A Bagheri, Hb Razeghi Nasrabad , M Saadati,
Volume 13, Issue 2 (9-2017)
Abstract
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.
F Amini, A Abadi, M Namdari, Z Ghorbani, S Azimi,
Volume 16, Issue 2 (8-2020)
Abstract
Background and Objectives: Cancer is a complex disease with a lengthy and expensive course of treatment that causes many problems for the community. Knowledge of oral cancer plays an important role in early diagnosis. The aim of this study was to determine the level of knowledge about the symptoms and risk factors of oral cancer and assess the related factors.
Methods: In this study, 671 parents of primary school children were randomly selected from primary schools in four districts of Tehran. The participants were asked to answer questions related to demographic characteristics and knowledge of the risk factors and symptoms of oral cancer. Data analysis was done using Poisson regression model and multi-level Poisson regression model using SPSS and STATA software. The AICI Akaike Information Criterion (AIC) was applied to evaluate the models.
Results: The mean score of knowledge was 3.7 with a standard deviation of 6.7. Among the studied variables, female gender, advanced age, a higher SES score, and a higher welfare index had positive effects on oral cancer knowledge (P <0.05).
Conclusion: The results of this study showed that demographic, social and economic factors of parents were effective on oral cancer. It can be statistically concluded that a multilevel Poisson regression model is more suitable for analyzing this data.
