Search

Background: Within the European Union (EU), substantial efforts are being made to achieve economic and social cohesion, and the reduction of health inequalities between EU regions is integral to this process. This paper is the first to examine how self-reported conditions and non-communicable diseases (NCDs) vary spatially between and within countries. Methods: Using 2014 European Social Survey (ESS) data from 20 countries, this paper examines how regional inequalities in self-reported conditions and NCDs vary for men and women in 174 regions (levels 1 and 2 Nomenclature of Statistical Territorial Units, 'NUTS'). We document absolute and relative inequalities across Europe in the prevalence of eight conditions: general health, overweight/obesity, mental health, heart or circulation problems, high blood pressure, back, neck, muscular or joint pain, diabetes and cancer. Results: There is considerable inequality in self-reported conditions and NCDs between the regions of Europe, with rates highest in the regions of continental Europe, some Scandinavian regions and parts of the UK and lowest around regions bordering the Alps, in Ireland and France. However, for mental health and cancer, rates are highest in regions of Eastern European and lowest in some Nordic regions, Ireland and isolated regions in continental Europe. There are also widespread and consistent absolute and relative regional inequalities in all conditions within countries. These are largest in France, Germany and the UK, and smallest in Denmark, Sweden and Norway. There were higher inequalities amongst women. Conclusion: Using newly available harmonized morbidity data from across Europe, this paper shows that there are considerable regional inequalities within and between European countries in the distribution of self-reported conditions and NCDs. [ABSTRACT FROM AUTHOR]

Background: Health inequalities persist between and within European countries. Such inequalities are usually explained by health behaviours and according to the conditions in which people work and live. However, little is known about the relative contribution of these factors to health inequalities in European countries. This paper aims to investigate the independent and joint contribution of a comprehensive set of behavioural, occupational and living conditions factors in explaining social inequalities in self-rated health (SRH). Method: Data from 21 countries was obtained from the 2014 European Social Survey and examined for respondents aged 25-75. Adjusted rate differences (ARD) and adjusted rate risks (ARR), generated from binary logistic regression models, were used to measure health inequalities in SRH and the contribution of behavioural, occupational and living conditions factors. Result: Absolute and relative inequalities in SRH were found in all countries and the magnitude of socio-economic inequalities varied considerably between countries. While factors were found to differentially contribute to the explanation of educational inequalities in different European countries, occupational and living conditions factors emerged as the leading causes of inequalities across most of the countries, contributing both independently and jointly with behavioural factors. Conclusion: The observed shared effects of different factors to health inequalities points to the interdependent nature of occupational, behavioural and living conditions factors. Tackling health inequalities should be a concentred effort that goes beyond interventions focused on single factors. [ABSTRACT FROM AUTHOR]

Background: Cross-national comparisons of health in European countries provide crucial information to monitor health and disease within and between countries and to inform policy and research priorities. However, variations in estimates might occur when information from cross-national European surveys with different characteristics are used. We compared the prevalence of very good or good self-perceived health across 10 European countries according to three European surveys and investigated which survey characteristics contributed to differences in prevalence estimates. Methods: We used aggregate data from 2004 to 2005 of respondents aged 55-64 years from the European Union Statistics on Income and Living Conditions (EU-SILC), the Survey of Health, Ageing and Retirement in Europe (SHARE) and the European Social Survey (ESS). Across the surveys, self-perceived health was assessed by the same question with response options ranging from very good to very bad. Results: Despite a good correlation between the surveys (intraclass correlation coefficient: 0.77), significant differences were found in prevalence estimates of very good or good self-perceived health. The survey response, sample size and survey mode contributed statistically significantly to the differences between the surveys. Multilevel linear regression analyses, adjusted for survey characteristics, showed a higher prevalence for SHARE (+6.96, 95% CIs: 3.14 to 10.8) and a lower prevalence (-3.12; 95% CIs: -7.11 to 0.86) for ESS, with EU-SILC as the reference survey. Conclusion: Three important health surveys in Europe showed substantial differences for presence of very good or good self- perceived health. These differences limit the usefulness for direct comparisons across studies in health policies for Europe. [ABSTRACT FROM AUTHOR]

Background: Studying social disparities in health implies the ability to measure them accurately, to compare them between different areas or countries and to follow trends over time. This study proposes a method for constructing a French European deprivation index, which will be replicable in several European countries and is related to an individual deprivation indicator constructed from a European survey specifically designed to study deprivation. Methods and Results: Using individual data from the European Union Statistics on Income and Living Conditions survey, goods/services indicated by individuals as being fundamental needs, the lack of which reflect deprivation, were selected. From this definition, which is specific to a cultural context, an individual deprivation indicator was constructed by selecting fundamental needs associated both with objective and subjective poverty. Next, the authors selected among variables available both in the European Union Statistics on Income and Living Conditions survey and French national census those best reflecting individual experience of deprivation using multivariate logistic regression. An ecological measure of deprivation was provided for all the smallest French geographical units. Preliminary validation showed a higher association between the French European Deprivation Index (EDI) score and both income and education than the Townsend index, partly ensuring its ability to measure individual socioeconomic status. Conclusion: This index, which is specific to a particular cultural and social policy context, could be replicated in 25 other European countries, thereby allowing European comparisons. EDI could also be reproducible over time. EDI could prove to be a relevant tool in evidence-based policymaking for measuring and reducing social disparities in health issues and even outside the medical domain. [ABSTRACT FROM AUTHOR]