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Objective: The clinical symptoms of schizophrenia are associated with serious social, quality of life and functioning alterations. Typically, data on health utilities are not available in clinical studies in schizophrenia. This makes the economic evaluation of schizophrenia treatments challenging. The purpose of this article was to provide a mapping function to predict unobserved utility values in patients with schizophrenia from the available clinical and socio-demographic information.Methods: The analysis was performed using data from EuroSC, a 2-year, multi-centre, cohort study conducted in France (N = 288), Germany (N = 618), and the UK (N = 302), totalling 1208 patients. Utility was calculated based on the EQ-5D questionnaire. The relationships between the utility values and the patients' socio-demographic and clinical characteristics (Positive and Negative Syndrome Scale--PANSS, Calgary Depression Scale for Schizophrenia--CDSS, Global Assessment of Functioning--GAF, extra-pyramidal symptoms measured by Barnes Akathisia Scale-BAS, age, sex, country, antipsychotic type) were modelled using a random and a fixed individual effects panel linear model.Results: The analysis demonstrated the prediction ability of the used parameters for estimating utility measures in patients with schizophrenia. Although there are small variations between countries, the same variables appear to be the key predictors. From a clinical perspective, age, gender, psychopathology, and depression were the most important predictors associated with the EQ-5D.Conclusion: This paper proposed a reliable, robust and easy-to-apply mapping method to estimate EQ-5D utilities based on demographic and clinical measures in schizophrenia. [ABSTRACT FROM AUTHOR]

Background: Neighborhood characteristics are important determinants of individual health and well-being. For example, characteristics such as noise and pollution affect health directly, while other characteristics affect health and well-being by either providing resources (e.g. social capital in the neighborhood), which individuals can use to cope with health problems, or limiting the use thereof (e.g. crime). This also suggests that there might be age differentials in the impact of these characteristics, since individuals at different stages of life might need different resources. However, there is a lack of empirical evidence on age differentials in associations between well-being, health, and neighborhood characteristics.Objective: This paper studies associations between a wide range of neighborhood characteristics with the health and well-being of residents of the greater Berlin area. In particular, we focus on differences in the effects between younger (aged 20-35) and older (aged 60+) residents.Methods: We used data from the Berlin Aging Study II (312 younger and 993 older residents of the Berlin metropolitan area in Germany). We used survey data on health and well-being, combined these with subjective perceptions of the neighborhood, and geo-referenced indicators on the neighborhood, e.g. amenities (public transport, physicians, and hospitals).Results: The results show that access to public transportation is associated with better outcomes on all measures of health and well-being, and social support is associated with higher life satisfaction and better mental health. There are considerable differences between both age groups: while the associations between access to public transport and health and well-being are similar for both age groups, neighborhood social capital shows stronger associations for older residents. However, the difference is not always statistically significant.Conclusion: Having access to services is associated with better health and well-being regardless of age. Local policy makers should focus on lowering barriers to mobility in order to improve the health and well-being of the population. Since the social capital of a neighborhood is associated with better health and well-being among older residents, investments that increase social capital (e.g. community centers) might be warranted in neighborhoods with higher shares of older residents. [ABSTRACT FROM AUTHOR]

This paper investigates the mechanisms behind the health effects of retirement. Using a Regression Discontinuity Design to exploit financial incentives in the German pension system for identification, I find that retirement improves subjective health status and mental health, while also reducing outpatient care utilization. I explore a wide range of health behaviors, time use, and effect heterogeneity as potential mechanisms. Relief from work-related stress and strain, increased sleep duration as well as more frequent physical exercise seem to be key mechanisms through which retirement affects health. [ABSTRACT FROM AUTHOR]