| dc.description.abstract | Nairobi which is the study area, is the largest urban centre and capital of Kenya. It acquired its urban status in 1950. It is located almost at the centre of the country. From North to south, it stretches from 2010'S to 2050'S and from East to West, it stretches from 370 10'E to 360 40'E, thus covering an area of 684 square kilometres. According to the 1979 Kenya population census statistics, Nairobi had a total population of 827,775 people. This was 5.4 per cent of the total annual population of Kenya which was 15,327,061 people. The main objectives of this study were to examine fertility levels between wards in Nairobi in order to establish how low they are, and if fertility differentials exist between wards. The study also attempts to identify the various socio-economic and demographic factors that influence fertility and in what direction. Motivation for this study stemmed from the fact that fertility is the major contributor to the population in the early years of life. This youthful population needs care in terms of provision of the essential services like education, health, food, shelter and transport especially in an urban centre where children depend directly on their parents for these services. There is need to understand the level of total fertility rates in Nairobi so as to assess the contribution of fertility to this youthful population. To achieve these objectives, the 1979 Kenya population census forms the basis of the data used in this study. It was found to be rather detailed unlike the other previous censuses of 1962, 1948 and 1969. Thus, data on fertility and other related socio-economic and demographic factors used in this study were obtained. The demographic techniques used for fertility estimation are: current fertility, life-time fertility, (P3)2/P2 fertility and the Brass p/F ratio fertility methods. The multiple regression analysis is the statistical technique used in this analysis. This technique is suitable in that it can enter many variables into the analysis and it can establish their absolute and relative effects upon the dependent variable (fertility in this case). The F-statistic test has been used to test the levels of significance and thus confirm the stated hypotheses. This study has revealed that fertility differentials exist between wards in Nairobi. A total fertility rate of 5.47 births was .estimated for Nairobi. At ward level, births ranging from 3.62 to 8.29 was observed in Kilimani and Maisha-Makongeni wards respectively. These differentials are quite high in an urban setting of this kind. Some wards are experiencing very high total fertility rates and this may be associated with the differentials in socio-economic and demographic factors. The analysis of the data revealed that the selected socio-economic and demographic variables are found to influence and account for 84.4 per cent (R2) of the variation in total fertility rates in Nairobi. The corresponding F-statistic at (df. .8,31) was 20.9 which is found significant ,.. .•. at .05,.. 01 and .001 levels. Female education proved to be the major determinant of total fertility rates in Nairobi. It was found to be negatively related to total fertility rates. A computed correlation coefficient (r) of -0.630 was obtained and this confirms the stated hypothesis. It explains 39.7 per cent of the total variation in total fertility rates between wards in Nairobi. Male education was also found to be negatively related, to total fertility , rates. A computed correlation coefficient (r) of -0.585 confirms the stated hypothesis. Illiteracy of both adults (Male and female was found to be positively related to total fertility rates in Nairobi. A compute K correlation coefficient (r) of 0.376 confirms stated hypothesis that illiteracy is positively related to fertility. Child mortality levels are also found to be inversely related to total fertility rates in Nairobi. A computed correlation coefficient (r) of -0.306 confirms the stated hypothesis. All the ethnic groups (Kikuyu, Luo, Luhyia and Kamba) considered in this study are found to have a positive influence on total fertility rates. Computed correlation coefficients (r) 0.346, 0.444, 0.274 and 0.119 respectively confirm the stated hypothesis that ethnicity is positively related to fertility rates. Some recon@endations that emerge from this study for both city and national policy planners are:- In order to reduce fertility rates both in Nairobi and in Kenya at large, the educational levels of both males and females should be increased. This will help wipe out illiteracy which is found to be positively related to fertility. It will also increase the knowledge and awareness about contraception and it will also change attitudes on family size desires. It will also help create employment opportunities. Secondly, child mortality rates should be reduced by providing better health and nutritional services to both mothers and children. This will increase the survival rates of children thus increase the confidence in parents that the children they have will survive, thus desired family sizes will be achieved. Ethnic groups should also be given more formal education in order to change their attitudes on family size and their life-styles | en |
