Terje A. Eikemo

Welfare state regimes, unemployment and health: a comparative study of the relationship between unemployment and self-reported health in 23 European countries

Background: The relationship between unemployment and increased risk of morbidity and mortality is well established. However, what is less clear is whether this relationship varies between welfare states with differing levels of social protection for the unemployed. Methods: The first (2002) and second (2004) waves of the representative cross-sectional European Social Survey (37 499 respondents, aged 25–60 years). Employment status was main activity in the last 7 days. Health variables were self-reported limiting long-standing illness (LI) and fair/poor general health (PH). Data are for 23 European countries classified into five welfare state regimes (Scandinavian, Anglo-Saxon, Bismarckian, Southern and Eastern). Results: In all countries, unemployed people reported higher rates of poor health (LI, PH or both) than those in employment. There were also clear differences by welfare state regime: relative inequalities were largest in the Anglo-Saxon, Bismarckian and Scandinavian regimes. The negative health effect of unemployment was particularly strong for women, especially within the Anglo-Saxon (ORLI 2.73 and ORPH 2.78) and Scandinavian (ORLI 2.28 and ORPH 2.99) welfare state regimes. Discussion: The negative relationship between unemployment and health is consistent across Europe but varies by welfare state regime, suggesting that levels of social protection may indeed have a moderating influence. The especially strong negative relationship among women may well be because unemployed women are likely to receive lower than average wage replacement rates. Policy-makers’ attention therefore needs to be paid to income maintenance, and especially the extent to which the welfare state is able to support the needs of an increasingly feminised European workforce.

Health inequalities according to educational level in different welfare regimes: a comparison of 23 European countries

The object of this study was to determine whether the magnitude of educational health inequalities varies between European countries with different welfare regimes. The data source is based on the first and second wave of the European Social Survey. The first health indicator describes peoples mental and physical health in general, while the second reports cases of any limiting longstanding illness. Educational inequalities in health were measured as the difference in health between people with an average number of years of education and people whose educational years lay one standard deviation below the national average. Moreover, South European welfare regimes had the largest health inequalities, while countries with Bismarckian welfare regimes tended to demonstrate the smallest. Although the other welfare regimes ranked relatively close to each other, the Scandinavian welfare regimes were placed less favourably than the Anglo-Saxon and East European. Thus, this study shows an evident patterning of magnitudes of health inequalities according to features of European welfare regimes. Although the greater distribution of welfare benefits within the Scandinavian countries are likely to have a protective effect for disadvantaged cities in these countries, other factors such as relative deprivation and class-patterned health behaviours might be acting to widen health inequalities.

Welfare state regimes and differences in self-perceived health in Europe: a multilevel analysis.

The aim of this study was to determine the degree to which welfare state regime characteristics explained the proportional variation of self-perceived health between European countries, when individual and regional variation was accounted for, by undertaking a multilevel analysis of the European Social Survey (2002 and 2004). A total of 65,065 individuals, from 218 regions and 21 countries, aged 25 years and above were included in the analysis. The health outcomes related to peoples own mental and physical health, in general. The study showed that almost 90% of the variation in health was attributable to the individual-level, while approximately 10% was associated with national welfare state characteristics. The variation across regions within countries was not significant. Type of welfare state regime appeared to account for approximately half of the national-level variation of health inequalities between European countries. People in countries with Scandinavian and Anglo-Saxon welfare regimes were observed to have better self-perceived general health in comparison to Southern and East European welfare regimes.

Welfare state regimes and income related health inequalities: a comparison of 23 European countries

OBJECTIVE The objective of this study was to determine whether the magnitude of income-related health inequalities varies between welfare regimes (Scandinavian, Anglo-Saxon, Bismarckian, Southern and Eastern). Specifically, it examined whether the Scandinavian welfare state regime has smaller income-based health inequalities than the other welfare state regimes. METHODS The first (2002) and second (2004) waves of the representative cross-sectional European Social Survey (ESS), which comprised more than 80 000 respondents, were used to analyse income inequalities (relative health difference between the first and third income tertile) in self-reported health (general health, limiting longstanding illness) amongst those aged 25 or more. Data related to 23 European countries classified into five welfare state regimes. The study controlled for age and adjusted for educational attainment. RESULTS When comparing the health of the first income tertile with the third, the Scandinavian countries only seemed to hold an intermediate position: they did not have the smallest, or the largest, health inequalities. However, the Anglo-Saxon welfare states had the largest income-related health inequalities for both men and women, while countries with Bismarckian welfare states tended to demonstrate the smallest. This pattern was unchanged after controlling for educational attainment. However, education seemed to explain the largest part of income-related health inequalities in the Southern regime. CONCLUSION This study shows that the magnitudes of income-related health inequalities indeed vary by welfare state regime. However, this variation was not always in the direction expected as the Scandinavian countries did not exhibit the smallest health inequalities.

The welfare state: a glossary for public health

Recently, there has been a surge in comparative social epidemiology, and a sizeable amount of this has examined the relation between different aspects of the welfare state and population health. Such research draws strongly, though usually implicitly, on welfare state theories and concepts. In this glossary, we explicitly define these concepts in order to enable more researchers, practitioners and policy-makers to engage with and contribute to this exciting and fruitful area of public health research.

Trends in inequalities in premature mortality: a study of 3.2 million deaths in 13 European countries

Background Over the last decades of the 20th century, a widening of the gap in death rates between upper and lower socioeconomic groups has been reported for many European countries. For most countries, it is unknown whether this widening has continued into the first decade of the 21st century. Methods We collected and harmonised data on mortality by educational level among men and women aged 30–74 years in all countries with available data: Finland, Sweden, Norway, Denmark, England and Wales, Belgium, France, Switzerland, Spain, Italy, Hungary, Lithuania and Estonia. Results Relative inequalities in premature mortality increased in most populations in the North, West and East of Europe, but not in the South. This was mostly due to smaller proportional reductions in mortality among the lower than the higher educated, but in the case of Lithuania and Estonia, mortality rose among the lower and declined among the higher educated. Mortality among the lower educated rose in many countries for conditions linked to smoking (lung cancer, women only) and excessive alcohol consumption (liver cirrhosis and external causes). In absolute terms, however, reductions in premature mortality were larger among the lower educated in many countries, mainly due to larger absolute reductions in mortality from cardiovascular disease and cancer (men only). Despite rising levels of education, population-attributable fractions of lower education for mortality rose in many countries. Conclusions Relative inequalities in premature mortality have continued to rise in most European countries, and since the 1990s, the contrast between the South (with smaller inequalities) and the East (with larger inequalities) has become stronger. While the population impact of these inequalities has further increased, there are also some encouraging signs of larger absolute reductions in mortality among the lower educated in many countries. Reducing inequalities in mortality critically depends upon speeding up mortality declines among the lower educated, and countering mortality increases from conditions linked to smoking and excessive alcohol consumption such as lung cancer, liver cirrhosis and external causes.

A balancing act? Work–life balance, health and well-being in European welfare states

BACKGROUND Recent analyses have shown that adverse psychosocial working conditions, such as job strain and effort-reward imbalance, vary by country and welfare state regimes. Another work-related factor with potential impact on health is a poor work-life balance. The aims of this study are to determine the association between a poor work-life balance and poor health across a variety of European countries and to explore the variation of work-life balance between European countries. METHODS Data from the 2010 European Working Conditions Survey were used with 24,096 employees in 27 European countries. Work-life balance is measured with a question on the fit between working hours and family or social commitments. The WHO-5 well-being index and self-rated general health are used as health indicators. Logistic multilevel models were calculated to assess the association between work-life balance and health indicators and to explore the between-country variation of a poor work-life balance. RESULTS Employees reporting a poor work-life balance reported more health problems (Poor well-being: OR = 2.06, 95% CI = 1.83-2.31; Poor self-rated health: OR = 2.00, 95% CI = 1.84-2.17). The associations were very similar for men and women. A considerable part of the between-country variation of work-life balance is explained by working hours, working time regulations and welfare state regimes. The best overall work-life balance is reported by Scandinavian men and women. CONCLUSION This study provides some evidence on the public health impact of a poor work-life balance and that working time regulations and welfare state characteristics can influence the work-life balance of employees.

Income-related health inequalities in the Nordic countries: examining the role of education, occupational class, and age.

Numerous studies have concluded that peoples socioeconomic position is related to mortality and morbidity, but that the strength of this association varies considerably both within and between European regions. This has spurred several researchers to more closely examine educational and occupational gradients in health in the Nordic countries to clarify the causes of cross-national differences. However, comparable studies using income as an indicator of socioeconomic position are still lacking. This study uses recent and highly comparable data to fill this gap. The aim of this study is threefold. First, we ask to what extent there is an income gradient in health in the Nordic countries, and to what extent the association differs between these countries. Second and third, we examine whether differences in the attenuation of the income gradient by education and occupational class, and age-specific differences between countries, may act as explanations for differences in the income gradient between the Nordic countries. The data source are three waves of the European Social Survey (ESS, 2002/2004/2006), which included 17,801 people aged 25 and over from Denmark, Finland, Norway, and Sweden. Two subjective health measures (physical/mental self reported health and limiting longstanding illness) were analysed by means of logistic regression. The results show that, in all countries, people reported significantly better health and were less likely to suffer from longstanding illness as they had a higher income. This association is strongest in Norway and Finland and weakest in Denmark. The income gradient in health, but not country differences in this gradient, is partly explained by education and occupational class. Additionally, the strength of the income gradient in health varies between age groups. The relatively high health inequalities between income groups in Norway and Finland are already visible in the youngest age groups. The results imply that the socioeconomic gradient in health will arguably not be strongly reduced in the near future as a result of cohort replacement, as has been suggested in previous studies. Health policy interventions may be particularly important five to ten years prior to retirement and in early adulthood.

How can inequalities in mortality be reduced? A quantitative analysis of 6 risk factors in 21 european populations

Background Socioeconomic inequalities in mortality are one of the greatest challenges for health policy in all European countries, but the potential for reducing these inequalities is unclear. We therefore quantified the impact of equalizing the distribution of six risk factors for mortality: smoking, overweight, lack of physical exercise, lack of social participation, low income, and economic inactivity. Methods We collected and harmonized data on mortality and risk factors by educational level for 21 European populations in the early 2000s. The impact of the risk factors on mortality in each educational group was determined using Population Attributable Fractions. We estimated the impact on inequalities in mortality of two scenarios: a theoretical upward levelling scenario in which inequalities in the risk factor were completely eliminated, and a more realistic best practice scenario, in which inequalities in the risk factor were reduced to those seen in the country with the smallest inequalities for that risk factor. Findings In general, upward levelling of inequalities in smoking, low income and economic inactivity hold the greatest potential for reducing inequalities in mortality. While the importance of low income is similar across Europe, smoking is more important in the North and East, and overweight in the South. On the basis of best practice scenarios the potential for reducing inequalities in mortality is often smaller, but still substantial in many countries for smoking and physical inactivity. Interpretation Theoretically, there is a great potential for reducing inequalities in mortality in most European countries, for example by equity-oriented tobacco control policies, income redistribution and employment policies. Although it is necessary to achieve substantial degrees of upward levelling to make a notable difference for inequalities in mortality, the existence of best practice countries with more favourable distributions for some of these risk factors suggests that this is feasible.

Educational differences in disability-free life expectancy: a comparative study of long-standing activity limitation in eight European countries

Healthy life expectancy is a composite measure of length and quality of life and an important indicator of health in aging populations. There are few cross-country comparisons of socioeconomic differences in healthy life expectancy. Most of the existing comparisons focus on Western Europe and the United States, often relying on older data. To address these deficiencies, we estimated educational differences in disability-free life expectancy for eight countries from all parts of Europe in the early 2000s. Long-standing severe disability was measured as a Global Activity Limitation Indicator (GALI) derived from the European Union Statistics on Income and Living Conditions (EU-SILC) survey. Census-linked mortality data were collected by a recent project comparing health inequalities between European countries (the EURO-GBD-SE project). We calculated sex-specific educational differences in disability-free life expectancy between the ages of 30 and 79 years using the Sullivan method. The lowest disability-free life expectancy was found among Lithuanian men and women (33.1 and 39.1 years, respectively) and the highest among Italian men and women (42.8 and 44.4 years, respectively). Life expectancy and disability-free life expectancy were directly related to the level of education, but the educational differences were much greater in the latter in all countries. The difference in the disability-free life expectancy between those with a primary or lower secondary education and those with a tertiary education was over 10 years for males in Lithuania and approximately 7 years for males in Austria, Finland and France, as well as for females in Lithuania. The difference was smallest in Italy (4 and 2 years among men and women, respectively). Highly educated Europeans can expect to live longer and spend more years in better health than those with lower education. The size of the educational difference in disability-free life expectancy varies significantly between countries. The smallest and largest differences appear to be in Southern Europe and in Eastern and Northern Europe, respectively.