Evidence mapPaperPMID 42286403Full record

ReviewHormones (Athens, Greece)2026

Global trends in the prevalence of type 2 diabetes mellitus: understanding trajectories through conceptual frameworks.

Deepa Bharti, Madhur Verma, Sanjay Kalra, Sanjeev Kumar, Pravin Pisudde, Nitin Kapoor, Rakesh Kakkar

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In one paragraph

Review in Hormones (Athens, Greece), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Deepa Bharti *Department of Community and Family Medicine, All India Institute of Medical Sciences, Bathinda, Punjab, 151001, India.ORCID http://orcid.org/0009-0005-0565-2109
Madhur Verma *Department of Community and Family Medicine, All India Institute of Medical Sciences, Bathinda, Punjab, 151001, India. drmadhurverma@gmail.com.ORCID http://orcid.org/0000-0002-1787-8392
Sanjay KalraDepartment of Endocrinology, Bharti Hospital, Karnal, India.
Sanjeev KumarDepartment of Community and Family Medicine, All India Institute of Medical Sciences, Bathinda, Punjab, 151001, India.
Pravin PisuddeDepartment of Community and Family Medicine, All India Institute of Medical Sciences, Bathinda, Punjab, 151001, India.
Nitin KapoorDept. of Endocrine, Diabetes and Metabolism, Christian Medical College, Vellore, TN, 632004, India.
Rakesh KakkarDepartment of Community and Family Medicine, All India Institute of Medical Sciences, Bathinda, Punjab, 151001, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundType 2 diabetes mellitus (T2DM) is imposing a substantial and rapidly growing global health burden. Disease estimates vary widely across geographies and time periods, reflecting not only true differences in disease occurrence but also variation in demographic structures, risk factor exposures, diagnostic practices, surveillance capacity, and biological heterogeneity within T2DM itself.

methodsA narrative, integrative synthesis of global epidemiological evidence was conducted. Data were sourced from major international platforms, supplemented with peer-reviewed literature. Evidence was synthesized across time, place, and person, with explicit attention to differences in case definitions, biomarker use, screening intensity, and modeling assumptions. Conceptual frameworks were applied to interpret observed patterns.

resultsHarmonized NCD-RisC analyses show a sustained rise in age-standardized prevalence from 1980 to 2014, increasing from 4.3% to 9.0% in men and from 5.0% to 7.9% in women. According to the IDF, the global burden is projected to reach 852.5 million by 2050. Approximately 42.8% (251.7 million) of cases remain undiagnosed, with the highest proportions concentrated in low-income regions. Substantial geographic heterogeneity is shaped by population aging, rising adiposity, dietary and physical activity transitions, urbanization, commercial food environments, and health system detection capacity. Subtype distribution and biological heterogeneity further contribute to variation in disease trajectories and complication profiles across populations.

conclusionsGlobal T2DM prevalence reflects the interaction of biological, social, and health system processes rather than incidence alone. Prevalence trajectories must be interpreted in light of surveillance limitations, diagnostic context, and within-disease heterogeneity. Addressing future burden requires combining improved detection and chronic-care capacity with upstream, life-course-oriented prevention strategies.

Indexed as

Commercial and structural determinantsGlobal prevalenceLife-course perspectiveSurveillance and underdiagnosisType 2 diabetes

Identifiers

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Registered trials

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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.