Age at the menopause can be assessed using predictive modelling
The natural menopause occurs when the menstrual periods cease due to the naturally decreased ovary function. There is a significant interindividual variation in the age at natural menopause but, on average, women undergo it around the age of 51 in Western countries. Furthermore, the length of the preceding menopausal transition, characterized by irregular menstrual cycles and menopausal symptoms, is also known to vary between individuals.
The study revealed that higher estradiol and follicle-stimulating hormone levels, irregular menstrual cycles, and menopausal symptoms are strong indicators of approaching menopause in middle-aged women. Additionally, information related to life habits, such as physical activity, alcohol consumption, and smoking, may provide useful information for assessing the time to natural menopause.
After the menopause, women can no longer get pregnant naturally, but the age at menopause has also been associated with the risk of several public health concerns such as cardiovascular disease, cancer, and osteoporosis.
"The prediction of the age at natural menopause is beneficial for health promotion with middle-aged and elderly women but it could also be useful for women making decisions related to family planning and treatments for menopausal symptoms," explains doctoral researcher Matti Hyvärinen from the Gerontology Research Center and Faculty of Sport and Health Sciences, University of Jyväskylä.
The predictive models constructed in the study demonstrated adequate prediction accuracy with absolute errors of slightly over 6 months between the predicted and observed age at natural menopause in middle-aged women.
According to Hyvärinen, the results indicate that the approach used in the study may be used to develop a tool for assessing the age at natural menopause also for women in their 30s or early 40s in the future.
The study was carried out in the Gerontology Research Center and Faculty of Sport and Health Science at the University of Jyväskylä, Finland. It was part of the Estrogenic Regulation of Muscle Apoptosis (ERMA) study led by Academy Research Fellow Eija Laakkonen. The participants in the ERMA study were women between the ages of 47 and 55 living in the Jyväskylä region at the baseline. Participants that were perimenopausal during the baseline measurements were invited to the follow-up study, which included laboratory visits every 3 to 6 months until the participant was categorized as postmenopausal. The research has been funded by the Academy of Finland, European Commission, and Juho Vainio Foundation.
Abstract
Objective:
To predict the age at natural menopause (ANM).
Methods:
Cox models with time-dependent covariates were utilized for ANM prediction using longitudinal data from 47 to 55-year-old women (n = 279) participating in the Estrogenic Regulation of Muscle Apoptosis study. The ANM was assessed retrospectively for 105 women using bleeding diaries. The predictors were chosen from the set of 32 covariates by using the lasso regression (model 1). Another easy-to-access model (model 2) was created by using a subset of 16 self-reported covariates. The predictive performance was quantified with c-indices and by studying the means and standard deviations of absolute errors (MAE ± SD) between the predicted and observed ANM.
Results:
Both models included alcohol consumption, vasomotor symptoms, self-reported physical activity, and relationship status as predictors. Model 1 also included estradiol and follicle-stimulating hormone levels as well as SD of menstrual cycle length, while model 2 included smoking, education, and the use of hormonal contraception as additional predictors. The mean c-indices of 0.76 (95% CI 0.71-0.81) for model 1 and 0.70 (95% CI 0.65-0.75) for model 2 indicated good concordance between the predicted and observed values. MAEs of 0.56 ± 0.49 and 0.62 ± 0.54 years respectively for model 1 and 2 were clearly smaller than the MAE for predicted sample mean (1.58 ± 1.02).
Conclusions:
In addition to sex hormone levels, irregularity of menstrual cycle, and menopausal symptoms, also life habits and socioeconomic factors may provide useful information for ANM prediction. The suggested approach could add value for clinicians’ decision making related to the use of contraception and treatments for menopausal symptoms in perimenopausal women.
Reference
Hyvärinen, M., Karvanen, J., Aukee, P., Tammelin T. H., Sipilä, S., Kujala, U. M., Kovanen, V., Rantalainen, T. & Laakkonen, E. K. Predicting the Age at Natural Menopause in Middle-Aged Women. Menopause, April 12, 2021.