Association of Stressful Life Events With Psychological Problems: A Large-Scale Community-Based Study Using Grouped Outcomes Latent Factor Regression With Latent Predictors Publisher Pubmed



Hassanzadeh A¹ ; Heidari Z¹ ; Feizi A^{1, 2} ; Hassanzadeh Keshteli A^{3, 4} ; Roohafza H^{2, 5} ; Afshar H² ; Adibi P^{4, 6}
Source: Computational and Mathematical Methods in Medicine Published:2017

Abstract

Objective. The current study is aimed at investigating the association between stressful life events and psychological problems in a large sample of Iranian adults. Method. In a cross-sectional large-scale community-based study, 4763 Iranian adults, living in Isfahan, Iran, were investigated. Grouped outcomes latent factor regression on latent predictors was used for modeling the association of psychological problems (depression, anxiety, and psychological distress), measured by Hospital Anxiety and Depression Scale (HADS) and General Health Questionnaire (GHQ-12), as the grouped outcomes, and stressful life events, measured by a self-administered stressful life events (SLEs) questionnaire, as the latent predictors. Results. The results showed that the personal stressors domain has significant positive association with psychological distress (β=0.19), anxiety (β=0.25), depression (β=0.15), and their collective profile score (β=0.20), with greater associations in females (β=0.28) than in males (β=0.13) (all P<0.001). In addition, in the adjusted models, the regression coefficients for the association of social stressors domain and psychological problems profile score were 0.37, 0.35, and 0.46 in total sample, males, and females, respectively (P<0.001). Conclusion. Results of our study indicated that different stressors, particularly those socioeconomic related, have an effective impact on psychological problems. It is important to consider the social and cultural background of a population for managing the stressors as an effective approach for preventing and reducing the destructive burden of psychological problems. © 2017 Akbar Hassanzadeh et al.