An association between multi-morbidity and depressive symptoms among Indian adults based on propensity score matching

Keeping in view the cascade of disturbances caused by the co-existence of multi-morbidity and depression among aged population, this study aims to ascertain the independent impact of multi-morbidity as a risk factor for the development of depressive symptoms among adults living in India. The present study utilizes data from the nationally representative survey “Longitudinal Ageing Study in India” (LASI, Wave-1, 2017–2018). The eligible sample size was 62,244 adults aged 45 years and above. Descriptive statistics along with bivariate analysis was used to understand the prevalence of depressive symptoms. Further, binary logistic regression and Propensity Score Matching (PSM) methods were applied to examine the independent effect of multi-morbidity on depressive symptoms while controlling the selected background characteristics. Overall, around one-third respondents had at least one chronic disease and one-fifth had multi-morbidity. The most prevalent chronic disease reported in the sampled population was hypertension followed by diabetes and joint disease. It is observed that older adults with multiple chronic diseases had 77% higher odds of having depressive symptoms as compared to those without a history of chronic disease in the multivariable logistic regression model. Results obtained from PSM indicate that the risk of having depressive symptoms was 3.7% higher for adults with multi- morbidity. Depressive symptom was identified to be associated with a wider range of multiple physical health problems and people with multi-morbidity are at a higher risk of having depressive symptoms. It is imperative that multi-morbidity can be used as a screener for identifying people with depressive symptoms.