ArticlePloS one2024
Age at natural menopause and its determinants in female population of Kharameh cohort study: Comparison of regression, conditional tree and forests.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Association of Depression with Age at Natural Menopause: A Cross-Sectional Analysis with NHANES Data.International journal of women's health · 2025Article
- Clustering Iranian women according to their menopausal severity symptoms and exploring the factors associated with severe categories, using baseline category logit model.BMC women's health · 2024Article
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Authors and funding
5 authors.
Funding
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Abstract
backgroundNatural menopause is defined as the permanent cessation of menstruation that occurs after 12 consecutive months of amenorrhea without any obvious pathological or physiological cause. The age of this phenomenon has been reported to be associated with several health outcomes.
objectivesThis study aimed to estimate the Age at Natural Menopause (ANM) and to identify reproductive and demographic factors affecting ANM.
methodsThis cross-sectional, population-based study was conducted on 2517 post-menopausal women aged 40-70 years participating in the first phase of the PERSIAN cohort study of Kharameh, Iran, during 2014-2017. To more accurately detect the determinants of ANM, we applied multiple linear regression beside some machine learning algorithms including conditional tree, conditional forest, and random forest. Then, the fitness of these methods was compared using Mean Squared Error (MSE) and Pearson correlation coefficient.
resultsThe mean±SD of ANM was 48.95±6.13. Both applied forests provided more accurate results and identified more predictors. However, according to the final comparison, the conditional forest was the most accurate method which recognized that more pregnancies, longer breastfeeding, Fars ethnicity, and urbanization have the greatest impact on later ANM.
conclusionsThis study found a wide range of reproductive and demographic factors affecting ANM. Considering our findings in decision-making can reduce the complications related to this phenomenon and, consequently, improve the quality of life of post-menopausal women.
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