Abstract
IntroductionMental disorders are among the most prevalent health problems of the adult population in the world. This study aimed to identify the subgroups of staff based on mental disorders and assess the independent role of metabolic syndrome (MetS) on the membership of participants in each latent class.MethodsThis cross-sectional study was conducted among 694 staff of a military unit in Tehran in 2017. All staff of this military unit was invited to participate in this study. The collected data included demographic characteristics, anthropometric measures, blood pressure, biochemical parameters, and mental disorders. We performed latent class analysis using a procedure for latent class analysis (PROC LCA) in SAS to identify class membership of mental disorders using Symptom Checklist-90.ResultsThree latent classes were identified as healthy (92.7%), mild (4.9%), and severe (2.4%) mental disorders. Having higher age significantly decreased the odds of belonging to the mild class (adjusted OR (aOR = 0.21; 95% confidence interval (CI): 0.05–0.83) compared to the healthy class. Also, obesity decreased the odds of membership in mild class (aOR = 0.10, 95% CI: 0.01–0.92) compared to healthy class. On the other hand, being female increased the odds of being in severe class (aOR = 9.76; 95% CI: 1.35–70.65) class in comparison to healthy class.ConclusionThis study revealed that 7.3% of staff fell under mild and severe classes. Considering educational workshops in the workplace about mental disorders could be effective in enhancing staff’s knowledge of these disorders. Also, treatment of comorbid mental disorders may help reduce their prevalence and comorbidity.
Highlights
Mental disorders are among the most prevalent health problems of the adult population in the world
According to estimations of Burden of Disease Study 2015 (GBD 2015), seven of the top 25 causes of years lived with disability (YLD) globally were mental disorders, with major depressive disorder rated as 2dn and anxiety
Based on the above-mentioned background, this study aimed to identify the subgroups of staff based on mental disorders and assess the independent role of metabolic syndrome (MetS) on the membership of participants in each latent class
Summary
Mental disorders are among the most prevalent health problems of the adult population in the world. Estimates of last year’s prevalence of mental health disorders vary between 9.6 and 27.8% in the general adult population [4,5,6,7,8,9]. Various national studies have already been conducted on the Abbasi-Ghahramanloo et al BMC Psychiatry (2021) 21:513 prevalence of mental health disorders in Iran [13,14,15,16]. The prevalence of these disorders was reported from 17.1 to 23.6% in large national studies in Iran. A recent meta-analysis indicated that the prevalence of mental disorders in studies that used screening tools was 31.03% and in studies that used clinical interviews was 25.42% among Iranian people [17]
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