Combination of Sociodemographic and Lifestyle Factors that Predict Multimorbidity: Findings from India Using LASI (2017-18) Wave-I

Ajay Kumar , International Institute for Population Sciences
Dr. Suryakant Yadav, international institute for population sciences

India has shown an escalating burden of NCDs together with a sizeable burden of CDs since the early 1990s. The disadvantage of the enormous burden of NCDs is analogous to high inequality in mortality and morbidity. While most research on multimorbidity has been in Western countries, a developing country like India may experience different patterns of multimorbidity clusters, morbidity onsets and survival conditions. The study uses information on 73,396 individuals 45 years and above surveyed in the LASI (Wave 1, 2017-18) India data. The study applies (1) the Kaplan-Meier method to examine the changing survival gradient of morbidities and survival probability of multimorbidity clusters, (2) Network analysis to examine the degree of interaction and relationship among morbidities, (3) Hierarchical clustering to examine the normative and dynamic clusters of multimorbidity, and (4) Random Survival Forest to examine the risk of multimorbidity by socio-economic backgrounds and demographic factors. The study finds that the significant gradient of multimorbidity is in the age group of 55 – 75 years. The median survival probability is lowest for hypertension (74 years). Seven multimorbidity clusters were identified and the degree of centrality was highest for Hypertension followed by Diabetes in the network. The RSF method reveals that the median expected risk of multimorbidity in female (66 years) is significantly higher than in male. The results also provide empirical evidence that individuals with the highest level of education, obesity, and poor childhood health are the crucial factors for the highest risk of multimorbidity at an early age.

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 Presented in Session 29. Flash session Morbidity