Identifying women who share patterns of reproductive hormones, vasomotor symptoms, and sleep maintenance problems across the menopause transition: group-based multi-trajectory modeling in the Study of Women's Health Across the Nation.

Abstract

To identify groups of women who share levels and patterns of change in follicle-stimulating hormone (FSH), self-reported sleep maintenance problems, and frequent vasomotor symptoms (VMS) up to 10 years before and after their final menstrual period and to evaluate their premenopausal characteristics. Group-based multi-trajectory modeling grouped 1,407 women from the Study of Women's Health Across the Nation who had an observed natural menopause and did not use hormone therapy, based on repeated measures of FSH, sleep maintenance problems, and frequent VMS relative to final menstrual period. Multivariable analyses assessed race/ethnicity, body mass index, smoking, and depressive symptoms as predictors of group membership. Women formed five distinct groups: (1) low symptoms (low VMS/sleep problems)/high FSH rise (N = 552; 39.2%); (2) moderate VMS and sleep problems/low FSH rise (N = 169; 12.0%); (3) dominant sleep problems (lower VMS/high sleep problems)/high FSH rise (N = 203; 14.4%); (4) dominant VMS (high VMS/lower sleep problems)/high FSH rise (N = 297; 21.1%)); and (5) high symptoms (high VMS/high sleep problems)/intermediate FSH rise (N = 186; 13.2%)). Multivariate analyses showed that race/ethnicity, premenopausal body mass index and depressive symptoms, and increasing depressive symptoms during the early phase of the transition predicted group membership. Women can be classified based on shared levels and patterns of FSH, sleep maintenance problems, and frequent VMS across the menopause transition. Either VMS or sleep maintenance problems can be dominant in the face of high FSH. Experiencing one menopause-related symptom or hormone profile does not automatically imply that another is also being experienced.