Employment status and perceived health condition: longitudinal data from Italy

Abstract: Countries in recession experience high unemployment rates and a decline in living conditions, which, it has been suggested, negatively influences their populations’ health. The present review examines the recent evidence of the possible association between economic recessions and mental health outcomes. Literature review of records identified through Medline, PsycINFO, SciELO, and EBSCO Host. Only original research papers, published between 2004 and 2014, peer-reviewed, non-qualitative research, and reporting on associations between economic factors and proxies of mental health were considered. One-hundred-one papers met the inclusion criteria. The evidence was consistent that economic recessions and mediators such as unemployment, income decline, and unmanageable debts are significantly associated with poor mental wellbeing, increased rates of common mental disorders, substance-related disorders, and suicidal behaviours. On the basis of a thorough analysis of the selected investigations, we conclude that periods of economic recession are possibly associated with a higher prevalence of mental health problems, including common mental disorders, substance disorders, and ultimately suicidal behaviour. Most of the research is based on cross-sectional studies, which seriously limits causality inferences. Conclusions are summarised, taking into account international policy recommendations concerning the cost-effective measures that can possibly reduce the occurrence of negative mental health outcomes in populations during periods of economic recession.

Abstract: Background: The impact of unemployment and precarious employment on the health of young people is not well understood. However, according to social causation, higher socio-economic positions and th...

Abstract: Sleep and depression are comorbid problems that contribute to the development of chronic medical conditions (CMC) over time. Although racial and gender differences in the bidirectional associations between sleep, depression, and CMC are known, very limited information exists on heterogeneity of the residual effects of sleep problems over depressive symptoms on CMC across race by gender groups. Using a life-course perspective, the present study compared race by gender groups for residual effects of restless sleep over depressive symptoms on CMC. We used data from waves 1 (year 1986), 4 (year 2001), and 5 (year 2011) of the Americans’ Changing Lives Study (ACL). The study followed 294 White men, 108 Black men, 490 White women, and 237 Black women for 25 years. Restless sleep, depressive symptoms (Center for Epidemiological Studies-Depression scale [CES-D]), and number of chronic medical conditions (hypertension, diabetes, chronic lung disease, heart disease, stroke, cancer, and arthritis) were measured in 1986, 2001, and 2011. We employed multi-group cross-lagged modeling, with chronic medical conditions as the outcome and race by gender as the groups. Major group differences were found in the residual effect of restless sleep on CMC over depressive symptoms across race by gender groups. Restless sleep in 2001 predicted CMC 10 years later in 2011 among Black women (standardized adjusted B = .135, P .05). Race by gender heterogeneity in the residual effect of restless sleep over depressive symptoms on CMC over 25 years suggests that comorbid poor sleep and depressive symptoms differently contribute to development of multi-morbidity among subpopulations based on the intersection of race and gender. Thus, interventions that try to prevent comorbid sleep problems and depression as a strategy to prevent medical conditions may benefit from tailoring based on the intersection of race and gender.

Abstract: The unemployed are often in poorer health than their employed counterparts. This cross-sectional correlation is often attributed to a causal effect of unemployment on health. Recent research analyzing longitudinal data often supports alternative explanations, such as spurious correlation and/or selection of unhealthy workers into unemployment (i.e., reverse causality). In this paper, we apply a dynamic panel data estimator (system GMM) to account for both unobserved confounders and reverse causality. Despite some evidence for health selection, we still find strong support for the causality thesis. Furthermore, we show that the adverse health effect is partially explained by the loss of self-perceived social status due to unemployment but not by the loss of household income or social contacts.

Abstract: The present paper gives a contribution to the Italian psychology literature dealing with identity uneasiness of the young adult, which represents a clinically significant life-span phase especially if considered within the critical working situation that compels them to postpone life-markers which are the first signs of entering adultness Those belonging to young adulthood seem uncompleted identities, hanging in between waiting to fulfil one’s life projects and the lack of satisfactory responses from modern society The present research aims to investigate the relationship between personal and social identity, identifying possible similarities and differences between a group of Italian employed adults and a group of unemployed adults A group of 173 Italian young adults, aged between 27 and 34, were recruited to complete an Identifying Information Form constructed ad hoc, the Intolerance of Uncertainty Scale, the Multi-Measure Agnostic Personality Scale, and the Identity Stage Resolution Index Data showed that unemployed young adults have a lower adult and social identity sense than employed ones, who also present an elevated level of ego-strength Furthermore, results underline that having a permanent employment, an elevated self-esteem, and good ego-strength, and internal locus of control are predictive of the adult identity among employed subjects These young people’s difficulties to securely enter a profession is a risk factor for establishing a social identity, as well as, for the mental health; they may even impact one’s awareness, especially because the principle on which post-modern society is based is the demonstration of the value of one’s own resources

Abstract: Using the result that under the null hypothesis of no misspecification an asymptotically efficient estimator must have zero asymptotic covariance with its difference from a consistent but asymptotically inefficient estimator, specification tests are devised for a number of model specifications in econometrics. Local power is calculated for small departures from the null hypothesis. An instrumental variable test as well as tests for a time series cross section model and the simultaneous equation model are presented. An empirical model provides evidence that unobserved individual factors are present which are not orthogonal to the included right-hand-side variable in a common econometric specification of an individual wage equation.

Abstract: We examine the growing number of studies of survey respondents' global self-ratings of health as predictors of mortality in longitudinal studies of representative community samples. Twenty-seven studies in U.S. and international journals show impressively consistent findings. Global self-rated health is an independent predictor of mortality in nearly all of the studies, despite the inclusion of numerous specific health status indicators and other relevant covariates known to predict mortality. We summarize and review these studies, consider various interpretations which could account for the association, and suggest several approaches to the next stage of research in this field.

Abstract: In data with a group structure, incidental parameters are included to control for missing variables. Applications include longitudinal data and sibling data. In general, the joint maximum likelihood estimator of the structural parameters is not consistent as the number of groups increases, with a fixed number of observations per group. Instead a conditional likelihood function is maximized, conditional on sufficient statistics for the incidental parameters. In the logit case, a standard conditional logit program can be used. Another solution is a random effects model, in which the distribution of the incidental parameters may depend upon the exogenous variables.

Abstract: This paper deals with data that has a group structure. A simple example in the context of a linear regression model is E(yitlx, 1S, ar) = P'xit + ai (i = 1, ...,9 N; t = 1, ... T), where there are T observations within each of N groups. The ai are group specific parameters. Our primary concern is with the estimation of f3, a parameter vector common to all groups. The role of the ai is to control for group specific effects; i.e. for omitted variables that are constant within a group. The regression function that does not condition on the group will not in general identify 1: E(yitlx, 13) 0 1'xit. In this case there is an omitted variable bias. An important application is generated by longitudinal or panel data, in which there are two or more observations on each individual. Then the group is the individual, and the ai capture individual differences. If these person effects are correlated with x, then a regression function that fails to control for them will not identify f. In another important application the group is a family, with observations on two or more siblings within the family. Then the ai capture omitted variables that are family specific, and they give a concrete representation to family background. We shall assume that observations from different groups are independent. Then the ai are incidental parameters (Neyman and Scott (1948)), and 0, which is common to the independent sampling units, is a vector of structural parameters. In the application to sibling data, T is small, typically T= 2, whereas there may be a large number of families. Small T and large N are also characteristic of many of the currently available longitudinal data sets. So a basic statistical issue is to develop an estimator for j that has good properties in this case. In particular, the estimator ought to be consistent as N -> ac for fixed T. It is well-known that analysis of covariance in the linear regression model does have this consistency property. The problem of finding consistent estimators in other models is non-trivial, however, since the number of incidental parameters is increasing with sample size. We shall work with the following probability model: Yit is a binary variable with

Abstract: The authors used theoretical models to organize the diverse unemployment literature, and meta-analytic techniques were used to examine the impact of unemployment on worker well-being across 104 empirical studies with 437 effect sizes. Unemployed individuals had lower psychological and physical well-being than did their employed counterparts. Unemployment duration and sample type (school leaver vs. mature unemployed) moderated the relationship between mental health and unemployment, but the current unemployment rate and the amount of unemployment benefits did not. Within unemployed samples, work-role centrality, coping resources (personal, social, financial, and time structure), cognitive appraisals, and coping strategies displayed stronger relationships with mental health than did human capital or demographic variables. The authors identify gaps in the literature and propose directions for future unemployment research.