{"title":"用层次线性模型解释伊朗育龄期已婚妇女生育率","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":"{\"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}","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}
Explaining the Married Women’s Fertility in Reproductive Ages in Iran Using Hierarchical Linear Model
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