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Revisiting the Effect of Income on Health in Europe: Evidence from the 8th Round of the European Social Survey


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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  1. 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.

  2. Available at:, accessed 26/3/2019.

  3. Look, also, at the European Social Survey suggestions when preparing data for multilevel models’ analyses at:

  4. Look at:

  5. For the theoretical underpinnings of this variable construction, look at the European Social Survey 2016 round 8 Welfare Final Module Template:

  6. 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.

  7. 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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Correspondence to Ioannis Galariotis.

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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).

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  • Income inequality
  • Individual income
  • Self-rated health
  • Europe
  • Multilevel modeling
  • Binary logistic regression