Job characteristics as mediators in SES–health relationships☆
Introduction
Inverse relationships between socioeconomic status (SES) and health outcomes are well documented (e.g., Marmot, Ryff, Bumpass, Shipley, & Marks, 1997b; Mulatu & Schooler, 2002; Wilson, 2001). The incidence and prevalence of health problems are higher for people with fewer socioeconomic resources. Despite this consensus of empirical findings, the causal mechanisms underlying SES–health relationships have remained less well understood. A 1998 NIH Program Announcement (PA-98-098) noted that “a better understanding of the mediators of the relationships between SES and health, disease, and disability is essential for more efficacious clinical and policy interventions to reduce adverse health impacts.” In this paper we examine the extent to which job characteristics mediate the relationship between SES and health.
There is tremendous debate about the direction of causality in SES–health relationships. In this paper, we take an agnostic view on this issue. We recognize that SES and health are empirically associated in our data, and we attempt to understand the sources of that association. One obvious source has to do with health-risk factors: higher SES people get more exercise, are less frequently obese, and less frequently smoke, and all of these things have health consequences. Another obvious source has to do with family socioeconomic origins—children from less advantaged backgrounds experience more health problems later in life and are disproportionately low SES in adulthood. However, it is clear that these factors do not entirely account for observed SES–health associations (Kaplan & Keil, 1993; Mulatu & Schooler, 2002). In this paper we demonstrate that job characteristics are another important source of observed SES–health associations—albeit to differing degrees by sex and across health outcomes.
Section snippets
The stratification of health outcomes
Self-assessed overall health is typically measured using a survey question that asks something like, “Would you say your health is excellent, very good, good, fair, or poor?” Such measures are highly correlated with more objective, concrete measures of morbidity and mortality (Idler & Benyamini, 1997). Self-assessments of overall health are also highly correlated with SES. For example, Wilson (2001) found very strong associations between overall, self-assessed health and education and income.
The stratification of job characteristics
There is a well-developed literature on the role of education in stratifying employment outcomes. Education has pronounced effects on earnings and occupational status (Blau & Duncan, 1967; Featherman & Hauser, 1978), even net of social origins, intelligence, and other confounding factors. There is also evidence that the qualities and characteristics of individuals’ jobs are related to education and to the socioeconomic properties of those jobs. Using data from the Survey of Job Characteristics,
The health consequences of job characteristics
While it is clear that job characteristics are stratified by SES, it is also clear that job characteristics have health consequences. In the literatures on job design, occupational stress and ergonomics, various aspects of work have been shown to influence workers’ health and well-being in positive or negative ways (Carayon & Smith, 2000; Smith & Carayon-Sainfort, 1989). Balance Theory—a macro-ergonomic model of work proposed by Smith and Carayon-Sainfort (1989)—is a systems approach based on
Methods
We use data from the Wisconsin Longitudinal Study (WLS) to investigate the association between the physical and psychosocial characteristics of paid employment and three important health outcomes. The WLS began as a study of a random sample of 10,317 men and women who graduated from Wisconsin high schools in 1957. Data were collected from the graduates or their parents in 1957, 1964, 1975, and 1992/1993. These data provide a full record of social background, schooling, labor market experiences,
Health outcomes
The first panel of Table 1 describes variables pertaining to respondents’ self-reported health problems and medical conditions. To measure self-perceived overall health, respondents were asked, “How would you rate your health at the present time?” Response options ranged from “excellent” (5) to “very poor” (1). In our multivariate analyses, we analyze self-reported overall health through the use of ordered logistic regression models (which are appropriate when the dependent variable is
Self-assessed overall health
In Table 2 we present results from models in which self-assessed overall health is regressed on SES, health-risk factors, family socioeconomic background, and the characteristics of respondents’ current or last jobs. Because the outcome variable is ordinal, these are ordered logistic regression models. We present separate results for the full sample, for women, and for men. Model 1 includes only the three SES measures as covariates. Respondents who have completed four or more years of college,
Discussion
Our paper is an effort to understand the mechanisms that link SES and health. We observed—as others have—that education, earnings, and occupational standing are associated with a variety of health outcomes. Some portion of these associations is explained by the fact that lower-SES individuals come from less advantaged social origins, exercise less frequently, have higher body mass indexes, are more likely to smoke, and are less likely to have health insurance. However, even after controlling
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Paper prepared for presentation at the 40th Anniversary Symposium of the University of Wisconsin—Madison's Center for Demography and Ecology, October 2002. Generous support for this work has been provided by the National Institute on Aging (R01-AG09775-10 and P01-AG21079-01) and the National Institute for Occupational Safety and Health. However, errors and omissions are the responsibility of the authors. Public use data from the Wisconsin Longitudinal Study are publicly available at http://dpls.dacc.wisc.edu/wls/index.html