Patterns and predictors of non-communicable disease multimorbidity among older adults in India: evidence from longitudinal ageing study in India (LASI), 2017–2018

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作者
Parul Puri
Shri Kant Singh
机构
[1] International Institute for Population Sciences,Department of Survey Research and Data Analytics
[2] International Institute for Population Sciences,undefined
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关键词
Chronic disease; Dyads; India; Multimorbidity; Multiple chronic conditions; Older adults; Triads;
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摘要
Escalating non-communicable disease multimorbidity rates among older adults is an emerging public health concern in India, but the literature sparsely addresses the epidemiology of multimorbidity. We explore levels, patterns, combinations and predictors of multimorbidity among older adults using information on 59,764 individuals, aged 45 years and older, from the first wave of Longitudinal Ageing Study in India (LASI), 2017–2018. We computed multimorbidity score for sixteen non-communicable diseases to identify frequently occurring morbidity patterns (dyads and triads) and assess the relationship between multimorbidity and selected background characteristics. Near third of the older adult population is affected by multimorbidity, with hypertension, gastrointestinal disorders, musculoskeletal disorders, diabetes and skin diseases being the most common. Policymakers should seek strategies to increase early detection and prevention of chronic diseases, delay the age at onset of disease for those who are not affected and improve management for those affected with multiple disease conditions.
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页码:109 / 128
页数:19
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