Purpose: A needs-based model of health systems planning uses a systematic estimate of service needs for a given population. Our objective was to derive annual prevalence estimates of specific mental disorders in the adult population of British Columbia, Canada and use a novel triangulation approach encompassing multiple data sources and stratifying these estimates by age, sex, and severity to inform Ministry partners, who commissioned this work.
Methods: We performed systematic literature reviews and subsequent meta-analyses to derive an annual prevalence estimate for each mental disorder. We then generated age- and sex-specific estimates by triangulating published epidemiological studies, routinely collected province-wide health administrative data, and nationally representative health survey data sources. The age- and sex-specific estimates were further stratified by severity using the Global Burden of Disease severity distributions and published literature.
Results: Anxiety disorders had the highest annual prevalence estimates (6.93%), followed by depressive disorders (6.42%). All other mental disorders had an annual prevalence of less than 1%. Prevalence estimates were consistently higher in younger age groups. Depressive disorders, anxiety disorders, and eating disorders were higher in women, while estimates for bipolar disorders, schizophrenia, and ADHD were slightly higher in men in younger age groups.
Conclusion: We generated robust annual prevalence estimates stratified by age, sex, and severity using a triangulation approach. Variation by age, sex, and severity implies that these factors need to be considered when planning for mental health services. Our approach is replicable and can be used as a model for needs-based planning in other jurisdictions.
Keywords: Age; Mental disorders; Prevalence; Service planning; Sex.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.