Predictors of sleep quality subscales among medical university employees in Iran: a Bayesian analysis of cross-sectional data

Abstract

Background: Poor sleep quality is prevalent among medical employees and adversely affects their performance and well-being. Limited evidence exists regarding behavioral, psychological, and health-related risk factors for poor sleep quality in medical university staff. We aimed to assess the sleep quality subscales among Iranian medical university employees, and to analyze their association with behavioral, psychological, and health-related factors. Methods: This cross-sectional analysis utilized baseline data from 1,250 employees at Qazvin University of Medical Sciences who participated in a cohort study conducted between 2021 and 2022. Demographic, behavioral, psychological, and health-related characteristics were assessed in relation to Pittsburgh Sleep Quality Index (PSQI) subscales and effort-reward imbalance (ERI). Participants were selected using a convenience sampling method. Statistical analyses included correlation, chi-square tests, and multinomial Bayesian modeling. Results: Among participants (56.56% male, mean age 40.57 ± 8.01 years) moderate-to-severe difficulties in sleep duration were most prevalent (54.08%), while sleep medication use was least reported (7.5%). ERI credibly associated with increased odds of sleep difficulties across all PSQI subscales (minimum OR for severe duration sleep quality difficulty = 1.78, 95% CrI: [1.02, 2.90]), except sleep medication use. Depression was associated with all PSQI subscales except sleep latency (minimum OR for severe sleep efficiency difficulty = 2.65, 95% CrI: [1.48, 4.38]). Comorbidity (> 2) was linked to sleep difficulties in specific subscales, including subjective sleep quality, sleep latency, sleep disturbances, and sleep medication use (minimum OR for severe sleep efficiency difficulty = 4.39, 95% CrI: [1.14, 12.28]). Conclusion: This first population-based study of Iranian medical employees demonstrates that demographic, behavioral, psychological, and health-related factors differentially affect sleep quality subscales, with ERI emerging as a key risk factor. These findings emphasize the importance of tailored interventions to address workplace stress and promote mental and physical health, aiming to enhance sleep quality and overall well-being among medical employees.