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\title{We're a team of epidemiologists from Columbia University's Mailman
School of Public Health, who published a recent study linking the wage
gap to gender disparities in mood disorders, Ask Us Anything!}



\author[1]{MailmanSchool_AMA }%
\author[1]{r/Science AMAs}%
\affil[1]{Affiliation not available}%


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  \date{April 24, 2026}


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\begin{abstract}
Hi, Reddit -- We're a team of epidemiologists from Columbia University's
Mailman School of Public Health. In our recent study titled, ``Unequal
depression for equal work? How the wage gap explains gendered
disparities in mood disorders,'' we used propensity scores to match
women and men on age, education, occupation, family composition, years
in the workforce, and other factors, and then estimated the effect of
income differentials on depression and generalized anxiety disorder. We
found that U.S. women whose income was lower than their male matches had
nearly 2.5 times the odds of major depression and 4 times the odds of
generalized anxiety disorder. Yet when women's income was greater than
their male matches, women's odds of generalized anxiety disorder or
depression were nearly equivalent to men. This finding, published in the
journal Social Science \& Medicine
(http://www.sciencedirect.com/science/article/pii/S0277953615302616),
may help explain why women are nearly twice as likely to have depression
or anxiety than men. We are\ldots{} Lisa Bates, an assistant professor
of Epidemiology and social epidemiologist engaged in research on gender
and other axes of inequality as they impact health outcomes; Katherine
M. Keyes, an assistant professor of Epidemiology whose research focuses
on life-course epidemiology with particular attention to psychiatric
disorders; Jonathan Platt, a second-year doctoral student in
Epidemiology who studies the incidence and social causes of gender
disparities of mood disorders; and Seth Prins, a PhD candidate in
Epidemiology who studies the political-economic determinants of mental
illness, in addition to mental illness and mass incarceration. We'll be
back at 1 pm EST (10 am PST, 6 pm UTC) to answer your questions, Ask Us
Anything! *Edit: Hello! We're online and ready to start answering your
questions. We'll be here for about an hour and a half. We're going to
answer as many questions as we can, and try to cover a range of issues,
from our findings to our methods and theory. * ***Edit: We're going to
wrap up now -- thanks so much for your great questions!***%
\end{abstract}%



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