Work package 8: Construct validation of the ESeC in relation to health inequalities
Health inequalities are of great concern to public health policies in the European Union and its member states. In each EU member state for which data are available, health problems occur much more often among lower socioeconomic groups. Detailed, valid and timely information on health inequalities are important for monitoring health inequalities within the EU and for evaluation of policies carried out at national and international levels. Core socioeconomic variables used for monitoring health inequalities are educational level, occupational class, and income level. For each core indicator, classification systems should be available that are comparable between EU member states and that are validated for each country individually. With regards to occupational class, international overviews and comparisons have been made using the EGP (Erikson-Goldthorpe-Portocarero, see Erikson and Goldthorpe 1992, pp 35-47) class schema. Although this schema was found to be useful for producing international overviews of inequalities in health, the validity and comparability of the resulting inequality estimates remained uncertain. Further improvement should come from applying and validating the ESeC in relation to health outcomes in several European countries.
The general objective of this study is to evaluate the ESeC as a useful comparative tool for the understanding and explanation of inequalities in health in EU member states. The specific objective of this study is to assess the construct validity of the ESeC in parallel analyses for several EU member states.
Data and EU countries covered
The study will use data from the ECHP, waves 1 to 5. We will analyse data from all 12 countries included in the ECHP, except Luxembourg. In previous analyses based on income and educational data, we have shown that the ECHP can be used to describe inequalities in health in a comparable way in each participating country. Waves 1 to 5 of the ECHP include useful information on three health indicators: general health, long term health problems, and activity restriction. We will also analyse data, available from wave 5 only, on three of the important risk factors of disease and premature mortality: smoking, excessive drinking, and overweight.
The general hypothesis is that class ‘matters’ and plays a key role in describing and explaining inequalities in health, and that ESeC is able to capture this key role better than previous class schemes such as EGP scheme.
With regard to description of health inequalities, the ESeC will be tested against its ability to identify social classes with most health problems. It is expected that, compared to the EGP schema:
- ESeC will allow for a more precise distinction between classes with poor and good average health, with more homogeneity within each class;
- ESeC will be able to show in more detail how patterns of inequalities differ according to gender, age, and country and health indicator/risk factor.
With regards to explanation, ESeC will be tested against its ability to differentiate more accurately between the different mechanisms that are expected to link class to health. It is expected to contribute to studies using education and income only because:
- ESeC should be able to capture most of the adverse health effects of low education and low income, and their combined effect;
- ESeC should be able to demonstrate that class also affects health independently of education and income, with health being positively related to more autonomy and control.Analysis
The four hypotheses will be tested applying multivariate regression models to the ECHP data. Logistic models will be developed with socioeconomic variables (EGP or ESeC, income, education) as the predictor variables, and health indicators or risk factors as the dependent variables. Parallel analyses will be made for each country individually, in addition to analyses on the pooled data for all countries together.
- Step 4: UNIMANN-MZES: Work package 5: ESeC and Education
- Step 4: UESSEX-ISER: Work package 6: Construct validation using the European Social Survey
- Step 4: INSEE: Work package 7: Criterion validation of ESeC using the ECT
- Step 4: SOFI: Work package 9: ESeC and EGP compared
- Step 4: UNIMIB: Work Package 10: Unemployment and Earnings Inequalities
- Step 4: ESRI: Work Package 11: Poverty and the Deprivation