Vincent Lorant

Several OECD countries have capped the number of physicians to be licensed to practice. However, a relevant cap must take into account changes in physician activities. We set out to study the transitions leading physicians to leave health care or to stop any activity in health system. These transitions were assessed using a register of medical practice. We studied changes in activity between 1994 and 2002 for about 19,840 physicians who in 1994 were already working for 5 years and were in 2002 less than 65 years old. After 8 years of career, one physician out of 20 were inactive in health system. Some medical specialties such as surgery and radiotherapy had a greater risk of leaving health care while GP's had a lower risk. Gender differences in leaving health system were mostly non-existant in younger age groups but then increased with age. Among physicians aged 55 and over, women were more likely to leave health system. We conclude that the percentage of physicians leaving health care after 5 years of practice is significant and deserve being taken into account for manpower planning and that planning should be aware of that some groups of physicians are more at risk than others to leave health care. Qualitative studies would help understand better this drop out.

Background: Low socio-economic status is associated with a higher prevalence of depression, but it is not yet known whether change in socio-economic status leads to a change in rates of depression.Aims: To assess whether longitudinal change in socio-economic factors affects change of depression level.Method: In a prospective cohort study using the annual Belgian Household Panel Survey (1992–1999), depression was assessed using the Global Depression Scale. Socio-economic factors were assessed with regard to material standard of living, education, employment status and social relationships.Results: A lowering in material standard of living between annual waves was associated with increases in depressive symptoms and caseness of major depression. Life circumstances also influenced depression. Ceasing to cohabit with a partner increased depressive symptoms and caseness, and improvement in circumstances reduced them; the negative effects were stronger than the positive ones.Conclusions: The study showed a clear relationship between worsening socio-economic circumstances and depression.

Background: Social factors have been shown to be predictors of suicide. It is not known whether these factors vary between countries.Aims: To present a first European overview of socio-economic inequalities in suicide mortality among men and women.Method: We used a prospective follow-up of censuses matched with vital statistics in ten European populations. Directly standardised rates of suicide were computed for each country.Results: In men, a low level of educational attainment was a risk factor for suicide in eight out often countries. Suicide inequalities were smaller and less consistent in women. In most countries, the greater the socio-economic disadvantage, the higher is the risk of suicide. The population of Turin evidenced no socio-economic inequalities.Conclusions: Socio-economic inequalities in suicide are a generalised phenomenon in western Europe, but the pattern and magnitude of these inequalities vary between countries. These inequalities call for improved access to psychiatric care for lower socio-economic groups.

Objective: We seek to investigate socio‐economic differences in psychiatric in‐patient care regarding admission, treatment and outcome. Method: This study is undertaken on a comprehensive and exhaustive psychiatric case register of all psychiatric in‐patient care carried out in Belgium in 1997 and 1998 (n=144 754). Results: Lower socio‐economic groups were more likely to be compulsorily admitted, to be cared for in a non‐teaching or psychiatric hospital, to be admitted in a hospital with unexpectedly long average length of stay and to be admitted to a ward with a more severe case‐mix. They were less likely to receive antidepressants and psychotherapies. The improvements in functioning and in symptoms were also less favourable for these groups. The lowest group had a higher risk of dying in the hospital. Conclusion: Psychiatric in‐patient care is associated with moderate socio‐economic differences in access, treatment and outcome. Further research is needed to clarify the causes of such disparities.

Low socioeconomic status (SES) is generally associated with high psychiatric morbidity, more disability, and poorer access to health care. Among psychiatric disorders, depression exhibits a more controversial association with SES. The authors carried out a meta-analysis to evaluate the magnitude, shape, and modifiers of such an association. The search found 51 prevalence studies, five incidence studies, and four persistence studies meeting the criteria. A random effects model was applied to the odds ratio of the lowest SES group compared with the highest, and meta-regression was used to assess the dose-response relation and the influence of covariates. Results indicated that low-SES individuals had higher odds of being depressed (odds ratio = 1.81, p < 0.001), but the odds of a new episode (odds ratio = 1.24, p = 0.004) were lower than the odds of persisting depression (odds ratio = 2.06, p < 0.001). A dose-response relation was observed for education and income. Socioeconomic inequality in depression is heterogeneous and varies according to the way psychiatric disorder is measured, to the definition and measurement of SES, and to contextual features such as region and time. Nonetheless, the authors found compelling evidence for socioeconomic inequality in depression. Strategies for tackling inequality in depression are needed, especially in relation to the course of the disorder.

Study objective: There is an increasing body of evidence about socioeconomic inequality in preventive use, mostly for cancer screening. But as far as needs of prevention are unequally distributed, even equal use may not be fair. Moreover, prevention might be unequally used in the same way as health care in general. The objective of the paper is to assess inequity in prevention and to compare socioeconomic inequity in preventive medicine with that in health care. Design: A cross sectional Health Interview Survey was carried out in 1997 by face to face interview and self administered questionnaire. Two types of health care utilisation were considered (contacts with GPs and with specialists) and four preventive care mostly delivered in a GP setting (flu vaccination, cholesterol screening) or in a specialty setting (mammography and pap smear). Setting: Belgium. Participants: A representative sample of 7378 residents aged 25 years and over (participation rate: 61%). Outcome measure: Socioeconomic inequity was measured by the HI_wvp index , which is the difference between use inequality and needs inequality. Needs was computed as the expected use by the risk factors or target groups. Main results: There was significant inequity for all medical contacts and preventive medicine. Medical contacts showed inequity favouring the rich for specialist visits and inequity favouring the poor for contacts with GPs. Regarding preventive medicine, inequity was high and favoured the rich for mammography and cervical screening; inequity was lower for flu immunisation and cholesterol screening but still favoured the higher socioeconomic groups. In the general practice setting, inequity in prevention was higher than inequity in health care; in the specialty setting, inequity in prevention was not statistically different from inequity in health care, although it was higher than in the general practice setting. Conclusions: If inequity in preventive medicine is to be lowered, the role of the GP must be fostered and access to specialty medicine increased, especially for cancer screening.