{"title":"Explaining the Married Women’s Fertility in Reproductive Ages in Iran Using Hierarchical Linear Model","authors":"S. Mahmoudiani","doi":"10.29252/payesh.19.3.289","DOIUrl":null,"url":null,"abstract":"2020] Objective (s ) : Regarding changes in women’s fertility in Iran, this study attempted to explain fertility changes of married women aged 15-49 years old in Iran at individual and province level. Methods: The data were extracted from the Census 2016 and some of the province data were analyzed based on hierarchical linear model through HLM software. Results: The findings showed that individual characteristics had a larger impact on fertility than province characteristics impact. Women's fertility difference by province was significant. All individual characteristics had a significant impact on fertility and it explained a total of 44% of variance of women's fertility. Also, about 46% of variance of interprovincial childbearing was explained through characteristics for provinces in this study. Conclusion: Since currently the socio-economic development indexes are sub-optimal, more intense decline in fertility is likely and the relative continuity of the current fertility level is to be","PeriodicalId":55683,"journal":{"name":"Payesh","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Payesh","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29252/payesh.19.3.289","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Nursing","Score":null,"Total":0}
引用次数: 1
Abstract
2020] Objective (s ) : Regarding changes in women’s fertility in Iran, this study attempted to explain fertility changes of married women aged 15-49 years old in Iran at individual and province level. Methods: The data were extracted from the Census 2016 and some of the province data were analyzed based on hierarchical linear model through HLM software. Results: The findings showed that individual characteristics had a larger impact on fertility than province characteristics impact. Women's fertility difference by province was significant. All individual characteristics had a significant impact on fertility and it explained a total of 44% of variance of women's fertility. Also, about 46% of variance of interprovincial childbearing was explained through characteristics for provinces in this study. Conclusion: Since currently the socio-economic development indexes are sub-optimal, more intense decline in fertility is likely and the relative continuity of the current fertility level is to be