Elsevier

Maturitas

Volume 23, Issue 3, April 1996, Pages 319-326
Maturitas

Predicting age at menopause

https://doi.org/10.1016/0378-5122(96)00992-9Get rights and content

Abstract

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.

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    However, as AMH still remains detectable at these reduced concentrations we can assume that the ovaries do not completely enter quiescence, with some follicular recruitment remaining. Decreased ovarian follicular activity during pregnancy would be consistent with the findings by some epidemiological studies that increased parity is associated with a delay in menopausal onset (Cramer and Xu, 1996; Gold et al., 2001; Whelan et al., 1990). The post-partum increase in AMH indicates that the presumed inhibition of follicular recruitment during pregnancy is released following birth.

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Financial Support: Supported by grant # R01 HD23661 from the National Institute of Child Health and Human Development.

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