The Population Mean Mood Predicts The Prevalence of Depression in an Australian Context

Abstract

Background: The mean population mood has been demonstrated to strongly correlate with the prevalence of depression in European populations. Mean population mood has, therefore, been proposed as both a metric to measure the impact of population-level interventions to prevent depression and a target for public health policy. Aim: To demonstrate the relationship between mean population mood and the prevalence of depression using Australian data in order to broaden the applicability of this finding to the Australian population. Methods: We used data from the Geelong Osteoporosis Study to assess the relationship between population mean mood and depression. Participants reported mood symptoms via questionnaire (the Hospital Anxiety and Depression Scale or General Health Questionnaire-12). Depression was diagnosed by semi-structured clinical interview ( Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Non-patient Edition). Stratification by age and socio-economic status was used to create subpopulation groups. Socio-economic status was measured using Index of Relative Socio-economic Advantage and Disadvantage quintiles, an area-based measure based on Australian census data and published by the Australian Bureau of Statistics. The mean subpopulation questionnaire scores and subpopulation prevalence of depression were then analysed using regression and predictive models. Results: Mean subpopulation questionnaire scores correlated well with the prevalence of depression across socio-economic status groups in women but not age groups. Questionnaire scores tended to underestimate the prevalence of depression in the young and overestimate it in the elderly. Conclusion: The mean population mood was demonstrated to correlate with the population prevalence of depression in Australia for women, but not for men. Due to the issues of questionnaire validity and sample size in the oldest age groups, the age analysis is unlikely to be a representative of population characteristics. Further work to identify population determinants of mean mood could potentially create policy targets to reduce the prevalence of depression.