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Figure 1.  Analytic Framework for the Systematic Review Question
Analytic Framework for the Systematic Review Question

This analytic framework visually represents the overall scope of the systematic review question and depicts the contributing elements that were examined and evaluated, including the target population, exposure, comparison, outcomes, and key confounders. Reproduced from the 2020 Dietary Guidelines Advisory Committee and Nutrition Evidence Systematic Review Team.14

Figure 2.  Literature Search and Screening Flowchart
Literature Search and Screening Flowchart

The literature search yielded 11 547 studies after the removal of duplicate articles. Dual screening resulted in the exclusion of 400 full-text articles or at least 1 reason, which may not reflect all possible reasons. The body of evidence included 153 articles.

Table.  Inclusion and Exclusion Criteria for Relevant Articles That Examined Dietary Patterns and All-Cause Mortalitya
Inclusion and Exclusion Criteria for Relevant Articles That Examined Dietary Patterns and All-Cause Mortalitya
1.
Hu  FB.  Dietary pattern analysis: a new direction in nutritional epidemiology.   Curr Opin Lipidol. 2002;13(1):3-9. doi:10.1097/00041433-200202000-00002 PubMedGoogle ScholarCrossref
2.
US Department of Health & Human Services, National Institutes of Health. 2020-2030 Strategic plan for NIH Nutrition Research. Accessed May 12, 2020. https://www.niddk.nih.gov/about-niddk/strategic-plans-reports/strategic-plan-nih-nutrition-research
3.
US Department of Agriculture, Agricultural Research Service, Dietary Guidelines Advisory Committee. Scientific report of the 2015 Dietary Guidelines Advisory Committee: advisory report to the Secretary of Health and Human Services and the Secretary of Agriculture. Published 2015. Accessed June 25, 2020. https://health.gov/sites/default/files/2019-09/Scientific-Report-of-the-2015-Dietary-Guidelines-Advisory-Committee.pdf
4.
US Department of Agriculture, Center for Nutrition Policy and Promotion, Nutrition Evidence Library, Dietary Patterns Technical Expert Collaborative. A series of systematic reviews on the relationship between dietary patterns and health outcomes. Published 2014. Accessed May 12, 2020. https://nesr.usda.gov/sites/default/files/2019-06/DietaryPatternsReport-FullFinal2.pdf
5.
Schulze  MB, Hoffmann  K.  Methodological approaches to study dietary patterns in relation to risk of coronary heart disease and stroke.   Br J Nutr. 2006;95(5):860-869. doi:10.1079/BJN20061731 PubMedGoogle ScholarCrossref
6.
Schulze  MB, Martínez-González  MA, Fung  TT, Lichtenstein  AH, Forouhi  NG.  Food based dietary patterns and chronic disease prevention.   BMJ. 2018;361:k2396. doi:10.1136/bmj.k2396 PubMedGoogle Scholar
7.
Reedy  J, Wirfält  E, Flood  A,  et al.  Comparing 3 dietary pattern methods—cluster analysis, factor analysis, and index analysis—with colorectal cancer risk: the NIH-AARP Diet and Health Study.   Am J Epidemiol. 2010;171(4):479-487. doi:10.1093/aje/kwp393 PubMedGoogle ScholarCrossref
8.
Edefonti  V, De Vito  R, Dalmartello  M, Patel  L, Salvatori  A, Ferraroni  M.  Reproducibility and validity of a posteriori dietary patterns: a systematic review.   Adv Nutr. 2020;11(2):293-326. doi:10.1093/advances/nmz097PubMedGoogle Scholar
9.
Becerra-Tomás  N, Blanco Mejía  S, Viguiliouk  E,  et al.  Mediterranean diet, cardiovascular disease and mortality in diabetes: a systematic review and meta-analysis of prospective cohort studies and randomized clinical trials.   Crit Rev Food Sci Nutr. 2020;60(7):1207-1227. doi:10.1080/10408398.2019.1565281 PubMedGoogle ScholarCrossref
10.
Eleftheriou  D, Benetou  V, Trichopoulou  A, La Vecchia  C, Bamia  C.  Mediterranean diet and its components in relation to all-cause mortality: meta-analysis.   Br J Nutr. 2018;120(10):1081-1097. doi:10.1017/S0007114518002593 PubMedGoogle ScholarCrossref
11.
Hlaing-Hlaing  H, Pezdirc  K, Tavener  M, James  EL, Hure  A.  Diet quality indices used in Australian and New Zealand adults: a systematic review and critical appraisal.   Nutrients. 2020;12(12):E3777. doi:10.3390/nu12123777 PubMedGoogle Scholar
12.
Soltani  S, Jayedi  A, Shab-Bidar  S, Becerra-Tomás  N, Salas-Salvadó  J.  Adherence to the Mediterranean diet in relation to all-cause mortality: a systematic review and dose-response meta-analysis of prospective cohort studies.   Adv Nutr. 2019;10(6):1029-1039. doi:10.1093/advances/nmz041 PubMedGoogle ScholarCrossref
13.
US Department of Agriculture, Agricultural Research Service, Dietary Guidelines Advisory Committee. Scientific report of the 2020 Dietary Guidelines Advisory Committee: advisory report to the Secretary of Health and Human Services and the Secretary of Agriculture. Accessed January 27, 2020. https://www.dietaryguidelines.gov/sites/default/files/2020-07/ScientificReport_of_the_2020DietaryGuidelinesAdvisoryCommittee_first-print.pdf
14.
US Department of Agriculture. Nutrition Evidence Systematic Review. Systematic review question: what is the relationship between dietary patterns consumed and all-cause mortality? Conclusion statement. Accessed July 27, 2021. https://nesr.usda.gov/2020-dietary-guidelines-advisory-committee-systematic-reviews
15.
Trumbo  P, Schlicker  S, Yates  AA, Poos  M; Food and Nutrition Board of the Institute of Medicine, The National Academies.  Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein and amino acids.   J Am Diet Assoc. 2002;102(11):1621-1630. doi:10.1016/S0002-8223(02)90346-9PubMedGoogle ScholarCrossref
16.
United Nations Development Programme, Human Development Reports. Human Development Index 1990-2017. Accessed January 27, 2020. http://hdr.undp.org/en/data
17.
The World Bank. World Bank country and lending groups. Accessed February 2020. https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-country-and-lending-groups
18.
Estruch  R, Ros  E, Salas-Salvadó  J,  et al; PREDIMED Study Investigators.  Primary prevention of cardiovascular disease with a Mediterranean diet supplemented with extra-virgin olive oil or nuts.   N Engl J Med. 2018;378(25):e34. doi:10.1056/NEJMoa1800389 PubMedGoogle Scholar
19.
Abe  S, Zhang  S, Tomata  Y, Tsuduki  T, Sugawara  Y, Tsuji  I.  Japanese diet and survival time: the Ohsaki cohort 1994 study.   Clin Nutr. 2020;39(1):298-303. doi:10.1016/j.clnu.2019.02.010 PubMedGoogle ScholarCrossref
20.
Akbaraly  TN, Ferrie  JE, Berr  C,  et al.  Alternative Healthy Eating Index and mortality over 18 y of follow-up: results from the Whitehall II cohort.   Am J Clin Nutr. 2011;94(1):247-253. doi:10.3945/ajcn.111.013128 PubMedGoogle ScholarCrossref
21.
Al Rifai  M, Greenland  P, Blaha  MJ,  et al.  Factors of health in the protection against death and cardiovascular disease among adults with subclinical atherosclerosis.   Am Heart J. 2018;198:180-188. doi:10.1016/j.ahj.2017.10.026 PubMedGoogle ScholarCrossref
22.
Atkins  JL, Whincup  PH, Morris  RW, Lennon  LT, Papacosta  O, Wannamethee  SG.  High diet quality is associated with a lower risk of cardiovascular disease and all-cause mortality in older men.   J Nutr. 2014;144(5):673-680. doi:10.3945/jn.113.186486 PubMedGoogle ScholarCrossref
23.
Baden  MY, Liu  G, Satija  A,  et al.  Changes in plant-based diet quality and total and cause-specific mortality.   Circulation. 2019;140(12):979-991. doi:10.1161/CIRCULATIONAHA.119.041014 PubMedGoogle ScholarCrossref
24.
Behrens  G, Fischer  B, Kohler  S, Park  Y, Hollenbeck  AR, Leitzmann  MF.  Healthy lifestyle behaviors and decreased risk of mortality in a large prospective study of U.S. women and men.   Eur J Epidemiol. 2013;28(5):361-372. doi:10.1007/s10654-013-9796-9 PubMedGoogle ScholarCrossref
25.
Bellavia  A, Tektonidis  TG, Orsini  N, Wolk  A, Larsson  SC.  Quantifying the benefits of Mediterranean diet in terms of survival.   Eur J Epidemiol. 2016;31(5):527-530. doi:10.1007/s10654-016-0127-9 PubMedGoogle ScholarCrossref
26.
Biesbroek  S, Verschuren  WMM, Boer  JMA,  et al.  Does a better adherence to dietary guidelines reduce mortality risk and environmental impact in the Dutch sub-cohort of the European Prospective Investigation into Cancer and Nutrition?   Br J Nutr. 2017;118(1):69-80. doi:10.1017/S0007114517001878 PubMedGoogle ScholarCrossref
27.
Bittoni  MA, Wexler  R, Spees  CK, Clinton  SK, Taylor  CA.  Lack of private health insurance is associated with higher mortality from cancer and other chronic diseases, poor diet quality, and inflammatory biomarkers in the United States.   Prev Med. 2015;81:420-426. doi:10.1016/j.ypmed.2015.09.016 PubMedGoogle ScholarCrossref
28.
Bo  S, Ponzo  V, Goitre  I,  et al.  Predictive role of the Mediterranean diet on mortality in individuals at low cardiovascular risk: a 12-year follow-up population-based cohort study.   J Transl Med. 2016;14:91. doi:10.1186/s12967-016-0851-7 PubMedGoogle ScholarCrossref
29.
Boggs  DA, Ban  Y, Palmer  JR, Rosenberg  L.  Higher diet quality is inversely associated with mortality in African-American women.   J Nutr. 2015;145(3):547-554. doi:10.3945/jn.114.195735 PubMedGoogle ScholarCrossref
30.
Bonaccio  M, Di Castelnuovo  A, Costanzo  S,  et al.  Mediterranean diet and mortality in the elderly: a prospective cohort study and a meta-analysis.   Br J Nutr. 2018;120(8):841-854. doi:10.1017/S0007114518002179 PubMedGoogle ScholarCrossref
31.
Bongard  V, Arveiler  D, Dallongeville  J,  et al.  Food groups associated with a reduced risk of 15-year all-cause death.   Eur J Clin Nutr. 2016;70(6):715-722. doi:10.1038/ejcn.2016.19 PubMedGoogle ScholarCrossref
32.
Booth  JN  III, Colantonio  LD, Howard  G,  et al.  Healthy lifestyle factors and incident heart disease and mortality in candidates for primary prevention with statin therapy.   Int J Cardiol. 2016;207:196-202. doi:10.1016/j.ijcard.2016.01.001 PubMedGoogle ScholarCrossref
33.
Brown  JC, Harhay  MO, Harhay  MN.  Physical activity, diet quality, and mortality among community-dwelling prefrail and frail older adults.   J Nutr Gerontol Geriatr. 2016;35(4):253-266. doi:10.1080/21551197.2016.1247022 PubMedGoogle ScholarCrossref
34.
Buckland  G, Agudo  A, Travier  N,  et al.  Adherence to the Mediterranean diet reduces mortality in the Spanish cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC-Spain).   Br J Nutr. 2011;106(10):1581-1591. doi:10.1017/S0007114511002078 PubMedGoogle ScholarCrossref
35.
Cárdenas-Fuentes  G, Subirana  I, Martinez-Gonzalez  MA,  et al.  Multiple approaches to associations of physical activity and adherence to the Mediterranean diet with all-cause mortality in older adults: the Prevención con Dieta Mediterránea study.   Eur J Nutr. 2019;58(4):1569-1578. doi:10.1007/s00394-018-1689-y PubMedGoogle ScholarCrossref
36.
Chan  RSM, Yu  BWM, Leung  J,  et al.  How dietary patterns are related to inflammaging and mortality in community-dwelling older Chinese adults in Hong Kong - a prospective analysis.   J Nutr Health Aging. 2019;23(2):181-194. doi:10.1007/s12603-018-1143-0 PubMedGoogle ScholarCrossref
37.
Cheng  E, Um  CY, Prizment  A, Lazovich  D, Bostick  RM.  Associations of evolutionary-concordance diet, Mediterranean diet and evolutionary-concordance lifestyle pattern scores with all-cause and cause-specific mortality.   Br J Nutr. 2018;1-10. doi:10.1017/S0007114518003483 PubMedGoogle Scholar
38.
Chrysohoou  C, Pitsavos  C, Lazaros  G, Skoumas  J, Tousoulis  D, Stefanadis  C; Ikaria Study Investigators.  Determinants of all-cause mortality and incidence of cardiovascular disease (2009 to 2013) in older adults: the Ikaria Study of the Blue Zones.   Angiology. 2016;67(6):541-548. doi:10.1177/0003319715603185 PubMedGoogle ScholarCrossref
39.
Cuenca-García  M, Artero  EG, Sui  X, Lee  DC, Hebert  JR, Blair  SN.  Dietary indices, cardiovascular risk factors and mortality in middle-aged adults: findings from the Aerobics Center Longitudinal Study.   Ann Epidemiol. 2014;24(4):297-303.e2. doi:10.1016/j.annepidem.2014.01.007 PubMedGoogle ScholarCrossref
40.
Dai  J, Krasnow  RE, Reed  T.  Midlife moderation-quantified healthy diet and 40-year mortality risk from CHD: the prospective National Heart, Lung, and Blood Institute Twin Study.   Br J Nutr. 2016;116(2):326-334. doi:10.1017/S0007114516001914 PubMedGoogle ScholarCrossref
41.
Drake  I, Gullberg  B, Sonestedt  E,  et al.  Scoring models of a diet quality index and the predictive capability of mortality in a population-based cohort of Swedish men and women.   Public Health Nutr. 2013;16(3):468-478. doi:10.1017/S1368980012002789 PubMedGoogle ScholarCrossref
42.
Ford  DW, Hartman  TJ, Still  C,  et al.  Body mass index, poor diet quality, and health-related quality of life are associated with mortality in rural older adults.   J Nutr Gerontol Geriatr. 2014;33(1):23-34. doi:10.1080/21551197.2014.875819 PubMedGoogle ScholarCrossref
43.
Ford  ES, Bergmann  MM, Boeing  H, Li  C, Capewell  S.  Healthy lifestyle behaviors and all-cause mortality among adults in the United States.   Prev Med. 2012;55(1):23-27. doi:10.1016/j.ypmed.2012.04.016 PubMedGoogle ScholarCrossref
44.
Ford  ES, Zhao  G, Tsai  J, Li  C.  Low-risk lifestyle behaviors and all-cause mortality: findings from the National Health and Nutrition Examination Survey III Mortality Study.   Am J Public Health. 2011;101(10):1922-1929. doi:10.2105/AJPH.2011.300167 PubMedGoogle ScholarCrossref
45.
Fresán  U, Sabaté  J, Martínez-Gonzalez  MA, Segovia-Siapco  G, de la Fuente-Arrillaga  C, Bes-Rastrollo  M.  Adherence to the 2015 Dietary Guidelines for Americans and mortality risk in a Mediterranean cohort: the SUN project.   Prev Med. 2019;118:317-324. doi:10.1016/j.ypmed.2018.11.015 PubMedGoogle ScholarCrossref
46.
George  SM, Ballard-Barbash  R, Manson  JE,  et al.  Comparing indices of diet quality with chronic disease mortality risk in postmenopausal women in the Women’s Health Initiative Observational Study: evidence to inform national dietary guidance.   Am J Epidemiol. 2014;180(6):616-625. doi:10.1093/aje/kwu173 PubMedGoogle ScholarCrossref
47.
Harmon  BE, Boushey  CJ, Shvetsov  YB,  et al.  Associations of key diet-quality indexes with mortality in the multiethnic cohort: the Dietary Patterns Methods Project.   Am J Clin Nutr. 2015;101(3):587-597. doi:10.3945/ajcn.114.090688 PubMedGoogle ScholarCrossref
48.
Hashemian  M, Farvid  MS, Poustchi  H,  et al.  The application of six dietary scores to a Middle Eastern population: a comparative analysis of mortality in a prospective study.   Eur J Epidemiol. 2019;34(4):371-382. doi:10.1007/s10654-019-00508-3 PubMedGoogle ScholarCrossref
49.
Haveman-Nies  A, de Groot  L, Burema  J, Cruz  JA, Osler  M, van Staveren  WA; SENECA Investigators.  Dietary quality and lifestyle factors in relation to 10-year mortality in older Europeans: the SENECA study.   Am J Epidemiol. 2002;156(10):962-968. doi:10.1093/aje/kwf144 PubMedGoogle ScholarCrossref
50.
Hodge  AM, Bassett  JK, Dugué  PA,  et al.  Dietary inflammatory index or Mediterranean diet score as risk factors for total and cardiovascular mortality.   Nutr Metab Cardiovasc Dis. 2018;28(5):461-469. doi:10.1016/j.numecd.2018.01.010 PubMedGoogle ScholarCrossref
51.
Hodge  AM, English  DR, Itsiopoulos  C, O’Dea  K, Giles  GG.  Does a Mediterranean diet reduce the mortality risk associated with diabetes: evidence from the Melbourne collaborative cohort study.   Nutr Metab Cardiovasc Dis. 2011;21(9):733-739. doi:10.1016/j.numecd.2010.10.014 PubMedGoogle ScholarCrossref
52.
Hu  EA, Steffen  LM, Coresh  J, Appel  LJ, Rebholz  CM.  Adherence to the Healthy Eating Index-2015 and other dietary patterns may reduce risk of cardiovascular disease, cardiovascular mortality, and all-cause mortality.   J Nutr. 2020;150(2):312-321. doi:10.1093/jn/nxz218 PubMedGoogle ScholarCrossref
53.
Hulsegge  G, Looman  M, Smit  HA, Daviglus  ML, van der Schouw  YT, Verschuren  WM.  Lifestyle changes in young adulthood and middle age and risk of cardiovascular disease and all-cause mortality: the Doetinchem cohort study.   J Am Heart Assoc. 2016;5(1):e002432. doi:10.1161/JAHA.115.002432 PubMedGoogle Scholar
54.
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55.
Kaluza  J, Håkansson  N, Harris  HR, Orsini  N, Michaëlsson  K, Wolk  A.  Influence of anti-inflammatory diet and smoking on mortality and survival in men and women: two prospective cohort studies.   J Intern Med. 2019;285(1):75-91. doi:10.1111/joim.12823 PubMedGoogle ScholarCrossref
56.
Kant  AK, Graubard  BI, Schatzkin  A.  Dietary patterns predict mortality in a national cohort: the National Health Interview Surveys, 1987 and 1992.   J Nutr. 2004;134(7):1793-1799. doi:10.1093/jn/134.7.1793 PubMedGoogle ScholarCrossref
57.
Kant  AK, Leitzmann  MF, Park  Y, Hollenbeck  A, Schatzkin  A.  Patterns of recommended dietary behaviors predict subsequent risk of mortality in a large cohort of men and women in the United States.   J Nutr. 2009;139(7):1374-1380. doi:10.3945/jn.109.104505 PubMedGoogle ScholarCrossref
58.
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59.
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60.
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62.
Kim  JY, Ko  YJ, Rhee  CW,  et al.  Cardiovascular health metrics and all-cause and cardiovascular disease mortality among middle-aged men in Korea: the Seoul male cohort study.   J Prev Med Public Health. 2013;46(6):319-328. doi:10.3961/jpmph.2013.46.6.319 PubMedGoogle ScholarCrossref
63.
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64.
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65.
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71.
Limongi  F, Noale  M, Gesmundo  A, Crepaldi  G, Maggi  S.  Adherence to the Mediterranean diet and all-cause mortality risk in an elderly Italian population: data from the ILSA Study.   J Nutr Health Aging. 2017;21(5):505-513. doi:10.1007/s12603-016-0808-9 PubMedGoogle ScholarCrossref
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74.
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75.
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78.
McCullough  ML, Patel  AV, Kushi  LH,  et al.  Following cancer prevention guidelines reduces risk of cancer, cardiovascular disease, and all-cause mortality.   Cancer Epidemiol Biomarkers Prev. 2011;20(6):1089-1097. doi:10.1158/1055-9965.EPI-10-1173 PubMedGoogle ScholarCrossref
79.
McNaughton  SA, Bates  CJ, Mishra  GD.  Diet quality is associated with all-cause mortality in adults aged 65 years and older.   J Nutr. 2012;142(2):320-325. doi:10.3945/jn.111.148692 PubMedGoogle ScholarCrossref
80.
Menotti  A, Alberti-Fidanza  A, Fidanza  F, Lanti  M, Fruttini  D.  Factor analysis in the identification of dietary patterns and their predictive role in morbid and fatal events.   Public Health Nutr. 2012;15(7):1232-1239. doi:10.1017/S1368980011003235 PubMedGoogle ScholarCrossref
81.
Menotti  A, Kromhout  D, Puddu  PE,  et al.  Baseline fatty acids, food groups, a diet score and 50-year all-cause mortality rates: an ecological analysis of the Seven Countries Study.   Ann Med. 2017;49(8):718-727. doi:10.1080/07853890.2017.1372622 PubMedGoogle ScholarCrossref
82.
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    1 Comment for this article
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    Ultra-processed dietary patterns and all-cause mortality
    Carlos Monteiro, MD | University of Sao Paulo
    Based on a systematic review done to inform the Dietary Guidelines for Americans (DGA) 2020-2025, English et al conclude that: ‘Dietary patterns associated with lower all-cause mortality risk were consistently characterized by higher intake of vegetables; legumes; fruits; nuts; either whole grains, cereals, or nonrefined grains; fish; and unsaturated vegetable oils … [and] by lower or no consumption of animal products (red and processed meat, meat and meat products, and high-fat dairy products), refined grains, and sweets (ie, higher in added sugars) … highlighting that high-quality diets with nutrient-dense foods are associated with better health, regardless of diet type or dietary pattern name.’ (1)

    Such patterns are listed as Mediterranean, prudent, Healthy Eating Index, DASH, plant-based, all abundant in varied fresh or minimally processed plant foods and with few ultra-processed foods. So another conclusion should be: Dietary patterns based on a variety of fresh or minimally processed foods, mostly plants, with few if any ultra-processed foods, are associated with better health (2).

    Their nutrient profile is no doubt a reason why these patterns are associated with lower mortality. But there are other reasons. As examples, positively there is the synergism between nutrients with other health-protective constituents in the intact food matrices of fresh and minimally processed foods (3). Negatively in ultra-processed foods, are xenobiotics neo-formed by high-temperature extrusion; molecules migrated from packaging materials; and additives like emulsifiers, sweeteners and colors. (4).

    English et al included in their review three large cohort studies on ultra-processed dietary patterns and all-cause mortality, all showing significant dose-response associations. These studies are reinforced by many large cohort studies showing similar associations with obesity, hypertension, type 2 diabetes, cardiovascular diseases, stroke, breast and all cancers, and other diseases liable to cause death (5). But ultra-processed dietary patterns were not mentioned in the DGA 2020-2025. The reason stated by English et al. was that ‘These patterns differed by the foods comprising the pattern (eg, some of which included highly palatable foods, such as ice cream and processed meats, and others included artificial flavors and texturizing agents), reducing the generalizability of these patterns and thus the results’.

    This reason is an error, for a number of reasons. One is that dietary patterns, by definition, are made of different foods, as in the Mediterranean diet's various vegetables, fruits, legumes, nuts, and fish, mainly consumed as freshly prepared meals. The ultra-processed dietary pattern contains different ultra-processed foods, such as soft drinks, packaged snacks, reconstituted meat products, pre-prepared dishes and meals, and many other products, often snacked, which together amount now to more than half the energy intake in the USA, including among children (6).

    Good dietary advice, as in recent national dietary guidelines such as issued in Brazil, Israel, and other countries, and supported by the English et al review, is: prefer fresh or minimally processed foods, mostly plants, eaten mostly as freshly prepared meals, and avoid ultra-processed foods.

    References

    1. doi:10.1001/jamanetworkopen.2021.22277

    2. Monteiro, C., Cannon, G., Levy, R., Moubarac, J., Louzada, M., Rauber, F., Jaime, P. (2019). Ultra-processed foods: What they are and how to identify them. Public Health Nutrition,22(5), 936-941. doi:10.1017/S1368980018003762

    3. Barabási, AL., Menichetti, G. & Loscalzo, J. The unmapped chemical complexity of our diet. Nat Food1, 33–37 (2020). https://doi.org/10.1038/s43016-019-0005-1

    4. Filippa Juul, Georgeta Vaidean, Niyati Parekh, Ultra-processed Foods and Cardiovascular Diseases: Potential Mechanisms of Action, Advances in Nutrition, 2021; nmab049, https://doi.org/10.1093/advances/nmab049

    5. Pagliai, G., Dinu, M., Madarena, M. P., Bonaccio, M., Iacoviello, L., & Sofi, F. (2020). Consumption of ultra-processed foods and health status: a systematic review and meta-analysis. British Journal of Nutrition, 1-11. https://doi.org/10.1017/S0007114520002688

    6. Wang L, Martínez Steele E, Du M, et al. Trends in Consumption of Ultraprocessed Foods Among US Youths Aged 2-19 Years, 1999-2018. JAMA. 2021;326(6):519–530. doi:10.1001/jama.2021.10238

    CONFLICT OF INTEREST: None Reported
    READ MORE
    Original Investigation
    Nutrition, Obesity, and Exercise
    August 31, 2021

    Evaluation of Dietary Patterns and All-Cause Mortality: A Systematic Review

    Author Affiliations
    • 1Nutrition Evidence Systematic Review, Office of Nutrition Guidance and Analysis (ONGA), Center for Nutrition Policy and Promotion (CNPP), US Department of Agriculture (USDA) Food and Nutrition Service (FNS), Alexandria, Virginia
    • 2Panum Group, Bethesda, Maryland
    • 3Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston Salem, North Carolina
    • 4Department of Nutrition Science, Purdue University, West Lafayette, Indiana
    • 5Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
    • 6Epidemiology Program, University of Hawai’i Cancer Center, Honolulu
    • 7ONGA, CNPP, USDA FNS, Alexandria, Virginia
    • 8Office of Disease Prevention and Health Promotion, Office of the Assistant Secretary for Health, US Department of Health and Human Services, Washington, DC
    • 9Departments of Nutrition and Medicine, The University of North Carolina at Chapel Hill, Chapel Hill
    • 10Nutritional Sciences, Human Nutrition, Food and Animal Sciences Department, College of Tropical Agriculture and Human Resources, University of Hawai’i at Mānoa, Honolulu
    • 11Center for Nutrition, Healthy Lifestyles, and Disease Prevention, School of Public Health, Loma Linda University, Loma Linda, California
    • 12Epidemiology, College of Public Health, University of Iowa, Iowa City
    • 13Nutrition Division, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
    • 14Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge
    JAMA Netw Open. 2021;4(8):e2122277. doi:10.1001/jamanetworkopen.2021.22277
    Key Points

    Question  What is the association between dietary patterns consumed and all-cause mortality?

    Findings  In this systematic review of 1 randomized clinical trial and 152 observational studies on dietary patterns and all-cause mortality, evidence demonstrated that dietary patterns characterized by increased consumption of vegetables, fruits, legumes, nuts, whole grains, unsaturated vegetable oils, fish, and lean meat or poultry (when meat was included) among adults and older adults were associated with decreased risk of all-cause mortality. These healthy patterns consisted of relatively low intake of red and processed meat, high-fat dairy, and refined carbohydrates or sweets.

    Meaning  This review found that a dietary pattern with nutrient-dense foods was associated with reduced risk of death from all causes.

    Abstract

    Importance  The 2020 Dietary Guidelines Advisory Committee conducted a systematic review of existing research on diet and health to inform the current Dietary Guidelines for Americans. The committee answered this public health question: what is the association between dietary patterns consumed and all-cause mortality (ACM)?

    Objective  To ascertain the association between dietary patterns consumed and ACM.

    Evidence Review  Guided by an analytical framework and predefined inclusion and exclusion criteria developed by the committee, the US Department of Agriculture’s Nutrition Evidence Systematic Review (NESR) team searched PubMed, the Cochrane Central Register of Controlled Trials, and Embase and dual-screened the results to identify articles that were published between January 1, 2000, and October 4, 2019. These studies evaluated dietary patterns and ACM in participants aged 2 years and older. The NESR team extracted data from and assessed risk of bias in included studies. Committee members synthesized the evidence, developed conclusion statements, and graded the strength of the evidence supporting the conclusion statements.

    Findings  A total of 1 randomized clinical trial and 152 observational studies were included in the review. Studies enrolled adults and older adults (aged 17-84 years at baseline) from 28 countries with high or very high Human Development Index; 53 studies originated from the US. Most studies were well designed, used rigorous methods, and had low or moderate risks of bias. Precision, directness, and generalizability were demonstrated across the body of evidence. Results across studies were highly consistent. Evidence suggested that dietary patterns in adults and older adults that involved higher consumption of vegetables, fruits, legumes, nuts, whole grains, unsaturated vegetable oils, fish, and lean meat or poultry (when meat was included) were associated with a decreased risk of ACM. These healthy patterns were also relatively low in red and processed meat, high-fat dairy, and refined carbohydrates or sweets. Some of these dietary patterns also included intake of alcoholic beverages in moderation. Results based on additional analyses with confounding factors generally confirmed the robustness of main findings.

    Conclusions and Relevance  In this systematic review, consuming a nutrient-dense dietary pattern was associated with reduced risk of death from all causes.

    Introduction

    Every 5 years, the US Department of Agriculture and Department of Health and Human Services convene the Dietary Guidelines Advisory Committee to review existing evidence on diet and health to inform the Dietary Guidelines for Americans. Over time, the committee’s focus has shifted away from single nutrients or foods and toward overall dietary patterns. Nutrient and food analyses cannot account for the interactions among or the degree of independent variation of coingested nutrients and food components.1 To advance nutrition research and inform the 2020-2025 Dietary Guidelines for Americans, understanding the role of dietary patterns in optimizing health and reducing the risk of chronic disease across the lifespan is a high priority.2

    Dietary patterns are the quantities, proportions, variety, or combination of different foods, beverages, and nutrients in diets as well as the frequency with which they are habitually consumed.3,4 Different approaches can be used to study dietary patterns. A priori methods are based on scientific consensus or evidence-based approaches and use scores that reflect the degree of adherence.5-7 A posteriori methods identify which factors explain the variation in patterns or aggregate individuals into groups with nonoverlapping patterns.8 Other approaches can include hybrid methods, clinical trials that assign consumption to a specific pattern, and/or observational studies on food avoidance (eg, vegetarian diets).

    The 2015 committee reviewed the associations between dietary patterns and multiple outcomes, including cause-specific mortality from cardiovascular disease (CVD) and dementia.3 Other literature reviews have examined specific diets or foods and cause-specific mortality.9-12 In line with these studies, the 2020 committee,13 with support from the Nutrition Evidence Systematic Review (NESR) team of the US Department of Agriculture, conducted a systematic review of the literature to ascertain the association between dietary patterns consumed and all-cause mortality (ACM).

    Methods

    The systematic review question was, “what is the relationship between dietary patterns consumed and ACM?” It also addressed the topic of diets on the basis of macronutrient distribution. Presented in full detail elsewhere,14 the review used NESR systematic review methods, which are summarized herein. We followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline.

    The committee developed a protocol, including an analytical framework (Figure 1) and inclusion and exclusion criteria (Table). The protocol was made available for public comment and was discussed by the committee in public meetings before evidence synthesis.

    The NESR librarians developed and implemented literature searches in PubMed, the Cochrane Central Register of Controlled Trials, and Embase to identify articles that were published from January 1, 2000, to October 4, 2019.14 These studies evaluated dietary patterns and ACM in participants aged 2 years and older. Two NESR analysts independently screened the search results to identify articles that met the predetermined criteria (Table), and then they manually searched the reference lists of the included articles. The NESR staff extracted data from and completed 2 independent risk-of-bias assessments of each included article.

    The 2020 committee synthesized the evidence qualitatively. The evidence was synthesized not by diet type or label but rather by similarities and differences in the foods and beverages that made up the dietary patterns that were examined. This synthesis approach was taken because the results of this systematic review were intended to inform dietary guidance and to allow for conclusions to be drawn regarding which dietary pattern components were most associated with risk of ACM.

    The results of the systematic review were organized according to a dietary pattern approach (a priori, a posteriori, and other). Based on the synthesized evidence, the committee developed conclusion statements to answer the systematic review question and graded the strength of evidence for the conclusions as follows: strong, moderate, limited, or grade not assignable. Grades were assigned using the NESR’s predefined criteria for grading elements (risks of bias, consistency, directness, precision, and generalizability) and approach, which takes study design into consideration. Future research recommendations for strengthening the body of evidence were based on the gaps and limitations that were identified during the systematic review process.

    Results
    Study Characteristics

    After dual screening, 11 547 relevant studies were identified. The body of evidence included 153 articles (involving 6 550 664 individuals), of which 1 was from a randomized clinical trial (RCT)18 and 152 were from observational studies19-170(Figure 2). Multiple articles used data from the same study but used different methods or represented unique subsamples or dietary patterns. Studies enrolled adults and older adults (aged 17-84 years at baseline) from 28 countries with a high or very high Human Development Index16 classification (Australia, Belgium, Canada, Czech Republic, Croatia, Denmark, Finland, France, Germany, Greece, Hong Kong, Hungary, Iran, Italy, Japan, Korea, Norway, Netherlands, Poland, Portugal, Russia, Serbia, Singapore, Spain, Sweden, Switzerland, United Kingdom, and United States). Fifty-three studies21,23,24,27,29,32,33,37,39,40,42-44,46,47,52,56-61,72-74,78,83,86,94-96,98,100-102,104,107,110,118,125-127,129,135,137,150,158,160,161,163,166 originated from the US. Some studies exclusively enrolled female 29,37,46,58,67,74,82,86,99,124,127,128,135,144,163 or male22,31,40,54,62,80,81,105,106,110,118,130,141,142,147,153 participants.

    The approaches for assessing dietary patterns included an RCT18; a priori methods, such as index or score analysis19-128; a posteriori methods, such as factor or cluster analysis29,36,56,93,109,129-148; and other methods,136,149-158 such as reduced rank regression and comparisons by animal product avoidance or ultraprocessed food consumption. eTable 1 in the Supplement describes the 185 dietary patterns that were examined. The ACM data were collected through validated methods (population-level registries, electronic databases, or medical or historical records) or active follow-up.

    Evidence Synthesis
    A Priori Studies

    In the RCT, participants at high-risk for CVD were randomized to a Mediterranean diet with extra-virgin olive oil or mixed nuts or to a control diet.18 Consumption of either intervention diet was associated with reduced ACM risk after a median follow-up of 4.8 years. Results were similar in subanalyses, which removed participants with protocol deviations and randomization issues. Most included studies of dietary patterns (110 of 153 [72%])19-39 used index or score analysis. Many different measures were reported, including variations of Mediterranean diet (n = 31), DASH (Dietary Approaches to Stop Hypertension) diet scores (n = 1), country-specific indices (n = 16), Healthy Eating Index or Dietary Guidelines for Americans scores (n = 7), and other indices or scales (n = 24) (eTable 1 in the Supplement). A complete description of these components and the scoring procedures has been published elsewhere.14

    Findings were consistent across the studies, despite the variety of indices or scores used (eTable 2 in the Supplement). Nutrient-dense dietary patterns, regardless of pattern label or name, were associated with significantly lower ACM risk. For example, all 12 comparisons that examined DASH diet scores suggested that higher adherence was associated with lower ACM risk,26,46-48,52,69,84,88,98,101,107,127 and 54 of the 63 comparisons that were reported in 44 articles that examined a Mediterranean-type index or score suggested that higher adherence was associated with lower ACM risk.24,25,30,32,34,35,46-53,63,64,68,69,71,76,79,81,83,88,97,98,104,106-108,111-117,122-125,127,128,141

    A few articles reported nonsignificant results with similar patterns.21,31,33,36,39,42,62,93,102,110 Common elements of these dietary indices or scores were (1) relatively higher intake of vegetables (with or without potatoes); legumes; fruit; nuts; either whole grains specifically, cereals unspecified, or nonrefined grains; fish and/or seafood; lean meat or poultry, when included (Dietary Guidelines for Americans or Healthy Eating Index scores reflect total protein foods and/or ratio of white to red meat); and unsaturated fats vs saturated fats; and (2) relatively lower intake of red and processed meat and/or meat and meat products; refined grains; added sugars and/or sugar-sweetened beverages; solid fats, saturated fats, and/or trans fat; and excessive sodium.

    Many of the indices considered alcoholic beverage intake in low to moderate amounts or within a threshold (eg, 10-25 g/d; 0.5-1.5 drinks/d for women and 0.5-2.0 drinks/d for men) as a positive component within the context of the entire dietary pattern. However, measurement and scoring procedures varied between indices.

    The associations reported between a priori–derived dietary patterns and ACM remained in sensitivity or subgroup analyses after combining the dietary patterns with anthropometry, physical activity, and/or smoking status24,35,37,44,53,118; performing stratification or additional adjustment for anthropometry, sex, age, educational level, race/ethnicity, and/or smoking status25,34,37,46,47,52,76,83,85-87,95,96,98,99,104,111,113,115,119,125,126; excluding early deaths or the first few years of follow-up results25,35,49,57,58,63,65,72,76,82,96,99,111-113,119,125,128; accounting for chronic disease status (eg, diabetes or CVD28,30,34,37,51,58,64,65,71,72,80,96,111,125); or underreporting or misreporting chronic disease.28,34,106,112 When adherence to dietary patterns was combined with other healthier lifestyle factors (eg, not smoking and meeting recommended physical activity levels), stronger associations were typically observed. For example, participants who adhered to a Mediterranean diet met recommended physical activity recommendations, were long-term nonsmokers, and had a lower mortality risk (relative risk [RR], 0.65; 95% CI, 0.63-0.68) compared to those that only followed the Mediterranean diet (RR, 0.86; 95% CI, 0.83-0.88).24

    A Posteriori Studies

    Most of the 25 articles (19 [76%]) that examined dietary patterns by using factor or cluster analysis reported significantly lower ACM risk when comparing higher with lower adherence to the same derived pattern29,56,93,130,131,134,135,139-148 or to different patterns109,138 (eTable 2 in the Supplement). For example, participants with higher vs lower adherence to the Prudent pattern had lower mortality risk (Quintile 1: reference; Q2: RR, 0.85 [95% CI, 0.78-0.92; Q3: RR, 0.84 [95% CI, 0.78-0.91]; Q4: RR, 0.81 [95% CI, 0.74-0.88]; Q5: RR, 0.83 [95% CI, 0.76-0.90]; P for trend <.001).135 Participants with higher vs lower adherence to the Western pattern had higher mortality risk (Q1: reference; Q2: RR, 1.00 [95% CI, 0.92-1.08]; Q3: RR, 1.10 [95% CI, 1.02-1.20]; Q4: RR, 1.16 [95% CI, 1.06-1.26]; Q5: RR, 1.21 [95% CI, 1.12-1.32]; P for trend <.001).135 Dietary patterns were given different labels, such as healthy, prudent, and Mediterraneanlike, but were similarly characterized by higher intake of vegetables, fruits, fish or other seafood, legumes and/or whole grains, nuts, vegetable or olive oils, and/or poultry (eg, white meat, such as chicken or turkey140).

    Several articles (5 of 25 [20%]) reported that the dietary patterns associated with significantly higher ACM risk (and/or shorter survival129,130,133,135,148) emphasized the following commonalities: higher intake of (1) meat and meat products such as beef, pork, sausage133; red meat and meat products130; red meat and processed meats135; fresh and processed meats and seafood148; (2) high-fat dairy products such as ice cream, cheese, and whole milk129; and/or (3) refined grains130,135 or flour-based foods such as pastries133 and/or sweets and desserts133,135,148 such as cake, cookies, chocolate, and candy129; as well as lower intake of (4) low-fat dairy products, rice and pasta, fruits, fish and other seafood, and dark green vegetables.129

    Results were similar whether stratified by country,131 after excluding participants with CVD or cancer at baseline,147 or in models that accounted for co-twin pairs.133 Stratification by sex was inconsistent, with no significant associations in women only but significant associations in pooled analyses.138 For example, Krieger et al138 reported lower risk of ACM at mean follow-up of 25 years in overall analyses, with men and women pooled and when comparing fish (hazard ratio [HR], 0.87; 95% CI, 0.78-0.97) and traditional (HR, 0.89; 95% CI, 0.80-0.98) dietary patterns to the sausage and vegetables dietary pattern (reference; HR, 1.0). However, in the Krieger et al138 analyses, which were stratified by sex, the results in women only were not statistically significant: sausage and vegetables pattern (reference; HR, 1.0) was compared with meat and salad (HR, 0.93; 95% CI, 0.80-1.08), fish (HR, 0.98; 95% CI, 0.83-1.15), traditional (HR, 1.02; 95% CI, 0.87-1.19), and high-fiber foods (HR, 0.91; 95% CI, 0.79-1.05) patterns.

    Nonsignificant associations were reported between a posteriori–derived dietary patterns and ACM, although the direction generally aligned with the significant results we have described, and may be attributed to smaller sample sizes,137 the sample evaluated,138 or the gradient between exposure comparisons.135

    Other Studies

    Dietary patterns that were derived from reduced rank regression showed inconsistent results (eTable 2 in the Supplement).136,150,153 Five articles examined the dietary patterns based on avoidance of animal-based products (eg, vegetarian diets).149,151,154,155,158 Vegetarian or plant-based patterns were associated with significantly lower ACM risk in 2 studies,155,158 but no significant associations were found in other exposure groups (eg, vegetarian vs pescovegetarian, and meat eaters vs vegetarian or vegan).149,151,154

    Three studies reported that the dietary pattern of higher vs lower consumption of ultraprocessed foods was associated with higher ACM risk152,156,157 as defined by the fourth level of the NOVA Food Classification System. These patterns differed by the foods comprising the pattern (eg, some of which included highly palatable foods, such as ice cream and processed meats, and others included artificial flavors and texturizing agents), reducing the generalizability of these patterns and thus the results.

    Assessment of Evidence

    Most studies were conducted with rigorous methods and at low or moderate risks of bias across domains.14 Most studies accounted for potential confounders except for race/ethnicity, which was often homogenous or not reported. In addition, most studies assessed dietary intake once and were, therefore, at risk of bias because of potential changes in dietary patterns among participants over time. However, these studies used validated methods, and their results aligned with findings of studies that assessed diet over time. Several studies did not account for missing data, primarily diet or exposure data at baseline. Participants with implausible energy intake, incomplete dietary data, and/or a history or presence of chronic diseases or medical conditions at baseline were typically removed from the studies or analyses.

    Dietary patterns that were examined with different approaches showed consistent direction and magnitude of associations with ACM. Precision was indicated by relatively narrow CIs between studies. Most studies did not report power analyses or sample size calculations but reported analytic sample sizes that were large enough to investigate the association, ranging from 161 participants68 to 451 256 participants.69 Total number of deaths ranged from 53 with approximately 4 years of total follow-up38 to 51 702 with approximately 13 to 18 years of follow-up.69 Although the incident number of deaths differed between studies, the number of events reported within groups confirmed precision across the body of evidence. The evidence base had directness and was generalizable to the US population. Results may be less generalizable to younger or less healthy populations. Results are likely generalizable to adults of various underreported racial/ethnic backgrounds, although it is difficult to ascertain exactly how race and/or ethnicity was involved in the association between dietary patterns and ACM because many studies did not report that information.

    The 2020 committee used multiple databases to obtain publications from a large, comprehensive search. Most of the studies identified had large prospective cohorts, but smaller sample sizes were also included. Therefore, risk of publication bias was low. Details regarding how the NESR accounted for publication bias have been described elsewhere.13 Primary and secondary analyses were included from the PREDIMED (Prevención con Dieta Mediterránea) trial, which reported randomization issues.171 However, PREDIMED investigators republished the data after reanalysis and reconfirmed the initial findings.18

    Discussion

    Despite the different approaches, study designs, dietary assessment methods, geographical regions, and dietary pattern labels, the evidence demonstrated that dietary patterns associated with lower ACM risk were consistently characterized by higher intake of vegetables; legumes; fruits; nuts; either whole grains, cereals, or nonrefined grains; fish; and unsaturated vegetable oils. These patterns were also characterized by lower or no consumption of animal products (red and processed meat, meat and meat products, and high-fat dairy products), refined grains, and sweets (ie, higher in added sugars). Labels that were assigned to the dietary patterns varied widely (eg, Mediterranean, prudent, Healthy Eating Index, DASH, and plant-based), highlighting that high-quality diets with nutrient-dense foods are associated with better health, regardless of diet type or dietary pattern name. Although we believe this systematic review is the most comprehensive examination of US dietary patterns and ACM that is currently available, its findings align with the results of previous meta-analyses that focused on select diet types and/or cause-specific mortality.9-12,172

    This systematic review included the most suitable study designs available to answer the question. Given the nature of the outcome (ACM), expense, duration, and power necessary for an experimental study design to explore this question, it is unlikely that many RCTs or non-RCTs would be available (funded, conducted, or published) for consideration. Studies that were included for this review were well designed and conducted using rigorous methods. Despite the preponderance of evidence from observational studies, this review presented a conclusion statement that was assigned a grade of strong, which was in accordance with studies at generally low or moderate risks of bias and with high consistency in direction and magnitude of findings, precision, directness, and generalizability. The methods used for grading the evidence underlying this conclusion statement align with other grading approaches173-175 and ensure that strengths and weaknesses in study design as well as each grading element were considered.176

    The findings of this review are further supported by a central tenet behind other works of the 2020 committee: a nutrient-dense dietary pattern can minimize the risk of multiple diet-related chronic diseases, such as CVD, obesity, diabetes, and some cancers, and can support bone and neurocognitive health.176,177 For women who are pregnant, a similar healthful dietary pattern has been associated with lower risk of poor maternal-fetal outcomes.178 Achieving a healthy dietary pattern at each life stage should also support health in subsequent life stages. The core elements of these dietary patterns across the committee’s reviews reflect higher diet quality, are appropriate to consume across the lifespan, and have the potential to substantially minimize chronic disease risk and mortality risk.

    Studies in this review suggested that dietary patterns containing nutrient-dense foods and alcoholic beverages that were within a given threshold or at low to moderate levels were associated with lower risk of ACM. However, the preponderance of this evidence varied in the methodological assessment of alcohol intake and scoring procedures within the context of the dietary patterns that were assessed. The committee conducted a separate systematic review179 to answer the question, what is the association between alcoholic beverages and ACM? Briefly, the focused analysis on alcoholic beverage consumption suggested that alcohol may increase ACM risk, but only minimally at low levels of intake. The committee concluded that moderating alcohol consumption to lower levels is recommended to better protect health. Other recommendations that were incorporated into the Dietary Guidelines for Americans, 2020-2025 were for individuals to not start drinking, avoid heavy drinking, and proceed with caution regarding alcoholic beverage consumption because it can contribute to increased rates of liver disease180 and excess energy intake, which is not advisable.

    Dietary patterns provide a meaningful and interpretable database on foods and food groups. This review found that multiple food choices can be made toward a healthy diet that promotes beneficial outcomes. Dietary pattern approaches are advantageous because they place an emphasis on the combination of foods and beverages that meet total energy needs and are associated with health, instead of the selection of specific nutrients or foods alone, which may be more difficult for consumers to translate into a total diet. We believe such an approach provides flexibility, allowing consumers the freedom to tailor food and food group combinations that were identified as healthful to their preferences (eg, cultural acceptability and taste) and needs (eg, cost).

    Limitations

    This study has several limitations. Observing study participants over time provides valuable insights regarding risk for mortality, although many included studies examined diet at only 1 time point (ie, baseline), which may or may not reflect usual dietary patterns. Most of the available evidence on dietary patterns was derived from studies that were conducted in adults. Data on dietary patterns earlier in the life course and ACM were unavailable. However, this lack of data was likely associated with the challenge and expense of undertaking long-term RCTs and/or studies with repeated measures over time, particularly starting in childhood, that examine mortality as an outcome. As a result, longitudinal data, particularly information on dietary patterns from childhood and continuing throughout the life course, are still greatly needed. Further exploration is also needed on the factors that modify or mediate the association between dietary patterns and ACM as well as the role that selected food groups, such as meat, plays in this association. In addition, the available evidence does not identify the inadequate or excessive intake or quantify the types and amounts of foods and food groups consumed in the context of dietary patterns.

    Active ongoing cohorts informed most of the findings reported herein, which showed consistency across the US and more than 20 other middle- to high-income countries. Results indicated good external validity, but future work is needed within population subgroups that could not be analyzed in this review because of the lack of reported details on individuals from racial/ethnic minority groups. The available evidence was not sufficient to assess how race/ethnicity affects the association between dietary patterns and ACM. In addition, this systematic review was conducted to identify the nature and direction of the association between dietary patterns and ACM, with an intention to consider dietary patterns regardless of label, name, or type. Because of this comprehensive approach, the methodological heterogeneity of the dietary patterns included in this review was best suited for qualitative synthesis of quantitative data. However, in the future, it may be worth exploring whether and how the magnitude of these findings could be quantified through a meta-analysis.

    Conclusions

    Evidence from this systematic review by the 2020 Dietary Guidelines Advisory Committee demonstrated that nutrient-dense dietary patterns, which were characterized by higher intake of vegetables, fruits, legumes, nuts, whole grains, unsaturated vegetable oils, fish, and lean meat or poultry, when included, were associated with decreased ACM risk in broadly generalizable populations of adults and older adults. These dietary patterns included relatively lower intake of red and processed meat, high-fat dairy, and refined carbohydrates or sweets. Some of these dietary patterns also included moderate intake of alcoholic beverages. Results based on additional analyses with confounding factors generally confirmed the robustness of the main findings.

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    Article Information

    Accepted for Publication: June 2, 2021.

    Published: August 31, 2021. doi:10.1001/jamanetworkopen.2021.22277

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 English LK et al. JAMA Network Open.

    Corresponding Author: Steven B. Heymsfield, MD, Pennington Biomedical Research Center, Louisiana State University System, 6400 Perkins Rd, Baton Rouge, LA 70808 (Steven.Heymsfield@pbrc.edu).

    Author Contributions: Dr Heymsfield had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: English, Bates, Boushey, Callahan, de Jesus, Novotny, Obbagy, Rahavi, Stoody, Van Horn, Heymsfield.

    Acquisition, analysis, or interpretation of data: English, Ard, Bailey, Bates, Bazzano, Boushey, Brown, Butera, Callahan, Mattes, Mayer-Davis, Obbagy, Sabate, Snetselaar, Van Horn, Venkatramanan, Heymsfield.

    Drafting of the manuscript: English, Boushey, Callahan, Mattes, Obbagy, Heymsfield.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Heymsfield.

    Administrative, technical, or material support: English, Bailey, Bates, Boushey, Brown, Callahan, de Jesus, Novotny, Obbagy, Rahavi, Snetselaar, Van Horn, Venkatramanan.

    Supervision: Obbagy, Rahavi, Sabate, Snetselaar, Stoody.

    Other - Creating the search strategy for the systematic review: Butera.

    Other - Served as chair of the committee: Boushey.

    Conflict of Interest Disclosures: Dr Ard reported receiving personal fees from Nestlé Healthcare Nutrition outside the submitted work. Dr Bailey reported serving as a former consultant to the National Institutes of Health (NIH) Office of Dietary Supplements, Nestlé/Gerber, General Mills Bell Institute, RTI International, and Nutrition Impact; serving as a trustee for the International Food Information Council; and receiving travel support in the past to present her research on dietary supplements outside the submitted work. Dr Sabate reported receiving grants that were paid to Loma Linda University from Hass Avocado Board outside the submitted work. Dr Heymsfield reported receiving personal fees from Medifast Corporation Medical Advisory Board outside the submitted work. No other disclosures were reported.

    Funding/Support: This study was supported by the USDA Food and Nutrition Service, Center for Nutrition Policy and Promotion.

    Role of the Funder/Sponsor: Scientists who are employed by the funder had a role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    Meeting Presentation: The abstract of this study was presented at the virtual meeting of Nutrition 2021; June 7-10, 2021.

    Additional Contributions: We thank Nancy Terry, MLS, NIH, who provided peer review of the literature search strategy. We also thank the peer reviewers of this systematic review for the Scientific Report of the 2020 Dietary Guidelines Advisory Committee.

    Additional Information: Panum Group employees worked under contract with the USDA Food and Nutrition Service.

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