This article analyzes (within the conceptual frame defined in the previous article) the impact of political variables such as time of government by political parties (social democratic, Christian democratic or conservative, liberal, and ex-dictatorial that have governed the OECD countries during the 1950–1998 period) and their electoral support on (1) redistributional policies in the labor market and in the welfare state; (2) the income inequalities measured by Theil and Gini indexes; and (3) health indicators, such as infant mortality and life expectancy. This analysis is carried out statistically by a bivariate and a multivariate analysis (a pooled cross-sectional study). Both analyses show that political variables play an important role in defining how public and social policies determine the levels of inequalities and affect the level of infant mortality. In general, political parties more committed to redistributional policies, such as social democratic parties, are the most successful in reducing inequalities and improving infant mortality. Less evidence exists, however, on effects on life expectancy. The article also quantifies statistically the relationship between the political and the policy variables and between these variables and the dependent variables—that is, the health indicators.

We examine to what extent the effect of early-life conditions (health and socioeconomic status) on health in later life is mediated by educational attainment and life-course trajectories (fertility, partnership, employment). Using data from the Survey of Health, Ageing and Retirement in Europe (N = 12,034), we apply, separately by gender, multichannel sequence analysis and cluster analysis to obtain groups of similar family and employment histories. The KHB method is used to disentangle direct and indirect effects of early-life conditions on health. Early-life-conditions indirectly impact on health in later life as result of their influence on education and family and employment trajectories. For example, between 22% and 42% of the effect of low parental socio-economic status at childhood on the three considered health outcomes at older age is explained by educational attainment for women. Even higher percentages are found for men (35% - 57%). On the contrary, the positive effect of poor health at childhood on poor health at older ages is not significantly mediated by education and life-course trajectories. Education captures most of the mediating effect of parental socio-economic status. More specifically, between 66% and 75% of the indirect effect of low parental socio-economic status at childhood on the three considered health outcomes at older age is explained by educational attainment for women. Again, higher percentages are found for men (86% - 93%). Early-life conditions, especially socioeconomic status, influence family and employment trajectories indirectly through their impact on education. We also find a persistent direct impact of early-life conditions on health at older ages. Our findings demonstrate that early-life experiences influence education and life-course trajectories and health in later life, suggesting that public investments in children are expected to produce long lasting effects on people’s lives throughout the different phases of their life-course.

This keynote chapter provides an overview of research into the relationship between health and gender/sex. Since health has multiple dimensions, several measures are needed to capture variations by gender and the use of multiple measures can help us better understand the underlying explanations for gender differences. Although life expectancy and mortality are the most extreme measures of health, relative to most other health metrics they are more amenable to accurate measurement, and are more comparable across countries and over time. We start with a review of the existing literature on sex differences in survival followed by a review of the empirical evidence on gender differences in objective and subjective health. Data on objective health are collected through physical performance tests or cognitive tests, or are based on medical diagnoses that are either recoded in administrative databases or collected through self-reports of diagnoses made by physicians. Subjective health measures strongly depend on individual perceptions that can be modified by contextual factors (socioeconomic, cultural, gender roles, etc.) and awareness of objective health status. We focus on three main subjective health indicators: self-perceived health, functional status, and health-related quality of life (HRQOL). These indicators have become core components of epidemiological, social, and economic research. Later in this chapter, we review the most frequently cited explanations for gender differences in health and mortality, grouping them into the following categories: biological (genetic and hormonal), lifestyle factors (tobacco and alcohol consumption, diet, and physical activity), and social profiles (education and employment). Finally, we conclude by providing possible directions for future research in this area.

The majority of empirical studies focus on a single Social Determinant of Health (SDH) when analysing health inequalities. We go beyond this by exploring how the combination of education (micro level) and household arrangements (mezzo level) is associated with self-perceived health. Our data source is the 2014 cross-sectional data from the European Survey of Living Conditions (EU-SILC). We calculate the predicted probabilities of poor self-perceived health for the middle-aged European population (30–59 years) as a function of the combination of the two SDHs. This is done separately for five European country groups (dual-earner; liberal; general family support; familistic; and post-socialist transition) and gender. We observe a double health gradient in all the country groups: first, there is a common health gradient by education (the higher the education, the lower the probability of poor health); second, household arrangements define a health gradient within each educational level according to whether or not the individual lives with a partner (living with a partner is associated with a lower probability of poor health). We observe some specificity in this general pattern. Familistic and post-socialist transition countries display large differences in the predicted probabilities according to education and household arrangements when compared with the other three country groups. Familistic and post-socialist transition countries also show the largest gender differences. Health differences in European populations seem to be defined, first, by education and, second, by living or not living with a partner. Additionally, different social contexts (gender inequalities, educational profile, etc.) in European countries change the influences on health of both the SDHs for both women and men.

Self-perceived health is a subjective health outcome that summarizes all the health conditions and is widely used in population health studies. Yet, despite its well-known relationship with survival, it is still unclear as to which health conditions are actually taken into account when making an individual assessment of one's own health. The aim of this paper is to assess the influence of four objective health conditions – IADLs, ADLs, chronic diseases, and depression – in predicting self-perceived health among Europeans by age group (50–64 and 65–79) and by sex.

The loss of a spouse/partner is a major stressor, undermining one’s mental health, especially in mid-life and old age. Social ties are key moderators of the impact of bereavement, serving to enhance psychological resilience and facilitating social engagement and access to resources. Our aim was to explore the association between depression levels and the interaction between the composition of, and level of satisfaction with, social networks among women who have lost their husband. The study was undertaken from a cross-national perspective, examining women throughout Europe. We used data from the SHARE Survey (sixth wave; N = 6,820). Using linear regression models, we find negative evaluations of social relations influenced the mental health of European widows, mostly when relatives exclusively composed their social network. The perceived quality of that network had more impact on the mental health of older widows in Northern and Western European countries than in their Southern and Eastern counterparts.