Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Feb 1:69:1606660.
doi: 10.3389/ijph.2024.1606660. eCollection 2024.

Predictors of Multimorbidity (Defined as Diabetes + Hypertension) Amongst Males Aged 15-54 in India: An Urban/Rural Split Analysis

Affiliations

Predictors of Multimorbidity (Defined as Diabetes + Hypertension) Amongst Males Aged 15-54 in India: An Urban/Rural Split Analysis

Vikramjit Brar et al. Int J Public Health. .

Abstract

Objectives: This study aimed to determine which sociodemographic and lifestyle factors may act as predictors of multimorbidity (defined as diabetes + hypertension) amongst men aged 15-54 within urban and rural areas of India. Methods: Data from the latest 2019-2021 India NFHS-5 survey were utilized. Presumed cases of multimorbidity were defined as men who had DM + HTN. A total of 22,411 men in urban areas and 66,768 rural men were analyzed using mixed-effect multi-level binary logistic regression models. Results: Various predictors were found to have a statistically significant association to multimorbidity. Urban areas: Age, region of residence, wealth, religion, occupation, and BMI. Rural areas: Age, education, region of residence, wealth, occupation, caste, BMI, alcohol consumption, media exposure, and tobacco consumption. Conclusion: Departing from the broad operational definitions often studied within literature, this study provided insight into one of the most prevalent specific multimorbidities across India. The urban/rural split analyses revealed substantial differences in high-risk characteristics across both areas, which have commonly been overlooked. These findings may better inform policymakers and assist in effectively reducing multimorbidity-related burden through area-specific preventative programs.

Keywords: India; diabetes and hypertension; males; multimorbidity; predictors of multimorbidity.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they do not have any conflicts of interest.

Similar articles

Cited by

References

    1. Basto-Abreu A, Barrientos-Gutierrez T, Wade AN, Oliveira de Melo D, Semeão de Souza AS, Nunes BP, et al. Multimorbidity Matters in Low and Middle-Income Countries. J Multimorbidity Comorbidity (2022) 12:26335565221106074. 10.1177/26335565221106074 - DOI - PMC - PubMed
    1. Luna F, Luyckx VA. Why Have Non-Communicable Diseases Been Left Behind? Asian Bioeth Rev (2020) 12(1):5–25. 10.1007/s41649-020-00112-8 - DOI - PMC - PubMed
    1. Nethan S, Sinha D, Mehrotra R. Non Communicable Disease Risk Factors and Their Trends in India. Asian Pac J Cancer Prev (2017) 18(7):2005–10. 10.22034/APJCP.2017.18.7.2005 - DOI - PMC - PubMed
    1. Yadav S, Arokiasamy P. Understanding Epidemiological Transition in India. Glob Health Action (2014) 7(1):23248. 10.3402/gha.v7.23248 - DOI - PMC - PubMed
    1. WHO. Multimorbidity: Technical Series on Safer Primary Care. Geneva: World Health Organization; (2016). Licence: CC BY-NC-SA 3.0 IGO.