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Measurement and determinants of health poverty and richness: evidence from Portugal

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Abstract

The analysis of health inequalities is a critical topic for health policy. With data for Portugal, we propose an algorithm to convert information provided by the official National Health Survey to EuroQol. Based on these data, we make two contributions. First, we extend measures and methods commonly applied in other fields of economic research in order to quantify the phenomena of health poverty, richness, and inequality. Second, using an ordered probit model, we evaluate the determinants of health inequalities in Portugal. The results show that there is a remarkable level of health inequality, with significant rates of poverty (11.64 %) and richness (22.64 %). The econometric study reveals that gender, age, education, region of residence, and eating habits are among the most critical determinant factors of health.

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Notes

  1. The survey includes groups of questions that were applied in all the quarters as well as some others that were answered only in a specific quarter.

  2. The original number of the questions from INS are also reported in the flowcharts.

  3. For an overview of the most recent contributions regarding measurement of inequality and inequity in health and health care, see Van Ourti et al. (2014).

  4. Depth instead of severity is used merely for terminological reasons.

  5. There is some degree of correlation between the explanatory variables. Concerning collinearity we used the VIF instrument (Variation Inflation Factor) which calculates the impact upon the variance of the one variable resulting from the correlations between the other regressors. It is usually mentioned in the literature that there is evidence of collinearity when the value that indicates the highest VIF is greater than 5. Our values are below this limit.

  6. One possible explanation for this result is that although the survey is collected at NUTS III level, researchers have information only at NUTS II level. Due to their size, regions defined using NUTS II level are very heterogeneous units.

  7. The recently launched DRIVERS project brings together leading organizations to review existing scientific evidence, develop guidelines for effective advocacy on health inequalities, and test the newly developed knowledge in real-life situations on the ground across Europe (http://eurohealthnet.eu/organisation/driversyes-we-can-reduce-health-inequali).

  8. In light of our results, as stressed by an anonymous referee, further exploring spatial inequalities in health would be an interesting research avenue.

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Acknowledgments

The authors are grateful to the National Statistics Office (INE) for kindly providing us with the survey data, and we acknowledge the financial support from FCT/Fundação para a Ciência e a Tecnologia PEst-OE/EGE/UI0315/2011. The remarks of two anonymous referees helped us to improve the paper considerably. The usual disclaimer applies.

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Authors and Affiliations

  1. ISCTE Business School Economics Department, BRU – IUL (Business Research Unit), Instituto Universitário de Lisboa (ISCTE – IUL), Lisbon, Portugal

    Nádia Simões & Nuno Crespo

  2. Department of Economics and Management, Instituto Politécnico de Setúbal (ESCE – IPS), Setúbal, Portugal

    Sandrina B. Moreira

  3. BRU – IUL (Business Research Unit), Instituto Universitário de Lisboa (ISCTE – IUL), Lisbon, Portugal

    Sandrina B. Moreira

  4. Department of Economics, Management and Industrial Engineering, GOVCOPP, University of Aveiro, Aveiro, Portugal

    Celeste A. Varum

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  1. Nádia Simões
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  2. Nuno Crespo
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  4. Celeste A. Varum
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Correspondence to Sandrina B. Moreira.

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Simões, N., Crespo, N., Moreira, S.B. et al. Measurement and determinants of health poverty and richness: evidence from Portugal. Empir Econ 50, 1331–1358 (2016). https://doi.org/10.1007/s00181-015-0967-2

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  • DOI: https://doi.org/10.1007/s00181-015-0967-2

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