Analyzing the roles of social class and power dynamics in health disparities over the life course - PROJECT SUMMARY/ABSTRACT
Socioeconomic and racial health disparities in the US are vast, with sinking life expectancy fueled by excess
mortality among poor and Black people. Hazardous working conditions, like low wages and poor job control,
propel disparities in mortality, self-rated health (SRH), and mental illness. Underused relational theories
suggest such conditions are caused by upstream power imbalances between workers, managers, and
employers: social classes divisible by managerial authority and business ownership. Trends like sinking labor-
union membership and surging class disparities in income suggest power has tipped away from workers, who
are most of the workforce and largely women and Black people. Thus, worsening disparities and population
health may reflect changing class power dynamics. However, while longitudinal studies have tested the effects
of downstream factors like wages, none using relational theories have tested class’s cumulative effects on
health over the life course, the modifying role of power dynamics, or the effects of worker empowerment. This
hinders efforts to identify adverse working conditions’ root causes and improve disparities and population
health. In the proposed K99/R00, I will obtain the advanced training needed to address these gaps and pursue
an independent research career. My research objectives are to: a) quantify class’s cumulative effects on SRH,
mental illness, and mortality over the life course, including by intersecting gender-race, b) test the modifying
role of power dynamics, and c) analyze the effects of workplace-level and state-level worker empowerment. To
achieve these objectives, I will apply methods to overcome the time-varying confounding that has impeded
prior research, like parametric g-formula and difference-in-differences designs, to nationally representative
1968-2019 Panel Study of Income Dynamics (PSID) and 1986-2018 National Health Interview Survey (NHIS)
data on US adults. PSID and NHIS are among the largest longitudinal or repeated cross-sectional health
datasets with detailed class data. My work will be embedded within Columbia University’s Mailman School of
Public Health, where I will be supported by an interdisciplinary mentorship team with considerable experience
mentoring early-career investigators. My research will be fostered by a training plan that includes training in: 1)
intersectionality theory, 2) life-course and aging research, 3) methods for testing cumulative effects and time-
varying effect modification in settings with healthy-worker bias, and 4) econometric methods. The proposal will
advance the field by analyzing the overlooked root causes of work-related health disparities over the life course
and by identifying actionable policy solutions. My findings will be critical to meeting NIA’s strategic goals of
understanding aging-related health disparities and developing strategies to improve older-adult health. The
accompanying training plan will help me launch an independent research career studying and addressing the
structural power dynamics fueling social class disparities in health.
