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dc.contributor.authorKarimi, Margaret W
dc.date.accessioned2013-05-22T08:38:09Z
dc.date.available2013-05-22T08:38:09Z
dc.date.issued1994
dc.identifier.citationDoctor Of Philosophyen
dc.identifier.urihttp://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/24369
dc.description.abstractThis study attempts to identify the salient determinants of fertility in Nairobi and Mombasa. The objectives of the study are to determine the level of fertility in these two urban centres as well as to assess the role played by background and proximate determinants in contributing to the observed fertility. The study uses data from 1989 Kenya Demographic and Health survey and from a sample survey of 1300 evermarried women who were selected from different socio-economic groups in both Nairobi and Mornbasa. The analytical framework used in this study is adopted from Davis and Blake (1956) as well as a later modification by Bongaarts (1978; 1983). The regression model is used to find out the overall effect of these determinants in affecting fertility. Total number of children everborn is used as the dependent variable. The background variatiles studied include education of the female, her ethnic and religious background, her occupation and the number of years she has lived in the urban centre. The proximate determinants studied are marriage, contraception and pos t.pazt.uml.nfecundabiil-ty.- The findings of the study indicate that the estimated total fertility rate for Nairobi and Mombasa is 4.02 . The background variables have little direct influence on fertility. These variables are explaining only 14-petten~ of total variation in observed fertility, with educar i on of the female explaining the largest portion. Their influence on fertility is therefore mediated l through the proximate determinants. All these background determinants are having a significant impact on age at first marriage, contraception, as well as postpartum infecundability. These background variables are explaining 27 percent of the total variation in age at first marriage. The proximate determinants are explaining a large portion of fertility variation observed In Nairobi and Mombasa. Postpartum infecundability is the single most important proximate determinant in explaining variation of fertility in Nairobi and Mombasa, followed by non-marriage and lastly by contraception. Postpartum infecundability is reducing Total fecundity for women in Nairobi and Mombasa by 41 percent. Further, it is reducing Total fecundity of women with no education by 42.4 percent, by 48.7 per cent for women with primary education and 31.3 percent for those with secondary education and above. The variable of non-marriage is reducing Total marital fertility for women in Nairobi and Mombasa by 34 percent. Its effect is slightly greater for women with secondary education and above than it is for the other category of women. It is reducing Total marital fertility by 37.8 percent for women with secondary education and above, by 31.5 percent for women with primary education and by 34.1 percent of those women with no education. Modern contraception is being used by only 36.7 percent of the women interviewed in Nairobi and Mombasa. It is reducing Total natural marital fertility in Nairobi and Mombasa by 32.5 percent. w.',. ~ Its effect In reducing fertility, lncreases with ascertdinglevels of women's education. Contraception is the greatest inhibitor of fertility for women wich II secondary education and above followed by non-marriage and lastly by postpartum infecundability. When both the background and proximate determinants are used in the multiple regression model, the results indicate that these variables are explaining 49 percent of total variation observed in fertility. Of these, desired family size is explaining 42 percent of the total variation in fertility. The main conclusion drawn from these findings is that education of the female, and especially secondary education is the single most important variable influencing fertility through the proximate determinants of age at first marriage, contraception, postpartum infecundability and desired family size. The study recommends to policy makers to have policies that would ensure that women are encouraged to finish school especially until they attain secondary education. Policies geared towards lowering desired family size would go along way in encouraging further fertility decline in these urban centres. Specific programs should be formulated to encourage women to use modern contraception and to breastfeed their children for longer periods. Such programs are likely to result in further decline in fertility. There is need for researchers to find out what really motivates the women to desire a certain family size. This calls for thorough ethnographic studies that would shed light about the factors that influence these sensitive decisions which are definitely critical in reproductive behaviour. Besides, researchers shou~d .._ loo"'"k into the other unconsidered variables that are contributing to the remaining ., unexplained variation in fertility.en
dc.language.isoenen
dc.publisherUniversity Of Nai, Robien
dc.titleDeterminants of fertility in urban centres in Kenya: a case study of Nairobi and Mombasaen
dc.typeThesisen
local.publisherDepartent Of Geographyen


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