Cited by 57Obesity, Physical Activity, DietDiabetes, Cardiovascular Risks, and LipoproteinsAdipokines, Inflammation, and Metabolic Diseases

Does a rise in BMI cause an increased risk of diabetes?: evidence from India

Open access
Gupta, Shivani, Bansal, Sangeeta·2020·PLoS ONE

Abstract

BACKGROUND: Overnutrition increases the risk of diabetes. Evidence on the causal impact of overnutrition on diabetes is scarce for India. Considering a representative sample from India, this study examines the causal effect of a rise in the Body Mass Index (BMI) of an individual on the likelihood of being diabetic while addressing the issue of unobserved endogeneity between overnutrition and diabetes. METHODS: The study considers individual level data from Demographic and Health Surveys (DHS) of India, namely, National Family Health Survey (NFHS) for the year 2015-16. The NFHS is a large-scale, multi-round survey conducted in a representative sample of households throughout India. The survey covers females having age 15-49 years and males having age 15-54 years. The instrument variable approach is used to address the potential endogeneity in the relationship between BMI and diabetes. We instrument BMI of an individual by BMI of a non-biologically related household member. Ordered Probit, Probit and IV-Probit models are estimated using two alternative definitions for measuring diabetes-self-reported diabetes status and blood glucose levels (ordinal measure). RESULTS: The coefficients obtained from the Ordered Probit and Probit models are much smaller than those estimated by an IV-Probit model. The latter estimates the causal impact of a rise in BMI on diabetes by taking into account the effect of the unobserved genetic and other related factors. The likelihood of being diabetic is twice or more among the overweight and obese individuals as compared to non-overweight individuals in all the specifications. With a unit increase in BMI the probability of being diabetic increases by about 1.5% among overweight and obese individuals and by 0.5% among the non-overweight individuals in the IV-Probit model. Similar results from the Ordered Probit model show that on average, the overweight and obese individuals experience about 0.2% increase in the probability of being diabetic and about 0.4% increase in the probability of being prediabetic. CONCLUSION: Our study demonstrates that the likelihood of being both prediabetic and diabetic is higher among the overweight and obese individuals as compared to the non-overweight individuals. We also find that the level of risk of being prediabetic or diabetic differs across gender, wealth quintiles and regions and the effects are more severe among population in the urban areas, belonging to the richest wealth quintile and men. Our findings have significant implications for the policy formulation as diabetes has a substantial health and economic burden associated with it. Future studies may investigate the effect of abdominal obesity on diabetes.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pone.0229716

Cites

43 of 43 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. [43]IDF (2017b), International Diabetes Federation, IDF Diabetes Atlas - 8th Edition, Accessed March 2019, URL: https://diabetesatlas.org/across-the-globe.html 35914061

Cited by

Sorted by citations

Authors
Gupta, S., & Bansal, S.
Affiliations
Jawaharlal Nehru University (IN)
Corresponding author
Bansal, Sangeeta
Venue
PLoS ONE
Published
2020-04-01
Volume
15
Issue
4
Pages
e0229716
ISSN
1932-6203 (ISSN-L)
OpenAlex
W3014717156
Cited by
57
References
43
Citations by year
2026: 2 · 2025: 8 · 2024: 13 · 2023: 14 · 2022: 12 · 2021: 7 · 2020: 1
FWCI
6.36
Type
journal article
Language
en
Open access
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • SSRN Electronic Journal (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
Funders
Jawaharlal Nehru University
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
  • Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
Keywords
body mass index, diabetes mellitus, obesity, overweight, prediabetes, overnutrition, endogeneity, blood glucose, gender differences, wealth inequality, urban-rural differences, India
MeSH terms
Adolescent, Adult, Female, Health Surveys, Humans, India, Male, Middle Aged, Obesity, Prediabetic State, Risk Factors, Body Mass Index, Young Adult

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.

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