{"title":"苏丹生育率的决定因素:多指标类集调查分析,2014","authors":"M. Hassan, S. Sukamdi, A. Pitoyo","doi":"10.22146/JP.44146","DOIUrl":null,"url":null,"abstract":"Sudan has continuously reported high fertility rates. While the influence of both underlying and proximate determinants is well documented in various studies worldwide, there’s a lack of recent information on their influence on fertility in Sudan. Therefore, the objective of this study to examine the levels, patterns and determinants of fertility in Sudan. The analyses were based on 2014 Sudan Multiple Indicators Cluster Survey (SMICS) data. The SMICS data is nationally representative data. The survey sampled 18,302 women across the country, collecting information on females aged 15-49 years. The analysis was based on the Bongaarts Model. Results show that post-partum infecundability has the largest effect in reducing fertility in Sudan (30.7 per cent or 4.7 birth) followed by marriage (27.5 per cent or 4.3 birth) and contraceptive (7.8 per cent or 1.2 birth). The findings of study shown also that significant differences between education, wealth, and place of residence. This means that the increase in education, especially higher education, improve the wealth status and living in urban areas seem to have a great influence toward fertility education in Sudan. Also, it agreed that there is a regional fertility differential associated with social and economic development in the different region and states. Therefore, in order to manage fertility in Sudan, policies and programmes should consider the effects of marriage, postpartum infecundity, contraception, education, and wealth on fertility. Lack of such targeted interventions, population growth will remain a challenge in Sudan. ","PeriodicalId":31592,"journal":{"name":"Populasi","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fertility Determinan in Sudan: Analysis of Multiple Indicator Cluster Survey, 2014\",\"authors\":\"M. Hassan, S. Sukamdi, A. Pitoyo\",\"doi\":\"10.22146/JP.44146\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sudan has continuously reported high fertility rates. While the influence of both underlying and proximate determinants is well documented in various studies worldwide, there’s a lack of recent information on their influence on fertility in Sudan. Therefore, the objective of this study to examine the levels, patterns and determinants of fertility in Sudan. The analyses were based on 2014 Sudan Multiple Indicators Cluster Survey (SMICS) data. The SMICS data is nationally representative data. The survey sampled 18,302 women across the country, collecting information on females aged 15-49 years. The analysis was based on the Bongaarts Model. Results show that post-partum infecundability has the largest effect in reducing fertility in Sudan (30.7 per cent or 4.7 birth) followed by marriage (27.5 per cent or 4.3 birth) and contraceptive (7.8 per cent or 1.2 birth). The findings of study shown also that significant differences between education, wealth, and place of residence. This means that the increase in education, especially higher education, improve the wealth status and living in urban areas seem to have a great influence toward fertility education in Sudan. Also, it agreed that there is a regional fertility differential associated with social and economic development in the different region and states. Therefore, in order to manage fertility in Sudan, policies and programmes should consider the effects of marriage, postpartum infecundity, contraception, education, and wealth on fertility. Lack of such targeted interventions, population growth will remain a challenge in Sudan. \",\"PeriodicalId\":31592,\"journal\":{\"name\":\"Populasi\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Populasi\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22146/JP.44146\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Populasi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22146/JP.44146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fertility Determinan in Sudan: Analysis of Multiple Indicator Cluster Survey, 2014
Sudan has continuously reported high fertility rates. While the influence of both underlying and proximate determinants is well documented in various studies worldwide, there’s a lack of recent information on their influence on fertility in Sudan. Therefore, the objective of this study to examine the levels, patterns and determinants of fertility in Sudan. The analyses were based on 2014 Sudan Multiple Indicators Cluster Survey (SMICS) data. The SMICS data is nationally representative data. The survey sampled 18,302 women across the country, collecting information on females aged 15-49 years. The analysis was based on the Bongaarts Model. Results show that post-partum infecundability has the largest effect in reducing fertility in Sudan (30.7 per cent or 4.7 birth) followed by marriage (27.5 per cent or 4.3 birth) and contraceptive (7.8 per cent or 1.2 birth). The findings of study shown also that significant differences between education, wealth, and place of residence. This means that the increase in education, especially higher education, improve the wealth status and living in urban areas seem to have a great influence toward fertility education in Sudan. Also, it agreed that there is a regional fertility differential associated with social and economic development in the different region and states. Therefore, in order to manage fertility in Sudan, policies and programmes should consider the effects of marriage, postpartum infecundity, contraception, education, and wealth on fertility. Lack of such targeted interventions, population growth will remain a challenge in Sudan.