Diabetes and Prediabetes Prevalence Among Young and Middle-aged Adults in India, with an Analysis of Geographic Differences: Findings from the National Family Health Survey

Overview

Journal Epidemiol Health

Specialty Public Health

Date 2020 Sep 25

PMID 32972049

Citations 10

Authors

Siddardha G Chandrupatla

Isma Khalid

Tejdeep Muthuluri

Satyanarayana Dantala

Mary Tavares

Affiliations

Soon will be listed here.

Abstract

Objectives: This study aimed to approximate the prevalence of hyperglycemia in India.

Methods: The study was conducted using the Demographic and Health Survey 2015-16 (also known as the National Family Health Survey-4), which surveyed 811,808 individuals using a stratified, multistage, cluster sampling design. This cross-sectional survey recorded socio-demographic and anthropometric data, including blood glucose levels, of adults aged 18 years to 54 years.

Results: The final analysis included 718,597 individuals, of whom 49.90% (weighted) were males. The overall prevalence of diabetes was 6.65% and that of prediabetes was 5.57%. A positive association was seen with urban residence, geographic region, sex, age, body mass index, socioeconomic status, and hypertension. Approximately two-thirds of individuals with diabetes lived in urban areas, and about half of the urban population was considered overweight/obese. South India showed a higher prevalence of diabetes (prevalence ratio, 2.01; p<0.001) than northern India.

Conclusions: Hyperglycemia (diabetes and prediabetes) has a high prevalence in India and is a major public health issue. Diabetes is unevenly distributed based on geographic location and urbanization. Prevention, early detection, and treatment strategies should consider this uneven distribution of diabetes.

Citing Articles

The incremental value of aspartate aminotransferase/alanine aminotransferase ratio combined with CURB-65 in predicting treatment outcomes in hospitalized adult community-acquired pneumonia patients with type 2 diabetes mellitus.

Zhou H, Zhu X, Zhang Y, Xu W, Li S BMC Pulm Med. 2025; 25(1):26.

PMID: 39825277 PMC: 11742778. DOI: 10.1186/s12890-025-03488-1.

Rural health dynamics: Exploring the prevalence of prediabetes and prehypertension among the rural population of Puducherry district.

Thamizhmaran S, Dsouza M, Ramadass D, Daniel J J Family Med Prim Care. 2024; 13(10):4299-4307.

PMID: 39629393 PMC: 11610848. DOI: 10.4103/jfmpc.jfmpc_332_24.

Charting Wellness in India: Piloting the iTHRIVE's Functional Nutrition Approach to Improve Glycaemic and Inflammatory Parameters in Prediabetes and Type 2 Diabetes Mellitus.

Pradhan M, Hedaoo R, Joseph A, Jain R Cureus. 2024; 16(7):e63744.

PMID: 39100011 PMC: 11296214. DOI: 10.7759/cureus.63744.

Comparison of clinical characteristics and disease burden between early- and late-onset type 2 diabetes patients: a population-based cohort study.

Wang M, He Y, He Q, Di F, Zou K, Wang W BMC Public Health. 2023; 23(1):2411.

PMID: 38049796 PMC: 10696789. DOI: 10.1186/s12889-023-17280-5.

Diabetes mellitus early warning and factor analysis using ensemble Bayesian networks with SMOTE-ENN and Boruta.

Wang X, Ren J, Ren H, Song W, Qiao Y, Zhao Y Sci Rep. 2023; 13(1):12718.

PMID: 37543637 PMC: 10404250. DOI: 10.1038/s41598-023-40036-5.

References

. 2. Classification and Diagnosis of Diabetes. Diabetes Care. 2016; 40(Suppl 1):S11-S24. DOI: 10.2337/dc17-S005. View

Pradeepa R, Anjana R, Joshi S, Bhansali A, Deepa M, Joshi P . Prevalence of generalized & abdominal obesity in urban & rural India--the ICMR-INDIAB Study (Phase-I) [ICMR- NDIAB-3]. Indian J Med Res. 2015; 142(2):139-50. PMC: 4613435. DOI: 10.4103/0971-5916.164234. View

Singh S, Sikri G, Garg M . Body Mass Index and Obesity : Tailoring "cut-off" for an Asian Indian Male Population. Med J Armed Forces India. 2016; 64(4):350-3. PMC: 5035251. DOI: 10.1016/S0377-1237(08)80019-6. View

Esteghamati A, Gouya M, Abbasi M, Delavari A, Alikhani S, Alaedini F . Prevalence of diabetes and impaired fasting glucose in the adult population of Iran: National Survey of Risk Factors for Non-Communicable Diseases of Iran. Diabetes Care. 2007; 31(1):96-8. DOI: 10.2337/dc07-0959. View

Hu F . Globalization of diabetes: the role of diet, lifestyle, and genes. Diabetes Care. 2011; 34(6):1249-57. PMC: 3114340. DOI: 10.2337/dc11-0442. View

Ramachandran A, Snehalatha C, Kapur A, Vijay V, Mohan V, Das A . High prevalence of diabetes and impaired glucose tolerance in India: National Urban Diabetes Survey. Diabetologia. 2001; 44(9):1094-101. DOI: 10.1007/s001250100627. View

Chan J, Malik V, Jia W, Kadowaki T, Yajnik C, Yoon K . Diabetes in Asia: epidemiology, risk factors, and pathophysiology. JAMA. 2009; 301(20):2129-40. DOI: 10.1001/jama.2009.726. View

Feller S, Boeing H, Pischon T . Body mass index, waist circumference, and the risk of type 2 diabetes mellitus: implications for routine clinical practice. Dtsch Arztebl Int. 2010; 107(26):470-6. PMC: 2905837. DOI: 10.3238/arztebl.2010.0470. View

Radha V, Mohan V . Genetic predisposition to type 2 diabetes among Asian Indians. Indian J Med Res. 2007; 125(3):259-74. View

10.

Anjana R, Deepa M, Pradeepa R, Mahanta J, Narain K, Das H . Prevalence of diabetes and prediabetes in 15 states of India: results from the ICMR-INDIAB population-based cross-sectional study. Lancet Diabetes Endocrinol. 2017; 5(8):585-596. DOI: 10.1016/S2213-8587(17)30174-2. View

11.

Akter S, Rahman M, Abe S, Sultana P . Prevalence of diabetes and prediabetes and their risk factors among Bangladeshi adults: a nationwide survey. Bull World Health Organ. 2014; 92(3):204-13, 213A. PMC: 3949596. DOI: 10.2471/BLT.13.128371. View

12.

Sadikot S, Nigam A, Das S, Bajaj S, Zargar A, Prasannakumar K . The burden of diabetes and impaired glucose tolerance in India using the WHO 1999 criteria: prevalence of diabetes in India study (PODIS). Diabetes Res Clin Pract. 2004; 66(3):301-7. DOI: 10.1016/j.diabres.2004.04.008. View

13.

. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004; 363(9403):157-63. DOI: 10.1016/S0140-6736(03)15268-3. View

14.

Chandrupatla S, Ramachandra R, Dantala S, Pushpanjali K, Tavares M . Importance and Potential of Dentists in Identifying Patients at High Risk of Diabetes. Curr Diabetes Rev. 2018; 15(1):67-73. DOI: 10.2174/1573399814666180531121921. View

15.

Wild S, Roglic G, Green A, Sicree R, King H . Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care. 2004; 27(5):1047-53. DOI: 10.2337/diacare.27.5.1047. View

16.

Zheng Y, Ley S, Hu F . Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat Rev Endocrinol. 2017; 14(2):88-98. DOI: 10.1038/nrendo.2017.151. View

17.

Chiu M, Austin P, Manuel D, Shah B, Tu J . Deriving ethnic-specific BMI cutoff points for assessing diabetes risk. Diabetes Care. 2011; 34(8):1741-8. PMC: 3142051. DOI: 10.2337/dc10-2300. View

18.

. Eight million women have unmet need for family planning in Uttar Pradesh. Natl Fam Health Surv Bull. 1995; (1):1-4. View

19.

Kaveeshwar S, Cornwall J . The current state of diabetes mellitus in India. Australas Med J. 2014; 7(1):45-8. PMC: 3920109. DOI: 10.4066/AMJ.2013.1979. View

20.

Mohan V, Deepa M, Pradeepa R, Prathiba V, Datta M, Sethuraman R . Prevention of diabetes in rural India with a telemedicine intervention. J Diabetes Sci Technol. 2013; 6(6):1355-64. PMC: 3570875. DOI: 10.1177/193229681200600614. View