Evidence map›Paper›PMID 37798718›Full record

ArticleBMC public health2023

Spatiotemporal variations and determinants of overweight/obesity among women of reproductive age in urban India during 2005-2021.

Aditya Singh, Subhojit Let, Seema Tiwari, Mahashweta Chakrabarty

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Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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7citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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7 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Aditya Singh *Department of Geography, Banaras Hindu University, Varanasi, Uttar Pradesh, India.ORCID http://orcid.org/0000-0003-3031-5225
Subhojit Let *Department of Geography, Banaras Hindu University, Varanasi, Uttar Pradesh, India.ORCID http://orcid.org/0000-0002-5692-6027
Seema TiwariGeography Section, Mahila Maha Vidyalaya, Banaras Hindu University, Varanasi, Uttar Pradesh, India. seemammvbhu2007@gmail.com.ORCID http://orcid.org/0000-0001-5755-6251
Mahashweta ChakrabartyDepartment of Geography, Banaras Hindu University, Varanasi, Uttar Pradesh, India. mahashweta.c1997@gmail.com.ORCID http://orcid.org/0000-0001-5151-9572

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndia has witnessed rapid urbanization in recent decades, leading to a worrisome surge in non-communicable diseases, particularly overweight/obesity, which now present a critical public health concern. Therefore, this study seeks to examine spatiotemporal variations and determinants of overweight/obesity among women of reproductive age (WRA) in urban India and its states during 2005-2021.

methodsThe study used 44,882, 171,443, and 135,272 WRA aged 15-49 from National Family Health Survey (NFHS)-3 (2005-06), NFHS-4 (2015-16), and NFHS-5 (2019-21), respectively. The outcome variable was overweight/obesity, defined as a Body Mass Index (BMI) of ≥ 25 kg/m

resultsOverweight/obesity prevalence among WRA in urban India has risen significantly, from 23% in 2005-06 to 33% in 2019-21. This increase is particularly pronounced among SC/ST women and women with lower educational levels. During the study period, overweight/obesity rates in different states exhibited varying increases, ranging from 3 percentage points (pp) in Rajasthan to 22 pp in Odisha. Certain southern (e.g., Tamil Nadu and Andhra Pradesh) and northeastern states saw a significant 15 pp or more increase. In contrast, several northern, central, and eastern states (e.g., Punjab, Haryana, Rajasthan, Madhya Pradesh, Chhattisgarh, Jharkhand, West Bengal) experienced relatively smaller increases ranging from 5 to 8 pp. As of 2019-21, two regions exhibited high prevalence rates of overweight/obesity, exceeding 35%: the southern region (Tamil Nadu, Andhra Pradesh, Kerala, and Karnataka) and the northern region (Punjab, Himachal Pradesh, Uttarakhand, and Haryana). In contrast, the Empowered Action Group states had relatively lower rates (25% or less) of overweight/obesity. Regression results showed that older women [AOR: 5.98, 95% CI: 5.71-6.27], those from the richest quintile [AOR: 4.23, 95% CI: 3.95-4.54], those living in south India [AOR: 1.77, 95% CI: 1.72-1.82], and those having diabetes [AOR: 1.92, 95% CI: 1.83-2.02] were more likely to be overweight/obese.

conclusionConsidering the significant increase in overweight/obesity among urban WRA in India, along with substantial disparities across states and socioeconomic groups, it is imperative for the government to formulate state-specific strategies and policies based on determinants to effectively combat overweight/obesity.

Indexed as

Diabetes MellitusOverweightAgedFemaleHumansIndiaObesityPrevalenceReproductionBMIIndiaNFHSObeseObesityOverweightReproductive AgeUrbanWomen’s Health

Identifiers

PMID37798718
PMCPMC10557305

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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 OpenQuestion graph.