Latent class modeling of markers of day-specific fertility

Abstract

There is a considerable interest in predicting the fertile days in a woman’s menstrual cycles in couples desiring a pregnancy and among those wishing to avoid conception by periodic abstinence. Cervical mucus detection is potentially an accurate marker of fertile days. It is therefore of great interest to assess the magnitude of heterogeneity among women and among cycles and among cycles of a given woman, in the evolution in time of the mucus secretions detected during an interval of potential fertility and defined relative to ovulation. In this paper, we study the problem of heterogeneity in cervical mucus hydration at various times relative to the mucus peak, both among cycles and among women, specifying and estimating appropriate multilevel latent class models for longitudinal data. Results showed that heterogeneity in mucus evolution among cycles and women is non-negligible. Model estimates identified different mucus patterns for groups of cycles and women, and the characteristics of the cycles and the women which influence mucus symptom evolution over time.