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Epidemiology and predictors of multimorbidity in Kharameh cohort study: A population-based cross-sectional study in
Leila Moftakhar1, Ramin Rezaeianzadeh2, Masoumeh Ghoddusi Johari3
1Student Research Committee Shiraz University of Medical Sciences Shiraz Iran.
Background And Aim:
Multimorbidity is one of the problems and concerns of public health. The aim of this study was to estimate the prevalence and identify the risk factors associated with multimorbidity based on the data of the Kherameh cohort study.
Methods:
This cross-sectional study was performed on 10,663 individuals aged 40-70 years in the south of Iran in 2015 to 2017. Demographic and behavioral characteristics were investigated. Multimorbidity was defined as the coexistence of two or more of two chronic diseases in a person. In this study, the prevalence of multimorbidity was calculated. Logistic regression was used to identify the predictors of multimorbidity.
Results:
The prevalence of multimorbidity was 24.4%. The age-standardized prevalence rate was 18.01% in males and 29.6% in females. The most common underlying diseases were gastroesophageal reflux disease with hypertension (33.5%). Multiple logistic regression results showed that the age of 45-55 years (adjusted odds ratio [ORadj]] = 1.22, 95% confidence interval [CI], 1.07-1.38), age of over 55 years (ORadj = 1.21, 95% CI, 1.06-1.37), obesity (ORadj = 3.65, 95% CI, 2.55-5.24), and overweight (ORadj = 2.92, 95% CI, 2.05-4.14) were the risk factors of multimorbidity. Also, subjects with high socioeconomic status (ORadj = 1.27, 95% CI, 1.1-1.45) and very high level of socioeconomic status (ORadj = 1.53, 95% CI, 1.31-1.79) had a higher chance of having multimorbidity. The high level of education, alcohol consumption, having job, and high physical activity had a protective role against it.
Conclusion:
The prevalence of multimorbidity was relatively high in the study area. According to the results of our study, age, obesity, and overweight had an important effect on multimorbidity. Therefore, determining interventional strategies for weight loss and control and treatment of chronic diseases, especially in the elderly, is very useful.
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