Evidence map›Paper›PMID 34689196›Full record

ArticleThe Journal of nutrition2021

Higher Global Diet Quality Score Is Inversely Associated with Risk of Type 2 Diabetes in US Women.

Teresa T Fung, Yanping Li, Shilpa N Bhupathiraju, Sabri Bromage, Carolina Batis, Michelle D Holmes, Meir Stampfer, Frank B Hu, Megan Deitchler, Walter C Willett

Open access · hybridAbstract read
In one paragraph

Article in The Journal of nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
5.1field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 41 citations in OpenAlex.

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  9. The global diet quality score (GDQS) of foods consumed by Nigerian adults.Journal of health, population, and nutrition · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 3 countries.

Teresa T FungDepartment of Nutrition, Simmons University, Boston, MA, USA.
Yanping LiDepartment of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA.ORCID 0000-0002-0412-2748
Shilpa N BhupathirajuDepartment of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA.
Sabri BromageDepartment of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA.
Carolina BatisCONACYT-Health and Nutrition Research Center, National Institute of Public Health, Cuernavaca, Mexico.
Michelle D HolmesChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Meir StampferChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Frank B HuDepartment of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA.
Megan DeitchlerIntake-Center for Dietary Assessment, FHI Solutions, Washington, DC, USA.
Walter C WillettDepartment of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA.
Brigham and Women's Hospital · USHarvard University · USFamily Health International 360 · USNational Institute of Public Health · SI

Funding

Life Course Cancer Epidemiology Cohort in WomenU01CA176726 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI ELIASSEN, A. HEATHER, WILLETT, WALTER C. · 2018 to 2025
$22.4M
NCI NIH HHS U01 CA176726
6 · The paper itself

Abstract

backgroundWe have developed a diet quality metric intended for global use. To assess its utility in high-income settings, an evaluation of its ability to predict chronic disease is needed.

objectivesWe aimed to prospectively examine the ability of the Global Diet Quality Score (GDQS) to predict the risk of type 2 diabetes in the United States, examine potential differences of association by age, and compare the GDQS with other diet quality scores.

methodsHealth, lifestyle, and diet information was collected from women (n = 88,520) in the Nurses' Health Study II aged 27-44 y at baseline through repeated questionnaires between 1991 and 2017. The overall GDQS consists of 25 food groups. Points are awarded for higher intake of healthy groups and lower intake of unhealthy groups (maximum of 49 points). Multivariable HRs were computed for confirmed type 2 diabetes using proportional hazards models. We also compared the GDQS with the Minimum Diet Diversity score for Women (MDD-W) and the Alternate Healthy Eating Index-2010 (AHEI-2010).

resultsWe ascertained 6305 incident cases of type 2 diabetes during follow-up. We observed a lower risk of diabetes with higher GDQS; the multivariable HR comparing extreme quintiles of the GDQS was 0.83 (95% CI: 0.76, 0.91; P-trend < 0.001). The magnitude of association was similar between women aged <50 y and those aged ≥50 y. An inverse association was observed with lower intake of unhealthy components (HR comparing extreme quintiles of the unhealthy submetric: 0.76; 95% CI: 0.69, 0.84; P-trend < 0.001) but was not with the healthy submetric. The inverse association for each 1-SD increase in the GDQS (HR: 0.93; 95% CI: 0.91, 0.96) was stronger (P < 0.001) than for the MDD-W (HR: 1.00; 95% CI: 0.94, 1.04) but was slightly weaker (P = 0.03) than for the AHEI-2010 (HR: 0.91; 95% CI: 0.88, 0.94).

conclusionsA higher GDQS was inversely associated with type 2 diabetes risk in US women of reproductive age or older, mainly from lower intake of unhealthy foods. The GDQS performed nearly as well as the AHEI-2010.

Indexed as

AdultDiabetes Mellitus, Type 2DietDiet, HealthyFemaleFollow-Up StudiesHumansLife StyleMiddle AgedNursesProspective StudiesRisk FactorsSurveys and QuestionnairesUnited Statesdiabetesdiet qualityepidemiologynutritionwomen

Identifiers

PMID34689196
PMCPMC8542093
OpenAlexW3210590572

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.