Austrian Academy of Sciences, Vienna Institute of Demography, Vordere Zollamtsstraße 3, 1030, Vienna, Austria.
TU Dortmund, Institute for Sociology, Emil-Figge-Str. 50, 44227, Dortmund, Germany.
Soc Sci Med. 2020 Dec;267:112913. doi: 10.1016/j.socscimed.2020.112913. Epub 2020 Mar 17.
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.
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.
Our model explains SRH rather well (R = .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 R increased.
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.
自评健康(SRH)可说是调查研究中使用最广泛的通用健康衡量标准。然而,对于研究人员来说,SRH 仍然是一个黑箱。在我们的论文中,我们希望通过确定其决定因素、量化不同健康领域对解释 SRH 的贡献,并探索性别、年龄组和居住国的调节作用,来更好地理解 SRH。
使用来自居住在 15 个欧洲国家的欧洲健康、老龄化和退休调查(SHARE)第五波(2013 年)的 61365 名参与者的数据,我们通过线性回归模型来解释 SRH。自变量分为五个健康领域:功能、疾病、疼痛、心理健康和行为。通过优势分析,我们专注于它们对解释 SRH 的个体贡献,并比较这些贡献在性别、三个年龄组和 15 个欧洲国家之间的差异。
我们的模型对 SRH 的解释相当好(女性为.51,男性为.48),其中功能对评估的贡献最大(女性为.20,男性为.18)。疾病是第二重要的健康维度(女性为.14,男性为.16),其次是疼痛(女性为.08,男性为.07)和心理健康(女性为.07,男性为.06)。健康行为(女性为.02,男性为.01)对健康评分的相关性较低。这种排名在几乎所有国家都成立,总体差异很小。对年龄组的比较表明,随着生命周期的发展,疾病和行为对 SRH 的贡献减少,而功能对 SRH 的贡献增加。
我们的论文表明,SRH 主要基于各种健康信息,其中功能和疾病最为重要。然而,仍然存在特殊性甚至偏见的空间。