Beyond Hours Worked and Dollars Earned: Multidimensional EQ, Retirement Trajectories and Health in Later Life

Abstract

The working lives of Americans have become less stable over the past several decades and older adults may be particularly vulnerable to these changes in employment quality (EQ). We aimed to develop a multidimensional indicator of EQ among older adults and identify EQ and retirement trajectories in the United States. Using longitudinal data on employment stability, material rewards, workers' rights, working-time arrangements, unionization, and interpersonal power relations from the Health and Retirement Study (HRS), we used principal component analysis to construct an EQ score. Then, we used sequence analysis to identify late-career EQ trajectories (age 50-70 years; N = 11,958 respondents), overall and by sociodemographics (race, gender, educational attainment, marital status). We subsequently examined the sociodemographic, employment, and health profiles of these trajectories. We identified 10 EQ trajectories; the most prevalent trajectories were Minimally Attached and Wealthy (13.9%) and Good EQ to Well-off Retirement (13.7%), however, 42% of respondents were classified into suboptimal trajectories. Those in suboptimal trajectories were disproportionately women, people of color, and less-educated. Individuals in the Poor EQ to Delayed and Poor Retirement and Unattached and Poor clusters self-reported the greatest prevalence of poor health and depression, while individuals in the Wealthy Business Owners and Great EQ to Well-off Retirement clusters self-reported the lowest prevalence of poor health and depression at baseline. Trajectories were substantially constrained for women of color. Although our study demonstrates EQ is inequitably distributed in later life, labor organizing and policy change may afford opportunities to improve EQ and retirement among marginalized populations.

Figure 1.

Construction of analytic sample.

Figure 2.

Visual representation of EQ trajectories, Health and Retirement Study 1992–2016. EQ, Employment Quality; NLBF, Not in the Labor Force.This figure shows the results of sequence analysis conducted on 11,958 Health and Retirement Study respondents interviewed 1992–2016. (a) shows the most common state at a given age for each cluster while (b) provides more detail of the states assumed by each individual at a given age within each cluster.

Figure 3.

Trajectory distribution by key sociodemographic characteristics, Health and Retirement Study 1992–2016. This figure shows the distribution of trajectory clusters identified conducting sequence analysis on 11,958 Health and Retirement Study respondents interviewed 1992–2016.

Figure 4.

Visual representation of EQ trajectories stratified by cumulative advantage, Health and Retirement Study 1992–2016. EQ, Employment Quality; NLBF, Not in the Labor Force. This figure shows the results of sequence analysis conducted in within strata of race, gender, and educational attainment on 11,958 Health and Retirement Study respondents interviewed 1992–2016. For each strata of interest, the figure on the left shows the most common state at a given age for each cluster while the figure on the right provides more detail of the states assumed by each individual at a given age within each cluster.