Suchergebnisse

This paper studies the connection between health—especially life expectancy—and unemployment in Hungary. Unemployment and health are recognised as being linked, though the relationship is complex. Unemployment happens to many people mainly in the period of crisis and can be a stressful and depressing time of life. On the one hand, the general state of health of the Hungarian people is worse than justified by the level of economic development. On the other hand, the role of the present economic crisis is to be predicted in the future run of health condition. Moreover, it would probably result health deterioration for those social groups who are most affected by unemployment and poverty.
The study consists of two major structural parts. The theoretical part provides an insight to the specific literature, while the empirical chapter examines the link between socioeconomic indicators, unemployment, and life chances with correlation and regression calculations.

Generalized linear mixed models are widely used for analyzing clustered data. If the primary interest is in regression parameters, one can proceed alternatively, through the marginal mean model approach. In the present study, a joint model consisting of a marginal mean model and a cluster‐specific conditional mean model is considered. This model is useful when both time‐independent and time‐dependent covariates are available. Furthermore our model is semi‐parametric, as we assume a flexible, smooth semi‐nonparametric density of the cluster‐specific effects. This semi‐nonparametric density‐based approach outperforms the approach based on normality assumption with respect to some important features of 'between‐cluster variation'. We employ a full likelihood‐based approach and apply the Monte Carlo EM algorithm to analyze the model. A simulation study is carried out to demonstrate the consistency of the approach. Finally, we apply this to a study of long‐term illness data.

This paper examines and compares U.S. poverty rates on two levels, with data obtained from the decennial censuses of 1960 through 2000. First, rates of poverty for five demographic groups are contrasted within each of the three most populous metropolises of the nation—Chicago, Los Angeles/Long Beach, and New York. Second, rates for each demographic group are contrasted among the three metropolises. The statistical evidence reveals both large differences among the individual demographic groups and also in the trends among the three most populous American cities.

This paper examines trends in mental health among adults in England during the period of economic recovery and austerity following the 2008 'great recession'. We report analysis of data on 17,212 individuals living in England, from the longitudinal Understanding Society Survey (USS). We examined how individual's self-reported mental health over time (2011–2017), related to their changing socio-geographical status. Self-reported mental health is reported in the USS using version 2 of the SF12 Mental Component Summary. Trends in this score (across 5 observations per subject) were categorised into Mental Health Trajectory Groups (MHTGs) using Group Based Trajectory Modelling. We used maximum-likelihood multinomial logit models to estimate for individuals the relative likelihood of belonging to different Mental Health Trajectory categories as compared with a 'base' category, for whom mental health was good and stable throughout the period. We focus on likelihood of belonging to a group showing 'declining' mental health. Predictor variables included individuals' attributes and area conditions in their places of residence (including Office of National Statistics indicators of local employment deprivation and data on average income loss within districts due to welfare benefit reforms, published by the Centre of Regional Economic and Social Research at Sheffield Hallam University, UK). Our results emphasise the multiple socio-geographical 'determinants' likely to be operating on individual mental health. Declining mental health was associated both with conditions at the start of the study period and with social and socio-geographical mobility by the end of the study period. Risks of declining mental health were significantly greater for more deprived individuals and also (controlling for individual attributes) among those living in English neighbourhoods that were already economically disadvantaged at the beginning of the 'great recession' and located in districts where average incomes were most severely impacted by the effects of governmental austerity programmes on welfare benefits.