Suicides account for over one million deaths per year worldwide with depression among the most important risk factors. Epidemiological research into the relationship between antidepressant utilization and suicide mortality has shown heterogeneous and contradictory results. Different methodological approaches and limitations could at least partially explain varying results. This is the first study assessing the association of suicide mortality and antidepressant sales across Germany using complex statistical approaches in order to control for possible confounding factors including spatial dependency of data. German suicide counts were analyzed on a district level (n = 402) utilizing ecological Poisson regressions within a hierarchical Bayesian framework. Due to significant spatial effects between adjacent districts spatial models were calculated in addition to a baseline non-spatial model. Models were adjusted for several confounders including socioeconomic variables, quality of psychosocial care, and depression prevalence. Separate analyses were performed for Eastern and Western Germany and for different classes of antidepressants (SSRIs and TCAs). Overall antidepressant sales were significantly negatively associated with suicide mortality in the non-spatial baseline model, while after adjusting for spatially structured and unstructured effects the association turned out to be insignificant. In sub-analyses, analogue results were found for SSRIs and TCAs separately. Suicide risk shows a distinct heterogeneous pattern with a pronounced relative risk in Southeast Germany. In conclusion, the results reflect the heterogeneous findings of previous studies on the association between suicide mortality and antidepressant sales and point to the complexity of this hypothesized link. Furthermore, the findings support tailored suicide preventive efforts within high risk areas.
Keywords: Antidepressants; Bayesian regression; Depression prevalence; Suicide; Suicide prevention.
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