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Global Health Econ Sustain Stochastic modeling of age at menopausal

5. Conclusion Conflict of interest

Menopause is a confirmed and non-avoidable event in the The authors declare that they have no competing interests
fertility life of women. It has different effects on the health, in publishing this article.
social, and physical status of women. In this paper, we used
different probability models to fit the distributional pattern Author contributions
of age at menopause for Nepalese women. Different test Conceptualization: Arjun Kumar Gaire
statistics were used to validate the model fitting. The logistic Investigation: All authors
distribution better fitted the menopause data of Nepalese Supervision: Yogendra Bahadur Gurung, Tara Prasad
women. The four-parameter RGLLog distribution was Bhusal
also found to better fit the menopausal data and used to Formal analysis: Arjun Kumar Gaire
construct the menopausal table using the fitted probability Writing – original draft: Arjun Kumar Gaire
of this distribution. It was observed that the distribution of Writing – review & editing: All authors
the data sets deviated from normality which was consistent
with many research findings. The fitted results of the Ethics approval and consent to participate
significant model were used to construct the menopausal life Not applicable.
table. It was estimated that the expected age of menopause
or waiting time of menopause at the birth of Nepalese girls Consent for publication
from 2005 data was 45.511 years by logistic distribution Not applicable.
and 46.131 years by RGLLog distribution; meanwhile, it
was 49.135 years by logistic distribution and 51.179 years Availability of data
by RGLLog distribution for 2018 data. Furthermore, when Data used for this research can be found in Aryal, T. R.,
menopause was expected from the age of menarche, and if & Yadava, K. N. S. (2005). Age at menopause among
girls have menarche at the age of 15, then the expected age Nepalese women. Journal of Population and Social Studies,
of menopause is after 30.507 years by logistic distribution 14(1), 95-114. https://so03.tci-thaijo.org/index.php/jpss/
and 31.146 years by RGLLog distribution for 2005 data, and article/view/103943 and https://elibrary.nhrc.gov.np/
after 34.973 years by logistic distribution and 36.49 years handle/20.500.14356/1580
by RGLLog distribution for 2018 data. The results and
findings of this research helped to further the projection References
of trends in the timing of menopause and provided Aryal, G.R. (2013). Transmuted log-logistic distribution. Journal
insights into the factors that influence this important of Statistics Applications and Probability, 2(1):11-20.
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helped to identify the most likely age at menopause, the
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who are dealing with the consequences of menopause
and postmenopause, researchers who are developing new https://doi.org/10.1016/j.jhydrol.2006.01.014
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managing menopause. of Statistical Theory and Applications, 11(3):265-291.
Gaire, A.K., & Aryal, R. (2015). Inverse Gaussian model to
Acknowledgments describe the distribution of age specific fertility rates
None. of Nepal. Journal of Institute of Science and Technology,
20(2):80-83.
Funding https://doi.org/10.3126/jist.v20i2.13954
None. Gaire, A.K., & Gurung, Y.B. (2023). Rayleigh generated log-

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