Forecasting the prevalence of overweight and obesity in India to 2040
Abstract
BACKGROUND: In India, the prevalence of overweight and obesity has increased rapidly in recent decades. Given the association between overweight and obesity with many non-communicable diseases, forecasts of the future prevalence of overweight and obesity can help inform policy in a country where around one sixth of the world's population resides. METHODS: We used a system of multi-state life tables to forecast overweight and obesity prevalence among Indians aged 20-69 years by age, sex and urban/rural residence to 2040. We estimated the incidence and initial prevalence of overweight using nationally representative data from the National Family Health Surveys 3 and 4, and the Study on global AGEing and adult health, waves 0 and 1. We forecasted future mortality, using the Lee-Carter model fitted life tables reported by the Sample Registration System, and adjusted the mortality rates for Body Mass Index using relative risks from the literature. RESULTS: The prevalence of overweight will more than double among Indian adults aged 20-69 years between 2010 and 2040, while the prevalence of obesity will triple. Specifically, the prevalence of overweight and obesity will reach 30.5% (27.4%-34.4%) and 9.5% (5.4%-13.3%) among men, and 27.4% (24.5%-30.6%) and 13.9% (10.1%-16.9%) among women, respectively, by 2040. The largest increases in the prevalence of overweight and obesity between 2010 and 2040 is expected to be in older ages, and we found a larger relative increase in overweight and obesity in rural areas compared to urban areas. The largest relative increase in overweight and obesity prevalence was forecast to occur at older age groups. CONCLUSION: The overall prevalence of overweight and obesity is expected to increase considerably in India by 2040, with substantial increases particularly among rural residents and older Indians. Detailed predictions of excess weight are crucial in estimating future non-communicable disease burdens and their economic impact. ; This study was supported in part by the Victorian Government's OIS Program, the Australian National Health and Medical Research Council (NHMRC Project no. 1122744), the Murdoch Children's Research Institute, and the Royal Children's Hospital Foundation (grant no. 2017-896). GA was supported by an NHMRC Early Career Fellowship (no. 1090462). MI was supported by the Munz Chair of Cardiovascular Prediction and Prevention. This study acknowledges the use of the following UK JIA cohort collections: The Biologics for Children with Rheumatic Diseases (BCRD) study (funded by Arthritis Research UK Grant 20747). The British Society for Paediatric and Adolescent Rheumatology Etanercept Cohort Study (BSPAR-ETN) (funded by a research grant from the British Society for Rheumatology (BSR). BSR has previously also received restricted income from Pfizer to fund this project). Childhood Arthritis Prospective Study (CAPS) (funded by Versus Arthritis, grant reference number 20542), Childhood Arthritis Response to Medication Study (CHARMS) (funded by Sparks UK, reference 08ICH09, and the Medical Research Council, reference MR/M004600/1), United Kingdom Juvenile Idiopathic Arthritis Genetics Consortium (UKJIAGC). Genotyping of the UK JIA case samples were supported by the Versus Arthritis grants reference numbers 20385 and 21754. This research was funded by the NIHR Manchester Biomedical Research Centre and supported by the Manchester Academic Health Sciences Centre (MAHSC). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We would like to acknowledge the assistance given by IT Services and the use of the Computational Shared Facility at The University of Manchester. Finally, the CHOP data used were funded by an Institute Development Fund to the CAG center from The Children's Hospital of Philadelphia and by NIH grant, U01-HG006830, from the NHGRI-sponsored eMERGE Network.
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