Fertility rates and trends in Kenya
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
Sponsorhip
The University of NairobiPublisher
Population studies and research institute ( PSRI)