Mammographic density is one of the strongest known risk factors for breast cancer, yet it has been described as among the most undervalued and underutilized factors in studies of breast cancer etiology. While recently there has been interest in the potential value of mammographic density as an intermediate marker of breast cancer risk, several questions remain unanswered. A needed area of research is the identification of risk factors for breast cancer that are related to mammographic density, and may therefore act through a causal pathway reflected directly or indirectly by this feature.
The aim of this study is to identify factors that are associated with mammographic density, with a special focus on race/ethnicity, circulating hormones (e.g., estradiol, progesterone, testosterone, sex hormone-binding globulin), bone mineral density, and modifiable factors such as diet (e.g., phytoestrogen, percent calories from fat,) and physical activity (e.g., recreational activity, occupational activity, and household activity). We will also look at how density changes as women transition through the menopause. This proposal seeks funding for obtaining and assessing mammograms on approximately 178 Chinese, 209 Japanese, 102 African-American, and 498 Caucasian women participating in SWAN (Study of Women's Health Across the Nation). We will request all mammograms performed as part of routine care during the SWAN follow-up period and request that women have a mammogram within six months of follow-up exam six. SWAN is a multi-site population-based study designed to investigate the menopausal transition in women of diverse ethnicities. At baseline and six annual follow-up exams, data are collected on a wide range of factors, including detailed anthropometry, bone mineral density, menstrual information (e.g., monthly calendars), and complete reproductive histories. In addition, blood is drawn, timed to the luteal phase of the menstrual cycle, for hormone analyses. An expert in assessing mammographic density will measure total area of the breast and area of dense tissue (for percent density) and classify mammograms according to parenchymal pattern (Wolfe system). This mammography information will be merged with data from SWAN to create analytic files. Repeated measures regression analysis will be used to examine the association between factors of interest and mammographic density. The SWAN study population provides a unique opportunity to efficiently examine the relationship between several established and suspected risk factors for breast cancer and mammographic density. The results will improve our understanding of a number of breast cancer risk factors and help determine whether mammographic density should be considered as a potential intermediate marker of breast cancer risk for intervention studies of several modifiable factors.
