Evidence map›Paper›PMID 40995598›Full record

ArticleFrontiers in endocrinology2025

Heterogeneity of type 2 diabetes in rural India.

Suvarna Patil, Ajay Patil, Kaustubh Tare, Pallavi Bhat, Akash Kumbhar, Datta Mulay, Dnyaneshwar Jadhav, Vaibhav Methi, Sachin Surnar, Tushar Humbare and 3 more

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

Suvarna PatilDepartment of Medicine, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.
Ajay PatilDepartment of Medicine, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.
Kaustubh TareDepartment of Medicine, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.
Pallavi BhatRegional Centre for Adolescent Health and Nutrition, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.
Akash KumbharDepartment of Medicine, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.
Datta MulayDepartment of Medicine, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.
Dnyaneshwar JadhavRegional Centre for Adolescent Health and Nutrition, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.
Vaibhav MethiDepartment of Medicine, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.
Sachin SurnarDepartment of Medicine, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.
Tushar HumbareRegional Centre for Adolescent Health and Nutrition, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.
Aniket KhaladkarDepartment of Medicine, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.
Shreyansh DeosaleDepartment of Medicine, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.
Charudatta JoglekarRegional Centre for Adolescent Health and Nutrition, BKL Walawalkar Rural Medical College and Hospital, Sawarde, Chiplun, Maharashtra, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The prevalence of diabetes continues to rise in India. The increase in diabetes, which has been previously concentrated in urban areas, is now also occurring in rural India, even though the rural population is predominantly non-obese/lean, undernourished, and physically active. Type 2 diabetes and its pathophysiology (hyperinsulinemia and insulin resistance) among the obese, overnourished, and physically inactive urban populations are very well characterized. However, there is a paucity of such characterization among those non-obese/lean and undernourished. We attempted to characterize type 2 diabetes in the rural Konkan region of India using BMI, body composition, and glycemic parameters. Methods: This cross-sectional study was conducted among 508 subjects with type 2 diabetes who visited the rural tertiary care center. They underwent anthropometry, body composition, and glycemic (i.e., glucose, HbA Results: The median age, the age at diagnosis, and the duration of type 2 diabetes were 59, 51.5, and 5.2 years, respectively. The BMI distribution showed that 6% were underweight, approximately 46% were normal weight, and 48% were overweight. Central obesity and adiposity were observed in 70% and 56%, respectively. Of those subjects with normal weight, 52% had central obesity, while 29% had excess adipose tissue. The lean group was characterized by a low BMI (mean, 16.7 kg/m Conclusion: The use of BMI and simple body composition measures led to the identification of a distinct lean phenotype that is characterized by a low BMI, poor insulin secretion, and the absence of central obesity and adiposity. Further research is warranted to understand the pathophysiology and to develop a personalized therapeutic approach for lean subjects with type 2 diabetes. It is time to reconsider the glucocentric, one-size-fits-all approach for type 2 diabetes treatment.

Indexed as

Diabetes Mellitus, Type 2Rural PopulationAdultAgedBlood GlucoseBody CompositionBody Mass IndexCross-Sectional StudiesFemaleHumansIndiaInsulin ResistanceMaleMiddle AgedObesityPrevalenceBlood Glucosebody compositionC-peptideIndialean diabetesnon-obeserural healthtype 2 diabetes

Identifiers

PMID40995598
PMCPMC12454038

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.