The vexing relationship between socioeconomic status and health
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(2020) 9:68
COMMENTARY
Open Access
The vexing relationship between socioeconomic status and health J. Travis Donahoe1
and Thomas G. McGuire2*
Abstract In a recent issue of this Journal, Politzer, Shmueli, and Avni estimate the economic costs of health disparities due to socioeconomic status (SES) in Israel (Politzer et al., Isr J Health Policy Res 8: 46, 2019). Using three measures of SES, the socioeconomic ranking of localities, individual income, and individual education, Politzer and colleagues estimate welfare loss due to higher mortality, productivity loss due to poorer health, excess health care treatment costs, and excess disability payments for individuals with below median SES relative to those with above median SES. They find the economic costs of health disparities are substantial, adding up to between 1.1 and 3.1 billion USD annually—between 0.7 and 1.6% of Israel’s GDP. This paper is useful and informative. It is, to our knowledge, the first comprehensive quantification of the economic costs stemming from health disparities in Israel. In spite of many social policies designed to level economic opportunity and social welfare generally, by most measures, Israel is among the most unequal in the distribution of income among all OECD countries (Cornfeld and Danieli, Isr Econ Rev 12:51–95, 2015). Politzer and colleagues expose the magnitude and sources of health-related loss that Israel faces because of such inequality and shows how the costs of inequality are borne to some degree by all members of society. This short commentary discusses the complicated relationship between SES and health and puts the findings from Politzer and colleagues in the context of the international literature on the subject. Keywords: Health disparities, Socioeconomic status and health, Causality
Main text The inverse relationship between SES and health is one of the most important and complicated issues in social policy. Poorer SES, whether measured by education, income, occupation, race and ethnicity, or locality, has been associated a variety of negative health outcomes including shorter life expectancy [1], worse mental health [2], higher mortality from a wide-range of diseases [3], worse health behaviors [4], and most recently, higher mortality from COVID-19 [5]. Two dominant models seek to explain the robust negative relationship between SES and health.
* Correspondence: [email protected] 2 Health Economics, Harvard Medical School, Boston, USA Full list of author information is available at the end of the article
First, SES can be one factor influencing health. There are multiple pathways through which SES influences health, including its impacts on individual health behaviors and lifestyles, exposures to environmental stressors and toxins, and access to health care [6]. Going a step further, the SES-to-health model argues that SES is a fundamental cause of health because it embodies all of the resources one has available to avoid risks and minimize the effects of diseases [7]. The second dominant model sees
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