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. 2020 Dec:267:112913.
doi: 10.1016/j.socscimed.2020.112913. Epub 2020 Mar 17.

Diverging ideas of health? Comparing the basis of health ratings across gender, age, and country

Patrick Lazarevič  1 , Martina Brandt  2
Affiliations

Diverging ideas of health? Comparing the basis of health ratings across gender, age, and country

Patrick Lazarevič et al. Soc Sci Med. 2020 Dec.

Abstract

Background: Self-rated health (SRH) is arguably the most widely used generic health measurement in survey research. However, SRH remains a black box for researchers. In our paper, we want to gain a better understanding of SRH by identifying its determinants, quantifying the contribution of different health domains to explain SRH, and by exploring the moderating role of gender, age groups, and the country of residence.

Method: Using data from 61,365 participants of the fifth wave (2013) of the Survey of Health, Ageing and Retirement in Europe (SHARE) living in fifteen European countries, we explain SRH via linear regression models. The independent variables are grouped into five health domains: functioning, diseases, pain, mental health, and behavior. Via dominance analysis, we focus on their individual contribution to explaining SRH and compare these contributions across gender, three age groups, and fifteen European countries.

Results: Our model explains SRH rather well (R2 = .51 for females/.48 for males) with functioning contributing most to the appraisal (.20/.18). Diseases were the second most relevant health dimension (.14/.16) followed by pain (.08/.07) and mental health (.07/.06). Health behavior (.02/.01) was less relevant for health ratings. This ranking held true for almost all countries with only little variance overall. A comparison of age groups indicated that the contribution of diseases and behavior to SRH decreased over the life-course while the contribution of functioning to R2 increased.

Conclusion: Our paper demonstrates that SRH is largely based on diverse health information with functioning and diseases being most important. However, there is still room for idiosyncrasies or even bias.

Keywords: Cross-national comparison; Epidemiology; Europe; Measurement invariance; Response behavior; Self-rated health; Survey of Health, Ageing and Retirement in Europe (SHARE).

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Figures

Fig. 1
Fig. 1
Cognitive model to explain the process of health-ratings.
Fig. 2
Fig. 2
Analytical model for explaining SRH by health dimension.
Fig. 3
Fig. 3
Amount of explained variance accounted for by health dimension by gender (95%-Confidence intervals).
Fig. 4
Fig. 4
Amount of explained variance accounted for by health dimension by gender and age-group (95%-Confidence intervals).
Fig. 5
Fig. 5
Amount of explained variance accounted for by health dimension by country (95%-Confidence intervals).
See this image and copyright information in PMC

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