Abstract
The existence of significant health disparities beyond those associated with race/ethnicity, poverty, and lack of health care has drawn the attention of researchers to the “challenge of the gradient.” Studies progressed from describing cross-sectional associations between disease risk and a single aspect of social disadvantage to identifying mechanisms by which these associations occur, encompassed objective and subjective measures of social status and stress processes, and used multilevel, dynamic models over the life course. The next stage is developing effective interventions targeting both the bases of disadvantage and the mediating pathways to reduce persistent disparities.
Four years before the founding of APS, the Whitehall study reported that, among predominantly White British civil servants, 10-year survival increased monotonically for each higher level of occupational grade (Marmot, Shipley, & Rose, 1984). Thus, it demonstrated that significant differences in longevity could occur even when poverty, race, and lack of health insurance were not relevant explanations of higher rates of mortality. This “challenge of the gradient” was especially intriguing to psychologists, as it seemed likely that psychosocial processes were playing a role (Adler et al., 1994).
Subsequent studies established that the graded association of socioeconomic status (SES) and health was not unique to British civil servants. Although the gradient is generally steeper at the bottom of the income and education distribution, disease prevalence and mortality risk in various U.S. samples were shown to decrease as income and education increase across the full spectrum. Along with studies of health differences across racial/ethnic groups, such findings became the core research on health disparities. This concept—now commonly acknowledged—took some time to gain traction. The first paper using health disparity or health disparities as a keyword was indexed in PsycINFO in 1991—a decade later there were only five. In contrast, over 900 articles on health disparities appeared in PsycINFO in 2012.
Measuring Objective and Subjective SES
Over the past two decades, researchers have asked increasingly nuanced and complex questions, proposed new concepts, and applied new methods to the question of health disparities. Initial studies tended to measure only one component of SES (e.g., income or education at either the individual or the neighborhood level) and considered that to be an overall indicator of a person’s SES. Some researchers created composites of multiple indicators without any theoretical basis for doing so. Subsequent studies paid much more attention to the specific resources provided by each indicator and tested their joint and independent relationships to health. Researchers began to control more regularly for race/ethnicity when studying SES effects and vice versa. For many, but not all, health outcomes, racial/ethnic disparities were markedly reduced or eliminated when SES was controlled for. The most dramatic exception, however, is in birth outcomes in which racial/ethnic differences remain significant. Infants born to Black mothers continue to have substantially higher mortality rates than infants born to White mothers at the same level of education and income. More recent research considers interactions as well as main effects and asks, for example, whether race/ethnicity moderates the relationship of education and health. For example, among Black and White children, rates of activity limitations due to poor health drop as parental education increases, but among Hispanic and Asian children, there is no association of children’s health with their parents’ educational attainment (Chen, Martin, & Matthews, 2006).
In addition to the objective factors constituting a person’s socioeconomic position (i.e., their educational attainment, occupation, and income), research in the last decade has shown the power of individuals’ own assessments of where they stand on the social ladder. Just as global self-rated health predicts mortality over and above objective health indicators, people’s subjective status (i.e. their estimation of where they stand vis-à-vis others nationally or in their community) predicts health status even when adjusted for objective measures of SES. Subjective status has been linked to diverse health indicators including overall self-rated health, depression, nurse-rated health, cortisol, visceral adiposity, obesity, mortality rates, and even vulnerability to the common cold (Cohen et al., 2008).
Mechanisms for the SES Gradient
Once evidence of the gradient was established, researchers turned to discovering the mechanisms responsible for it—in other words, how SES “gets under the skin” to affect health. These mechanisms included environments with greater exposure to toxins, carcinogens, and violence; fewer resources (parks, libraries, supermarkets); lack of access to health care; health-damaging behaviors such as use of cigarettes, excessive alcohol use, and lack of exercise; and psychological states such as anger and low sense of control, autonomy, and trust, all of which occur more frequently in socially disadvantaged populations.
Most of the mechanisms noted above involve the stress process. Some contribute to the experience of stress (e.g., environments that are more threatening) whereas others represent responses to such exposures (e.g., lack of control or substance use). Efforts to characterize the body’s physiological responses to the kind of day-in, day-out exposures associated with lower social position fostered some key advances in the conceptualization and measurement of chronic stress. Among others, Sapolsky’s work on the adverse effects of low social rank among baboons and McEwen’s development of the concept of allostatic load inspired extensive research on the biological costs of stress exposures associated with low relative status.
The kinds of physiological changes and dysregulation observed by Sapolsky (2005) and captured in the measure of allostatic load (McEwen, 1998) happen universally with aging. This observation suggests that chronic stress exposure, including SES-related stress, accelerates the aging process. More recent data on telomere length, a marker of cellular aging, are consistent with this hypothesis. Telomeres are protein complexes that cap the ends of chromosomes. They shorten over time, and shorter length predicts onset of disease and of subsequent mortality. Chronic stress is associated with shorter telomere length, and recent studies are finding that telomere length is shorter among those with less education and income than it is among those higher on the SES hierarchy. (Adler et al., 2012).
The vast majority of studies of health disparities are cross-sectional, but there is increasing interest in the accumulation of disadvantage over the life course. SES effects may even begin before birth, as the uterine environment is affected by the mother’s environmental exposures and physiological responses. Early risks associated with low SES are not only linked to childhood health problems, but also to adult health status, regardless of one’s SES in adulthood.
Past and Future
Over the past two decades, we have addressed the challenge of understanding how the SES gradient emerges. The challenge for the next generation of researchers is to discover ways to flatten the gradient and reduce health disparities. The discoveries we have made to date provide us with more possibilities for doing so. Not only can we advocate for social policies that will reduce the extreme levels of income inequality and social disadvantage that now create stress and poor health, but we can also design more effective interventions aimed at the pathways by which inequality damages health to help buffer the effects that, unfortunately, are currently happening.
Footnotes
Declaration of Conflicting Interests
The author declared no conflicts of interest with respect to the authorship or the publication of this article.