Analyses: Data will be analyzed and summarized for publication with representatives from KPCO, DCEG and UMMS. Simple proportions will be used to estimate participation rates. Extant electronic records at KPCO will be used to compare participants to non-participants, overall and by pre-specified subgroups (5-year age groups, race/ethnicity, length of KPCO enrollment), with descriptive statistics and logistic regression. For the primary objective, fecal microbial 16S rRNA pyrosequences will be classified by phylogenetic and principal components analyses, while estrogen levels and Beta-glucuronidase RNA expression and enzymatic activity levels will be categorized using log standard deviations. The study will have 80% power to detect a 17% increase in estrogen level per 2.4-fold increase in glucuronidase activity and 80% power to detect a 3-fold case-control difference in above-median microbiome alpha diversity.