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dc.contributor.authorNjuguna, Njenga John
dc.date.accessioned2013-05-21T14:29:26Z
dc.date.available2013-05-21T14:29:26Z
dc.date.issued2010
dc.identifier.urihttp://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/24224
dc.description.abstractThe study set out to find the contribution of each of the principal proximate determinants of fertility to the change in fertility observed between 2003 and 2008/09. Bongaarts model as proposed in 1978 and modified in 1983 was used in this study. Four factors were examined and these were marriage, contraception, postpartum infecundability and sterility. The other factor, abortion, which was identified by Bongaarts as being a key factor was not examined due to lack of data. The study first calculated the index of each of the four factors for both 2003 and 2008/09. After calculating these indexes, fertility levels for each of the two years were estimated by fitting the indexes into Bongaarts model. Using the estimated total fertility rates, the study estimated the reduction of total fecundity rate (TF) due to each of the four factors. Lastly, the study decomposed the estimated fertility change between 2003 and 2008/09 into proportions that were due to each of the four proximate determ inants. The findings of the study indicate that TFR declined by 7.5% at the aggregate level between 2003 and 2008/09. This decline is decomposed into a 3.3% decline due to change in marriage patterns, a 7.1% decrease due to an increase in contraceptive practice and a 2.9% increase due to shortening of the duration of postpartum infecundability. At sub population level TFR decreased in all regions except in Central province where fertility increased by 3.0% between 2003 and 2008/09. This increase can mostly be attributed to the shortening of the duration of postpartum infecundability which contributed 8.1% increase. A change in marriage pattern in Central province also contributed to the increase in TFR by 1.9%. The change in TFR in Central would even have been higher had the effect of postpartum infecundability and change in marriage pattern not been offset by the increase in contraceptive practice. Among all the regions, Western province had the highest decline in TFR of about 19% between 2003 and 2008/09. The province also had the highest increase in contraceptive practice as attested by 16.0% decrease in TFR due to this practice. TFR among women with no education, women with secondary education and higher and the richest women increased between 2003 and 2008/09. It is interesting to note that, among the most educated women, all the 3 key proximate determinants contributed to the increase in TFR between 2003 and 3008/09 with change in marriage pattern and decrease in the duration of postpartum infecundability each contributing about 4% in the 12% of estimated fertility increase. Richest women also saw their TFR increase between the two reference years by 2.2%. This increase was mostly due to the shortening of the duration of postpartum infecundability which contributed 4.0% in this increase. There was no change in marriage pattern among the richest between 2003 and 2008/09. All in all, increase in the contraceptive practice had the highest impact in the decrease of IV i J fertility between 2003 and 2008/09 at the aggregate and across all sub population levels except among the most educated women. Except in Eastern province, the duration of postpartum infecundability decreased at the aggregate and at sub population levels leading to an increase in fertility due to this factor between 2003 and 2008/09. The highest such increase was recorded among women with no education and women in Central province. The study recommends that due to the important role contraception is playing in fertility reduction in the country, there is need to sustain the current trend in the increase in contraception prevalence. In particular, special attention should be paid to regions that have continued to register low contraception prevalence such as North Eastern province by addressing the known factors that are responsible for this. These factors are accessibility, affordability, and awareness. The case of Central province calls for enhancing other fertility control methods other than just relying on contraception. Despite the province having some of the highest increase in contraception prevalence, it still recorded an increase in fertility rate. Contraception alone is not enough to reduce fertility levels. Lastly, the study recommends that research be done on the role of induced abortion in Kenya in order to give more accurate estimates of the impact of fertility inhibiting variables and their implication on family planning programs.en
dc.description.sponsorshipThe University of Nairobien
dc.language.isoenen
dc.subjectProximate determinants of fertility on change in total fertility rate in Kenyaen
dc.subject2003 and 2008/09en
dc.titleImpact of proximate determinants of fertility on change in total fertility rate in Kenya between 2003-2008/09en
dc.typeThesisen
local.publisherPSRIen


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