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مقالات فارسیISIکنفرانسهاژورنالها

Evaluation of multiple linear regression function and generalized linear model types in estimating natural menopausal age: A cross-sectional study

محل انتشار: مجله طب تولید مثل ایران، دوره: 20، شماره: 5
سال انتشار: 1401
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 362

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استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:
https://civilica.com/doc/1459704

شناسه ملی سند علمی:

JR_IJRM-20-5_004

تاریخ نمایه سازی: 17 خرداد 1401

چکیده مقاله:

Background: Since women spend about one-third of their lifespan in menopause, accurate prediction of the age of natural menopause and its effective parameters are crucial to increase women's life expectancy. Objective: This study aimed to compare the performance of generalized linear models (GLM) and the ordinary least squares (OLS) method in predicting the age of natural menopause in a large population of Iranian women. Materials and Methods: This cross-sectional study was conducted using data from the recruitment phase of the Shahedieh Cohort Study, Yazd, Iran. In total, ۱۲۵۱ women who had the experience of natural menopause were included. For modeling natural menopause, the multiple linear regression model was employed using the ordinary least squares method and GLMs. With the help of the Akaike information criterion, root-mean-square error (RMSE), and mean absolute error, the performance of regression models was measured. Results: The mean age of menopausal women was ۴۹.۱ ± ۴.۷ yr (۹۵% CI: ۴۸.۸-۴۹.۳) with a median of ۵۰ yr. The analysis showed similar Akaike criterion values for the multiple linear models with the OLS technique and the GLM with the Gaussian family. However, the RMSE and mean absolute error values were much lower in GLM. In all the models, education, history of salpingectomy, diabetes, cardiac ischemic, and depression were significantly associated with menopausal age. Conclusion: To predict the age of natural menopause in this study, the GLM with the Gaussian family and the log link function with reduced RMSE and mean absolute error can be a good alternative for modeling menopausal age.

کلیدواژه ها:

Menopause ، Etiology ، Statistics ، Numerical data. ، سن یائسگی ، مدل­های تعمیم­یافته خطی ، کوهورت شاهدیه.

نویسندگان

Nasrin Sadeghi

Department of Statistics and Epidemiology, Shahid Sadoughi University of Medical Sciences, Yazd, Iran. Sadeghi.stat۸۹@ gmail.com (+۹۸)۰۹۳۸۷۷۸۶۹۵۱

Hossien Fallahzadeh

Research Center of Prevention and Epidemiology of Non-Communicable Diseases, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd-Iran. Fallahzadeh.ho@gmail.com (+۹۸)۰۹۱۳۱۵۲۹۴۸۶

Maryam Dafei

Research Center for Nursing and Midwifery Care, School of Nursing and Midwifery, Shahid Sadoughi University of Medical Sciences Yazd-Iran. maryam_dafei@yahoo.com (+۹۸)۰۹۱۳۲۵۸۸۴۹۹

Maryam Sadeghi

Ferdowsi University of Mashhad, Faculty of Mathematical Sciences, Mashhad, Iran. Sadeghi.maryam@mail.um.ac.ir (+۹۸)۰۹۳۷۸۰۹۹۹۷۹

Masoud Mirzaei

Center for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology, School of public health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran. Masoud_mirzaei@hotmail.com (+۹۸) ۰۹۱۳۴۵۰۹۹۱۷

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