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.