Health Care Cost of Socioeconomic Inequalities: A Pioneering Population-Wide Study

Does worsening socioeconomic inequality cause higher health care costs? There is a growing body of literature attempting to show the link between social and economic factors such as wealth levels and health care costs. Low socioeconomic status and living in deprived neighborhoods not only increase poor health but also increase the use of high-cost health care.

HUMAN CAPITAL

The links between health and wealth levels of societies are well known to economists, economic policy modelers, and in the economic growth literature.¹ Besides skills, qualifications, and knowledge, health status is one of the most important elements of human capital. As López-Casasnovas et al.² emphasize, the link between health and productivity is obvious because healthy human capital generates higher income and better labor productivity. Compared with the high human capital levels in developed countries, one of the factors is that the most economically adverse and severe barrier to economic growth is poor health conditions in underdeveloped countries. Therefore, investment in health to eliminate poor health conditions is essential for both economic reasons and providing social justice. Economists mainly focus on the fact that poor health conditions are causing bad economic outcomes (i.e., poor economic growth). But health economists are in fact also arguing that the causality involved goes both ways (i.e., poor economic conditions such as worsening inequality lead to worse health conditions).

Household income and economic wealth of individuals also play crucial roles because of their direct effect on living conditions and access to health services and medical care. According to the relevant literature, there are two channels for this. First, higher income allows people to purchase goods that improve health—for example, health insurance. In addition, higher income increases steady-state consumption and thus raises the utility of living to an older age.

In general, there is a considerable health economics literature linking wealth levels and health care costs. For example, Tosun et al.³ argue that wealthier people are less likely to be infected by hepatitis B, hepatitis C, and HIV. The Public Health Agency of Canada⁴ carried out similar research in Canada, which indicated that individuals with lower incomes, less education, or lower occupational skill levels tend to be less healthy than those who enjoy greater advantages in these areas. They concluded that health care costs decline as income rises, and Canadians in the lowest income quintile have the highest age-standardized average health care costs.

NEIGHBORHOOD EFFECTS

The current issue of AJPH includes an article by de Boer et al. (p. 927), who aimed to identify disparities in several types of health care costs across neighborhoods with different socioeconomic statuses in the Netherlands and to assess room for improvement. The authors used 2015 health care cost data, which was provided by Vektis, the health care information center established by Dutch health insurers. The data for all insured individuals cover almost the entire population. The neighborhood is defined by the first three digits of each postcode. They estimated the socioeconomic gradient by regressing health care on dummy variables for each of the five neighborhood socioeconomic status quintiles. Their empirical findings indicated that low neighborhood socioeconomic status is associated with high health care costs, and thus represents considerable potential for savings in health care costs in the Netherlands.

The study reveals remarkable insights and empirical evidence on the subject matter. Having almost the whole population in their data set is unique and exceptional because no other studies so far have provided a comprehensive, population-wide analysis of the cost implications of the socioeconomic gradient in health, not to mention the advantages of having practically the whole population for providing statistically robust results. Generally, health care information data created by health insurers make the data available for similar health cost studies in the other parts of the world. This study is a pioneer among future studies that will use such large, reliable data sets. The creation of a patient databank via the help of health institutions is likely to create more reliable data than any individual survey study. This aspect of the study is also helpful for economic modelers and health economics policymakers.

Of course, their analyses are not without some limitations. Economic policy modelers develop aggregate models as opposed to single equation models, one of which is constructed in this article. A more comprehensive way to examine the economy-wide dynamic impacts of socioeconomic status on average health care costs is to construct aggregate economic models with this type of study embedded in the aggregate structure, which are likely to create more detailed policy options for health policymakers. Thus, the study also provides useful tools for health economics policy modelers to develop better health policy advice.

INTERDISCIPLINARY APPROACH

Today it is widely recognized that unequal socioeconomic conditions intensely shape population health. As a consequence, an important way to reduce population health differences is to reduce social inequality and poverty. Professional health policymakers, policy advisers, economic health policy modelers, and health economics researchers share common commitments and responsibilities and should collaborate more across their individual sectors.