Determinants of Multimorbidity in Community-dwelling Older Adults: A Decision-tree-based Analysis

Aims and background:The aging population represents a critical group from a public health perspective.This cross-sectional study aims to understand the determinants and health conditions associated with multimorbidity in a sample of community-dwelling older adults.Materials and methods: A sample of 1,100 individuals aged 60 and above was drawn from the population in Dibrugarh district, Assam, India.The highest recorded health conditions and the presence of multiple chronic conditions are identified.A heat map of dyads and triads is generated using the descriptive statistics tool, and factors responsible for the number of health conditions occurring concurrently in the sample are identified through a Classification and Regression Tree (CRT) decision-tree model in IBM SPSS Statistics 27.Results: Among the 25 health conditions reported, hypertension, arthritis, and gastritis graced the top three spots individually.In terms of co-occurring conditions, the most significant dyad was hypertension and diabetes.Hypertension, diabetes, and heart disease constituted the prime triad.As per the decision tree, education, income, and body mass index have been found to influence multimorbidity the most.The model is 70.6% accurate.Conclusion: Noncommunicable diseases (NCDs) dominate the multimorbidity burden in the population studied.Health policies directed toward older adults need to be strengthened to equip them with the changing lifestyles and risk factors associated therewith.Clinical significance: Consideration of sociocultural realities influencing multimorbidity leads to better health outcomes for patients undergoing treatment and targeted preventive interventions for those perceived to be at risk.