Analysis codes.

Globally, one in five people in post-conflict areas are estimated to be living with a mental health condition. As a key public health issue, these conditions negatively affect individuals, communities, and societies to function after a conflict. Documenting the prevalence of mental health conditions amongst these populations is crucial to prioritise and guide future mental health interventions. This study was the first to use a repeated cross-sectional design and sex-disaggregated analysis, with the aim of estimating the prevalence of depression (PHQ-9) and anxiety (GAD-7) in a post-conflict population of the Kasai Province, Democratic Republic of the Congo. Several domains of Quality of life (WHO-QoL-BREF) were also assessed to gain insight into the relationship between bio-psychosocial stressors and mental health status. Using random cluster sampling, data were collected in two waves from 385 participants, with a one-year interval. The pooled prevalence across both waves was 34.3% for major depression disorder and 26.5% for generalised anxiety disorder. Multivariable linear regression analysis showed that depression and anxiety were both predicted by being female, being of older age, and by experiencing lower physical quality of life, but not by the passing of time. For both mental health outcomes, environmental quality of life served as a significant predictor for women, but not for men. In conclusion, these results suggest that a lack of mental health services and continued exposure to daily stressors are linked to a sustained high prevalence of mental health conditions in our study population. There is a significant need for the development of mental health services in the region. These services should go beyond biomedical interventions and include multi-sectoral approaches that consider the social determinants of (mental) health.