resources, updating of medical and other health care licensing and certification standards to include nutrition education, assessing health and cost impacts of medically tailored meals and produce prescriptions, and leveraging Medicaid flexible benefit services and Medicare Advantage for better nutrition and health ( 268 , 269 ). The rapidly growing private and public interest and investment in such “Food is Medicine” approaches must be informed by robust research. Strengthened coordination of research priorities and investments across CMS, CMMI, CDC, Health Resources and Service Administration (HRSA), NIH, and USDA, among others, can inform how best to engage in these strategies together with the allied health community in real-time. In addition, more research is needed across the policy development and dissemination spectrum to advance our understanding of efficacy, cost-effectiveness, equity, and feasibility of policy, systems changes, and environmental supports that promote healthy eating.

Key cross-agency research priorities for nutrition-related investments

Coordinated research is also important to better leverage the many federal investments in nutrition. This includes the $27 billion annual investment in USAID, 1 of the 3 foundational pillars for promoting and protecting US national security interests abroad, for which expanded research in nutrition and agricultural innovation is central ( 11 , 270 , 271 ). The DoD also has key nutrition research priorities around human performance and military readiness that would benefit from cross-agency coordination ( 11 ). Increased investment in nutrition research would also benefit many active-duty families who suffer from diet-related chronic illnesses as well as often coexisting food insecurity ( 87–91 ). The majority of veterans receiving care at VHA, the largest integrated health care system in the US, suffer from ≥1 diet-related conditions ( 86 ). NASA conducts some of its own nutrition research but relies heavily on other federal departments and agencies to help define nutrient requirements and healthy eating strategies for extended space exploration ( 11 ). Other cross-governmental opportunities for coordinated nutrition research include how best to strengthen and leverage the nearly $100 billion annual national investment in USDA nutrition assistance programs ( 241 ) and research on food safety, a joint FDA and USDA priority. Many other FDA regulatory actions require robust research findings, yet are often limited by incomplete evidence. This includes decisions on Nutrition Facts labeling, front-of-pack labels, restaurant menu labeling, health claims, dietary supplements, food additives, standards of identity (e.g., around plant-based dairy and meat alternatives), and cellular agriculture ( 210 ). An expanded federal nutrition research effort to better support regulatory actions could create renewed industry support for nutrition research as well as interest in developing innovative public–private partnerships ( 272 ).

Intersections with food production, supply chains, and sustainability

The federal government has many priorities around US farming, rural development, food production, food manufacturing, and supply chains ( 9 , 156 , 157 ). Nutrition research intersects with each of these, such as on how to increase production of and access to affordable, healthful food; develop technologies and collaborations to produce new high-value products for farmers and food manufacturers; foster public–private partnerships for innovation and adoption of novel technologies; and expand technology development and other entrepreneurship efforts between academic institutions and small businesses ( 147 ). As summarized in earlier sections, fundamental research questions are also emerging on how food production jointly intersects with human and planetary health, including effects of different strategies for plant and animal breeding, livestock and farming practices, regenerative agriculture, production of plant-based meat and dairy alternatives, and cellular agriculture ( 11 , 156 , 273 ).

Monitoring and surveillance

Nutrition-related monitoring and surveillance are critical to inform nutrition research, which then bidirectionally guides surveillance priorities ( 11 , 274 ). The COVID-19 crisis has highlighted the fragmented and often incomplete national infra-structure for monitoring food- and nutrition-related questions in real time, including, for example, information on local, regional, and national food insecurity; dietary choices; diet-related health disparities; neighborhood food environments; and supply chains ( 3–9 ). Expanded and modernized monitoring and surveillance are essential components of a strategy to strengthen and better coordinate federal nutrition research.

Return on investment

The ROI for federal research has been documented across several metrics ( 275 ). Considering commercial innovation, ∼1 in 12 NIH grants directly lead to patents, while ∼1 in 3 granted patents cite NIH-funded research ( 276 ). In a 2012 analysis, each $1 increase in NIH funding was estimated to increase the size (output) of the bioscience industry by between $1.70 and $3.20 ( 277 ). A $3.8 billion federal investment in the human genome project plus an additional $8.5 billion in related research and support have been estimated to produce nearly $1 trillion of economic growth, amounting to a 180-fold ROI ( 278 ). In 2014 Senate testimony, NIH Director Francis Collins reported that NIH funding supported >402,000 jobs and $58 billion in economic output nationwide, whereas NIH discoveries contributed $69 billion to GDP and supported 7 million jobs in 2011 ( 279 ).

Our review suggests that expanded federal coordination and investment in nutrition research will generate similarly meaningful ROI. Opportunities include more efficient leveraging of existing nutrition research infrastructure and investments, as well as other current federal investments in nutrition-related programs and policies at USDA (∼$100 billion/y), USAID (∼$27 billion/y), DoD, VA, FDA, CDC, CMS, FEMA, and more. Such investments could also be crucial to help reduce population diet and health inequities across diverse population subgroups.

One of the most promising areas for ROI would be advancing basic, clinical, and implementation science to reduce diet-related diseases. As mentioned in earlier sections, a recent NIH prevention research portfolio analysis compared national risk factors for death with NIH research investments ( 120 ). The largest gap was for nutrition, which was the top cause of attributable deaths (estimated to cause 19.1% of all deaths) but represented only 6.7% of all NIH prevention research funding (∼$0.43 billion based on the 2019 NIH budget, or ∼1.1% of all NIH funding) ( 117 , 120 ). In comparison, estimated government spending on direct health care for diabetes alone was ∼$160 billion/y in 2017, with an expected growth rate of 5% (∼$8 billion) per year ( 280 ). Medical care for people with diagnosed diabetes accounts for ∼1 in 4 health care dollars in the US, with more than half of these costs being directly attributable to diabetes ( 280 ). And, while mounting evidence suggests that severity, complications, and costs of type 2 diabetes can be rapidly reduced through better lifestyle including dietary changes ( 281–284 ), the optimal dietary priorities, behavior change strategies, microbiome implications, and personalization needs to most effectively improve diabetes remain uncertain. A major effort to expand and harmonize federal nutrition research could have rapid ROI based on reduced health care costs alone. For instance, a new, additive $1–2 billion annual investment in nutrition research could potentially generate a several-fold ROI if this helped flatten the anticipated ∼$8 billion/y annual increase in government expenditures on medical care for diabetes ( 280 ). Estimates of potential ROI of expanded federal nutrition research can be considered against health care and other societal costs of other diet-sensitive conditions, such as hypertension, food allergies, coronary heart disease, certain cancers, and more. As stated by the FDA Commissioner in 2018, “Improvements in diet and nutrition offer us one of our greatest opportunities to have a profound and generational impact on human health … The public health gains of such efforts would almost certainly dwarf any single medical innovation or intervention we could discover” ( 285 ).

Greater coordination and investment in federal nutrition research could also catalyze and unlock economic growth through new public–private partnerships and new private capital investment, small businesses, jobs, and inventions. In addition to potential for lower health care spending, accelerated nutrition research could help foster a healthier and more productive workforce, more active and thriving children, and healthier and more independent seniors. New research investment and structure should also support the training of a new generation of scientists and health care professionals who can leverage nutrition-related knowledge for public good. Enhanced nutrition science and cross-governmental authority can also strengthen dietary guidance, reduce public confusion, and improve consumer food choices.

Together with increased investment in food and agricultural research, strengthened multidisciplinary nutrition science could better support the long-term economic vibrancy of US farmers and rural communities. Past increases in agricultural productivity, for example, have come almost entirely from science-based innovations ( 146 ). Such integrated efforts would also be able to address the critical emerging nexus of health, food, agriculture, climate, and sustainability ( 147 , 286 , 287 ), positioning the US as the global leader in this area. This would further improve stewardship of US natural resources, including water, soil, forests, and oceans. In sum, this would strengthen long-term US food security, farmers’ incomes, national and rural economic growth, and resilience of the food and agricultural sector, which accounts for 1 in 9 US jobs ( 288 ).

Appropriate federal investment and coordination of nutrition research could improve national resilience against chronic threats and acute crises. The COVID-19 pandemic highlights the need to have a coordinated, vigorous scientific research infrastructure before crises strike ( 3–8 ). The bidirectional impacts between food and nutrition and COVID-19 have also revealed a vital new area for research and policy that requires significant investment and coordination ( 289 ).

In 2019, the Director of National Intelligence reported to Congress that our national disinvestment in science and technology is 1 of 10 global threats because, without the research to produce disruptive US technologies, we weaken our economic competitiveness ( 290 ). A new structure for coordination of existing federal nutrition research, combined with a major new investment—for example, increasing federal nutrition funding by $1–2 billion or more each year—could together provide highly cost-effective approaches to addressing the poor health, rising disparities, spiraling health care costs, declining qualified military recruits, and other pressing food and agricultural challenges facing the US.

Options for Strengthening National Nutrition Research

Based on our review, a strengthened federal nutrition research effort is necessary and should be additive to and synergistic with existing efforts across departments and agencies. Expanded coordination and investment in nutrition science, rather than a silo-ing of nutrition research or a rearrangement of existing investments, are essential. Based on the documented burdens, current landscape of research and coordination efforts, and identified opportunities, we first identified 2 priority strategies to strengthen federal nutrition research, which we defined and reviewed in detail. These were as follows: 1 ) a new authority for robust cross-governmental coordination of nutrition research and other nutrition-related policy and 2 ) strengthened authority, investment, and coordination for nutrition research within NIH.

These 2 strategies were identified as complementary, with benefits accruing independently and further synergies to be gained by joint implementation. A third important, and further complementary, identified strategy was to strengthen authority, investment, and coordination at USDA for human nutrition research, food and agricultural research, education, extension, and economics.

To achieve success, a key identified theme was the need for not just additional investment but also new authority and structure. Multiple assessments over many decades have identified the fundamental need to strengthen federal nutrition research in the US. This includes, among others, the 1969 White House Conference; the 1977 Congressional call for improved coordination of human nutrition research; the 1983 creation of ICHNR; the 1994 Institute of Medicine report on nutrition and food sciences; the 1996 joint OSTP and the National Science and Technology Council (NSTC) report on health, safety, and food; the 2000 National Nutrition Summit; and more ( Supplemental Table 5 and Supplemental Table 10 ). Several within- and cross-agency convenings of federal departments and agencies have further identified critical shared interests and research gaps in nutrition research ( Table 2 ). Yet, the full intended impacts of these important efforts were mostly not achieved, in large part because they lacked any new federal structure with strong and sustained authority, robust coordination capacity, and dedicated appropriations.

The following sections describe the identified promising options for strengthening nutrition research through 1 ) increased cross-governmental coordination; 2 ) increased authority, investment, and coordination within NIH; and 3 ) increased authority, investment, and coordination at USDA. The majority of these options are being set forth for the first time and, where possible, we reference comparable examples.

Identified cross-governmental coordination strategies for strengthening national nutrition research

Improved coordination between federal departments and agencies conducting nutrition research has tremendous potential for strengthening our nation's ability to achieve essential fundamental, clinical, public health, and translational discoveries. Key identified strategies are summarized in  Table 3 and reviewed below. These options were not found to be mutually exclusive and could be even more effective in combination.

Key cross-governmental coordination strategies for strengthening and accelerating national nutrition research 1

New Office of the National Director of Food and Nutrition

Modeled after the Office of the Director of National Intelligence (ODNI) ( 291 ), but with a smaller budget and staffing scale, an Office of the National Director of Food and Nutrition (ONDFN) would provide essential coordination and harmonization of the work of the ≥10 US departments and agencies comprising the federal nutrition community ( Supplemental Figure 3 ). ODNI is a crucial office created as part of the Intelligence Reform and Terrorism Prevention Act of 2004 (Public Law 108–458) to lead and integrate the diverse intelligence efforts of 16 departments and agencies. Working as one team, ODNI helps synchronize intelligence collection, analysis, and counterintelligence, forging a harmonized system to deliver the most insightful intelligence possible. ODNI prioritizes intelligence-community-wide mission requirements, manages strategic investments to foster innovation and efficiency, evaluates the effectiveness of intelligence programs and spending, and absorbs new missions and develops new capabilities without adding to staff size. Nearly half (40%) of ODNI staff are on rotation from 1 of the 16 participating departments and agencies. Of note, the combined budgets of ODNI members ($50 billion/y) are of a similar scale as the overall current nutrition-related programs (including research) of ICHNR members.

ONDFN would be led by a new, cabinet-level Director of National Food and Nutrition, serving as the Principal Food and Nutrition Advisor to the White House, heads of executive branch departments and agencies, senior military commanders, and Congress. Similar to ODNI, ONDFN functions would include reviewing and coordinating priorities and strategies to maximize nutrition research efforts across various federal investments; establishing objectives and priorities for the collection, analysis, and dissemination of national nutrition monitoring and surveillance; ensuring provision of accurate and timely nutrition information to decision makers; evaluating and improving the effectiveness and synergies of federal nutrition research and policy efforts; overseeing the coordination of external advisory groups and public–private partnerships around nutrition research and policy; developing policies and programs to leverage the distinct efforts of departments and agencies around nutrition; and developing and reporting on performance goals and program milestone criteria.

This tested and successful model is on a comparable area of national importance and with a similar size and breadth of relevant involved departments and agencies. ONDFN would build on ICHNR, but with a much stronger platform to create effective coordination and synergies. ONDFN would deliver relevant harmonized information to the President, Cabinet, other executive branch leadership, senior military commanders, and Congress for developing policy, programmatic, and budget initiatives. A clear Congressional mandate would provide cross-agency coordination of strategic planning, programmatic review, annual reporting and quadrennial assessments to the President, Congress, and other key stakeholders, budgetary needs, and external research and cooperation. There could also be additional Congressional oversight as needed and interests arise. ONDFN would also provide dedicated leadership and staff in the executive branch cabinet for federal nutrition research and policy, providing a crucial bridge between research and implementation. These activities and personnel would more efficiently and effectively help identify topics of strategic interest across multiple departments and agencies with significant impact and feasibility, and advance emerging opportunities to accelerate progress across new fundamental and transactional scientific topics. A broad focus would increase synergies, shared priorities, and effectiveness and efficiency of different departments and agencies engaged in activities related to innovation in nutrition, agriculture, and food systems.

Like ODNI, a meaningful number of staff would be drawn from existing departments and agencies, creating budgetary efficiencies while maximizing cross-fertilization of ideas and innovations. ONDFN would have the infrastructure and authority necessary for true cross-department/agency coordination—for example, to develop a modernized approach to the nexus between the agriculture-food-health value chain—including research, policy, and practice from farm inputs and food processing/production to consumer behavior to human health. ONDFN would also advance the coordination for communication of trusted nutrition information to the American public, which occurs across separate departments and agencies including CMS and VHA (health care providers), USDA (DGAs, SNAP-Ed, WIC education, food safety for meat and poultry), FDA (food safety for other foods, Nutrition Facts, health claims, package warning labels, restaurant menu labeling), NIH (scientific studies), DoE (nutrition and STEM curricula), CDC (school, community, and public health nutrition education), and more. This would help meet the almost explosive growth in public demand for better information on the science of diet-related health. ONDFN would combine a national food strategy with coordinated new science, considered crucial to better harmonize law and policymaking around food and agriculture, food safety and nutrition research, and establishing, prioritizing, and pursuing common goals ( 292 ). Such a strategic plan would create transparency and accountability, including tasks of identifying and monitoring budgets and metrics of success across its purview. A high-level, cross-governmental structure like ONDFN would also be crucial for effective and timely responses on urgent nutrition and food challenges during complex situations like COVID-19, which require immediate and ongoing leadership and coordination at the highest levels of the government ( 9 , 293 ).

Disadvantages

This new position and office would require Congressional (legislative) authorization and appropriations. As a cabinet-level office, ONDFN would naturally focus on major federal nutrition issues beyond research (e.g., nutrition assistance programs), which could dilute its relative focus on research and innovation. ONDFN may also be too politically high-level to directly address ways to strengthen on-the-ground infrastructural and investment needs within key federal nutrition research departments and agencies.

Path forward

Congress can authorize the establishment of ONDFN to advise the President on food and nutrition and lead the coordination of multiple federal departments and agencies, policies, budgets, and programs. The mandate should include a clear emphasis on strengthening national nutrition research. Congress would also appropriate funding to establish this Office and then provide annual appropriations directly to the ONDFN. Congress would also indicate the required frequency of reporting (e.g., annual reporting and quadrennial assessments) and indicate the committees of oversight in the House and Senate. The President would then appoint the National Director of Food and Nutrition.

New US Global Nutrition Research Program

A new US Global Nutrition Research Program (USGNRP) would be charged with improving coordination and integration of federal research on food and nutrition and implications for the country ( Supplemental Figure 4 ). The USGNRP would be modeled after the successful US Global Change Research Program (USGCRP), established in 1989 by a Presidential Initiative and codified in Congress through the Global Change Research Act of 1990 (Public Law 101–606) ( 294 ). This Act required a comprehensive and integrated US research program to assist the nation to assess, predict, and respond to human-induced and natural processes of global climate change. Bringing together 13 departments and agencies, USGCRP is steered by the Subcommittee on Global Change Research under the Committee on Environment, Natural Resources, and Sustainability, overseen by the Executive Office of the President, and facilitated by a National Coordination Office ( 295 ). USGCRP has its own budget that mainly supports the National Coordination Office, staffed with professional coordination support staff. USGCRP is supported by statute through small apportions of participating departments’ and agencies’ research funding dedicated to climate issues ( 296 ). Guided by a series of multi-stakeholder strategic plans since 1989 ( 297 ), the efforts of participating departments and agencies are coordinated through Interagency Working Groups that span interconnected topics. Annual USGCRP reports and other scientific assessments and resources highlight key program accomplishments, such as observing and understanding changes in climate, the ozone layer, and land cover; identifying impacts of these changes on ecosystems and society; estimating future changes in the physical environment, and associated vulnerabilities and risks; and providing scientific information to enable effective decision making to address corresponding threats and opportunities ( 297 ).

Similar to USGCRP, USGNRP leadership would be overseen by the Executive Office of the President. Likewise, its National Coordination Office would be staffed by dedicated staff and temporary (“detailed”) staff from participating departments and agencies, and funded by small portions of relevant research budgets from each participating department and agency. In addition to current ICHNR members, USGNRP could include a more contemporary vision of federal stakeholders who engage with and leverage nutrition research, such as CMS, CMMI, HHS Office of the Surgeon General, FEMA, and Departments of Veterans Affairs, Education, Energy, Transportation, Labor, Homeland Security, Housing and Urban Development, Interior, and Justice (e.g., related to optimal nutrition in the federal prison system). Like USGCRP, functions of USGNRP would include multi-stakeholder–informed strategic planning; Inter-agency Working Groups to identify and coordinate shared priority research and translation; assessment and modernization of nutrition monitoring and surveillance; and creating partnerships with academic, private, and international science stakeholders.

This is a tested, successful model on a similarly crucial area of science. USGNRP could build on ICHNR but with the establishment of a dedicated budget from participating departments and agencies. Through strategic planning, new and additive budget initiatives could be formulated and implemented through more sustained appropriations. Compared with ICHNR, USGNRP would have a renewed and clear mandate around improved coordination and harmonization, with explicit requirements for programmatic review, strategic planning, annual reporting, fiscal coordination on new initiatives, quadrennial assessments submitted to the President, and international research and cooperation. Like ONDFN, USGNRP activities would more efficiently and effectively identify topics that resonate across multiple departments and agencies with significant population impact and feasibility, while advancing emerging scientific opportunities and discoveries. Also like ONDFN, a strategic planning process would create transparency and accountability, including tasks of identifying and monitoring budgets and metrics of success.

ICHNR subcommittees could be transitioned to Interagency Working Groups to effectively and efficiently foster cross-department and cross-agency actions. As one example, a new DGA Interagency Working Group would have a stronger charge and dedicated staff to address new research needs identified by the latest DGAC. Like USGCRP, the participating USGNRP departments and agencies would utilize a National Coordination Office to help produce high-level and informative reports ( 298 ). USGNRP would also intersect with other high-level coordinating structures, such as USGCRP's Interagency Working Group on Climate Change and Health, to enable effective and rapid responses to acute threats such as COVID-19, other pandemics, or other future challenges.

If based on the USGCRP appropriations model, USGCRP would be funded by a legislative mandate for contributions by participating members (rather than any new appropriations), so its budget would vary with the size and consistency of commitment of participating departments or agencies to its research areas of interest. Ideally, Congress would also authorize and appropriate some core funding for USGNRP, although no new, dedicated funding has emerged for USGCRP thus far. Also, significant staffing in the National Coordination Office would be temporary (“detailed”) personnel from participating members, which could reduce continuity.

USGNRP could be established by a Presidential Initiative, without legislative action. For longer-term success, Congress could later codify USGNRP into law ( 296 ). Alternatively, Congress could directly establish USGNRP (e.g., in place of ICHNR). In any of these cases, separate Congressional appropriations are not needed but would be ideal.

New Associate Director for Nutrition Science within the OSTP

A new OSTP Associate Director for Nutrition Science would be a non–cabinet-level position, President-appointed and Senate-confirmed, who would serve as the President's advisor on issues related to nutrition research ( Supplemental Figure 5 ). OSTP, established by Congress in 1976, has a broad mandate “to provide, within the Executive Office of the President, advice on the scientific, engineering, and technological aspects of issues that require attention at the highest level of Government” (Public Law 94–282). OSTP advises the President on science and technology topics related to domestic and international affairs, leads interagency efforts to develop and implement sound science and technology policies and budgets, and works with the private sector, state and local governments, science and academic communities, and other nations ( 299 ). In addition to the Director, Congress provides the President the authority to appoint up to 4 Associate Directors, subject to Senate confirmation. The statute provides great flexibility to the President with respect to corresponding areas of focus, expertise, and responsibility. Under President George W Bush, there were 2 Associate Directors—one focused on science and the other on technology—each with a Deputy Director. The Clinton Administration had 4 Associate Directors, focused on science, technology, environment, and national security and international affairs. President Obama's 4 Associate Directors focused on similar areas, with additional joint appointments of OSTP staff to the National Economic Council, National Security Council (NSC), Domestic Policy Council (DPC), and White House Office of Management and Budget (OMB) ( 300 ). President Trump's OSTP Director, confirmed in January 2019, has expressed interest in military readiness and national security, communication networks, energy and environmental leadership, health and bioeconomic innovation, and space exploration, among other areas ( 301 ). President Trump has appointed only 1 Associate Director, confirmed in August 2019, who also serves as the US Chief Technology Officer ( 302 ).

Prior OSTPs have had advisors on nutrition and, at the highest level, an Assistant Director of Nutrition in 2014–2015. However, OSTP has never had an Associate Director of Nutrition Science. Modeled after other Associate Directors, the Associate Director for Nutrition Science would provide high-level leadership to leverage and translate federal and nonfederal nutrition science efforts, identify and help develop more coordinated and innovative nutrition research initiatives, and advise the President on corresponding national and international issues.

OSTP has a long history of identifying and elevating science and technology opportunities for the President to help shape policy, programmatic, and resource allocation decisions. OSTP advises the OMB on research and development programs for annual White House budgetary requests. For example, OSTP support was instrumental to the doubling of the NIH's budget between 1998 and 2003 ( 303 ). OSTP can lead important coordination activities and reports among different federal departments and agencies as well as external stakeholders ( 304 ). An Associate Director of Nutrition Science provides a key leader to the White House to improve coordination, communication, and strategic planning around key priority areas in nutrition science. The Associate Director would also work closely with and elevate the communication and impact of individual federal departments and agencies and the ICHNR. The Associate Director can hire advisors, special assistants, or White House fellows to deepen expertise and impact and can lead efforts to create new collaborations with the private sector, state and local governments, academic communities, and other countries. Legislative action is not required; the President can simply assign 1 of the 4 allocated Associate Director slots.

OSTP positions and areas of focus can dramatically change across administrations, greatly diminishing continuity and long-term effectiveness. OSTP staffing is often small, transient, and reliant on temporary (“detailed”) staff from relevant departments and agencies. Success of this approach would be highly dependent on the skills and interests of the new Associate Director, rather than any concrete or consistent structure or process for strengthening federal nutrition research through increased coordination, funding, and alignment. OSTP initiatives may not align with focus or levels of research funding.

A President can appoint an Associate Director for Nutrition Science, with Senate confirmation. Congress can also recommend a specific Associate Director focus, although recent recommendations were not successful [e.g., the 110th Congress recommended an Associate Director for Earth Science and Applications (Senate 1745), and the 111th Congress recommended an Associate Director and Coordinator for Societal Dimensions of Nanotechnology (House of Representatives 5116)] ( 299 ).

New US Task Force on Federal Nutrition Research

A new US Task Force on Federal Nutrition Research would be charged with improving coordination and integration of federal nutrition research—for example, modeled after other timely US task forces such as on Combating Antibiotic-Resistant Bacteria ( 305 ); on Veteran Wellness, Empowerment, and Suicide Prevention ( 306 ); or on Combating Drug Addiction and the Opioid Crisis ( 307 ). As an example, in 2013, CDC, G7, and WHO each released reports or statements on the importance of dedicated prevention and infection-control efforts for antibiotic-resistant bacteria ( 305 , 308 , 309 ). In 2014, a Presidential Executive Order established combating antibiotic-resistant bacteria as a federal priority and created a new high-level task force ( 310 ). This Task Force for Combating Antibiotic-Resistant Bacteria was co-chaired by the Secretaries of HHS, USDA, and DoD, with representatives from Departments of State, DoJ, VA, and DHS and the EPA, USAID, OMB, DPC, NSC, OSTP, and NSF. Its functions included developing a 5-y National Action Plan and reporting to the President on the plan's progress. In addition, a Presidential Advisory Council on Combating Antibiotic-Resistant Bacteria composed of up to 30 members, appointed or designated by the co-chairs, was required to help advise the task force, culminating in a report to the President with recommended actions ( 311 ). The resulting National Action Plan, put forward in 2015, continues to guide federal actions toward a coordinated response to this pressing public health issue, directing efforts, personnel, and funding of participating departments and agencies toward a common critical agenda ( 312 ).

Modeled on that successful task force, the leadership, members, and general functions of a Task Force on Federal Nutrition Research would develop and report to the President on a major new National Action Plan for accelerating and strengthening nutrition discoveries ( Supplemental Figure 6 ). Co-chairs could include HHS, USDA, and DoD (and perhaps VA) Secretaries, with additional broad representation from other diverse departments and agencies. A complementary Presidential Advisory Council on Nutrition Research would include expert members appointed by the co-chairs to advise the task force and provide a report of recommended actions to the President. This task force could also work well with ONDFN and/or the Associate Director of Nutrition Sciences in the OSTP.

This is a tested, successful model on an area of science with some similarities, including multiple relevant federal departments and agencies and a need for international collaboration ( 313 ). The Presidential Executive Order would appropriately elevate the prioritization of nutrition research, create a concrete action plan, and include reporting on progress. The task force would benefit from cross-governmental cabinet-level leadership and include diverse relevant departments and agencies. The high-level Advisory Council provides a formal mechanism to leverage external expertise and input. These elements would together strengthen coordination and communication of existing important research efforts toward the highest impact agenda. Task force activities and reporting would help inform and amplify research budgets directed to participating departments and agencies. This approach does not require legislation.

Despite its successes, no new funding was provided nor has emerged for the Task Force on Combating Antibiotic-Resistant Bacteria. That task force also has not developed any coordinated budget initiatives to date. A Presidential Executive Order remains in effect only until revoked, although it can endure across administrations (e.g., the Task Force for Combating Antibiotic-Resistant Bacteria has remained in place). A task force would likely have a defined scope over a set time period, and not provide sustained leadership and coordination into the future.

The President can issue an Executive Order to establish nutrition research as a priority and create a US Task Force on Federal Nutrition Research. The President can also direct the heads of OSTP, DPC, and NSC to revise ICHNR coordination structure to more closely follow the Task Force model. Congress could also initiate such a task force by inquiring with the Executive Office of the President or with the relevant department and agency leadership about updating ICHNR or a potential new Presidential Executive Order or directive around nutrition research coordination. Congress could also revise the charge, structure, and funding of ICHNR via legislation to create appropriate activities consistent with such a task force.

Other new cross-governmental options

• At the cabinet level, the Joint Chiefs of Staff could be called upon to focus on necessary nutrition research to address escalating diet-related health burdens on military readiness and national security ( 25 , 86 , 92 , 314–318 ), leading coordinated efforts across DoD, other ICHNR members, and the National Collaborative on Childhood Obesity Research ( Supplemental Text 2 , Supplemental Figure 7 ).
• Congress could amend the National Nutrition Monitoring and Related Research Act of 1990 (Public Law 101–445) to authorize and appropriate a specific funding stream for the DGAs, DRIs, and associated monitoring and surveillance processes.
• HHS could mobilize existing or new positions within the Office of the Assistant Secretary of Health (e.g., a new HHS Office of Nutrition, modeled after the HHS Office of Women's Health or Office of Infectious Disease and HIV/AIDS Policy) to coordinate nutrition research needs and opportunities within and outside HHS.
• An ongoing GAO evaluation of federal policies and activities in relation to diet-related diseases and their economic burdens ( 319 ) may provide additional recommendations for increased coordination of nutrition research.
• Congress could authorize and appropriate funds for NASEM to assess the gaps and options to strengthen and coordinate federal nutrition research to address escalating diet-related health burdens and related economic, equity, national security, and sustainability challenges ( 320 ).
• Congress could appoint a global health coordinator to lead a new interagency council that reaffirms domestic and global health as a core national security interest. The coordinator and council would be charged with developing strategic plans to detect and prevent acute and chronic health threats, such as new infectious pandemics. Such a focus should incorporate the critical role of food and nutrition in population health and resilience, including against infectious diseases, and appropriate and coordinate the necessary activities for relevant research.

Identified NIH strategies for strengthening national nutrition research

As the nation's largest funder of research, NIH is one essential (although not exclusive) home for increased authority, coordination, and funding for nutrition science ( 110 ). Any new NIH strategy must leverage and amplify, not replace or compete with, existing extramural and intramural nutrition research efforts across the 27 current NIH institutes, centers, or offices or with existing nutrition research across other federal departments and agencies. Key identified strategies are summarized in  Table 4 and reviewed below.

Key strategies within the NIH for strengthening and accelerating national nutrition research 1

New National Institute of Nutrition

A new NIH National Institute of Nutrition (NIN) would be additive to the 27 current institutes and centers leading research within NIH ( Supplemental Figure 8 ). NIN would be a crucial new asset for NIH to accomplish its mission “to seek fundamental knowledge about the nature and behavior of living systems and the application of that knowledge to enhance health, lengthen life, and reduce illness and disability” ( 321 ). NIN would be tasked with leading innovative, cross-cutting, and foundational research on nutrition and health, including intramural and extramural programs and training and outreach activities. Under the leadership of the NIN Director, NIN would help guide strategic planning, coordination, and review of nutrition research across NIH and with other federal departments and agencies. This would increase harmonization, collaboration, and leveraging of all nutrition-related research programs across NIH institutes, centers and offices. NIN priority areas and funding should be coordinated with, additive to, and synergistic with existing NIH nutrition research efforts, such as within NIDDK, NHLBI, and NCI, among others, as well as with USDA, CDC, FDA, DoD, VHA, and NASA, among others. Rather than “silo-ing” nutrition research, NIN would help craft strategies and focus areas that span across, support, and/or are not covered by specific interest areas of other federal nutrition research efforts. A new NIH National Advisory Council on Nutrition Research—comprising research experts, health professionals, and community members—would advise the HHS Secretary, NIH Director, and NIN Director on matters related to the NIN's mission.

NIN would expand the knowledge base of research on diet-related illnesses and their intersections with other fields through strategic planning, coordination, and evaluation of NIH nutrition research and through conduct and support of research in nutrition science and related areas. Relevant cross-cutting areas of focus could include many priority areas from genetic, molecular, and biological science to clinical, behavioral, and translational research, as well as research on health systems, workforce development, and health equity ( Table 2 ). NIN's efforts would support, expand, and amplify key science relevant to other NIH institutes, centers, and offices, such as on nutrition and diabetes, obesity, cardiovascular disease, cancer, brain health, minority health and disparities, child health, and more. Within NIH, NIN would represent a natural authority and partner to support and coordinate cross-cutting intramural research that complements existing nutrition research portfolios across NIH. NIN would also promote and support the training of a diverse 21st century nutrition science workforce, including in cross-disciplinary priority areas like quantitative methods, personalization, and technology. Given NIH's roles in supporting training of health care professionals, NIN would also guide and support innovative programs to build a cadre of well-trained health professionals for both clinical care and basic and translational science in nutrition ( 269 , 323 ).

NIN would provide required leadership, staff, expertise, and resources to build meaningful partnerships on nutrition-related activities and research priorities of other federal departments and agencies, in particular USDA as well as FDA, CDC, DoD, VA, USAID, and CMS, among others. For example, this role could include development of joint requests with USDA for applications investigating the interlinkages between food, nutrition, health, and agricultural practices. NIN would support the efforts of HHS ODPHP in the USDA–HHS partnership to review evidence and, importantly, address new scientific needs for the DGAs. NIN would similarly support collaborative new science to inform the DRIs, FDA food safety and regulatory activities, USDA nutrition assistance programs, CDC surveillance and public health activities, USAID priorities, and DoD and VA research needs for US active-duty forces (including enhanced human performance and military readiness), military families, and veterans. NIN would inform and support CMS and CMMI efforts, such as “Food is Medicine” interventions to reduce diet-related illness and associated health care costs ( 268 , 324 , 325 ). Such joint initiatives will have the greatest impact if nutrition research at these other departments and agencies were simultaneously strengthened with new investments. NIN would also lead and have the required staff capacity to engage meaningfully in public–private partnerships and with nonprofit organizations and international entities such as the WHO and World Bank.

NIN would add strong authority, infrastructure, investment, and external advisory mechanisms for nutrition research to the nation's largest funder of science. NIN would require a Federal Advisory Committee (Council) and would have a budget and funding authority. NIN would allow NIH to better address nutrition science that is cross-cutting rather than disease-specific, both across institutes, centers, and offices within NIH and with other federal departments and agencies. For example, the NIN would be instrumental in implementing and achieving the goals of the new 2020–2030 Strategic Plan for NIH Nutrition Research ( 129 ). As a long-term structure, NIN's activities and benefits would provide both expected and unexpected returns over many decades, outlasting shorter-term options such as cross-agency initiatives and changing priorities of individual administrations, and evolving appropriately with changes in science, food systems, nutritional needs, and disease conditions of the US public. A new institute could help maintain the strength of NIH focus on laboratory and clinical research in nutrition while, at the same time, facilitating expansion to research efforts to other translational priorities across NIH and across other federal departments and agencies. As has been seen with NIH research overall, NIN's coordinated leadership, structure, and capacity would likely provide a strong ROI to the US economy. The combination of NIN plus a new cross-governmental approach ( Table 3 ) would provide a powerful strategy to address the scope and scale of the challenges and opportunities we face as a nation.

The addition of a new institute would require legislative action to increase the current limit of 27 NIH institutes and centers (Public Law 109–482) and provide additive new appropriations to prevent reductions in any ongoing NIH or other federal nutrition research. NIN could increase silo-ing of nutrition research or divestment in nutrition research from other parts of NIH, which has historically been and should remain a component of almost all NIH institutes, offices, and centers. Even with a remit to coordinate and complement existing efforts, a new institute would need to navigate potentially entrenched cultures and perspectives around the “home” of certain areas of research. Congressional appropriations for expanded nutrition research funding within and outside NIH would be needed to prevent increased competition for resources.

Congress can authorize the establishment of NIN, updating the cap (Public Law 109–482) on the total number of NIH institutes and centers and providing new, additive appropriations to NIH. As an intermediary step, Congress could submit an inquiry to appropriate federal departments and agencies, host hearings, as well as appropriate funds, to explore the current status of federal nutrition research and potential options including the NIN.

New National Center for Nutrition Research

As a smaller model than a new institute, a new NIH National Center for Nutrition Research (NCNR) could be created, representing a 28th institute or center at NIH that would be broadly similar to a new NIN, although with less stature, staff, and funding ( Supplemental Text 3 ). The NCNR could aim to accomplish many of the same goals as an NIN, on a lesser scale. Advantages, disadvantages, and the path forward for NCNR are likewise similar, on a reduced scale, to NIN. Long term, the NCNR could further evolve into an institute, as has happened to other centers at NIH. However, if a research area is of sufficient national priority that it may transition into an institute within a decade or less, then starting as a center can be inefficient, compared with directly creating an institute. For example, both the National Institute of Minority Health and Health Disparities (NIMHD) and National Institute of Nursing Research (NINR) were founded as centers but transitioned into institutes within ≤10 y (Public Laws 111–148, 99–158, 103–43).

New NIH ONR within the NIH Office of the Director

This option would return ONR to the NIH Office of the Director ( Supplemental Figure 9 ) ( 326 ), the central entity for setting NIH policy and planning and for managing and coordinating NIH programs and activities ( 327 ). Multiple offices and divisions within the NIH Office of the Director function together to identify opportunities and needs across the agency ( 328 ). The NIH ONR can be modeled after other Congressionally mandated offices within the NIH Office of the Director (see “Path forward” below). Each of these lead and coordinate trans-NIH efforts, guided by an Office director, dedicated expert staff (ranging from 15 to 30 full-time employees), and specific budgetary resources. Like the NIH Office of Disease Prevention Director who also serves as the Associate Director for Prevention (Public Law 99–158), the Director of the NIH ONR would also serve as the Associate Director for Nutrition Research.

The NIH ONR would lead efforts to build and coordinate new collaborative relationships and synergies within the NIH, with other federal departments and agencies, and with external stakeholders including public–private partnerships to drive nutrition research and innovation. The NIH ONR would lead cooperative efforts to identify and stimulate priority areas of science, provide guidance on rigorous methodology, offer trainings, and increase the impact, visibility, and dissemination of findings. The new office would plan and coordinate relevant trans-NIH initiatives (see below), such as supported by the NIH Common Fund, a “venture” fund within the NIH Office of the Director, which aims to propel high-risk, high-reward research to speed scientific discovery and translation to improve health at a faster pace ( 329 ). The new office would develop approaches and resources to support analyses and reporting of nutrition research portfolios across NIH.

Restoring the ONR into the NIH Office of the Director would elevate the leadership, staffing, resources, and capacities of this important area within and outside NIH. This structure would reestablish close communication and coordination with the NIH Director, other divisions and offices within the NIH Office of the Director, and the nutrition activities across all the NIH institutes and centers. This is particularly important for identification and prioritization of concrete, timely research focus areas, given the breadth of areas and topics touched by nutrition. This office would have some dedicated funds to help stimulate priority research across NIH and encourage NIH institutes, centers, and other offices to direct or pool their funds toward common priority areas and would not be dependent on or viewed as serving any single institute. This office could help stimulate new, flexible appropriations for the NIH Office of the Director to focus broadly on nutrition priority areas, outside the Common Fund per se.

In addition to research strategy and harmonization, the new office director and staff (including communications specialists, present in other similar NIH Office of the Director Offices) would increase capacity and expertise for dissemination of nutrition science to the public and other stakeholders. This office could engage strong external advisory mechanisms, strengthening input from other federal departments and agencies, academic institutions, advocacy groups, state and local governments, and community members. Based on Congressional prioritization of new national research areas, such an office can transition into a center (e.g., National Center for Complementary and Integrative Health; Public Laws 103–42, 105–277, 113–235) or an institute (e.g., NINR, Public Law 103–43; NIMHD, Public Laws 103–43, 106–525, 111–148).

The size and resources of such an office would remain limited to coordinating and developing nutrition strategy across all NIH institutes, centers, and offices, inform and collaborate with other federal departments and agencies engaged in nutrition-relevant research and programming, assist with communication to the public, work with ODPHP in the USDA–HHS partnership to develop the DGAs, and meaningfully engage in public–private or other external partnerships. Such an office does not generally have sufficient independent funding to promote major extramural or intramural science. Such an office does not have sufficient authority or resources to support national training of new scientists and health care professionals in nutrition. An office's budget, staff size, and influence can vary widely across offices and over time depending on other NIH priorities.

The NIH Director has discretion to restore this office into the NIH Office of the Director. Congress can also pass legislation to create a new Office of Nutrition Research within the NIH Office of the Director, similar to other Congressionally mandated offices such as the NIH Office of AIDS Research (Public Law 103–43), Office of Research on Women's Health (Public Law 103–340), Office of Behavioral and Social Sciences Research ( 330 ) (Public Law 103–43), Office of Disease Prevention ( 331 ) (Public Law 99–158), and Office of Dietary Supplements ( 332 ) (Public Law 103–417).

New trans-NIH initiative(s) in nutrition research

Trans-NIH initiatives are efforts to promote collaborative research across NIH in a particular area of science. These initiatives can originate from the NIH Director; NIH institutes, centers, or offices; or Congress. Some of these initiatives engage with external stakeholders such as businesses and nonprofit foundations. The funding, leadership, and structures for trans-NIH initiatives tend to vary. Generally, trans-NIH programs utilize the same mechanisms of grant funding that NIH currently offers: research grants (R series), career development awards (K series), research training and fellowships (T & F series), program project/center grants (P series), and resource grants (various series) ( 333 ). NIH currently supports a variety of broad-reaching programs that are trans-NIH in nature; examples include Biomedical Information Science and Technology Institute (BISTI), NIH Blueprint for Neuroscience Research, Research Supplements to Promote Diversity in Health-Related Research, Administrative Supplements to Existing NIH Grants and Cooperative Agreements, New and Early Stage Investigators Policies, Genome-Wide Association Studies, NIH Common Fund, NIH Basic Behavioral and Social Science Research Opportunity Network (OppNet), Presidential Early Career Award for Scientists and Engineers, Stem Cell Information (PECASE), and the Trans-NIH Countermeasures Against Chemical Threats (CounterACT) program ( 333 ).

The NIH Common Fund has emerged as one approach to support trans-NIH programs and uses the same mechanisms of support. The NIH Common Fund is a specific component of the NIH budget and is managed by the Office of Strategic Coordination/Division of Program Coordination, Planning, and Strategic Coordination/Office of the NIH Director ( 329 ). Common Fund programs are short-term (usually ∼5 y), goal-driven strategic investments that are “intended to change paradigms, develop innovative tools and technologies, and/or provide fundamental foundations for research that can be used by the broad biomedical research community” ( 329 ). Then, an NIH institute, center, or office or multiple institutes, centers, and offices must continue the support of these time-limited programs.

As one example, the NIH Human Microbiome Project was a trans-NIH initiative supported by the NIH Common Fund from 2007 to 2016 ( 334 ). This project aimed to expand science on the microbiome. Initially funded as an initiative of the NIH Roadmap for Biomedical Research, the NIH Human Microbiome Project was originally established as a 5-y project with a budget of $150 million ( 335 ). The project began with a “jumpstart” phase in 2007 and a set of grants was funded in mid-2009 and additional demonstration project grants were awarded. These activities were supported by a Data Analysis and Coordination Center and a set of additional grants was awarded for developing new technologies, new software tools, and studying the ethical, legal, and social implications of this work. The grantees worked together in a highly cooperative consortium. Ultimately, this 10-y $215 million project spanned >20 of the NIH institutes, centers, and offices and resulted in a >40-fold increase in nonproject investment in microbiome research ( 336 ). That is, individual or multiple institutes, centers, and offices used program announcements or request for applications. Some of these funding mechanisms were supported by the Common Fund and others were additional commitments by the participating NIH institutes, centers, and offices from their own budgets. The Trans-NIH Microbiome Working Group established in 2012 provided a forum for coordinating NIH extramural research activities related to the human microbiome and continues to coordinate this work after the NIH Human Microbiome Project was completed. Notably, the NIH Human Microbiome Project identified several potential priority areas around food and the microbiome, but these topics have not yet been systematically pursued.

The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) initiative is an example of a trans-NIH initiative ( 337 ), supported by staff within NIH and across federal working groups and providing funding for intramural and extramural research, training, and technology development. Between 2013 and 2019, this initiative supported >700 research projects totaling ∼$1.3 billion through support across the NIH, including appropriations through the 21st Century Cures Act (Public Law 114–255) ( 337 ). The BRAIN initiative is managed by 10 NIH institutes and centers, with coordination at multiple levels. Extramural program staff and institute and center directors meet regularly to integrate strategic planning, management, and a BRAIN Multi-Council Working Group and Neuroethics Working Group provide further input on a variety of issues.

Another trans-NIH example is the All of US Research Program (Public Law 115–31), directly supported through annual appropriations from Congress ($1.5 billion over 10 y) (Public Law 115–31). This initiative, supported and overseen by NIH, arose from recommendations by the NIH's Precision Medicine Initiative Working Group of the Advisory Committee to the Director ( 338 ). The program staff are based in the NIH Office of the Director, with a Trans-NIH Liaisons Coordinating Team made up of scientific leaders from across NIH and has an external advisory panel.

A potential trans-NIH program in Precision Nutrition is being considered as an NIH Common Fund program for fiscal year 2021 ( 131 , 339 ), and the NIH Director included Precision Nutrition in the NIH's congressional budget justification for fiscal year 2021 ( 131 ). A new Program Director in the NIDDK ONR was hired in 2020 to lead this initiative.

Legislation is not required. A trans-NIH initiative can help galvanize NIH to develop a coordinated approach to a specific topic on nutrition and human health (e.g., see Table 2 ). Such an effort would generally be preceded by a careful—and separately useful—review of relevant NIH leadership, staffing, funding, external advisory mechanisms, and collaborative approaches available. A trans-NIH initiative brings new strategic planning, working groups, funding opportunities, training, and technology development. A trans-NIH initiative is complementary to other NIH and cross-governmental strategies to strengthen federal nutrition research. Such initiatives can also help build new or enhanced public–private partnerships.

The needs and opportunities across nutrition research are broad and complex, and a new trans-NIH initiative would cover 1 focused topic, such as, if funded, precision nutrition. Addressing the science gaps and opportunities for nutrition—a leading cause of disease in the US—will require greater and more sustained authority, coordination, resources, and collaboration than provided by a single initiative, especially one only limited to precision nutrition. Trans-NIH initiatives are generally time-limited, difficult to sustain, and not easily communicated to a broad range of external stakeholders. The long-term success of such initiatives can be dependent on a single leading NIH institute, center, and/or office to commit to carry that area of work forward after the initial investments.

The NIH Director could propose new trans-NIH budget initiatives for Congress to review; as noted earlier, Precision Nutrition is proposed in NIH's congressional budget justification for fiscal year 2021 ( 131 ). Congress could authorize and appropriate funds for this proposed initiative or put forth support for another or additional trans-NIH initiative(s) focused on ≥1 areas of nutrition research. NIH institutes, centers, and offices can develop and collectively support trans-NIH initiatives. External support through the private and nongovernment sectors can also be mobilized through public–private partnerships.

Identified USDA strategies for strengthening national nutrition research

In addition to NIH, the USDA is an important home for increased authority, coordination, and funding for nutrition science ( 110 ). As for NIH options, any new USDA strategy must leverage and strengthen, not supplant, existing extramural and intramural nutrition research efforts across USDA as well as other federal departments and agencies. Key identified strategies are discussed below. Each was considered as complementary, rather than mutually exclusive. Comparative advantages and disadvantages, executive and legislative considerations, and paths forward for these options should be the subject of future reports.

Increased investment in nutrition research across REE

Declining appropriations for nutrition-relevant research and statistics at USDA, compounded by declining public investment in agrifood research and development, is limiting the nation's ability to fully understand and leverage the critical nexus between agriculture, food, and health ( 12 , 146 , 147 ). An emphasis on agricultural production research has created pressure on the USDA nutrition portfolio to respond to these growing research needs and opportunities with its limited budget. Strong Congressional appropriations for nutrition research across REE is critical to reestablish the US as the global leader in food and agricultural science and technology, which creates healthy and productive communities, families, and youth. A renewed commitment to advancing and integrating nutrition into the overall crop, livestock, food manufacturing, food safety, natural resources, and climate research agendas has tremendous potential to improve economic growth, national security, competitiveness, sustainability, climate resilience, food security, and public health. Such investment would also maximize cross-governmental coordination and public–private partnerships with the greatest potential to accelerate progress in this complex nexus.

The USDA also implements major nutrition programs and thus must rely upon an integrated focus that connects nutrition research to policy and practice to improve the health of the public. To accomplish this integrated approach, each of the science mission areas at ARS, ERS, and NIFA must be at full capacity including sufficient staffing and resources. Nutrition research investment in ARS is essential for food-composition research and development, dietary surveys and food databases instrumental to national surveillance and scientific discovery, and the Human Nutrition Research Center network that pursues long-term, translation research priorities impractical to assess in short-term programs. NIFA complements ARS with competitive extramural funding vital to strengthening our nation's capacity to address opportunities related to diet, health, food safety, food security, and food science and technology. In addition, ERS provides invaluable food supply data, federal nutrition assistance program evaluations, and surveys on food insecurity and food acquisition and purchases.

Expanded USDA research to improve public guidance and education

As detailed in earlier sections, the USDA CNPP plays a major role in the development of the DGAs, with far-reaching implications for many federal and nonfederal policies and programs such as the suite of 15 federal nutrition assistance programs, FDA regulatory policies, and clinical guidance for individuals from allied health professionals. Yet, the CNPP 2020 budget is only $6.6 million for nutrition evidence reviews, committee support, and DGA-related educational development. Further work is needed to provide consistent funding and staff to maintain and protect the scientific integrity for nutrition evidence systematic reviews; fundamental nutrition research, monitoring, and surveillance processes; and to develop, translate, and disseminate dietary guidance.

Other USDA investments in public guidance include SNAP-Ed, with $441 million in funding in 2020 ( 340 ). The benefits of this major effort could be further amplified by the creation of a robust SNAP-Ed infrastructure [e.g., similar to the USDA NIFA Gus Schumacher Nutrition Incentive Program (GusNIP) or SNAP Employment and Training] to support evaluation of novel educational interventions, including policy and systems changes, online purchasing strategies, and other environmental supports, using SNAP pilot authority ( 13 ). Similarly, expanded research on WIC Nutrition Education should address approaches to further strengthen this valuable program, such as new strategies for education on breastfeeding practices, food and beverage choices, sleep, and screen time, as well as novel information systems and technology including online, mobile, and telehealth options to deploy this guidance to WIC participants ( 13 ). Greater research on the USDA's State Nutrition Action Committee (SNAC) program—which helps states coordinate USDA food-assistance programs, Affordable Care Act community benefits, wellness, and other food and nutrition programs—and the USDA Farm to School Grant Program—which funds school districts, state and local agencies, Indian tribal organizations, agricultural producers, and nonprofit organizations to increase local foods served through child nutrition programs, teach children about food and agriculture through garden and classroom education, and develop schools’ and farmers’ capacities to participate in farm to school—would amplify benefits of these investments ( 13 ).

Innovative USDA research to strengthen benefits of nutrition assistance programs

New research efforts supported by USDA, as well as NIH, are critical to develop the evidence base and collaborations to further augment the positive impacts of large federal investments in nutrition assistance (∼$100 billion/y). Such research must, for example, delineate and address the tremendous increases in food insecurity, associated economic disruptions, and nutrition-related health disparities stemming from COVID-19. Now is the time to expand our understanding of the best approaches to increase the public health impacts of our suite of 15 federal nutrition assistance programs. This approach can include, for instance, new USDA-supported pilots and waivers to evaluate innovations that better support healthier eating in SNAP (e.g., healthy retail approaches, healthy food incentives combined with disincentives, online purchasing technologies) ( 13 , 341 ). Further critical research needs include how USDA's nutrition assistance programs can be better integrated and coordinated with other federal and state programs, in particular Medicaid and Medicare, to improve diet-related health outcomes ( 13 ). These translational research investments will help address the varying geographic, contextual, and cultural needs of Americans and ensure the most effective outcomes from these essential federal programs.

Summary and Conclusions

This report identified stark national challenges in nutrition: diet-related illnesses, food insecurity, diet-related health disparities, health care costs for public and private payers, workforce productivity, military readiness, tremendous scientific debate and public confusion on a variety of critical topics, sustainability, and food system and population resilience to unexpected crises. Multiple federal departments and agencies are currently involved and investing in nutrition research and nutrition-related programs. However, as a share of total federal research expenditures, investments in nutrition research have been generally flat over the past 4 decades, despite the dramatic increase in diet-related illnesses such as obesity and type 2 diabetes and other identified diet-related challenges. Several current federal initiatives and collaborations aim to increase coordination of specific aspects of nutrition research and related activities across departments and agencies. Yet, the full potential of these efforts has not been realized, as documented by multiple governmental and other assessments since at least 1969, due to insufficient authority and funding.

The opportunities to be gained by greater coordination and investment in federal nutrition research are clear, with potential for large and rapid ROI. This report identified and described 2 priority strategies to strengthen federal nutrition research: 1 ) a new authority for cross-governmental coordination of nutrition research and other nutrition-relevant policy and 2 ) strengthened authority, investment, and coordination for nutrition research within NIH. These 2 strategies were found to be complementary and synergistic, each providing benefits that would be largest and most effective in concert. These options could potentially be a part of a multiyear strategy, initiated in part or whole (in some cases) by Congress or the President. Optimally, these options would garner full bipartisan support from the executive and legislative branches. Additional relevant priorities to strengthen federal nutrition research, particularly within USDA, were also recognized. Each of the identified options in this report would help create the new leadership, strategic planning, coordination, and investment the nation requires to address the challenges and grasp the opportunities we face.

Supplementary Material

Nqaa179_supplemental_file, acknowledgments.

We are indebted to a variety of federal agency staff and other stakeholders for their candid reflections of the past and present, as well as thorough assessments of potential strategies for moving forward. We are grateful to Dr. Sally Rockey and Dr. Yvonne Maddox for critical advisory comments and input and for input from Emily Broad Leib and Sarah Downer at the Center for Health Law and Policy Innovation at Harvard Law School. We are grateful for input from members of the Nutrition Action Alliance (NAA), a coalition of organizations working to advance federal nutrition research, nutrition education, and nutrition monitoring and surveillance, among other activities, which includes ASN, Academy of Nutrition and Dietetics, American Society for Parenteral and Enteral Nutrition, Association of Nutrition Departments and Programs, Institute of Food Technologists, National Board of Physician Nutrition Specialists, Society for Nutrition Education and Behavior, and The Obesity Society. This opportunity to review and provide feedback did not imply that the NAA nor any individual member organization has taken a specific policy position on every strategy option referenced in the paper. We thank Sylara Marie Cruz for outstanding management support.

The authors’ responsibilities were as follows—SEF, CEW, PMC, VSH, and DM: were on the lead writing group of this paper; the remaining authors regularly reviewed drafts and provided substantive feedback during regular calls and rounds of reviews; and all authors: read and approved the final manuscript. PMC reports paid consultancies with the Indiana University School of Public Health at Bloomington, Purdue University Department of Nutrition Sciences, and the Friedman School of Nutrition Science and Policy at Tufts University. SEF reports paid consultancies with the Friedman School of Nutrition Science and Policy at Tufts University and various paid work with Healthy Eating Research, a national program of the Robert Wood Johnson Foundation. VSH reports paid consultancies with the Indiana University School of Public Health at Bloomington and the Friedman School of Nutrition Science and Policy at Tufts University. DM reports research funding from the NIH and the Gates Foundation; personal fees from GOED, Bunge, Indigo Agriculture, Motif FoodWorks, Amarin, Acasti Pharma, Cleveland Clinic Foundation, America's Test Kitchen, and Danone; participating on scientific advisory boards of start-up companies focused on innovations for health including Brightseed, DayTwo, Elysium Health, Filtricine, Foodome, HumanCo, and Tiny Organics; and chapter royalties from UpToDate, all outside the submitted work; as well as research funding from The Rockefeller Foundation. PJS reports grant/research support from the NIH; participating on scientific advisory and/or membership boards of Marabou Foundation, the National Academy of Sciences, Engineering, and Medicine, the ASN, and International Council on Amino Acid Science; and holding stock in TIAA, all outside the submitted work. CEW reports a paid consultancy with the World Wildlife Fund for their research on sustainable food systems under a grant from The Rockefeller Foundation, outside the submitted work with the Friedman School of Nutrition Science and Policy at Tufts University. The other authors report no conflicts of interest.

Supported by the Rockefeller Foundation (award number: 2019 FOD 011). The views expressed herein do not necessarily represent the views of the funders or Tufts University.

The views and opinions expressed in this article are those of the authors, and do not necessarily reflect the official policy or position of the ASN. This article did not undergo review by the editors of The American Journal of Clinical Nutrition but did undergo review by several members of ASN.

Supplemental Figures 1–9, Supplemental Tables 1–10, and Supplemental Text 1–3 are available from the “Supplementary data” link in the online posting of the article and from the same link in the online table of contents at https://academic.oup.com/ajcn/ .

Abbreviations used: AHRQ, Agency for Healthcare Research and Quality; ARS, USDA Agricultural Research Service; BRAIN, NIH Brain Research through Advancing Innovative Neurotechnologies; CHAMP, Consortium for Health and Military Performance; CMMI, HHS Center for Medicare and Medicaid Innovation; CMS, HHS Centers for Medicare and Medicaid Services; CNPP, USDA Center for Nutrition Policy and Promotion; COVID-19, coronavirus disease 2019; DGA, Dietary Guidelines for Americans ; DGAC, Dietary Guidelines Advisory Committee; DHS, Department of Homeland Security; DNRC, NIH Division of Nutrition Research Coordination; DoC, Department of Commerce; DoD, Department of Defense; DoE, Department of Education; DoJ, Department of Justice; DPC, Domestic Policy Council; DPCPSI, NIH Division of Program Coordination, Planning, and Strategic Initiatives; EPA, Environmental Protection Agency; ERS, USDA Economic Research Service; FEMA, Federal Emergency Management Agency; FNS, USDA Food and Nutrition Service; FTC, Federal Trade Commission; GAO, Government Accountability Office; GDP, Gross Domestic Product; HHS, Department of Health and Human Services; HNCC, USDA Human Nutrition Coordinating Committee; HNRIM, Human Nutrition Research and Information Management; IBNMRR, Interagency Board for Nutrition Monitoring and Related Research; ICHNR, Interagency Committee on Human Nutrition Research; JSHNR, Joint Subcommittee on Human Nutrition Research; MND, Military Nutrition Division; NASA, National Aeronautics and Space Administration; NASEM, National Academies of Sciences, Engineering, and Medicine; NCC, NIH Nutrition Coordinating Committee; NCI, National Cancer Institute; NCNR, proposed NIH National Center for Nutrition Research; NHLBI, NIH National Heart, Lung, and Blood Institute; NIDDK, NIH National Institute of Diabetes and Digestive and Kidney Diseases; NIFA, USDA National Institute of Food and Agriculture; NIMHD, NIH National Institute of Minority Health and Health Disparities; NINR, NIH National Institute of Nursing Research; NIN, NIH new National Institute of Nutrition; NNMRRP, National Nutrition Monitoring and Related Research Program; NSC, National Security Council; NSF, National Science Foundation; OCS, USDA Office of the Chief Scientist; ODNI, Office of the Director of National Intelligence; ODPHP, HHS Office of Disease Prevention and Health Promotion; OMB, White House Office of Management and Budget; ONDFN, New Office of the National Director of Food and Nutrition; ONR, NIDDK Office of Nutrition Research; OSTP, White House Office of Science and Technology Policy; RCDC, Research, Condition, and Disease Categorization; REE, USDA Research, Economics, and Education mission area; RePORTER, NIH Research Portfolio Online Reporting Tools Expenditures and Results; ROI, return on investment; SNAP, USDA Supplemental Nutrition Assistance Program; SNAP-Ed, USDA Supplemental Nutrition Assistance Program Education; USAID, US Agency for International Development; USGCRP, US Global Climate Research Program; USGNRP, New US Global Nutrition Research Program; VA, Department of Veterans Affairs; VHA, Veterans Health Administration; WIC, USDA Special Supplemental Nutrition Program for Women, Infants, and Children.

Contributor Information

Sheila E Fleischhacker, Fly Health, LLC and Georgetown University Law Center, Washington, DC, USA.

Catherine E Woteki, University of Virginia Biocomplexity Institute and Initiative, Arlington, VA, USA.

Paul M Coates, Retired, National Institutes of Health, Bethesda, MD, USA.

Van S Hubbard, Retired, National Institutes of Health, Bethesda, MD, USA.

Grace E Flaherty, Gerald J and Dorothy R Friedman School of Nutrition Science and Policy at Tufts University, Boston, MA, USA.

Daniel R Glickman, The Aspen Institute, Washington, DC, USA.

Thomas R Harkin, Retired US Senator, Des Moines, IA, USA.

David Kessler, Former Food and Drug Administration Commissioner, College Park, MD, USA.

William W Li, The Angiogenesis Foundation, Cambridge, MA, USA.

Joseph Loscalzo, Department of Medicine at Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Anand Parekh, Bipartisan Policy Center, Washington, DC, USA.

Sylvia Rowe, SR Strategy, Washington, DC, USA.

Patrick J Stover, Texas A&M AgriLife, Texas A&M College of Agriculture and Life Sciences, and Texas A&M AgriLife Research, College Station, TX, USA.

Angie Tagtow, Äkta Strategies LLC, Des Moines, IA, USA.

Anthony Joon Yun, Yun Family Foundation, San Mateo, CA, USA.

Dariush Mozaffarian, Gerald J and Dorothy R Friedman School of Nutrition Science and Policy at Tufts University, Boston, MA, USA.

Diet Review: Mediterranean Diet

Finding yourself confused by the seemingly endless promotion of weight-loss strategies and diet plans? In this series , we take a look at some popular diets—and review the research behind them.

What Is It?

Chances are you have heard of the Mediterranean diet. If you have a chronic condition like heart disease or high blood pressure, your doctor may even have prescribed it to you. It is often promoted to decrease the risk of heart disease, depression, and dementia.

The traditional diets of countries bordering the Mediterranean Sea differ slightly so there are different versions of the Mediterranean diet. However, in 1993 the Harvard School of Public Health, Oldways Preservation and Exchange Trust, and the European Office of the World Health Organization introduced the Mediterranean Diet Pyramid as a guide to help familiarize people with the most common foods of the region. More of an eating pattern than a strictly regimented diet plan, the pyramid emphasized certain foods based on the dietary traditions of Crete, Greece, and southern Italy during the mid-20 th century. [1,2] At that time, these countries displayed low rates of chronic disease and higher than average adult life expectancy despite having limited access to healthcare. It was believed that the diet—mainly fruits and vegetables, beans, nuts, whole grains, fish, olive oil, small amounts of dairy, and red wine—contributed to their health benefits. The pyramid also highlighted daily exercise and the beneficial social aspects of eating meals together.

How It Works

The Mediterranean diet is a primarily plant-based eating plan that includes daily intake of whole grains, olive oil, fruits, vegetables, beans and other legumes, nuts, herbs, and spices. Other foods like animal proteins are eaten in smaller quantities, with the preferred animal protein being fish and seafood. Although the pyramid shape suggests the proportion of foods to eat (e.g., eat more fruits and vegetables and less dairy foods), it does not specify portion sizes or specific amounts. It is up to the individual to decide exactly how much food to eat at each meal, as this will vary by physical activity and body size. There are additional points that make this eating plan unique:

• An emphasis on healthy fats . Olive oil is recommended as the primary added fat, replacing other oils and fats (butter, margarine). Other foods naturally containing healthful fats are highlighted, such as avocados, nuts, and oily fish like salmon and sardines; among these, walnuts and fish are high in omega-3 fatty acids.
• Choosing fish as the preferred animal protein at least twice weekly and other animal proteins of poultry, eggs, and dairy (cheese or yogurt) in smaller portions either daily or a few times a week. Red meat is limited to a few times per month.
• Choosing water as the main daily beverage, but allowing a moderate intake of wine with meals, about one to two glasses a day for men and one glass a day for women.
• Stressing daily physical activity through enjoyable activities.

This sample meal plan is roughly 2000 calories, the recommended intake for an average person. If you have higher calorie needs, you may add an additional snack or two; if you have lower calorie needs, you may remove a snack. If you have more specific nutritional needs or would like assistance in creating additional meal plans, consult with a registered dietitian.

Breakfast: 1 cup cooked steel-cut oats mixed with 2 tablespoons chopped walnuts, ¾ cup fresh or frozen blueberries, sprinkle of cinnamon

Snack: ¼ cup nuts, any type

• Beans and rice – In medium pot, heat 1 tbsp olive oil. Add and sauté ½ chopped onion, 1 tsp cumin, and 1 tsp garlic powder until onion is softened. Mix in 1 cup canned beans, drained and rinsed. Serve bean mixture over 1 cup cooked brown rice.
• 2 cups salad (e.g., mixed greens, cucumbers, bell peppers) with dressing (mix together 2 tbsp olive oil, 1 tbsp lemon juice or vinegar, ½ teaspoon Dijon mustard, ½ teaspoon garlic powder, ¼ tsp black pepper)

Snack: 1 medium orange

• 3 ounces baked salmon brushed with same salad dressing used at lunch
• 1 medium baked sweet potato with 1 tbsp soft margarine
• 1 cup chopped steamed cauliflower

Snack: 1 ounce 75% dark chocolate

The Research So Far

Research has consistently shown that the Mediterranean diet is effective in reducing the risk of cardiovascular diseases and overall mortality. [3, 4]  A study of nearly 26,000 women found that those who followed this type of diet had 25% less risk of developing cardiovascular disease over the course of 12 years. [5]  The study examined a range of underlying mechanisms that might account for this reduction, and found that changes in inflammation, blood sugar, and body mass index were the biggest drivers. Similar benefits were found in a meta-analysis of 16 prospective cohort studies following more than 22,000 women for a median of 12.5 years. [6] Those who had the highest adherence to a Mediterranean diet showed a 24% lower risk of cardiovascular disease and 23% lower risk of premature death compared with those who had the lowest adherence.

One interesting finding of this eating plan is that it dispels the myth that people with or at risk for heart disease must eat a low fat diet. Although it does matter which types of fats are chosen, the percentage of calories from fat is less of an issue. The PREDIMED study, a primary prevention trial including thousands of people with diabetes or other risk factors for heart disease found that a Mediterranean diet supplemented with extra virgin olive oil or nuts and without any fat and calorie restrictions reduced the rates of death from stroke by roughly 30%. [7] Most dietary fats were healthy fats, such as those from fatty fish, olive oil, and nuts, but total fat intake was generous at 39-42% of total daily calories, much higher than the 20-35% fat guideline as stated by the Institute of Medicine. [8]  Risk of type 2 diabetes was also reduced in the PREDIMED trial. [9]

There has also been increased interest in the diet’s effects on aging and cognitive function. [10-12] Cell damage through stress and inflammation that can lead to age-related diseases has been linked to a specific part of DNA called telomeres. These structures naturally shorten with age, and their length size can predict life expectancy and the risk of developing age-related diseases. Telomeres with long lengths are considered protective against chronic diseases and earlier death, whereas short lengths increase risk. Antioxidants can help combat cell stress and preserve telomere length, such as by eating foods that contain antioxidants nutrients like fruits, vegetables, nuts, and whole grains. These foods are found in healthy eating patterns like the Mediterranean diet. [13] This was demonstrated in a large cohort of 4676 healthy middle-aged women from the Nurses’ Health Study where participants who more closely followed the Mediterranean diet were found to have longer telomere length. [13]

Another Nurses’ Health Study following 10,670 women ages 57-61 observed the effect of dietary patterns on aging. [14] Healthy aging was defined as living to 70 years or more, and having no chronic diseases (e.g., type 2 diabetes, kidney disease, lung disease, Parkinson’s disease, cancer) or major declines in mental health, cognition, and physical function. The study found that the women who followed a Mediterranean-type eating pattern were 46% more likely to age healthfully. Increased intake of plant foods, whole grains, and fish; moderate alcohol intake; and low intake of red and processed meats were believed to contribute to this finding.

Potential Pitfalls

• There is a risk of excess calorie intake because specific amounts of foods and portion sizes are not emphasized, which could lead to weight gain. It might be helpful to use the Mediterranean Diet Pyramid, which provides guidance on specific types of foods to choose, along with a balanced plate guide such as the Harvard Healthy Eating Plate , which gives a better indication of proportions of food to eat per meal. However, it is important to note that—probably in part due to the higher intake of olive oil and less processed foods—the Mediterranean dietary pattern provides satiety and enables long term adherence. In one of the most successful weight loss trials to date, those assigned to the Mediterranean diet maintained weight loss over a period of six years. [15]
• Research supports the health benefits of a Mediterranean-style eating pattern that includes several different foods. It is the combination of these foods that appear protective against disease, as the benefit is not as strong when looking at single foods or nutrients included in the Mediterranean diet. [13] Therefore it is important to not simply add olive oil or nuts to one’s current diet but to adopt the plan in its entirety.

Bottom Line

Research supports the use of the Mediterranean diet as a healthy eating pattern for the prevention of cardiovascular diseases, increasing lifespan, and healthy aging. When used in conjunction with caloric restriction, the diet may also support healthy weight loss.

• Healthy Weight
• The Best Diet: Quality Counts
• Healthy Dietary Styles
• Other Diet Reviews
• Willett WC, Sacks F, Trichopoulou A, Drescher G, Ferro-Luzzi A, Helsing E, Trichopoulos D. Mediterranean diet pyramid: a cultural model for healthy eating. AJCN . 1995 Jun 1;61(6):1402S-6S.
• Gifford KD. Dietary fats, eating guides, and public policy: history, critique, and recommendations. Am J Med . 2002 Dec 30;113(9):89-106.
• Fung TT, Rexrode KM, Mantzoros CS, Manson JE, Willett WC, Hu FB. Mediterranean diet and incidence of and mortality from coronary heart disease and stroke in women.  Circulation . 2009 Mar 3;119(8):1093-100.
• Lopez-Garcia E, Rodriguez-Artalejo F, Li TY, Fung TT, Li S, Willett WC, Rimm EB, Hu FB. The Mediterranean-style dietary pattern and mortality among men and women with cardiovascular disease. AJCN . 2013 Oct 30;99(1):172-80.
• Ahmad S, Moorthy MV, Demler OV, Hu FB, Ridker PM, Chasman DI, Mora S. Assessment of Risk Factors and Biomarkers Associated With Risk of Cardiovascular Disease Among Women Consuming a Mediterranean Diet. JAMA Network Open . 2018 Dec 7;1(8):e185708-.
• Pant A, Gribbin S, McIntyre D, Trivedi R, Marschner S, Laranjo L, Mamas MA, Flood V, Chow CK, Zaman S. Primary prevention of cardiovascular disease in women with a Mediterranean diet: systematic review and meta-analysis. Heart . 2023 Feb 15.
• Estruch R, Ros E, Salas-Salvadó J, Covas MI, Corella D, Arós F, Gómez-Gracia E, Ruiz-Gutiérrez V, Fiol M, Lapetra J, Lamuela-Raventos RM. Primary prevention of cardiovascular disease with a mediterranean diet supplemented with extra-virgin olive oil or nuts.  New England Journal of Medicine . 2018 Jun 13.  [Note: reference updated in June 2018 due to retraction and republication ]
• Food and Nutrition Board, Institute of Medicine of the National Academies. Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids. The National Academies Press , 2005. Accessed 10/16/17.
• Salas-Salvadó J, Bulló M, Babio N, Martínez-González MÁ, Ibarrola-Jurado N, Basora J, Estruch R, Covas MI, Corella D, Arós F, Ruiz-Gutiérrez V. Reduction in the incidence of type 2 diabetes with the Mediterranean diet. Diabetes care . 2011 Jan 1;34(1):14-9.
• Loughrey DG, Lavecchia S, Brennan S, Lawlor BA, Kelly ME. The impact of the Mediterranean diet on the cognitive functioning of healthy older adults: a systematic review and meta-analysis. Advances in Nutrition . 2017 Jul 6;8(4):571-86.
• Aridi YS, Walker JL, Wright OR. The association between the Mediterranean dietary pattern and cognitive health: a systematic review. Nutrients . 2017 Jun 28;9(7):674.
• Bhushan A, Fondell E, Ascherio A, Yuan C, Grodstein F, Willett W. Adherence to Mediterranean diet and subjective cognitive function in men. European journal of epidemiology . 2017 Nov 17:1-2.
• Crous-Bou M, Fung TT, Prescott J, Julin B, Du M, Sun Q, Rexrode KM, Hu FB, De Vivo I. Mediterranean diet and telomere length in Nurses’ Health Study: population based cohort study. BMJ . 2014 Dec 2;349:g6674.
• Samieri C, Sun Q, Townsend MK, Chiuve SE, Okereke OI, Willett WC, Stampfer M, Grodstein F. The Association Between Dietary Patterns at Midlife and Health in Aging: An Observational Study. Annals of internal medicine . 2013 Nov 5;159(9):584-91.
• Shai I, Schwarzfuchs D, Henkin Y, Shahar DR, Witkow S, Greenberg I, Golan R, Fraser D, Bolotin A, Vardi H, Tangi-Rozental O. Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet. NEJM . 2008 Jul 17;2008(359):229-41.

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• Estimated changes in free sugar consumption one year after the UK soft drinks industry levy came into force: controlled interrupted time series analysis of the National Diet and Nutrition Survey (2011–2019)
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• http://orcid.org/0000-0003-1857-2122 Nina Trivedy Rogers 1 ,
• http://orcid.org/0000-0002-3957-4357 Steven Cummins 2 ,
• Catrin P Jones 1 ,
• Oliver Mytton 3 ,
• Mike Rayner 4 ,
• Harry Rutter 5 ,
• Martin White 1 ,
• Jean Adams 1
• 1 MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus , University of Cambridge , Cambridge , UK
• 2 Department of Public Health, Environments & Society , London School of Hygiene & Tropical Medicine , London , UK
• 3 Great Ormond Street Institute of Child Health , University College London , London , UK
• 4 Nuffield Department of Population Health , University of Oxford , Oxford , UK
• 5 Department of Social and Policy Sciences , , University of Bath , Bath , UK
• Correspondence to Dr Nina Trivedy Rogers, MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, University of Cambridge, Cambridge, CB2 1TN, UK; nina.rogers{at}mrc-epid.cam.ac.uk

Background The UK soft drinks industry levy (SDIL) was announced in March 2016 and implemented in April 2018, encouraging manufacturers to reduce the sugar content of soft drinks. This is the first study to investigate changes in individual-level consumption of free sugars in relation to the SDIL.

Methods We used controlled interrupted time series (2011–2019) to explore changes in the consumption of free sugars in the whole diet and from soft drinks alone 11 months after SDIL implementation in a nationally representative sample of adults (>18 years; n=7999) and children (1.5–19 years; n=7656) drawn from the UK National Diet and Nutrition Survey. Estimates were based on differences between observed data and a counterfactual scenario of no SDIL announcement/implementation. Models included protein consumption (control) and accounted for autocorrelation.

Results Accounting for trends prior to the SDIL announcement, there were absolute reductions in the daily consumption of free sugars from the whole diet in children and adults of 4.8 g (95% CI 0.6 to 9.1) and 10.9 g (95% CI 7.8 to 13.9), respectively. Comparable reductions in free sugar consumption from drinks alone were 3.0 g (95% CI 0.1 to 5.8) and 5.2 g (95% CI 4.2 to 6.1). The percentage of total dietary energy from free sugars declined over the study period but was not significantly different from the counterfactual.

Conclusion The SDIL led to significant reductions in dietary free sugar consumption in children and adults. Energy from free sugar as a percentage of total energy did not change relative to the counterfactual, which could be due to simultaneous reductions in total energy intake associated with reductions in dietary free sugar.

• PUBLIC HEALTH

Data availability statement

Data are available in a public, open access repository. Data from the National Diet and Nutrition Survey years 1–11 (2008–09 to 2018–19) can be accessed on the UK Data Service ( https://ukdataservice.ac.uk/ ).

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/jech-2023-221051

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WHAT IS ALREADY KNOWN ON THIS TOPIC

High intakes of free sugars are associated with a range of non-communicable diseases. Sugar sweetened beverages constitute a major source of dietary free sugars in children and adults.

The UK soft drink industry levy (SDIL) led to a reduction in the sugar content in many sugar sweetened beverages and a reduction in household purchasing of sugar from drinks.

No previous study has examined the impact of the SDIL on total dietary consumption of free sugars at the individual level.

WHAT THIS STUDY ADDS

There were declining trends in the intake of dietary free sugar in adults and children prior to the UK SDIL.

Accounting for prior trends, 1 year after the UK SDIL came into force children and adults further reduced their free sugar intake from food and drink by approximately 5 g/day and 11 g/day, respectively. Children and adults reduced their daily free sugar intake from soft drinks alone by approximately 3 g/day and approximately 5 g/day, respectively.

Energy intake from free sugars as a proportion of total energy consumed did not change significantly following the UK SDIL, indicating energy intake from free sugar was reducing simultaneously with overall total energy intake.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

The UK SDIL was associated with significant reductions in consumption of free sugars from soft drinks and across the whole diet and reinforces previous research indicating a reduction in purchasing. This evidence should be used to inform policy when extending or considering other sugar reduction strategies.

Energy intake from free sugars has been falling but levels remain higher than the 5% recommendation set by the WHO. Reductions in dietary sugar in relation to the SDIL may have driven significant reductions in overall energy.

Introduction

High consumption of free sugars is associated with non-communicable diseases. 1 Guidelines from the World Health Organization (WHO) and the UK Scientific Advisory Committee on Nutrition (SACN) suggest limiting free sugar consumption to below 5% of total energy intake to achieve maximum health benefits, 1 2 equivalent to daily maximum amounts of 30 g for adults, 24 g for children (7–10 years) and 19 g for young children (4–6 years). In the UK, consumption of free sugar is well above the recommended daily maximum, although levels have fallen over the last decade. 3 For example, adolescents consume approximately 70 g/day 4 and obtain 12.3% of their energy from free sugars. 3 Sugar sweetened beverages (SSBs) constitute a major source of free sugar in the UK diet, 2 5 and are the largest single source for children aged 11–18 years where they make up approximately one-third of their daily sugar intake. 6 A growing body of evidence has shown a link between consumption of SSBs and higher risk of weight gain, type 2 diabetes, coronary heart disease and premature mortality, 7 such that the WHO recommends taxation of SSBs in order to reduce over-consumption of free sugars and to improve health. 8 To date, >50 countries have introduced taxation on SSBs, which has been associated with a reduction in sales and dietary intake of free sugar from SSBs. 9 Reductions in the prevalence of childhood obesity 10 11 and improvements in dental health outcomes 12 13 have also been reported.

In March 2016 the UK government announced the UK soft drink industry levy (SDIL), a two-tier levy on manufacturers, importers and bottlers of soft drinks which would come into force in March 2018. 14 The levy was designed to incentivise manufacturers to reformulate and reduce the free sugar content of SSBs (see details in online supplemental text 1 ).

Supplemental material

One year after the UK SDIL was implemented there was evidence of a reduction in the sugar content of soft drinks 15 and households on average reduced the amount of sugar purchased from soft drinks by 8 g/week with no evidence of substitution with confectionary or alcohol. 16 However, lack of available data meant it was not possible to examine substitution of purchasing other sugary foods and drinks, which has previously been suggested in some but not all studies. 17 18 Household purchasing only approximates individual consumption because it captures only those products brought into the home, products may be shared unequally between household members, and it does not account for waste.

To examine the effects of the SDIL on total sugar intake at the individual level, in this study we used surveillance data collected using 3- or 4-day food diaries as part of the UK National Diet and Nutrition Survey (NDNS). We aimed to examine changes in absolute and relative consumption of free sugars from soft drinks alone and from both food and drinks (allowing us to consider possible substitutions with other sugary food items), following the announcement and implementation of the UK SDIL.

Data source

We used 11 years of data (2008–2019) from the NDNS. Data collection, sampling design and information on response is described in full elsewhere. 19 In brief, NDNS is a continuous national cross-sectional survey capturing information on food consumption, nutritional status and nutrient intake inside and outside of the home in a representative annual sample of approximately 500 adults and 500 children (1.5–18 years) living in private households in the UK. Participants are sampled throughout the year, such that in a typical month about 40 adults and 40 children participate (further details are shown in online supplemental text 2 ).

Outcomes of interest

Outcomes of interest were absolute and relative changes in the total intake of dietary free sugar from (1) all food and soft drinks combined and (2) from soft drinks alone. A definition of free sugar is given in online supplemental text 3 . Drink categories examined were those that fell within the following NDNS categories: soft drinks – not low calorie; soft drinks – low calorie; semi-skimmed milk; whole milk; skimmed milk; fruit juice, 1% fat milk and other milk and cream. Additionally, we examined absolute and relative changes in percentage energy from free sugar in (1) food and soft drinks and (2) soft drinks alone. While examination of changes in sugar consumption and percentage energy from sugar across the whole diet (food and drink) captures overall substitutions with other sugar-containing products following the UK SDIL, examination of sugar consumption from soft drinks alone provides a higher level of specificity to the SDIL.

Protein intake was selected as a non-equivalent dependent control. It was not a nutritional component specifically targeted by the intervention or other government interventions and therefore is unlikely to be affected by the SDIL but could still be affected by confounding factors such as increases in food prices 20 (see online supplemental text 4 ).

Statistical analysis

Controlled interrupted time series (ITS) analyses were performed to examine changes in the outcomes in relation to the UK SDIL separately in adults and children. We analysed data at the quarterly level over 11 years with the first data point representing dates from April to June 2008 and the last representing dates from January to March 2019. Model specifications are shown in online supplemental text 5 . Where diary date entries extended over two quarters, the earlier quarter was designated as the time point for analysis. Generalised least squares models were used. Autocorrelation in the time series was determined using Durbin–Watson tests and from visualisations of autocorrelation and partial correlation plots. Autocorrelation-moving average correlation structure with order (p) and moving average (q) parameters were used and selected to minimise the Akaike information criterion in each model. Trends in free sugar consumption prior to the announcement of SDIL in April 2016 were used to estimate counterfactual scenarios of what would have happened if the SDIL had not been announced or come into force. Thus, the interruption point was the 3-month period beginning April 2016. Absolute and relative differences in consumption of free sugars/person/day were estimated by calculating the difference between the observed and counterfactual values at quarterly time point 45. To account for non-response and to ensure the sample distribution represented the UK distribution of females and males and age profile, weights provided by NDNS were used and adapted for analysis of adults and children separately. 21 A study protocol has been published 22 and the study is registered ( ISRCTN18042742 ). For changes to the original protocol see online supplemental text 6 . All statistical analyses were performed in R version 4.1.0.

Data from 7999 adults and 7656 children were included across 11 years representing approximately 40 children and 40 adults each month. Table 1 gives descriptive values for the outcomes of interest. Compared with the pre-announcement period, free sugars consumed from all soft drinks reduced by around one-half in children and one-third in adults in the post-announcement period. Total dietary free sugar consumption and percentage of total dietary energy derived from free sugars also declined. Mean protein consumption was relatively stable over both periods in children and adults. The age and sex of the children and adults were very similar in the pre- and post-announcement periods.

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Mean amount of free sugar (g) consumed in children and adults per day during the study period before and after the announcement of the soft drinks industry levy (SDIL)

All estimates of change in free sugar consumption referred to below are based on g/individual/day in the 3-month period beginning January 2019 and compared with the counterfactual scenario of no UK SDIL announcement and implementation.

Change in free sugar consumption (soft drinks only)

In children, consumption of free sugars from soft drinks was approximately 27 g/day at the start of the study period but fell steeply throughout. By the end of the study period mean sugar consumption from soft drinks was approximately 10 g/day ( figure 1 ). Overall, relative to the counterfactual scenario, there was an absolute reduction in daily free sugar consumption from soft drinks of 3.0 g (95% CI 0.1 to 5.8) or a relative reduction of 23.5% (95% CI 46.0% to 0.9%) in children ( table 2 ). In adults, free sugar consumption at the beginning of the study was lower than that of children (approximately 17 g/day) and was declining prior to the SDIL announcement, although less steeply ( figure 1 ). Following the SDIL announcement, free sugar consumption from soft drinks appeared to decline even more steeply. There was an absolute reduction in free sugar consumption from soft drinks of 5.2 g (95% CI 4.2 to 6.1) or a relative reduction of 40.4% (95% CI 32.9% to 48.0%) in adults relative to the counterfactual ( figure 1 , table 2 ).

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Observed and modelled daily consumption (g) of free sugar from drink products per adult/child from April 2008 to March 2019. Red points show observed data and solid red lines (with light red shadows) show modelled data (and 95% CIs) of free sugar consumed from drinks. The dashed red line indicates the counterfactual line based on pre-announcement trends and if the announcement and implementation had not happened. Modelled protein consumption from drinks (control group) was removed from the graph to include resolution but is available in the supplementary section. The first and second dashed lines indicate the announcement and implementation of the soft drinks industry levy (SDIL), respectively.

Change in free sugar consumption in food and drink and energy from free sugar as a proportion of total energy compared with the counterfactual scenario of no announcement and implementation of the UK soft drinks industry levy (SDIL)

Change in total dietary free sugar consumption (food and soft drinks combined)

Consumption of total dietary free sugars in children was approximately 70 g/day at the beginning of the study but this fell to approximately 45 g/day by the end of the study ( figure 2 ). Relative to the counterfactual scenario, there was an absolute reduction in total dietary free sugar consumption of 4.8 g (95% CI 0.6 to 9.1) or relative reduction of 9.7% (95% CI 18.2% to 1.2%) in children ( figure 2 ; table 2 ). In adults, consumption of total dietary free sugar consumption at the beginning of the study was approximately 60 g/day falling to approximately 45 g/day by the end of the study ( figure 2 ). Relative to the counterfactual scenario there was an absolute reduction in total dietary free sugar consumption in adults of 10.9 g (95% CI 7.8 to 13.9) or a relative reduction of 19.8% (95% CI 25.4% to 14.2%). Online supplemental figures show that, relative to the counterfactual, dietary protein consumption and energy from protein was more or less stable across the study period (see online supplemental figures S3–S6 ).

Observed and modelled daily consumption (g) of free sugar from food and drink products per adult/child from April 2008 to March 2019. Red points show observed data and solid red lines (with light red shadows) show modelled data (and 95% CIs) of free sugar consumed from food and drinks. The dashed red line indicates the counterfactual line based on pre-announcement trends and if the announcement and implementation had not happened. Modelled protein consumption from food and drinks (control group) was removed from the graph to include resolution but is available in the supplementary section. The first and second dashed lines indicate the announcement and implementation of the soft drinks industry levy (SDIL), respectively.

Change in energy from free sugar as a proportion of total energy

The percentage of energy from total dietary free sugar decreased across the study period but did not change significantly relative to the counterfactual scenario in children or adults, with relative changes in free sugar consumption of −7.6 g (95% CI −41.7 to 26.5) and −24.3 g (95% CI −54.0 to 5.4), respectively (see online supplemental figure S1 and table 2 ). Energy from free sugar in soft drinks as a proportion of total energy from soft drinks also decreased across the study period but did not change significantly relative to the counterfactual (see online supplemental figure S2 ).

Summary of main findings

This study is the first to examine individual level consumption of free sugars in the total diet (and in soft drinks only) in relation to the UK SDIL. Using nationally representative population samples, we found that approximately 1 year following the UK SDIL came into force there was a reduction in total dietary free sugar consumed by children and adults compared with what would have been expected if the SDIL had not been announced and implemented. In children this was equivalent to a reduction of 4.8 g of free sugars/day from food and soft drinks, of which 3 g/day came from soft drinks alone, suggesting that the reduction of sugar in the diet was primarily due to a reduction of sugar from soft drinks. In adults, reductions in dietary sugar appeared to come equally from food and drink with an 11 g reduction in food and drink combined, of which 5.2 g was from soft drinks only. There was no significant reduction compared with the counterfactual in the percentage of energy intake from free sugars in the total diet or from soft drinks alone in both children and adults, suggesting that energy intake from free sugar was reducing simultaneously with overall total energy intake.

Comparison with other studies and interpretation of results

Our finding of a reduction in consumption of free sugars from soft drinks after accounting for pre-SDIL announcement trends is supported by previous research showing a large reduction in the proportion of available soft drinks with over 5 g of sugar/100 mL, the threshold at which soft drinks become levy liable. 15 Furthermore, efforts of the soft drink industry to reformulate soft drinks were found to have led to significant reductions in the volume and per capita sales of sugar from these soft drinks. 23

Our findings are consistent with recent research showing reductions in purchasing of sugar from soft drinks of approximately 8 g/household/week (equivalent to approximately 3 g/person/week or approximately 0.5 g/person/day) 1 year after the SDIL came into force. 16 The estimates from the current study suggest larger reductions in consumption (eg, 3 g free sugar/day from soft drinks in children) than previously reported for purchasing. Methodological differences may explain these differences in estimated effect sizes. Most importantly, the previous study used data on soft drink purchases that were for consumption in the home only. In contrast, we captured information on consumption (rather than purchasing) in and out of the home. Consumption of food and particularly soft drinks outside of the home in young people (1–21 years) increases with age and makes a substantial contribution to total free sugar intakes, highlighting the importance of recording both in home and out of home sugar consumption. 4 Purchasing and consumption data also treat waste differently; purchase data record what comes into the home and therefore include waste, whereas consumption data specifically aim to capture leftovers and waste and exclude it from consumption estimates. While both studies use weights to make the population samples representative of the UK, there may be differences in the study participant characteristics in the two studies, which may contribute to the different estimates.

Consistent with other studies, 24 we found that across the 11-year study period we observed a downward trend in free sugar and energy intake in adults and children. 3 A decline in consumption of free sugars was observed in the whole diet rather than just soft drinks, suggesting that consumption of free sugar from food was also declining from as early as 2008. One reason might be the steady transition from sugar in the diet to low-calorie artificial sweeteners, which globally have had an annual growth of approximately 5.1% between 2008 and 2015. 25

Public health signalling around the time of the announcement of the levy may also have contributed to the changes we observed. Public acceptability and perceived effectiveness of the SDIL was reported to be high 4 months before and approximately 20 months after the levy came into force. 26 Furthermore, awareness of the SDIL was found to be high among parents of children living in the UK, with most supporting the levy and intending to reduce purchases of SSBs as a result. 27 Health signalling was also found following the implementation of the SSB tax in Mexico, with one study reporting that most adults (65%) were aware of the tax and that those aware of the tax were more likely to think the tax would reduce purchases of SSBs, 28 although a separate study found that adolescents in Mexico were mostly unaware of the tax, 29 suggesting that public health signalling may differ according to age.

In 2016 the UK government announced a voluntary sugar reduction programme as part of its childhood obesity plan (which also included SDIL) with the aim of reducing sugar sold by industry by 5% no later than 2018 and by 20% in time for 2020 through both reformulation and portion size reduction. 30 While the programme only managed to achieve overall sugar reductions of approximately 3.5%, this did include higher reductions in specific products such as yoghurts (−17%) and cereals (−13%) by 2018 which may have contributed to some of the observed reductions in total sugar consumption (particularly from foods) around the time of the SDIL. While there is strong evidence that the UK SDIL led to significant reformulation 15 and reductions in purchases of sugar from soft drinks, 16 the products targeted by the sugar reduction programme were voluntary with no taxes or penalties if targets were not met, possibly leading to less incentive for manufacturers to reformulate products that were high in sugar. The 5-year duration of the voluntary sugar reduction programme also makes it challenging to attribute overall reductions using interruption points that we assigned to the ITS to align with the date of the SDIL announcement. The soft drinks categories in our study included levy liable and non-levy liable drinks because we wanted to examine whether individuals were likely to substitute levy liable drinks for high sugar non-liable options. The decline in sugar consumed overall and in soft drinks in relation to the levy suggests that individuals did not change their diets substantially by substituting more sugary foods and drinks. This is consistent with findings from a previous study that found no changes in relation to the levy in sugar purchased from fruit juice, powder used to make drinks or confectionery. 16

Consistent with previous analyses, 3 our findings showed that there was a downward trend in energy intake from sugar as a proportion of total energy across the duration of the study. While there was no reduction compared with the counterfactual scenario (which was also decreasing), our estimates suggest that, by 2019, on average energy from sugar as a proportion of all energy appears to be in line with the WHO recommendation of 10% but not the more recent guidelines of 5% which may bring additional health benefits. 1 31 This finding may suggest that reductions in energy intake from sugar were reducing in concert with overall energy intake and indeed may have been driving it. However, the magnitude of calories associated with the reduction in free sugars, compared with the counterfactual scenario in both adults and children, was modest and thus potentially too small to reflect significant changes in the percentage of energy from sugar. In children, a daily reduction of 4.8 g sugar equates to approximately 19.2 kilocalories out of an approximate daily intake of approximately 2000 kilocalories which is equivalent to approximately 1% reduction in energy intake. Furthermore, overall measures of dietary energy are also likely to involve a degree of error reducing the level of precision in any estimates.

Our estimates of changes in sugar consumption in relation to SDIL suggest that adults may have experienced a greater absolute reduction in sugar than children, which is not consistent with estimates of the distributional impact of the policy. 32 However, our understanding may be aided by the visualisations afforded by graphical depictions of our ITS graphs. Children’s consumption of sugar at the beginning of the study period, particularly in soft drinks, was higher than in adults but reducing at a steeper trajectory, which will have influenced our estimated counterfactual scenario of what would have happened without the SDIL. This steep downward trajectory could not have continued indefinitely as there is a lower limit for sugar consumption. No account for this potential ‘floor effect’ was made in the counterfactual. Adults had a lower baseline of sugar consumption, but their trajectory of sugar consumption decreased at a gentler trajectory, potentially allowing more scope for improvement over the longer run.

Reductions in the levels of sugar in food and drink may have also impacted different age groups and children and adults differently. For example, the largest single contributor to free sugars in younger children aged 4–10 years is cereal and cereal products, followed by soft drinks and fruit juice. By the age of 11–18 years, soft drinks provide the largest single source (29%) of dietary free sugar. For adults the largest source of free sugars is sugar, preserves and confectionery, followed by non-alcoholic beverages. 5

Strengths and limitations

The main strengths of the study include the use of nationally representative data on individual consumption of food and drink in and out of the home using consistent food diary assessment over a 4-day period, setting it apart from other surveys which have used food frequency questionnaires, 24 hour recall, shortened dietary instruments or a mixture of these approaches across different survey years. 33 The continual collection of data using consistent methods enabled us to analyse dietary sugar consumption and energy quarterly over 11 years (or 45 time points) including the announcement and implementation period of the SDIL. Information on participant age allowed us to examine changes in sugar consumption in adults and children separately. Limited sample sizes restricted our use of weekly or monthly data and prevented us from examining differences between sociodemographic groups. At each time point we used protein consumption in food and drink as a non-equivalent control category, strengthening our ability to adjust for time-varying confounders such as contemporaneous events. The trends in counterfactual scenarios of sugar consumption and energy from free sugar as part of total energy were based on trends from April 2008 to the announcement of the UK SDIL (March 2016); however, it is possible that the direction of sugar consumption may have changed course. Ascribing changes in free sugar consumption to the SDIL should include exploration of other possible interventions that might have led to a reduction in sugar across the population. We are only aware of the wider UK government’s voluntary sugar reduction programme implemented across overlapping timelines (2015–2020) and leading to reductions in sugar consumption that were well below the targets set. 30 In turn, under-reporting of portion sizes and high energy foods, which may be increasingly seen as less socially acceptable, has been suggested as a common error in self-reported dietary intake with some groups including older teenagers and females, especially those who are living with obesity, more likely to underestimate energy intake. 34 35 However, there is no evidence to suggest this would have changed as a direct result of the SDIL. 36

Conclusions

Our findings indicate that the UK SDIL led to reductions in consumption of dietary free sugars in adults and children 1 year after it came into force. Energy from free sugar as a proportion of overall energy intake was falling prior to the UK SDIL but did not change in relation to the SDIL, suggesting that a reduction in sugar may have driven a simultaneous reduction in overall energy intake.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

For NDNS 2008–2013, ethical approval was obtained from the Oxfordshire A Research Ethics Committee (Reference number: 07/H0604/113). For NDNS 2014–2017, ethical approval was given from the Cambridge South NRES Committee (Reference number: 13/EE/0016). Participants gave informed consent to participate in the study before taking part.

• World Health Organization
• Scientific Advisory Committee on Nutrition
• Griffith R ,
• O’Connell M ,
• Smith K , et al
• Roberts C ,
• Maplethorpe N , et al
• Tedstone A ,
• Targett V ,
• Mizdrak A , et al
• Rogers NT ,
• Cummins S ,
• Forde H , et al
• Gracner T ,
• Marquez-Padilla F ,
• Hernandez-Cortes D
• Petimar J ,
• Gibson LA ,
• Wolff MS , et al
• Conway DI ,
• Mytton O , et al
• Scarborough P ,
• Adhikari V ,
• Harrington RA , et al
• Mytton OT , et al
• Powell LM ,
• Chriqui JF ,
• Khan T , et al
• Lawman HG ,
• Bleich SN , et al
• Venables MC ,
• Nicholson S , et al
• Lopez Bernal J ,
• Gasparrini A
• Public Health England
• Briggs A , et al
• Marriott BP ,
• Malek AM , et al
• Sylvetsky AC ,
• Penney TL , et al
• Gillison F ,
• Álvarez-Sánchez C ,
• Contento I ,
• Jiménez-Aguilar A , et al
• Ortega-Avila AG ,
• Papadaki A ,
• Briggs ADM ,
• Mytton OT ,
• Kehlbacher A , et al
• Campbell M ,
• Baird J , et al
• Prentice AM ,
• Goldberg GR , et al
• Hebert JR ,
• Pbert L , et al
• Page P , et al

Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1

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Contributors OM, SC, MR, HR, MW and JA conceptualised and acquired funding for the study. NTR carried out statistical analyses. NTR and JA drafted the manuscript. All authors contributed to the article and approved the submitted version.

As the guarantor, NTR had access to the data, controlled the decision to publish and accepts full responsibility for the work and the conduct of the study.

Funding NTR, OM, MW and JA were supported by the Medical Research Council (grant Nos MC_UU_00006/7). This project was funded by the NIHR Public Health Research programme (grant nos 16/49/01 and 16/130/01) to MW. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, or the Department of Health and Social Care, UK. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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