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Date of Award


Access Type

Campus Access

Document type


Degree Name

Doctor of Philosophy (PhD)

Degree Program

Epidemiology and Biostatistics

First Advisor

Brian Whitcomb

Second Advisor

Elizabeth Bertone-Johnson

Third Advisor

Raji Balasubramanian

Subject Categories



There are 8 commonly used algorithms for classifying the ovulatory status of menstrual cycles, however a gold standard algorithm has not been identified. Disagreement between algorithms may influence study results and interpretations. Excessive alcohol consumption and physical activity can have negative effects on menstrual cycle function, including ovulation. Less clear however are the effects of moderate alcohol consumption and moderate amounts of physical activity. The purpose of this dissertation was to evaluate different methods for classifying ovulation status, and to explore modifiable risk factors, including alcohol consumption and physical activity, for anovulation and menstrual cycle dysfunction. We used data from a large prospective cohort study, The BioCycle Study, which followed 259 healthy premenopausal women for 1-2 menstrual cycles. Estradiol, progesterone, luteinizing hormone, follicle-stimulating hormone, and sex hormone binding globulin (SHBG) were measured in serum up to 8 times per cycle, timed using fertility monitors to capture relevant cycle phase data. Fiber intake was assessed with multiple 24-h dietary recalls. Alcohol and physical activity were assessed with daily diaries and baseline questionnaires. We calculated the prevalence of anovulation and assessed the effect of fiber consumption on anovulation using each of the 8 algorithms and compared odds ratios (ORs) and 95% confidence intervals (CI). We used linear mixed models to determine the effect of alcohol and physical activity on menstrual cycle hormone values, and generalized linear mixed models to evaluate their effect on anovulation. The prevalence of anovulation ranged from 3.3% to 17.5% across the 8 algorithms. In multivariate analyses of fiber consumption and risk of anovulation, fiber intake was positively associated with anovulation across all algorithms, however precision varied widely; when comparing first to forth quartiles, odds ratios ranged from 3.39 (95% CI: 1.01-11.46) to 7.52 (95% CI: 0.77-73.25). Both physical activity and alcohol were associated with decreased levels of SHBG, but only in the follicular and luteal phases, and had no effect on other hormones or ovulation. The results of this study suggest that moderate levels of physical activity do not have substantial effects on reproductive hormone levels or ovulation status, aside from a slight decrease in SHBG levels.