Volume 13, Issue 2 (Vol.13, No.2, Summer 2017)
irje 2017, 13(2): 153-161 |
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Bagheri A, Razeghi Nasrabad H, Saadati M. Identification of Fertility Preference Determinants Using Poisson Regression. irje 2017; 13 (2) :153-161
URL: http://irje.tums.ac.ir/article-1-5761-en.html
URL: http://irje.tums.ac.ir/article-1-5761-en.html
1- Assistant Professor, National Population Studies & Comprehensive Management Institute, Tehran, Iran , arezoo.bagheri@psri.ac.ira
2- Assistant Professor, National Population Studies & Comprehensive Management Institute, Tehran, Iran
2- Assistant Professor, National Population Studies & Comprehensive Management Institute, Tehran, Iran
Abstract: (6908 Views)
Background and Objectives: Changes in ideals and aspirations of childbearing are important factors in fertility behavior. Nowadays, fertility rate reduction below the replacement level and decreased childbearing ideals are the most common fertility challenges in Iran. So, with the decrease in the fertility rate, it is necessary to be aware of the ideal number of children and its determinants in order to adopt suitable population policies contexts. The main objective of this study was to investigate factors affecting the ideal number of children using Poisson regression model.
Methods: In 2012, 389 ever married women aged 15-49 in Semnan Province were selected using two-phase stratified random sampling method and studied through applying a structured questionnaire. To model the ideal number of children by Poisson regression model, marriage duration has taken as offset and the number of children, job status, education level, marriage type, and resident place were considered as predictors. The model was fitted with SPSS software version 22.
Results: All predictors in this study had significant effects on ideal number of children in Semnan (p-value <0.05). Women’s ideal number of children who had 2 or fewer children, were employed, and had university education with consanguineous and rural marriage was higher than those who had 3 and more children, were unemployed, and had elementary and secondary education with inter-family and urban marriage.
Conclusion: To model the ideal number of children, since it is discrete and count, a Poisson regression model is more efficient as compared to linear regression model.
Methods: In 2012, 389 ever married women aged 15-49 in Semnan Province were selected using two-phase stratified random sampling method and studied through applying a structured questionnaire. To model the ideal number of children by Poisson regression model, marriage duration has taken as offset and the number of children, job status, education level, marriage type, and resident place were considered as predictors. The model was fitted with SPSS software version 22.
Results: All predictors in this study had significant effects on ideal number of children in Semnan (p-value <0.05). Women’s ideal number of children who had 2 or fewer children, were employed, and had university education with consanguineous and rural marriage was higher than those who had 3 and more children, were unemployed, and had elementary and secondary education with inter-family and urban marriage.
Conclusion: To model the ideal number of children, since it is discrete and count, a Poisson regression model is more efficient as compared to linear regression model.
Type of Study: Research |
Subject:
General
Received: 2017/08/30 | Accepted: 2017/08/30 | Published: 2017/08/30
Received: 2017/08/30 | Accepted: 2017/08/30 | Published: 2017/08/30
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