AccScience Publishing / GHES / Volume 1 / Issue 2 / DOI: 10.36922/ghes.1239
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Stochastic modeling of age at menopause for Nepalese women and development of menopausal life table

Arjun Kumar Gaire1* Yogendra Bahadur Gurung1 Tara Prasad Bhusal2
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1 Central Department of Population Studies, Tribhuvan University, Nepal
2 Central Department of Economics, Tribhuvan University, Nepal
Submitted: 4 July 2023 | Accepted: 21 August 2023 | Published: 25 September 2023
© 2023 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( )

Menopause, which connotes the end of a woman’s fertility, is a key turning point in her reproductive life. Women’s age at which menopause occurs is affected by several biological, social, as well as economic factors. The previous studies on age at menopause mainly concerned with describing the status, differential, determination, and consequence of it on women’s health. Stochastic analysis of distributional patterns of the age at menopause has been paid little attention by researchers. Therefore, probability distributions are applied to analyze the timing of menopause stochastically. The results of the fitted model are used to construct the menopausal life table. The main aim of this research was to identify an efficient probability distribution to explain the age at menopause in Nepalese women. This involved identifying the model that best fits the data, determining the characteristics of age at menopause described by the model, and constructing a menopausal life table to compute the waiting time of menopause for women. Further, the probability of having menopause and not having menopause at a particular age was presented. To achieve these objectives, secondary data sets were used to fit probability models, and a range of statistical tools were employed to test and validate the model fitting. The results showed that the logistic distribution better captured tshe menopausal information of Nepalese women and can be applied to formulate the menopausal life table. Further, out of several parameter models used, the Rayleigh-generated log-logistic model better fitted the data so it was considered to construct a menopausal life table. This study provided a distributional pattern of the current and future menopausal timing of Nepalese women. Furthermore, it provided insights into the factors that influence this important milestone in women’s reproductive life. These findings could be helpful to medical personnel who are dealing with the consequences of menopause and post-menopause, policymakers who aim to improve women’s health, and researchers who are working in this field.

Menopausal life table

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Conflict of interest
The authors declare that they have no competing interests in publishing this article.
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Global Health Economics and Sustainability, Electronic ISSN: 2972-4570 Published by AccScience Publishing