RESEARCH REPORTS

Social inequality in the prevalence of depressive disorders

I Andersen, K Thielen, E Nygaard, F Diderichsen

Institute of Public Health Science, Copenhagen University, Centre for Health and Society, Denmark

Dr I Andersen, Institute of Public Health Science, Copenhagen University, Centre for Health and Society, Øster Farimagsgade 5, Postbox 2099, 1014 Copenhagen K, Denmark; inan{at}pubhealth.ku.dk

Background: Uncertainties exist about the strength of the relation between socioeconomic position and depressive disorders. The aim of this study was to investigate the association between education, occupation, employment and income and depressive disorders measured as minor and major depression, as well as antidepressant prescriptions.

Methods: Data were collected from a Danish cross-sectional study collected year 2000, comprising 9254 subjects, 55% women, and aged 36–56 years. Register-based information on education, income and prescription were used.

Results: The prevalence of major depression DSM-IV algorithm was 3.3% among men and women, whereas minor depression and prescriptions revealed statistically significant higher prevalence among females. A social gradient was found for all depressive end-points with the strongest estimates related to major depressive disorder (MDD). The associations were as follows: MDD and low education odds ratio (OR) 2.38 (CI 95% 1.68 to 3.37), MDD and non-employment OR 11.67 (CI 95% 8.06 to 16.89), MDD and low income OR 9.78 (CI 95% 6.49 to 14.74). Education only explained a minor part of the association between non-employment and depressive disorders and no associations were found between education and prescription. This indicates a strong two-way association between depression and non-employment, low-income respectively.

Conclusion: A social gradient in depressive disorders was found regardless of socioeconomic position being measured by education, occupation, employment or income. Severe socioeconomic consequences of depression are indicated by the fact that the associations with non-employment and low income were much stronger than the association with low education.

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