The relationship between living arrangements and higher use of hospital care at middle and older ages: to what extent do observed and unobserved individual characteristics explain this association?

BACKGROUND: Previous research has shown that certain living arrangements, such as living alone, are associated with worse health at older ages. We assessed the association between living arrangements and hospital care use among middle-aged and older adults, and investigated to what extent observed and unobserved individual characteristics explain this association. METHODS: Longitudinal Finnish registry data for men and women aged 50-89 years were used for the period 1987-2007. The relationship between living arrangements (based on whether an individual lived with a partner, other adults or alone, and whether they lived with minor/adult children) and heavy hospital care use (i.e., having been in hospital for 8 or more days in a year) was studied. First, we applied logistic regression models and linear probability models controlling for observed time-invariant factors (socioeconomic status measured by education, labour force status, and household income; and marital status), and then individual linear probability models with fixed-effects to further account for unobserved time-invariant individual characteristics in the measurement period. Analyses were done separately for 10 year age-groups. RESULTS: In the logistic regression models, men and women who lived alone had higher crude odds of heavy hospital care use than those living only with their partner. These odds ratios were highest for men and women in the youngest age category (50-59 years, 1.72 and 1.36 respectively) and decreased with age. Adjusting for observed time-invariant socioeconomic status attenuated these odds by 14-40%, but adjusting for marital status did not affect the results. Lower odds were observed among adults aged 50-59 years who lived with their partner and (minor or adult) children. But odds were higher for individuals aged 60-79 years who co-resided with their adult children, regardless of whether they lived with a partner. Adjusting for observed time-invariant factors generally did not change these results. After further adjusting for unobserved time-invariant individual characteristics in the individual fixed-effects models, most of these associations largely attenuated or disappeared, particularly for ages 80-89 years. CONCLUSIONS: The association between living arrangements and higher use of hospital care at middle and older ages is largely explained by socioeconomic disadvantage and unobserved time-invariant individual characteristics.

What's the difference? A gender perspective on understanding educational inequalities in all-cause and cause-specific mortality.

BACKGROUND: Material and behavioural factors play an important role in explaining educational inequalities in mortality, but gender differences in these contributions have received little attention thus far. We examined the contribution of a range of possible mediators to relative educational inequalities in mortality for men and women separately. METHODS: Baseline data (1991) of men and women aged 25 to 74 years participating in the prospective Dutch GLOBE study were linked to almost 23 years of mortality follow-up from Dutch registry data (6099 men and 6935 women). Cox proportional hazard models were used to calculate hazard ratios with 95% confidence intervals, and to investigate the contribution of material (financial difficulties, housing tenure, health insurance), employment-related (type of employment, occupational class of the breadwinner), behavioural (alcohol consumption, smoking, leisure and sports physical activity, body mass index) and family-related factors (marital status, living arrangement, number of children) to educational inequalities in all-cause and cause-specific mortality, i.e. mortality from cancer, cardiovascular disease, other diseases and external causes. RESULTS: Educational gradients in mortality were found for both men and women. All factors together explained 62% of educational inequalities in mortality for lowest educated men, and 71% for lowest educated women. Yet, type of employment contributed substantially more to the explanation of educational inequalities in all-cause mortality for men (29%) than for women (- 7%), whereas the breadwinner's occupational class contributed more for women (41%) than for men (7%). Material factors and employment-related factors contributed more to inequalities in mortality from cardiovascular disease for men than for women, but they explained more of the inequalities in cancer mortality for women than for men. CONCLUSIONS: Gender differences in the contribution of employment-related factors to the explanation of educational inequalities in all-cause mortality were found, but not of material, behavioural or family-related factors. A full understanding of educational inequalities in mortality benefits from a gender perspective, particularly when considering employment-related factors.

Assessing the impact of natural policy experiments on socioeconomic inequalities in health: how to apply commonly used quantitative analytical methods?

BACKGROUND: The scientific evidence-base for policies to tackle health inequalities is limited. Natural policy experiments (NPE) have drawn increasing attention as a means to evaluating the effects of policies on health. Several analytical methods can be used to evaluate the outcomes of NPEs in terms of average population health, but it is unclear whether they can also be used to assess the outcomes of NPEs in terms of health inequalities. The aim of this study therefore was to assess whether, and to demonstrate how, a number of commonly used analytical methods for the evaluation of NPEs can be applied to quantify the effect of policies on health inequalities. METHODS: We identified seven quantitative analytical methods for the evaluation of NPEs: regression adjustment, propensity score matching, difference-in-differences analysis, fixed effects analysis, instrumental variable analysis, regression discontinuity and interrupted time-series. We assessed whether these methods can be used to quantify the effect of policies on the magnitude of health inequalities either by conducting a stratified analysis or by including an interaction term, and illustrated both approaches in a fictitious numerical example. RESULTS: All seven methods can be used to quantify the equity impact of policies on absolute and relative inequalities in health by conducting an analysis stratified by socioeconomic position, and all but one (propensity score matching) can be used to quantify equity impacts by inclusion of an interaction term between socioeconomic position and policy exposure. CONCLUSION: Methods commonly used in economics and econometrics for the evaluation of NPEs can also be applied to assess the equity impact of policies, and our illustrations provide guidance on how to do this appropriately. The low external validity of results from instrumental variable analysis and regression discontinuity makes these methods less desirable for assessing policy effects on population-level health inequalities. Increased use of the methods in social epidemiology will help to build an evidence base to support policy making in the area of health inequalities.

Work-Family Trajectories and the Higher Cardiovascular Risk of American Women Relative to Women in 13 European Countries.

OBJECTIVES: To investigate whether less-healthy work-family life histories contribute to the higher cardiovascular disease prevalence in older American compared with European women. METHODS: We used sequence analysis to identify distinct work-family typologies for women born between 1935 and 1956 in the United States and 13 European countries. Data came from the US Health and Retirement Study (1992-2006) and the Survey of Health, Aging, and Retirement in Europe (2004-2009). RESULTS: Work-family typologies were similarly distributed in the United States and Europe. Being a lone working mother predicted a higher risk of heart disease, stroke, and smoking among American women, and smoking for European women. Lone working motherhood was more common and had a marginally stronger association with stroke in the United States than in Europe. Simulations indicated that the higher stroke risk among American women would only be marginally reduced if American women had experienced the same work-family trajectories as European women. CONCLUSIONS: Combining work and lone motherhood was more common in the United States, but differences in work-family trajectories explained only a small fraction of the higher cardiovascular risk of American relative to European women.

The contribution of national disparities to international differences in mortality between the United States and 7 European countries.

OBJECTIVES: This study examined to what extent the higher mortality in the United States compared to many European countries is explained by larger social disparities within the United States. We estimated the expected US mortality if educational disparities in the United States were similar to those in 7 European countries. METHODS: Poisson models were used to quantify the association between education and mortality for men and women aged 30 to 74 years in the United States, Belgium, Denmark, Finland, France, Norway, Sweden, and Switzerland for the period 1989 to 2003. US data came from the National Health Interview Survey linked to the National Death Index and the European data came from censuses linked to national mortality registries. RESULTS: If people in the United States had the same distribution of education as their European counterparts, the US mortality disadvantage would be larger. However, if educational disparities in mortality within the United States equaled those within Europe, mortality differences between the United States and Europe would be reduced by 20% to 100%. CONCLUSIONS: Larger educational disparities in mortality in the United States than in Europe partly explain why US adults have higher mortality than their European counterparts. Policies to reduce mortality among the lower educated will be necessary to bridge the mortality gap between the United States and European countries.

Marital status, labour force activity and mortality: a study in the USA and six European countries.

AIMS: Labour force activity and marriage share some pathways through which they potentially influence health. In this paper, we examine whether marriage and labour force participation interact in the way they influence mortality in the USA and six European countries. METHODS: We used data from the US National Health Interview Survey linked to the National Death Index, and national mortality registry data for Austria, England/Wales, Finland, Hungary, Norway and Spain (specifically, the Basque country) during 1999-2007, for men and women aged 30-59 years at baseline. We used Poisson regression to estimate both the additive (relative excess risk due to interaction) and multiplicative interactions between marriage and labour force activity on mortality. RESULTS: Labour force inactivity was associated with higher mortality, but this association was stronger for unmarried, rather than married, individuals. Likewise, being unmarried was associated with higher mortality, but this association was stronger for inactive than for active individuals. To illustrate, among US women out of the labour force, being unmarried was associated with a 3.98 times (95%CI 3.28-4.82) higher risk of dying than being married; whereas the relative risk (RR) was 2.49 (95%CI 2.10-2.94), for women who were active in the labour market. Although this interaction between marriage and labour force activity was only significant for women on a multiplicative scale, there was a significant additive interaction for both men and women. The pattern was similar across all countries. CONCLUSIONS: Marriage attenuated the increased mortality risk associated with labour force inactivity; while labour force activity attenuated the mortality risk associated with being unmarried. Our study emphasizes the importance of public health and social policies that improve the health and well-being of unmarried and inactive men and women.

Cohabitation and mental health: Is psychotropic medication use more common in cohabitation than marriage?

Marriage is associated with better mental health. While research on the mental health of cohabiting individuals has increased in recent years, it has yielded mixed results thus far. We assessed whether the mental health of cohabiters is comparable to that of married individuals or those living alone using longitudinal data on psychotropic medication purchases. Panel data from an 11% random sample of the population residing in Finland for the years 1995 to 2007, with annual measurements of all covariates, were used. Ordinary least squares (OLS) models were applied to disentangle the relation between cohabitation and psychotropic medication purchases while controlling for relevant time-varying factors (age, education, economic activity, and number of children), and individual fixed effects (FE) models to further account for unobserved time-invariant individual factors. Our sample consisted of 63,077 men and 61,101 women aged 25 to 39 years in 1995. Descriptive results and the OLS model indicated that the likelihood of purchasing psychotropic medication was lowest for married individuals, higher for cohabiters, and highest for individuals living alone. This difference between cohabiting and married individuals disappeared after controlling for time-varying covariates (percent difference [% diff] for men: 0.3, 95% confidence interval [CI]: -0.0, 0.6; % diff for women: -0.2, 95% CI: -0.6, 0.2). Further controlling for unobserved confounders in the FE models did not change this non-significant difference between cohabiting and married individuals. The excess purchases of psychotropic medication among individuals living alone compared to those cohabiting decreased to 1.2 (95% CI: 1.0, 1.4) and 1.4 (95% CI: 1.1, 1.6) percentage-points in the fully-adjusted FE model for men and women, respectively. Similar results were found for all subcategories of psychotropic medication. In summary, these findings suggested that the mental health difference between cohabiting and married individuals, but not the difference between cohabiting individuals and those living alone, was largely due to selection.