Population attributable fractions of psychiatric disorders for suicide in low and middle-income countries: a systematic review and meta-analysis

Background: Low and middle-income countries (LMICs) have a high burden of suicide with limited resources. The population attributable fraction (PAF) is a valuable tool to help policymakers prioritise suicide prevention activities. Objectives: To estimate the PAFs of psychiatric morbidity in suicide in LMICs. Methods: We searched MEDLINE, Embase, and PsycINFO for empirical studies assessing the prevalence of psychiatric disorders among suicide in LMICs. This is an update and extension of a previous review. We meta-analysed estimates of associations, and calculated PAFs with 95% confidence intervals (CI) for different psychiatric disorders in relation to suicide. Publication bias was assessed using contour plots. Results: 14 studies which met our eligibility criteria were included. Five studies were published from China, 13 were case-control studies, and all the studies gathered data between 2000 and 2021. The studies assessed 2132 suicides. Estimates from 10 reasonable quality studies contributed to our meta-analysis. The PAF was 62.1% (95% CI 48.5%-73.6%) for any psychiatric disorder, 28.4% (12.7%-50.1%) for mood disorder, and 23.0% (9.7%-42.8%) for depression. There was substantial heterogeneity in association estimates for these exposures between included studies. PAFs ranged between 1.6% and 7.6% for all other psychiatric disorder categories identified. Contour plots indicated publication bias. Conclusions: Treating psychiatric disorders could reduce the incidence of suicide by more than a half in some LMICs. Our findings need to be interpreted with caution due to data not being available from 94% of LMICs and evidence of publication bias which would lead to overestimations in PAF estimates.