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Variation in Chronic Diseases Across Households, Communities, Districts, and States in India.

Research paper by Suyash S Mishra, Jessica M JM Perkins, Pijush Kanti PK Khan, Rockli R Kim, Sanjay K SK Mohanty, S V SV Subramanian

Indexed on: 23 Oct '19Published on: 22 Oct '19Published in: American Journal of Preventive Medicine



Abstract

Globally, chronic noncommunicable diseases are the leading cause of death and accounted for 6 million deaths in India in 2016. However, the extent to which variation in chronic disease can be attributed to different population levels in India is unknown, as is whether variation in individual-level factors explains outcome variation at different population levels. Cross-sectional data from the District Level Household and Facility Survey 2012-2013 conducted across 21 states, 275 districts, 14,235 villages, 378,487 households, and 1,098,940 individuals aged ≥18 years in India were analyzed in 2018‒2019. Multilevel logistic models were used to partition variation in outcomes and attribute it to individual, household, village, district and state population levels. Outcomes included experiencing respiratory, cardiovascular, musculoskeletal, or eye symptoms; reporting a positive diagnosis by a doctor for chronic heart disease, hypertension, diabetes, or vision problems; and objectively assessed real-time measures of hypertension and diabetes. For reported diagnosis of hypertension or diabetes, a much larger percentage of variation in these outcomes was attributed to differences among households as compared to differences among units within other population levels. However, for objectively measured hypertension and diabetes, variation in these outcomes was important at the village level, followed by variation at the household level. Wealth status was positively associated with respiratory and cardiovascular symptoms, as well as all reported diagnoses and real-time measurements except for vision problems. Inclusion of individual-level sociodemographic variables explained 0%-30% of variation attributed to the household level for most chronic disease symptoms and diagnoses, but almost none at the higher levels. These findings imply that household- and village-level factors explain substantial variation in the prevalence of chronic disease symptoms and reported diagnoses in India. Copyright © 2019 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.