Unequal depression for equal work?

Current doctoral students Jonathan Platt and Seth Prins, along with Cluster faculty Lisa Bates and Katherine Keyes recently reported that structural workplace discrimination, measured as the presence of a gender wage gap, largely explained higher rates of mood disorders among woman as compared to men. The full paper was published in the January issue of Social Science and Medicine.

reddit_AMAThe authors will be doing a Reddit Ask Me Anything on Friday Jan 29th from 1-2 pm, you can participate HERE and discuss the research.  Social Science and Medicine will also be removing their pay-wall for the article for a week starting on Friday Jan 29th.  So if you don’t have access to a subscription you can read the article HERE.

Below Jonathan describes their work.

There is strong and consistent evidence that women are more likely to suffer from depression and anxiety disorders than men (see below for selected examples). This is true whether depression is indexed as a diagnosed mental disorder or as subclinical symptoms.  For depression these symptoms include depressed mood, decreased interest in usual activities, significant weight change, sleep problems, and loss of energy. For general anxiety disorder symptoms include restlessness, fatigue, difficulty concentrating, irritability, muscle tension, and sleep disturbance. Differences in risk for these mood disorders by gender emerge in adolescence and persist throughout adulthood, causing significant morbidity and increasing risks for numerous other physical and mental health conditions. A variety of explanations have been proposed to explain these gender differences, for example; as the result of greater or more traumatic stressors, differences in coping responses, and even differences in sex hormones during puberty. In addition, others have sought to explain these differences as results of measurement error or construct invalidity, by comparing differences in symptom reporting, illness severity, or in help seeking behavior. These explanations account for a limited portion of overall differences. No one theory has completely explained these gender differences, so it is likely that the reasons are complex and to some extent the result of social experiences.

Selected studies of gender differences in Major Depressive Disorder and Generalized Anxiety Disorder

Major Depression:

Kessler, R. C. (2003). Epidemiology of women and depression. Journal of affective disorders, 74(1), 5-13.

Nolen-Hoeksema, S. (2001). Gender differences in depression. Current Directions in Psychological Science, 10(5), 173-176.

Piccinelli, M., & Wilkinson, G. (2000). Gender differences in depression Critical review. The British Journal of Psychiatry, 177(6), 486-492.

Generalized Anxiety Disorder:

Kessler, R. C., Chiu, W. T., Demler, O., & Walters, E. E. (2005). Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62(6), 617-627.

Vesga-Lopez, O., Schneier, F. R., Wang, S., Heimberg, R. G., Liu, S. M., Hasin, D. S., & Blanco, C. (2008). Gender differences in generalized anxiety disorder: results from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). The Journal of clinical psychiatry, 69(10), 1606-1616.

It is understood that overt gender bias can have negative mental health consequences for women in the workplace. For example, sexual harassment or being monitored more closely on the job than others may do harm when the experience is perceived as discriminatory. In addition to overt discrimination, it has been hypothesized that structural and institutional discrimination, which may or may not be perceptible, has mental health consequences and such effects have been documented. Our study used the gender wage gap as a measure of these less visible forms of discrimination. We hypothesized that the gender wage gap could serve as a proxy for forms of structural and institutional discrimination including, but not limited to, women’s social disadvantage in the process of negotiating responsibilities, salaries, and raises; the social value placed on the type of work women tend to do; and gender bias in labor market and workplace policies surrounding reproductive healthcare and maternity leave.

While the wage gap is simple enough to measure, there are several competing explanations for what it represents in the American workforce. Some argue that the wage gap is the result of different individual-level, productivity-related characteristics between men and women, which are used to determine salaries. For example, two employees with the same job title may have substantially different levels of education, years of prior work experience, or may work in industries where salaries are lower (e.g., a researcher for a medical non-profit vs. a researcher for a pharmaceutical company). Similarly, individuals may self-select into jobs that pay less but have other benefits, like schedule flexibility. Alternately, broader social structures and biases, such as those noted above, may cause men and women with the same qualifications to be paid unequally for the same work. These competing explanations underscore the complexity inherent in studying social factors like gender.

We used the data on men and women age 30–65, with full or part-time employment, in non-military occupations (n=22,581) who took part in the National Epidemiologic Survey on Alcohol and Related Conditions. To address underlying individual differences between the men and women in our data, we used propensity score matching to create pairs of men and women who were most similar on all measured individual-level productivity characteristics. This matching procedure identified men and women who were similar for accumulated work experience/potential for advancement, occupation, industry employer type, full verses part-time employment, marital status and number of children at home.

While the matched pairs did not represent literal workplace counterparts, they represent two individuals who have generally equal qualifications and personal/demographic characteristics aside from their gender and thus, we would expect, should receive equal salaries.

In the matched sample, the wage gap decreased by 25% (from $0.54 to $0.68 of every dollar earned by men). In other words, 25% of the wage gap between men and women could be explained by individual-level differences and self-selection processes in our sample. Nevertheless, the gap was still significant, which suggests that part of the residual wage gap may be due to factors operating at other levels beyond the individual, such as structural gender bias in wages. We then tested how much of the difference in depression and anxiety disorders by gender could be explained by this relative difference in income. We created two groups: one group included women who earned less than their male counterparts, and the other group included women who earned an equal or greater salary than their male counterparts. When women earned less than their male counterparts, they were 4 times more likely to report having past-year anxiety disorder and 2.4 times more likely to report past-year depression. When women earned as much or more than their male counterparts, the differences in depression disappeared and there were nearly no differences in GAD.

We wondered, though, how our results would hold up to a range of different kinds of restrictions and reanalysis. To test the sensitivity of our results, we:

  • Restricted the sample to those with income < $1,000,000 to test if study results were due only to those with the largest incomes, and thus the greatest matched pair income differences.
  • Restricted our sample to exclude imputed income, to test if imputed data could explain our findings.
  • Restricted our sample to those in executive, administrative, managerial occupations as a way to test a more narrowly defined workforce population.
  • Included spousal income in the propensity score estimation and matching to test the explanation that high earning women were more likely to be married and/or live in a two-income household, and therefore generally less likely to develop mood disorders.
  • Finally, we removed education status from the propensity scores, and stratified the matched pairs by three levels of education (some high school, high school diploma/GED through some college, and a college degree or more) to see if the pattern was consistent for pairs at each level of education.

The results were consistent and striking – women who earned less than their male counterparts were more likely to report having anxiety disorder and depression with the past year and when women earned as much or more than their male counterparts, the differences in depression disappeared and there were nearly no differences in GAD. This clear signal in these data reflects real health consequences of structural and institutional gender discrimination in the the workforce.

More research is needed to understand the factors underlying the wage gap that may affect women’s health, and how this phenomenon gets “under the skin” to cause mood disorders. The answer likely involves numerous, interacting mechanisms at multiple levels. The wage gap may be a proxy for women’s cumulative lifetime experience of perceived and invisible material disadvantage and undervaluation, from the primary school classroom to the boardroom. It may represent vestigial cultural norms about women’s role in the family and society, which have material and psychosocial consequences, such as women’s political under representation, which in turn may lead to policies that reproduce women’s disadvantage and undervaluation. And when a woman enters the workforce, she may not even perceive negative workplace experiences as biased, and thus attribute a missed promotion or raise as reflective of her abilities rather than her gender. When this attribution is internalized, it may lead to greater symptoms of anxiety and depression. More research is needed to test theoretical explanations of what the wage gap does and does not represent.

We believe that above and beyond the absolute effects of income on health, the wage gap reflects other ways that wages may be reinforcing gender disparities in depression and anxiety. We believe that our findings give further support for gender parity in wages, and we support existing calls for more transparency in the ways that wages and promotions are determined across companies and industries, as well as more research into the negative impacts of typically gendered workplace policies, like maternity leave.

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