Classifications of Women's Menstrual Patterns and Related Epidemiology Explanations

• Activity Number: 520
• Type: Contributed
• Date/Time: Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Xiaobi Huang*+ and Sioban D Harlow and Michael R. Elliott
• Companies: Merck and University of Michigan and University of Michigan
• Keywords: menopause ; menstrual cycle ; ovary ; women's health

Abstract

Changes in women's menstrual bleeding patterns precede the onset of menopause. In this paper, the authors identify population subgroups based on menstrual characteristics of the menopausal transition experience. Using the TREMIN data set (1943-1979), the authors apply a Bayesian change-point model with 8 parameters for each woman that summarize change in menstrual patterns during the menopausal transition. The authors use estimates from this model to classify menstrual patterns into subgroups using a K-medoids algorithm. They identify 6 subgroups of women whose transition experience can be distinguished by age at onset, variability of the menstrual cycle, and duration of the early transition. The results suggest that for most women, mean and variance change points are well aligned with proposed bleeding markers of the menopausal transition, but for some women they are not clearly associated. Increasing understanding of population differences in the transition experience may lead to new insights into ovarian aging. Because of age inclusion criteria, most longitudinal studies of the menopausal transition probably include only a subset of the 6 subgroups, suggesting potential bias.