Post-traumatic stress, depression, and anxiety during the 2021 Myanmar con fl ict: a nationwide population-based survey

Background The UN warns that Myanmar faces the ' triple crises ' of mass con fl ict, uncontrolled COVID-19, and economic collapse. Therefore, we aimed to assess the population mental health burden, healthcare needs, and the associated risk factors in Myanmar. Methods We established a nationwide random sample and recruited 1038 adults via random digit dialling from July 3 - Aug 9, 2021, during the ongoing con fl ict since Feb 1, 2021, and surge in SARS-CoV-2 infections. Probable post -traumatic stress disorder (PTSD) was assessed using the PTSD Checklist - Civilian Version. Probable depression and anxiety were assessed using the Patient Health Questionnaire -2 and the Generalized Anxiety Disorder -2. We calculated population attributable fractions for probable mental disorders using multivariable logistic regression models. Based on the mental health burden and healthcare -seeking patterns, we projected the need for mental health services. Findings During the ' triple crises ' , a third of adults in Myanmar (34.9%, 95% CI 32.0 - 37.7) reported a probable mental disorder. Prevalence of probable PTSD, depression, and anxiety were 8.1% (6.6 - 9.7), 14.3% (12.0 - 16.6), and 22.2% (19.7 - 24.7), respectively. We estimated that up to 79.9% (43.8 - 97.9) of probable PTSD was attributable to political stress. This corresponds to 2.1 million (1.1 - 3.2 million) fewer adults with probable PTSD if political stress was removed from the population. The mental health burden could translate into roughly 5.9 million adults seeking mental health services. Interpretation The mental health burden in Myanmar is substantial, and population mental health might only be restored when the three crises have ended. An accelerated peace process is critical to protecting Myanmar ' s population mental health. Funding This research was supported the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. HKU 17606122) and the Michele Tansella Award. Copyright (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY -NC -ND license