Educational inequalities in mortality amenable to healthcare. A comparison of European healthcare systems.

BACKGROUND: Educational inequalities in health and mortality in European countries have often been studied in the context of welfare regimes or political systems. We argue that the healthcare system is the national level feature most directly linkable to mortality amenable to healthcare. In this article, we ask to what extent the strength of educational differences in mortality amenable to healthcare vary among European countries and between European healthcare system types. METHODS: This study uses data on mortality amenable to healthcare for 21 European populations, covering ages 35-79 and spanning from 1998 to 2006. ISCED education categories are used to calculate relative (RII) and absolute inequalities (SII) between the highest and lowest educated. The healthcare system typology is based on the latest available classification. Meta-analysis and ANOVA tests are used to see if and how they can explain between-country differences in inequalities and whether any healthcare system types have higher inequalities. RESULTS: All countries and healthcare system types exhibited relative and absolute educational inequalities in mortality amenable to healthcare. The low-supply and low performance mixed healthcare system type had the highest inequality point estimate for the male (RII = 3.57; SII = 414) and female (RII = 3.18; SII = 209) population, while the regulation-oriented public healthcare systems had the overall lowest (male RII = 1.78; male SII = 123; female RII = 1.86; female SII = 78.5). Due to data limitations, results were not robust enough to make substantial claims about typology differences. CONCLUSIONS: This article aims at discussing possible mechanisms connecting healthcare systems, social position, and health. Results indicate that factors located within the healthcare system are relevant for health inequalities, as inequalities in mortality amenable to medical care are present in all healthcare systems. Future research should aim at examining the role of specific characteristics of healthcare systems in more detail.

The use of complementary and alternative medicine (CAM) in Europe.

BACKGROUND: While the use of complementary and alternative medicine (CAM) has become increasingly popular in western societies, we do not understand why CAM use is more frequent in some countries than in others. The aim of this article is to examine the determinants of CAM use at the individual and country-level. METHODS: Logistic multilevel regressions were applied analyzing data from 33,371 respondents in 21 European countries (including Israel) from the seventh round of the European Social Survey. We examined CAM in terms of overall use and also dichotomized treatments into physical and consumable subgroups. RESULTS: At the individual level, we found CAM use to be associated with a range of socioeconomic, demographic and health indicators. At the country level, we found that countries' health expenditures were positively related to the prevalence of overall and physical CAM treatments. CONCLUSIONS: A common predictor for CAM use, both at the individual (in terms of education and financial strain) and country-level (in terms of health expenditures per capita), is greater resources.

Subjective perceptions of unmet need for health care in Europe among social groups: Findings from the European social survey (2014) special module on the social determinants of health.

Background: Unmet need can be defined as the individually perceived subjective differences between services judged necessary to deal with health problems and the services actually received. This study examines what factors are associated with unmet need, as well as how reasons for unmet need are distributed across socioeconomic and demographic groups in Europe. Methods: Multilevel logistic regression models were employed using data from the 7th round of the European Social Survey, on people aged 25­75. Self-reported unmet need measured whether respondents had been unable to get medical consultation or treatment in the last 12 months. Reasons for unmet need were grouped into three categories: availability, accessibility and acceptability. Health status was measured by self-reported health, non-communicable diseases and depressive symptoms. Results: Two-thirds of all unmet need were due waiting lists and appointment availability. Females and young age groups reported more unmet need. We found no educational inequalities, while financial strain was found to be an important factor for all types of unmet need for health care in Europe. All types of health care use and poor health were associated with unmet need. Low physician density and high out-of-pocket payments were found to be associated with unmet need due to availability. Conclusion: Even though health care coverage is universal in many European welfare states, financial strain appeared as a major determinant for European citizens' access to health care. This may suggest that higher income groups are able to bypass waiting lists. European welfare states should, therefore, intensify their efforts in reducing barriers for receiving care.

Informal care in Europe: findings from the European Social Survey (2014) special module on the social determinants of health.

Background: Against the background of a rising demand for informal care in European societies, this study sets out to provide descriptive information by gender on (i) prevalence rates of (intensive) informal caregiving, (ii) characteristics of (intensive) informal caregivers and (iii) consequences of (intensive) informal caregiving in terms of mental well-being. Results: On average, 34.3% of the population in 20 European countries were informal caregivers and 7.6% were intensive caregivers (providing care for minimum 11 h a week). Countries with high numbers of caregivers had low numbers of intensive caregivers. Caregiving was most prevalent among women, 50­59 year olds, non-employed­especially those doing housework­and religious persons. Determinants of providing care hardly differed by gender. Caregivers, especially female and intensive caregivers, reported lower mental well-being than non-caregivers. Conclusions: Our results suggest support for both crowding-in and crowding-out effects of the welfare state. Middle-aged women may become increasingly time squeezed as they are likely to be the first to respond to higher demands for informal care, while they are also the major target groups in employment policies aiming for increased labour market participation. Caregivers, and especially female and intensive caregivers, report lower levels of mental well-being. Supportive policies such as respite care or training and counselling may therefore be needed in order to sustain informal care as an important resource of our health care systems.

Exploring the differences in general practitioner and health care specialist utilization according to education, occupation, income and social networks across Europe: findings from the European social survey (2014) special module on the social determinants of health.

Background: Low socioeconomic position (SEP) tends to be linked to higher use of general practitioners (GPs), while the use of health care specialists is more common in higher SEPs. Despite extensive literature in this area, previous studies have, however, only studied health care use by income or education. The aim of this study is, therefore, to examine inequalities in GP and health care specialist use by four social markers that may be linked to health care utilization (educational level, occupational status, level of financial strain and size and frequency of social networks) across 20 European countries and Israel. Methods: Logistic regression models were employed using data from the seventh round of the European Social Survey; this study focused upon people aged 25­75 years, across 21 countries. Health care utilization was measured according to self-reported use of GP or specialist care within 12 months. Analyses tested four social markers: income (financial strain), occupational status, education and social networks. Results: We observed a cross-national tendency that countries with higher or equal probability of GP utilization by lower SEP groups had a more consistent probability of specialist use among high SEP groups. Moreover, countries with inequalities in GP use in favour of high SEP groups had comparable levels of inequalities in specialist care utilization. This was the case for three social markers (education, occupational class and social networks), while the pattern was less pronounced for income (financial strain). Conclusion: There are significant inequalities associated with GP and specialist health care use across Europe­with higher SEP groups more likely to use health care specialists, compared with lower SEP groups. In the context of health care specialist use, education and occupation appear to be particularly important factors.