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This dissertation aims at analyzing the relationship between socio-economic status (SES) and mental health and care. It attempts to understand how different socio-economic groups present unequal risk of mental disorders and to what extent different socio-economic groups use unequal quantity, type and quality of mental care. Since its earlier beginnings, psychiatric epidemiology has evidenced the association between socio-economic status and mental disorder. However, the numerous prevalence studies addressing depression have yielded inconsistent results. This calls for a thorough investigation of the sources of such heterogeneity. This dissertation attempts to achieve the following objectives: · To unfold methodological and contextual covariates influencing the SES/mental health relationship. · To assess the longitudinal influences of material deprivation on depression. · To assess the extent to which outpatient and inpatient mental care are fairly used. The methodological influences of socio-economic inequalities in mental health were tackled through a meta-analysis of previously published works. We built a database of previous published studies addressing the socio-economic factors of depression prevalence, incidence and persistence in adults population studies and being published in English, French, German and Spanish after 1979. The lower socio-economic group has 80% more prevalence of depression. Inequalities are more acute for persistent depression than for new episode. The results indicated that inequalities are much more pronounced when mental health is looked at from a subjective point of view or in terms of resulting disability. Social inequalities in mental health are also influenced by geographic context. Europe has a gradient 30% less pronounced than North-America. As the period of reference decreased, the gradient rose, suggesting that duration might be an explanatory factor. Geographical analysis of socio-economic inequalities in mortality is carried out with the death certificates of the Belgian National Institute of Statistics (NIS), covering all causes mortality and 11 specific mortality causes, from 1985 to 1993. Spatial concentration was computed through a Moran'I. We compare a simultaneous autoregressive model with a weighted-least-square model. Findings show that spatial concentration is pervasive, that suicide and mortality by liver cirrhosis are among the most correlated causes of death. Getting rid of spatial autocorrelation leads to significant change in the relationship between deprivation and mortality, suggesting the influence of contextual effects on socio-economic inequalities. The difficulty to move from correlation to causation between SES and depression owes partly to the difficulty of disentangling the direct effect of socio-economic status from other –and numerous- confounding factors such as family history, genetic endowment, cognitive abilities, early schooling experience, which, for most of them are rather stable overtime. The longitudinal analysis attempts to estimate the impact of time-varying socio-economic covariates on depression. The results show that material deprivation (and change of) does not affect the level or the risk of depression while social network does slightly. We found much stronger gradient with time invariant socio-economic factors such as educational level. Inequity in outpatient mental care was assessed with the data of the first Belgian Health Interview Survey (HIS), a cross-sectional household-health interview survey carried out in Belgium in 1997. The Minimum Psychiatric Summary, a case register of all psychiatric admissions in Belgium (1997-98), allowed us to carry out the study of inpatient inequalities of mental care. In terms of mental health services uses, inequalities arise in the setting were care is delivered: less well-off use more primary care and less specialised care, are more likely to be admitted in a non-teaching, psychiatric hospitals with long length of stay. The lower the socio-economic groups with mood disorders are less likely to receive the expected treatment such as antidepressant and psychotherapies. Finally, the outcomes of the hospitalisation, in terms of overall functioning and in terms of psychological symptoms are less favourable for the individuals of lower socio-economic status. Part of such unequal outcome is related to unequal treatment. We concluded that inequalities in health should be addressed in their geographical context, that early and stable socio-economic factors are more important than time-varying factors. Horizontal socio-economic inequities arise in the type of care used as well as in the appropriateness of care. However, for a given equal treatment and use, outcome inequalities remain so that it seems relevant to consider socio-economic status as a general vertical equity principle.

Mental Health --- Socioeconomic Factors

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The stability and quality of work careers are major social and economic issues, as the funding of the Nordic welfare state is based on the employment of working-age people and the tax revenue collected from work, production and consumption. This edited volume examines how work careers have developed in specific industrial sectors and at different levels of education in recent decades.The research results are based on the linked employer-employee data of Statistics Finland, company statistics and interviews with industry experts. Careers are examined from several different perspectives, including career stability, employment status, income development, mobility between industries and places of work, and on-the-job training.Based on the results, careers have not weakened between cohorts on average in Finland. Instead of the often-expressed perception of greater job instability, there is high stability of employment combined with high mobility within the careers, owing to the high frequency of changing industries and jobs. However, the career development of women and the low-skilled lags behind that of men and the more highly educated, meaning that equality in earnings has not progressed. Other key findings of the study suggest that adult education differs according to the level of education, and that companies' investments in intangible capital anticipate positive career outcomes for employees.

Career changes. --- Socioeconomic Factors.

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Fertility. --- Socioeconomic Factors. --- Demography

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Breast Neoplasms --- Socioeconomic Factors

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Retirement --- Socioeconomic Factors