Sex-specific differences in the associated factors of depressive symptoms: a population-based study

Objectives. The study aimed to determine the point prevalence of clinically relevant depressive symptoms among the general adult population of Latvia, and analyze sex-specific associated factors of detected depressive symptoms.

Materials and Methods. The cross-sectional study was conducted on a representative sample of the Latvian adult population (n = 2687), selected using a stratified random sampling method. Computer assisted face-to-face interviews were carried out between November 2019 and March 2020 in the households of the respondents. A 9-item self-evaluation scale Patient Health Questionnaire (PHQ-9) with a cut-off score of 10 was used for detecting clinically relevant depressive symptoms. Respondents were also interviewed using the specially developed questionnaire about socio-demographic and health-related information, and possible comorbid alcohol use disorder was assessed using the MINI International Neuropsychiatric Interview (M.I.N.I.). Binary logistic regression was applied to calculate the odds ratios (OR) for the univariate and multivariate logistic analyses.

Results. The point prevalence of depressive symptoms according to the PHQ-9 was 6.4% (95% CI 5.8–7.6). The point prevalence of depressive symptoms was significantly higher among females [7.7% (95% CI 6.4–9.0)], than among males [4.8% (95% CI 4.2–6.7), p = 0.02]. After adjustment for all independent
variables, being divorced, widowed, or living separately increased the odds of depressive symptoms in males (vs. being married/cohabiting, aOR 2.6, p = 0.02). For females, unfinished primary education (vs. higher education, aOR 5.2, p = 0.001) and economically inactive status (vs. being employed, aOR 2.0, p = 0.03)
were strongly associated with depressive symptoms.

Conclusions. The most significant sex-specific factors associated with depressive symptoms among males were being divorced, widowed, or living separately, and for females it was poor education and economic inactivity.