Evidence mapPaperPMID 39046947Full record

ArticlePloS one2024

Spatial clustering of overweight/obesity among women in India: Insights from the latest National Family Health Survey.

Mahashweta Chakrabarty, Subhojit Let

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Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing 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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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Mahashweta ChakrabartyBanaras Hindu University, Varanasi, Uttar Pradesh, India.ORCID https://orcid.org/0000-0001-5151-9572
Subhojit LetBanaras Hindu University, Varanasi, Uttar Pradesh, India.ORCID https://orcid.org/0000-0002-5692-6027

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOverweight/obesity has become global health concern with increasing prevalence. This study examined district-level disparities and spatial clustering of overweight/obesity among women of reproductive age (WRA) in India using the latest National Family Health Survey-5 (2019-2021) data.

methodInformation of 623,656 women aged 15 to 49 from the NFHS-5 (2019-2021) were analysed in this study. The outcome variable was BMI as classified by the world health organisation (WHO). Utilising Global Moran's I, Anselin's Local Moran's I, and spatial regression models spatial clustering and associated factors were analysed.

resultThe study found that 24% (95% CI: 23.8-24.3) of WRA in India were overweight/obese in 2019-21. The prevalence was greatest in Punjab (41%) and lowest in Meghalaya (11%). Additionally, the Global Moran's I value for the outcome variable was 0.73, indicating a positive spatial autocorrelation in the overweight/obesity. Districts of Tamil Nadu, Andhra Pradesh, Karnataka, Kerala, Telangana, Punjab, Himachal Pradesh, Jammu & Kashmir, Haryana, and Delhi were hotspots of overweight/obesity. Several factors of overweight/obesity among WRA were identified, including place of residence (β: 0.034, p: 0.011), parity (β: 0.322, p: 0.002), social group (β: -0.031, p: 0.016), religion (β: -0.044, p: <0.001), household wealth status (β: 0.184, p: <0.001), mass-media exposure (β: 0.056, p: 0.031), and diabetes (β: 0.680, p: <0.001).

conclusionThe study emphasizes the importance of targeted interventions and region-specific strategies, while also stressing the need to address associated factors to develop effective public health initiatives aimed at reducing overweight/obesity prevalence among WRA in India.

Indexed as

Health SurveysObesityOverweightAdolescentAdultBody Mass IndexCluster AnalysisFemaleHumansIndiaMiddle AgedPrevalenceYoung Adult

Identifiers

PMID39046947
PMCPMC11268665

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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 Socratic graph.