Abstract
This study provides new evidence about the effects of income on population health. To do so, our first research question controls for the absolute income hypothesis: Has the recent deterioration of individual income had as a result a lower health status in population across European countries? We assume, as the bulk of the associated studies have found, that the lower the income of an individual, the lower his/her health status. Our second research objective is to examine the validity of the relative income hypothesis. To shed light on this issue, we test two different questions: What is the relationship between an individual’s health status and a country’s wealth and how self-rated health is associated with the degree of income inequality in a society? We expect that the population in wealthier countries report higher health status and individuals who live in countries with higher income inequalities report lower health status. By employing a multilevel binomial model and treating data from the latest European Social Survey Round 8 (2016/2017) from 23 countries in Europe, we have found strong evidence in favor of the above-mentioned hypotheses.
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Notes
Despite its careful construction as a comparative cross-national survey, the ESS suffers from non-sampling errors such as frame errors, measurement errors, response and non-response errors and interviewer errors (for a thorough discussion of non-sampling errors and remedies to mediate them see, for example, at Groves et al. 2004; Lessler and Kalsbeek 1992; McNabb 2013). This sort of errors has an impact on the results of our analysis. We provide a few arguments about how these errors affect the results of this study in the discussion section.
Available at: https://www.europeansocialsurvey.org/docs/round8/survey/ESS8_appendix_a2_e02_1.pdf, accessed 26/3/2019.
Look, also, at the European Social Survey suggestions when preparing data for multilevel models’ analyses at: http://essedunet.nsd.uib.no/cms/topics/multilevel/ch5/2.html.
For the theoretical underpinnings of this variable construction, look at the European Social Survey 2016 round 8 Welfare Final Module Template: https://www.europeansocialsurvey.org/docs/round8/questionnaire/ESS8_welfare_final_module_template.pdf.
The beta coefficients in Table 2 are equal to \(\log \frac{\left( p \right)}{{\left( {1 - p} \right)}}\). But, \(\frac{\left( p \right)}{{\left( {1 - p} \right)}}\) is the odds, therefore coefficient = log(odds). If we raise the coefficient in \(e\), namely \(e^{coefficient}\) = odds.
The graphs represent probabilities according to the ‘Effect’ R package’s documentation (Fox 2003).
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We would like to thank Nevena Kulic (Max Weber Fellow at the European University Institute in Florence) and the two anonymous reviewers for providing useful comments and feedback.
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Papazoglou, M., Galariotis, I. Revisiting the Effect of Income on Health in Europe: Evidence from the 8th Round of the European Social Survey. Soc Indic Res 148, 281–296 (2020). https://doi.org/10.1007/s11205-019-02193-x
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DOI: https://doi.org/10.1007/s11205-019-02193-x