Depressed during the depression: has the economic crisis affected mental health inequalities in Europe? Findings from the European Social Survey (2014) special module on the determinants of health.

Background: Economic crises constitute a shock to societies with potentially harmful effects to the mental health status of the population, including depressive symptoms, and existing health inequalities. Methods: With recent data from the European Social Survey (2006­14), this study investigates how the economic recession in Europe starting in 2007 has affected health inequalities in 21 European nations. Depressive feelings were measured with the CES-D eight-item depression scale. We tested for measurement invariance across different socio-economic groups. Results: Overall, depressive feelings have decreased between 2006 and 2014 except for Cyprus and Spain. Inequalities between persons whose household income depends mainly on public benefits and those who do not have decreased, while the development of depressive feelings was less favorable among the precariously employed and the inactive than among the persons employed with an unlimited work contract. There are no robust effects of the crisis measure on health inequalities. Conclusion: Negative implications for mental health (in terms of depressive feelings) have been limited to some of the most strongly affected countries, while in the majority of Europe persons have felt less depressed over the course of the recession. Health inequalities have persisted in most countries during this time with little influence of the recession. Particular attention should be paid to the mental health of the inactive and the precariously employed.

In-Work Poverty and Self-Rated Health in a Cohort of Working Germans: A Hybrid Approach for Decomposing Within-Person and Between-Persons Estimates of In-Work Poverty Status.

In this study, we investigated whether self-rated health (SRH) can be predicted by in-work poverty and how between-persons and within-person differences in the poverty status of people who are working contribute to this relationship. We used a logistic random-effects model designed to test within-person and between-persons differences with data from a nationally representative German sample with 19 waves of data collection (1995-2013) to estimate effects of between-persons and within-person differences in working poverty status on poor SRH. Interactions by age and sex were tested, and models controlled for sociodemographic, socioeconomic, and work-related characteristics. We found significant differences in SRH between individuals with different working poverty status but no evidence that within-person differences in working poverty status are associated with poor SRH. The association between in-work poverty and SRH was significantly stronger for women but did not differ significantly by age. All findings were robust when including sociodemographic, socioeconomic, and working characteristics. In this sample of German adults, we found a polarization of poor SRH between the working nonpoor and the working poor but no causal association of within-person differences in working poverty status with SRH.

The Intrinsic Estimator, Alternative Estimates, and Predictions of Mortality Trends: A Comment on Masters, Hummer, Powers, Beck, Lin, and Finch.

In this article, we discuss a study by Masters et al. (2014), published in Demography. Masters and associates estimated age, period, and cohort (APC) effects on U.S. mortality rates between 1959 and 2009 using the intrinsic estimator (IE). We first argue that before applying the IE, a grounded theoretical justification is needed for its fundamental constraint on minimum variance of the estimates. We next demonstrate IE's high sensitivity to the type of dummy parameterization used to obtain the estimates. Finally, we discuss challenges in the interpretation of APC models. Our comments are not restricted to the article in question but pertain generally to any research that uses the IE.

The Non-uniqueness Property of the Intrinsic Estimator in APC Models.

This article explores an important property of the intrinsic estimator that has received no attention in literature: the age, period, and cohort estimates of the intrinsic estimator are not unique but vary with the parameterization and reference categories chosen for these variables. We give a formal proof of the non-uniqueness property for effect coding and dummy variable coding. Using data on female mortality in the United States over the years 1960-1999, we show that the variation in the results obtained for different parameterizations and reference categories is substantial and leads to contradictory conclusions. We conclude that the non-uniqueness property is a new argument for not routinely applying the intrinsic estimator.