Breast Cancer and Women's Labor Supply

Abstract

The National Cancer Institute's Office of Cancer Survivorship has as one of its objectives “to develop an agenda for the continuous acquisition of knowledge concerning the problems facing cancer survivors, including the medical, psychological, and economic effects of treatment” (National Cancer Institute 1999). To date, most studies of cancer survivors can be classified under the rubric of “quality of life,” where the focus is on survivors' impressions of their well-being along physical, psychological, social, and spiritual domains (for a review, refer to Gotay and Muraoka 1998). However, very little work has examined objective measures of individuals' economic circumstances after a cancer diagnosis. This study explores an important economic outcome—labor market participation of breast cancer survivors relative to women who have never had the disease.

Employers often fear that cancer patients have lower job performance and productivity and higher absenteeism (McKenna 1987). However, economic studies of breast cancer survivors to date, though not expansive, have found mixed results of the effect of breast cancer on labor market participation. At least two studies (Ganz et al. 1996; Satariano and DeLorenze 1996) indicate that breast cancer's effect on employment is minimal. In a study of patients two and three years after their primary treatment, Ganz et al. (1996) found that 65 percent (n = 139) of breast cancer survivors were either working for pay or volunteering their services. The mean number of hours worked was 34.4 and 33.2 hours per week among women who were two and three years post-treatment respectively. This study concluded that women generally continue to work and perform their usual roles after treatment for breast cancer. In a study of three hundred working women at the time of their breast cancer diagnosis, 71 percent returned to work three months after diagnosis (Satariano and Delorenze 1996). However, certain factors can negatively influence employment including physical disability (Fow 1996), lack of control over schedules and type of work performed (Satariano and Delorenze 1996; Greenwald et al. 1989), and in some cases discrimination on the part of employers (Carter 1994; Berry 1993). A limitation to all studies reviewed is they do not include a noncancer control group, making the evidence difficult to interpret.

In this paper, we explore factors that influence breast cancer survivors' labor market decisions. We expand existing research in several important ways: (1) we control for health status to partially isolate the effect of breast cancer from other health conditions; (2) we compare breast cancer survivors to a noncancer group; and (3) we explore the influence of the availability of health insurance. Ideally, we would like to control for health insurance source since health insurance via an employer may play a role in increasing or at the least maintaining labor market participation. Due to our concern over the potential endogeneity of a woman's health insurance in both the decision to work and the intensity of work, we instead indicate whether a woman's spouse has health insurance through his employer (Buchmueller and Valetta 1999).

Our findings can help researchers, clinicians, and policymakers better understand an important measure of well-being—the ability to work—once patients have been diagnosed and successfully treated. An understanding of labor market outcomes is particularly important for this population as more working age women are screened for breast cancers that might not otherwise be detected during their working years.

Means or sample percentages are reported with standard deviations of continuous variables in parentheses.

Standard errors shown in parentheses. Omitted categories are: excellent, good, or average health status, no high school diploma, white/other, married, and no children younger than age 18 living at home or away. Partial derivatives of the probability of employment are reported, evaluated at sample means. In a related regression, the inclusion of publicly insured women (n = 482) did not substantively alter the results.

See notes to Table 2.

Standard errors shown in parentheses. Omitted categories are: excellent, good, or average health status, no high school diploma, white/other, married, no children younger than 18 living at home or away, and white collar employment. These estimates were not sensitive to excluding a few apparent outliers. In a related regression, the inclusion of publicly insured women (n = 482) did not substantively alter the results.

Standard errors shown in parentheses. Omitted categories are: excellent, good, or average health status, married, and no children younger than 18 living at home or away.

Acknowledgments