CoChat
Sign Up
Cited by 601Nutritional Studies and DietNutrition, Health, and Society StudiesAgriculture Sustainability and Environmental Impact

Food groups and risk of all-cause mortality: a systematic review and meta-analysis of prospective studies ,

Open access
Schwingshackl, Lukas, Schwedhelm, Carolina, Hoffmann, Georg, Lampousi, Anna-Maria, Knüppel, Sven, Iqbal, Khalid, Bechthold, Angela, Schlesinger, Sabrina +1 more·2017·The American Journal of Clinical Nutrition
DOI 10.3945/ajcn.117.153148
Open this paper in CoChat — free accountOpen PDF

Abstract

Background: Suboptimal diet is one of the most important factors in preventing early death and disability worldwide.Objective: The aim of this meta-analysis was to synthesize the knowledge about the relation between intake of 12 major food groups, including whole grains, refined grains, vegetables, fruits, nuts, legumes, eggs, dairy, fish, red meat, processed meat, and sugar-sweetened beverages, with risk of all-cause mortality.Design: We conducted a systematic search in PubMed, Embase, and Google Scholar for prospective studies investigating the association between these 12 food groups and risk of all-cause mortality. Summary RRs and 95% CIs were estimated with the use of a random effects model for high-intake compared with low-intake categories, as well as for linear and nonlinear relations. Moreover, the risk reduction potential of foods was calculated by multiplying the RR by optimal intake values (serving category with the strongest association) for risk-reducing foods or risk-increasing foods, respectively.Results: With increasing intake (for each daily serving) of whole grains (RR: 0.92; 95% CI: 0.89, 0.95), vegetables (RR: 0.96; 95% CI: 0.95, 0.98), fruits (RR: 0.94; 95% CI: 0.92, 0.97), nuts (RR: 0.76; 95% CI: 0.69, 0.84), and fish (RR: 0.93; 95% CI: 0.88, 0.98), the risk of all-cause mortality decreased; higher intake of red meat (RR: 1.10; 95% CI: 1.04, 1.18) and processed meat (RR: 1.23; 95% CI: 1.12, 1.36) was associated with an increased risk of all-cause mortality in a linear dose-response meta-analysis. A clear indication of nonlinearity was seen for the relations between vegetables, fruits, nuts, and dairy and all-cause mortality. Optimal consumption of risk-decreasing foods results in a 56% reduction of all-cause mortality, whereas consumption of risk-increasing foods is associated with a 2-fold increased risk of all-cause mortality.Conclusion: Selecting specific optimal intakes of the investigated food groups can lead to a considerable change in the risk of premature death.

Integrity signals

Registry

Crossref · 10.3945/ajcn.117.153148

Cites

141 of 141 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 23 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    There is no evidence of a nonlinear dose-response relation between refined grains and all-cause mortality (P-nonlinearity = 0.11).

    “Furthermore, no evidence of a nonlinear doseresponse association was found (P-nonlinearity = 0.11; n = 3 studies)”
    Quote in the paperNot a substantial claim
  • Findingown data

    Legume intake up to about 150 g/day is associated with about 16% lower all-cause mortality risk.

    “The risk of all-cause mortality decreased by w16% with increasing intake of legumes up to w150 g/d”
    Quote in the paperSubstantial claim
  • Findingown data

    Legume intake in the highest versus lowest category is associated with lower all-cause mortality (RR 0.96; 95% CI 0.93, 1.00).

    “An inverse association was observed for the highest compared with lowest legume intake categories (RR: 0.96; 95% CI: 0.93, 1.00;I 2 = 48%; P-heterogeneity = 0.01)”
    Quote in the paperSubstantial claim
  • Findingown data

    Nut intake in the highest versus lowest category is associated with lower all-cause mortality (RR 0.80; 95% CI 0.74, 0.86).

    “A strong inverse association was observed for the highest compared with the lowest nut intake category (RR: 0.80; 95% CI: 0.74, 0.86; I 2 = 84%; P-heterogeneity , 0.001)”
    Quote in the paperSubstantial claim
  • Findingown data

    Vegetable intake in the highest versus lowest category is associated with lower all-cause mortality (RR 0.93; 95% CI 0.90, 0.95).

    “An inverse association was observed for the high intake compared with the low intake (RR: 0.93; 95% CI: 0.90, 0.95; I 2 = 75%; P-heterogeneity , 0.001)”
    Quote in the paperSubstantial claim
  • May combine two claims. 21
  • Classified as probably not a substantial claim. 14

  • May combine two claims.

    Findingown data

    The nut dose-response relation is nonlinear, with mortality risk decreasing by about 17% up to about 15-20 g/day and no further benefit above that intake.

    “Evidence exists of a nonlinear dose-response association (P-nonlinearity , 0.001; n = 13 studies).The risk of all-cause mortality decreased by w17% with increasing intake of nuts up to w15-20 g/d.No benefit was apparent when increasing intake above this value”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The fruit dose-response relation is nonlinear, with mortality risk decreasing by about 10% up to about 250-300 g/day and no further benefit above that intake.

    “Evidence exists of a nonlinear doseresponse association (P-nonlinearity , 0.001; n = 13 studies).The risk of all-cause mortality decreased by w10%, with increasing intake of fruit up to w250-300 g/d.No benefit was apparent when increasing intake above this value”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The egg dose-response relation is nonlinear, with mortality risk increasing by about 10% up to about 60 g/day.

    “We found evidence of a nonlinear dose-response association (P-nonlinearity , 0.001; n = 3 studies).The risk of all-cause mortality increased by w10% with increasing intake of eggs up to w60 g/d”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The whole-grain dose-response relation is nonlinear, with mortality risk decreasing by 25% as intake increases up to about 100 g/day.

    “Although the test for nonlinearity was significant (P-nonlinearity , 0.01; n = 10 studies), a clear dose-response relation was observed.The risk of mortality decreased by 25% with increasing intake of whole grains up to w100 g/d”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The vegetable dose-response relation is nonlinear, with mortality risk decreasing by 11% up to about 300 g/day and no further benefit above that intake.

    “Evidence exists of a nonlinear dose-response association (P-nonlinearity , 0.001; n = 14 studies).The risk of mortality decreased by 11% with increasing intake of vegetables up to w300 g/d.No benefit was apparent when increasing intake above this value”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Processed meat intake (30 g/d) is positively associated with all-cause mortality, with risk ratios increasing from 1.12 to 1.35 across 1 to 4 servings/day.

    “| Processed meat (30 g/d) | 1.00 1.12 (1.10, 1.14) 1.20 (1.17, 1.23) 1.28 (1.23, 1.32) 1.35 (1.28, 1.41) | NA | NA | | | | |”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Food frequency questionnaire data are sufficiently valid to rank individuals by usual dietary intake for the purpose of this meta-analysis.

  • May combine two claims.

    Findingown data

    The processed-meat dose-response relation is nonlinear but shows a clear pattern, with mortality risk increasing by about 60% up to about 200 g/day.

    “Although the test for nonlinearity was significant (P-nonlinearity = 0.02; n = 7 studies), a clear dose-response relation was observed.The risk of all-cause mortality increased by w60% with increasing intake of processed meat up to w200 g/d”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Vegetable intake (80 g/d) is inversely associated with all-cause mortality, with risk ratios decreasing to 0.89 at 3 or more servings/day.

    “| Vegetables (80 g/d) | 1.00 0.94 (0.93, 0.96) 0.91 (0.89, 0.93) 0.89 (0.87, 0.92) 0.89 (0.87, 0.91) 0.89 (0.87, 0.91) 0.89 (0.86, 0.92) | | | | | | |”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Food frequency questionnaire data are sufficiently valid to rank individuals by usual dietary intake for the purpose of this meta-analysis.

  • May combine two claims.

    Findingown data

    Fish intake (100 g/d) is inversely associated with all-cause mortality, with risk ratios of 0.93 at 1 serving/day and 0.90 at 2 servings/day.

    “| Fish (100 g/d) | 1.00 0.93 (0.90, 0.96) 0.90 (0.84, 0.96) | NA | NA | NA | NA | | |”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Food frequency questionnaire data are sufficiently valid to rank individuals by usual dietary intake for the purpose of this meta-analysis.

  • May combine two claims.

    Findingown data

    Red meat intake (85 g/d) is positively associated with all-cause mortality, with risk ratios of 1.16 at 1 serving/day and 1.35 at 2 servings/day.

    “| Red meat (85 g/d) | 1.00 1.16 (1.14, 1.18) 1.35 (1.32, 1.38) | NA | NA | NA | NA | | |”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Food frequency questionnaire data are sufficiently valid to rank individuals by usual dietary intake for the purpose of this meta-analysis.

  • May combine two claims.

    Findingown data

    The dairy dose-response relation is nonlinear: no detrimental effect is observed up to about 750 g/day, while intakes of at least 1000 g/day are associated with 15% higher mortality risk.

    “Evidence of a nonlinear doseresponse association was seen between dairy products and allcause mortality (P-nonlinearity = 0.01; n = 12 studies).No detrimental effects were observed up to an intake of w750 g/d, whereas intakes of #1000 g/d were associated with a 15% increased risk of mortality”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Whole grain intake (30 g/d) is inversely associated with all-cause mortality in a nonlinear dose-response manner, with risk ratios of 0.91, 0.84, and 0.79 at 1, 2, and 3 servings/day compared with 0 servings/day.

    “| Whole grains (30 g/d) | 1.00 0.91 (0.89, 0.92) 0.84 (0.82, 0.86) 0.79 (0.76, 0.83) | NA | NA | NA | | | |”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Food frequency questionnaire data are sufficiently valid to rank individuals by usual dietary intake for the purpose of this meta-analysis.

  • May combine two claims.

    Findingown data

    Nine of the 12 food groups showed an association with all-cause mortality in categorical or continuous dose-response analyses: inverse for whole grains, vegetables, fruits, nuts, legumes, and fish, and positive for red meat, processed meat, eggs, and sugar-sweetened beverages.

    “Nine of the 12 food groups showed an association with all-cause mortality in the categorical or continuous dose-response analyses; an inverse association was present for whole grain, vegetable, fruit, nut, legume, and fish consumption, whereas a positive association was present for red meat, processed meat, egg, and SSB consumption.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Legume intake (100 g/d) is inversely associated with all-cause mortality, with a risk ratio of 0.90 at 1 serving/day.

    “| Legumes (100 g/d) | 1.00 0.90 (0.85, 0.96) | NA | NA | NA | NA | NA | |”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Food frequency questionnaire data are sufficiently valid to rank individuals by usual dietary intake for the purpose of this meta-analysis.

  • May combine two claims.

    Findingown data

    Refined grain intake (30 g/d) is not associated with all-cause mortality, with risk ratios not significantly different from 1.00 across servings.

    “| Refined grains (30 g/d) | 1.00 0.96 (0.92, 1.01) 0.96 (0.90, 1.02) 0.97 (0.91, 1.05) 1.00 (0.92, 1.08) 1.03 (0.92, 1.16) | NA | | | | | |”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Food frequency questionnaire data are sufficiently valid to rank individuals by usual dietary intake for the purpose of this meta-analysis.

  • May combine two claims.

    Findingown data

    Dairy intake (200 g/d) shows an inverse association at low intakes and a positive association at high intakes, with risk ratios of 0.97 at 1 serving/day and 1.16 at 5 servings/day.

    “| Dairy (200 g/d) | 1.00 0.97 (0.95, 0.99) 0.99 (0.97, 1.01) 1.04 (1.01, 1.07) 1.11 (1.05, 1.17) 1.16 (1.08, 1.23) | NA | | | | | |”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Food frequency questionnaire data are sufficiently valid to rank individuals by usual dietary intake for the purpose of this meta-analysis.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Previous meta-analyses found that red and processed meats were associated with increased all-cause mortality.

    “whereas red and processed meats were associated with an increased risk (8).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [8] Wang, 2016, Red and processed meat consumption and mortality: dose-response meta-analysis of prospective cohort studies, Public Health Nutr source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    The systematic review was planned and conducted according to MOOSE standards.

    “This systematic review was planned and conducted according to the standards of the Meta-analysis of Observational Studies in Epidemiology (11).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [11] Stroup, 2000, Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of Observational Studies in Epidemiology (MOOSE) group, JAMA source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    Publication bias and small-study effects were explored with the Egger test and funnel plots when at least 10 studies were available.

    “Potential small-study effects such as publication bias were explored using the Egger test and funnel plots (21) if $10 studies were available, as recommended by the Cochrane Handbook (22).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [21] Egger, 1997, Bias in meta-analysis detected by a simple, graphical test, BMJ source

      Not checked in the free run.

    • cites [22] Higgins JPT, Green S, editors. Cochrane handbook for systematic reviews of interventions version 5.1.0. London: The Cochrane Collaboration; 2011 [updated 2011 Mar]. Available from:. http://www.handbook.cochrane.org.

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Previous meta-analyses found that whole grains, fruits and vegetables, nuts, and fish were associated with lower all-cause mortality.

    “Previous meta-analyses showed that whole grains, fruits and vegetables, nuts, and fish were associated with a lower risk of allcause mortality (4-7)”
    Quote in the paperSubstantial claim0 of 4 sources checked
    • cites [4] Wang, 2014, Fruit and vegetable consumption and mortality from all causes, cardiovascular disease, and cancer: systematic review and dose-response meta-analysis of prospective cohort studies, BMJ source

      Not checked in the free run.

    • cites [5] Aune, 2016, Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality: systematic review and dose-response meta-analysis of prospective studies, BMJ source

      Not checked in the free run.

    • cites [6] Mayhew, 2016, A systematic review and meta-analysis of nut consumption and incident risk of CVD and all-cause mortality, Br J Nutr source

      Not checked in the free run.

    • cites [7] Zhao, 2016, Fish consumption and all-cause mortality: a meta-analysis of cohort studies, Eur J Clin Nutr source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductown data

    The various analyses performed-high versus low intake, dose-response meta-analysis, nonlinear dose-response, subgroup, and sensitivity analyses-enabled detection of nonlinear associations and identification of optimal intake with the lowest all-cause mortality risk.

    “Furthermore, we performed different types of analyses (high compared with low intake, dose-response metaanalysis, nonlinear dose-response analysis, and subgroup and sensitivity analyses), which allowed us to detect associations where the relation was nonlinear and find an optimal consumption with the lowest risk of all-cause mortality.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    The literature search was conducted by two authors, and disagreements were resolved by consensus after discussion with another reviewer.

    “The literature search was conducted by 2 authors (LS and A-ML); disagreements were resolved by consensus after discussion with another reviewer (HB).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Study quality was assessed using the NutriGrade scoring system for each food group.

    “Finally, we assessed the quality of the studies using meta-evidence for each food group through use of the NutriGrade scoring system.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    A sensitivity analysis was performed for studies with a low risk of bias.

    “Furthermore, we analyzed sensitivity for studies with a low risk of bias.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    The NutriGrade scoring system was used to evaluate the meta-evidence for the associations between the 12 food groups and all-cause mortality.

    “To evaluate the meta-evidence for the association between 12 predefined food groups and all-cause mortality (quality of evidence of meta-analyses was defined as the confidence in the estimate), we applied the NutriGrade scoring system (a maximum of 10 points)”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [15] Schwingshackl, 2016, Perspective: NutriGrade: a scoring system to assess and judge the meta-evidence of randomized controlled trials and cohort studies in nutrition research, Adv Nutr source

      Not checked in the free run.

    • Rests on an assumption: Meta-analyses rarely assess the quality of evidence.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductcitation

    The meta-analysis has strengths including a published a priori protocol, a comprehensive literature search, and large numbers of prospective studies, deaths, and food groups.

    “Among the strengths of the present meta-analysis are the a priori published systematic review protocol (14), the comprehensive literature search, and the large numbers of prospective studies, death cases, and food groups included.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [14] Schwingshackl, 2016, Food groups and risk of chronic disease: a protocol for a systematic review and network meta-analysis of cohort studies, Syst Rev source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Foods are directly linked to food-based dietary guidelines.

    “Moreover, foods are directly linked to food-based dietary guidelines, which are based on the preventive actions of foods and should be released for each country depending on dietary practices and intake amounts (10).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [10] 2010, Scientific opinion on establishing food-based dietary guidelines, EFSA J

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Data extraction was performed by two reviewers.

    “After selecting studies, 2 reviewers (LS and A-ML) extracted the following information”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The review was registered in PROSPERO under identifier CRD42016037069.

    “The review was registered in PROSPERO International Prospective Register of Systematic Reviews (www.crd.york.ac.uk/PROSPERO/; identifier CRD42016037069).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    High adherence to diet quality indexes such as the Healthy Eating Index and DASH is associated with a 22% decrease in all-cause mortality risk.

    “a recent metaanalysis showed that high adherence to diet quality indexes such as the Healthy Eating Index and Dietary Approaches to Stop Hypertension were associated with a 22% decrease in the risk of all-cause mortality (9).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [9] Schwingshackl, 2015, Diet quality as assessed by the Healthy Eating Index, the Alternate Healthy Eating Index, the Dietary Approaches to Stop Hypertension score, and health outcomes: a systematic review and meta-analysis of cohort studies, J Acad Nutr Diet source

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductcitation

    Risk of bias was assessed by examining exposure ascertainment, outcome assessment, follow-up duration of at least 10 years, and adjustment for basic and outcome-relevant factors.

    “To determine the risk of bias of the prospective studies, we assessed how the studies ascertained exposure, how they assessed outcomes, whether the follow-up was adequate ($10 y), and whether they adjusted the basic model and made any outcomerelevant adjustments (age, sex, education, BMI, smoking, physical activity, or energy intake) (15).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [15] Schwingshackl, 2016, Perspective: NutriGrade: a scoring system to assess and judge the meta-evidence of randomized controlled trials and cohort studies in nutrition research, Adv Nutr source

      Not checked in the free run.

31 of 31

  • The paper relies on this without support.

    Up-to-date evidence on the association between all-cause mortality and legumes, eggs, and sugar-sweetened beverages had not been synthesized before this review.

    “Up-to-date evidence about the association of all-cause mortality risk with consumption of legumes, eggs, and sugar-sweetened beverages (SSBs) has not been synthesized.”

  • The paper relies on this without support.

    Meta-analyses rarely assess the quality of evidence.

    “Moreover, metaanalyses rarely assess the quality of evidence.”

  • The paper relies on this without support.

    The associations between food group intakes and all-cause mortality observed in the included studies are causal.

    “In conclusion, an optimal intake of whole grains, vegetables, fruits, nuts, legumes, and fish, as well as reduced consumption of red and processed meats and SSBs, can lead to an important decrease-by w80%-in the relative risk of premature death when compared with intakes always from the highest risk category.”

  • The paper relies on this without support.

    The effects of optimal intakes of different food groups on mortality risk are independent and combine multiplicatively (or additively) to produce the stated approximately 80% reduction.

    “In conclusion, an optimal intake of whole grains, vegetables, fruits, nuts, legumes, and fish, as well as reduced consumption of red and processed meats and SSBs, can lead to an important decrease-by w80%-in the relative risk of premature death when compared with intakes always from the highest risk category.”

  • The paper relies on this without support.

    The pooled estimates from the included study populations are applicable to the general population to which the conclusion refers.

    “In conclusion, an optimal intake of whole grains, vegetables, fruits, nuts, legumes, and fish, as well as reduced consumption of red and processed meats and SSBs, can lead to an important decrease-by w80%-in the relative risk of premature death when compared with intakes always from the highest risk category.”

  • The paper relies on this without support.

    Food frequency questionnaire data are sufficiently valid to rank individuals by usual dietary intake for the purpose of this meta-analysis.

    “Dietary information of most of the included studies derives from food frequency questionnaires, which represent a subjective approximation of past dietary behaviors rather than an assessment of absolute intakes.”
6 of 6

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Association count disagrees with the food groups listed

    Minor

    The discussion says nine food groups showed an association, but its own list names six with inverse associations and four with positive associations-a total of ten.

1 of 1

Cites

Flagged first, then by citations

1 of the 142 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. Wang, 2014, Fruit and vegetable consumption and mortality from all causes, cardiovascular disease, and cancer: systematic review and dose-response meta-analysis of prospective cohort studies, BMJ, 349, g4490, 10.1136/bmj.g4490 · DOI · Paper page

Cited by

Sorted by citations

Related

Authors
Schwingshackl, L., Schwedhelm, C., Hoffmann, G., Lampousi, A.-M., Knüppel, S., Iqbal, K., Bechthold, A., Schlesinger, S., & Boeing, H.
Affiliations
  • German Institute of Human Nutrition (DE)
  • University of Vienna (AT)
  • Heinrich Heine University Düsseldorf (DE)
Corresponding author
Schwingshackl, Lukas
ORCID
Venue
The American Journal of Clinical Nutrition
Publisher
Elsevier BV
Published
2017-06
Volume
105
Issue
6
Pages
1462-1473
ISSN
0002-9165 (ISSN-L)
DOI
10.3945/ajcn.117.153148
OpenAlex
W2609492761
Cited by
600
References
142
Citations by year
2026: 52 · 2025: 62 · 2024: 62 · 2023: 66 · 2022: 78 · 2021: 89 · 2020: 54 · 2019: 72 · 2018: 54 · 2017: 11
FWCI
8.49
Type
journal article
Language
en
Open access
Licence
Locations
  • American Journal of Clinical Nutrition (publishedVersion)
  • PubMed (publishedVersion)
  • Informationszentrum Lebenswissenschaften (ZB MED) (submittedVersion)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
  • Life Sciences › Agricultural and Biological Sciences › Food Science › Nutrition, Health, and Society Studies
  • Physical Sciences › Environmental Science › Ecology › Agriculture Sustainability and Environmental Impact
Keywords
all-cause mortality, food groups, whole grains, refined grains, vegetables, fruits, nuts, Fabaceae, eggs, dairy products, fish, red meat, processed meat, sugar-sweetened beverages, diet and mortality, dose-response relationship, nonlinear dose-response relationship, dietary recommendations
MeSH terms
Cause of Death, Diet, Feeding Behavior, Humans, Risk Factors, Risk Reduction Behavior

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-07.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-07.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review