Ecological study of the association between mental illness with human development, income inequalities and unemployment across OECD countries. Issue 4 (20th April 2020)

• Record Type: Journal Article
• Authors: Barbalat, Guillaume; Franck, Nicolas
• Is Part Of: BMJ open. Volume 10:Issue 4(2020)
• Publication Date: 2020-04-20
• Subjects: mental health -- epidemiology -- social medicine; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2019-035055
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Objectives: Recent studies have demonstrated worsened mental health in relatively highly developed countries impacted by social inequalities and unemployment. Here, we investigate (1) whether mental health issues are differently or similarly affected by these social factors and (2) whether their effects on mental health are related or unrelated to each other. Setting: Analysis at the country level among Organization for Economic Cooperation and Development (OECD) countries (n=36). Data on social indicators were collected from OECD and the United Nations Development Programme databases. Data on the prevalence of mental issues were obtained from the Institute for Health Metrics and Evaluation's Global Burden of Disease study 2017. Participants: No involvement of participants. Primary and secondary outcome measures: Using linear regression models, we investigated the relative contribution played by human development (as measured by the Human Development Index (HDI)), social inequalities (Gini index) and unemployment (unemployment rate) on the prevalence of 10 mental health issues. We then measured the relationship between the socioeconomic factors' effects on mental issues using 2×2 Pearson's correlation test and principal component analysis. Results: First, the overall effect of each socioeconomic factor on a combination of mental health disorders was large (r range: 0.51 to 0.76; p<0.002). However, the influence of social factors on mental health was relative to each mental issue (r range: −0.34 to 0.74). Second, the socioeconomic factors' effects on mental health showed strong interdependence (rHDI-Gini =0.93, rHDI-unemploy =0.81, runemploy-Gini =0.84; p<0.001. Principal component analysis demonstrated that the first principal component of the three variables (rHDI, rGini, runemploy ) explained 91.5% of the variance. Conclusion: These results implore a reanalysis of the socioeconomic determinants of mental health where (1) the heterogeneity of mental health issues would be taken into account and (2) each socioeconomic indicator's effect would be analysed and interpreted in conjunction with the others.