Life Expectancy Gain Due to Employment Status Depends on Race, Gender, Education, and Their Intersections



Despite the well-established health effects of socioeconomic status (SES), SES resources such as employment may differently influence health outcomes across sub-populations. This study used a national sample of US adults to test if the effect of baseline employment (in 1986) on all-cause mortality over a 25-year period depends on race, gender, education level, and their intersections.


Data came from the Americans’ Changing Lives (ACL) study, which followed 2025 Whites and 1156 Blacks for 25 years from 1986 to 2011. The focal predictor of interest was baseline employment (1986), operationalized as a dichotomous variable. The main outcome of interest was time to all-cause mortality from 1986 to 2011. Covariates included baseline age, health behaviors (smoking, drinking, and exercise), physical health (obesity, chronic disease, function, and self-rated health), and mental health (depressive symptoms). A series of Cox proportional hazard models were used to test the association between employment and mortality risk in the pooled sample and based on race, gender, education, and their intersections.


Baseline employment in 1986 was associated with a lower risk of mortality over a 25-year period, net of covariates. In the pooled sample, baseline employment interacted with race (HR = .69, 95% CI = .49–.96), gender (HR = .73, 95% CI = .53–1.01), and education (HR = .64, 95% CI = .46–.88) on mortality, suggesting diminished protective effects for Blacks, women, and individuals with lower education, compared to Whites, men, and those with higher education. In stratified models, the association was significant for Whites (HR = .71, 95%CI = .59–.90), men (HR = .60, 95%CI = .43–.83), and individuals with high education (HR = .66, 95%CI = .50–.86) but not for Blacks (HR = .77, 95%CI = .56–1.01), women (HR = .88, 95%CI = .69–1.12), and those with low education (HR = .92, 95%CI = .67–1.26). The largest effects of employment on life expectancy were seen for highly educated men (HR = .50, 95%CI = .32–.78), White men (HR = .55, 95%CI = .38–.79), and highly educated Whites (HR = .63, 95%CI = .46–.84). The effects were non-significant for Black men (HR = 1.10, 95%CI = .68–1.78), Whites with low education (HR = 1.01, 95%CI = .67–1.51), and women with low education (HR = 1.06, 95%CI = .71–1.57).


In the USA, the health gain associated with employment is conditional on one’s race, gender, and education level, along with their intersections. Blacks, women, and individuals with lower education gain less from employment than do Whites, men, and highly educated people. More research is needed to understand how the intersections of race, gender, and education alter health gains associated with socioeconomic resources.

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Shervin Assari is supported by the Heinz C. Prechter Bipolar Research Fund and the Richard Tam Foundation at the University of Michigan Depression Center.

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Correspondence to Shervin Assari.

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The Americans’ Changing Lives (ACL) survey was funded by the United States Department of Health and Human Services, National Institutes of Health, and National Institute on Aging (AG05561) and also Grant # AG018418 from the National Institute on Aging (DHHS/NIH). NIH is not responsible for the data collection or analyses represented in this article. The ACL study was conducted by the Institute of Social Research, University of Michigan.

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The University of Michigan Institutional Review Board (IRB) approved the study protocol.


All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) with the Helsinki Declaration of 1975, as revised in 2000.

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Informed consent was obtained from all participants included in the study.

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No animal studies were carried out by the authors for this article.

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Assari, S. Life Expectancy Gain Due to Employment Status Depends on Race, Gender, Education, and Their Intersections. J. Racial and Ethnic Health Disparities 5, 375–386 (2018).

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  • Employment
  • Socioeconomic status
  • Mortality
  • Ethnic groups