Structural equation modeling of associated factors and regional variations in major depressive disorders and generalized anxiety disorders among reproductive-age Bangladeshi women: a nationally representative study
Issued Date
2026-12-01
Resource Type
eISSN
1744859X
Scopus ID
2-s2.0-105027446890
Journal Title
Annals of General Psychiatry
Volume
25
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Annals of General Psychiatry Vol.25 No.1 (2026)
Suggested Citation
Suanrueang P., Peltzer K. Structural equation modeling of associated factors and regional variations in major depressive disorders and generalized anxiety disorders among reproductive-age Bangladeshi women: a nationally representative study. Annals of General Psychiatry Vol.25 No.1 (2026). doi:10.1186/s12991-025-00619-0 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/114720
Title
Structural equation modeling of associated factors and regional variations in major depressive disorders and generalized anxiety disorders among reproductive-age Bangladeshi women: a nationally representative study
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Abstract
Background: The study’s objective was to (1) assess the prevalence among women and associated factors of major depressive disorder (MDD) and generalized anxiety disorder (GAD); (2) identify associated factors and regional variations in the relationship between GAD-7 and PHQ-9 scores; and (3) yield insights to support and strengthen mental health policy and service delivery in Bangladesh. Methods: Data from 19,987 women (aged 15–49 years) who participated in the 2022 Bangladesh Demographic and Health Survey and completed the mental health module were analyzed. Descriptive statistics assessed MDD/GAD prevalence. SEM analyzed factors associated with psychological distress, and regional variations were examined via linear regression. Results: Among 2388 Bangladeshi women aged 15–49 who had MDD and/or GAD, who provided complete responses for all related variables, sociodemographic factors, resource-related determinants, and negative life events were significantly associated with higher levels of depression and anxiety. The path analysis model indicated that sociodemographic factors (β = 0.69), resource-related factors (β = 0.19), and negative life events (β = 0.05) contributed to depression (PHQ score: β = 0.81, p < 0.001) and anxiety (GAD score: β = 0.84, p < 0.001). Age (β = 0.21, p < 0.001) and marital status (β = 0.20, p < 0.001) were the strongest sociodemographic factors associated with psychological distress, while education (β = 0.41, p < 0.001) and wealth status (β = 0.41, p < 0.001) were the most important resource-related factors. The model demonstrated an acceptable to good fit (Chi-square = 240.67, df = 63, RMSEA = 0.050, GFI = 0.967, AGFI = 0.952, and CFI = 0.826). Regionally, Sylhet City indicated the strongest relationship between GAD and MDD (R<sup>2</sup> = 0.567), followed by Khulna (R<sup>2</sup> = 0.543) and Rajshahi (R<sup>2</sup> = 0.508). An R<sup>2</sup> Value of 0.567 indicated that approximately 57% of the variability in MDD score in Sylhet can be explained by GAD score. Conclusion: Path analysis highlighted a multidimensional approach to understanding psychological distress. Sociodemographic, resource factors, and negative life events as determinants collectively serve as associated factors of psychological distress among Bangladeshi females, highlighting the need for culturally tailored interventions with early anxiety screening and coping skills training to improve mental health outcomes.