Profile and patterns of chronic non-communicable diseases multimorbidity among older adults in India

Parul Puri, International Institute for Population Sciences, Mumbai

In the absence of adequate nationally representative empirical evidence on multimorbidity, the existing health care delivery system is based on a single disease model, which is not adequately oriented to cater to the growing needs of the multimorbid older adult population in India. The study identifies recurrent multimorbidity among the older adult population, using data on 58,975 older adults from the Longitudinal Ageing Study in India, 2020. The study incorporated a list of sixteen non-communicable chronic diseases to identify patterns using latent class analysis. Model fit indices were employed to identify the optimal number of disease clusters, which were labelled on the basis of computed item-response probabilities. The study exhibits five disease patterns, namely 'hypertensive diabetics', 'gastrointestinal disorders', 'metabolic disorders', 'hypertension-musculoskeletal-gastrointestinal disorders ', and 'complex cardio metabolic disorders'. These findings can assist physicians in devising treatment and management strategies for individuals belonging to explicit disease clusters so that they do not accumulate additional chronic conditions. Thus, advocating policies to reorganize the existing healthcare services to accommodate older adults' rising requirements. Alternatively, targeted interventions in the form of equitable prevention strategies are essential to reduce the burden on the country's high-risk 'Relatively Healthy' older adult population.

Keywords: Latent class analysis, Longitudinal studies, Older adults, Health and morbidity

See extended abstract.

  Presented in Session 140. Profiles and Patterns of Chronic Multimorbidity