To determine the prevalence and predictors of combined BMI-WC disease risk categories among Indian adults. The study utilizes data from Longitudinal Ageing Study in India (LASI Wave 1) with an eligible sample of 66, 859 individuals. Bivariate analysis was done to get the proportion of individuals in different BMI-WC risk categories. Multinomial logistic regression was used to identify the predictors of BMI-WC risk categories. Poor self-rated health, female sex, urban place of residence, higher educational status, increasing MPCE quintile, and cardio-vascular disease increased with increasing BMI-WC disease risk level while increasing age, tobacco consumption, and engagement in physical activities was negatively associated with BMI-WC disease risk. Elderly persons in India have a considerable higher prevalence of BMI-WC disease risk categories which make them vulnerable to developing several disease. Findings emphasize the need of using combined BMI categories and waist circumference to assess the prevalence of obesity and associated disease risk. Finally, we recommend that intervention programs with an emphasis on urbanites wealthy women and those with a higher BMI-WC risk categories be implemented.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10090356 | PMC |
| http://dx.doi.org/10.3389/ijph.2023.1605595 | DOI Listing |
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