Pattern and Predicting Risk Factors of Multi-Morbidity in the AzarCohort Population Using Structural Equation Model

Abstract

Background: The co-existence of chronic diseases (CD), a condition defined as multimorbidity (MM), is becoming a major public health issue. Understanding the general framework of MM diseases according to the well-known risk factors can assist in finding direct and indirect relationships among them. Therefore, we aimed to determine pattern and predicting risk factors of multi-morbidity in the Azar Cohort population using Structural Equation Model (SEM). Methods: In this study, the prevalence of MM in 15006 XXX cohort population was evaluated. MM was defined as the co-existence of two or more CDs. The information regarding socio-economic, demographic, sleeping habits, and physical activity were collected by questionnaires. A multi-group SEM was employed to model complex relationships between directly- and indirectly-observed variables. Results: The overall MM was seen in 28.8% of the population. The most prevalent chronic diseases were obesity, hypertension, depression, and diabetes, respectively. Obesity, depression, and diabetes were the most co-occurring CDs in our population. The SEM diagram indicated the overall effect of socio-demographic (predictors) and sleep and physical activity (mediators) on the number of CDs. The number of CDs in the active participants and those who sleep 6.6-7.3 hours/day was lower than the inactive participants and those who sleep ≤6.5 hours/day. Conclusions: According to our results, it seems that the reduction of MM is possible through promoting public health from an early age and for a wide range of socio-economic conditions, provided that the necessary support for general health is offered for the aging population.