Predicting age at menopause

This article reviews methodologic and clinical aspects of predicting age at menopause. Lifetable methods or logistic models applied to a perimenopausal population represent the most feasible and the least biased methods for estimating the probability of menopause: by age. Information is emerging about risk factors besides age which influence risk for an earlier menopause and include a variety of medical, demographic, environmental, and genetic factors. The concept of menopause as a consequence of depleted oocytes suggests that the estimated number of ovulatory cycles might also be a useful predictor. Using these variables in a logistic model yields estimated probabilities of menopause for various risk profiles. Smokers who have accumulated more than 10 pack-years, women estimated to have had more than 300 ovulatory cycles, women with a history of depression, women who have lost one ovary at an early age, and women who have a family history of early menopause have earlier menopause and the greatest shift in the cumulative probability of menopause occurs in women with multiple risk factors.