Evidence mapPaperPMID 40770495Full record

ReviewDiabetologia2025

Race, ethnicity and ancestry in global diabetes research: grappling with complexity to advance equity and scientific integrity - a narrative review and viewpoint.

Nish Chaturvedi, Benjamin F Voight, Jonathan C Wells, Cheryl Pritlove

Abstract readReview
In one paragraph

Review in Diabetologia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
field-weighted citation impact
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

8 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Clinical Thresholds for Visceral Adiposity Accumulation: A Comparative Analysis in Sex-, Age-, and BMI-Matched Black and White Adults.American journal of human biology : the official journal of the Human Biology Council · 2025
    Article
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

4 authors.

Nish ChaturvediUnit for Lifelong Health & Ageing, Research Department of Population Science & Experimental Medicine, Institute of Cardiovascular Science, University College London, London, UK. n.chaturvedi@ucl.ac.uk.ORCID http://orcid.org/0000-0002-6211-2775
Benjamin F VoightDepartment of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0002-6205-9994
Jonathan C WellsPopulation Policy and Practice Department, University College London Great Ormond Street Institute of Child Health, London, UK.ORCID http://orcid.org/0000-0003-0411-8025
Cheryl PritloveLi Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, ON, Canada.ORCID http://orcid.org/0000-0001-9627-7562

Funding

An interactive resource to generate and provide integrated knowledge of the human pancreasU24DK138512 · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2025 to 2025
$2.0M
NIDDK NIH HHS DK126194NIDDK NIH HHS DK138512NIDDK NIH HHS U24 DK138512NIDDK NIH HHS UM1 DK126194
6 · The paper itself

Abstract

The global burden of diabetes-across major forms such as type 2 diabetes, type 1 diabetes and gestational diabetes mellitus-disproportionately affects people of non-European ancestry, the majority of whom live in low- and middle-income countries. The heterogeneity of diabetes risks and phenotypes indicates that knowledge derived principally from European-origin populations may not be readily transferable to other groups. In this review our aim is to enhance the quality of diabetes research by championing the inclusion of diverse populations, ensuring clarity of population definition and encouraging exploration of population differences. We review the terminology used to define populations and make recommendations on the use of these terms. We argue that population membership by itself does not determine risks or response to intervention; rather, it is the confluence of genetic, environmental, sociocultural and policy factors that are causal and should be identified. We note that, while common diabetes forms are polygenic and populations are unlikely to harbour single genes that account for significant risk, environmental change that impacts lifestyle and biology demonstrably alters diabetes risk and provides opportunities for effective intervention. Similarly, while genetic variants are associated with adverse events, population group membership may sometimes not be a valid proxy for such variants, which has implications for healthcare equity. For most drugs used in diabetes there is little evidence that drug responsiveness materially differs by population grouping, although it is only recently that well-designed studies have been performed. In contrast, other population characteristics, such as sex, age and obesity, appear to alter glucose-lowering drug effectiveness and should be considered when prescribing. Inclusion of diverse populations in diabetes research, combined with a multidisciplinary approach, is essential if we are to combat the global burden of diabetes.

Indexed as

Diabetes MellitusDiabetes, GestationalDiabetes Mellitus, Type 2EthnicityFemaleHumansPregnancyRacial GroupsEquity, diversity and inclusionGeneticsIntergenerational diabetes risksPopulation groupsPopulation stratificationReviewStructural and environmental determinants of health

Identifiers

PMID40770495
PMCPMC12534298

What Socratic holds

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LicenceCC BY
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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 Socratic graph.