| dc.description.abstract | This study is a build-up on the findings of other studies, censuses and surveys in Kenya
whose results reveal that rural fertility has been consistently higher than that of the urban (Kangi,
1978; Omagwa, 1985; Osiemo, 1986; Ong'uti, 1987; the 1969 and 1979 National Population
Censuses; KDHS 1989 and 1993; KCPS, 1984). Recent findings indicate that the country's TFR
is 5.4 children per woman against the expected 3.4 (see table 1.1a), and that on average a rural
woman has 5.8 children as opposed to 3.4 for her urban counterpart (NCPD et al, 1994:21). The
major objective of the study was to determine the factors which contribute to urban-rural fertility
differentials, then generate policy and research recommendations based on the findings.
The major source of data for this study was KDHS, 1993. It was one of the latest and
most detailed surveys so far conducted in Kenya. The sample size was a total of 7540 women
aged 15-49 years of whom 15% lived in the urban areas while the remaining 85% were rural
dwellers. A series of important socio-economic, demographic, socio-cultural and Family
Planning (FP) factors formed the basis for the independent variables which included female
(mothers') education, work status, marital status, age at first marriage, under-five mortality,
ethnicity, religion, and access to the nearest FP service out-let in terms of time (minutes) to get to
source. The dependent variable was children ever born (CEB) while contraception served as the
proximate variable.
The study used various statistical methods ranging from frequencies and percentages,
cross tabulations with chi-square, to simple and multiple regression analysis. These techniques,
while fairly easy to understand and apply, proved most comprehensive and exhaustive in
producing the expected results. All the study variables were tested at 0.05 level of significance.
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The study has revealed that fertility differentials exist between urban and rural areas in
Kenya and that fertility is higher in the rural. As shown in table 4.1, whereas 24 4% of the rural
women had 6+ children, only 9.2% of the urban women had the same number of children. Of the
variables which had positive relationship with CEB, age of the mother at 35+ years had the
strongest significant influence on CEB followed by under-five mortality and the married
category of marital status in both urban and rural areas. Their impact was, however, generally
greater in the rural suggesting higher fertility for rural women. Late age at marriage and
secondary- education were found to be the major factors in fertility reduction, but with greater
influence in the urban explaining the low fertility that characterise urban areas. Contraception
had reducing effect on CEB in both areas, but its depressing effect was strongest for women with
secondary-^ education and lived in the urban, while minimal in the rural except among the highly
educated. Results indicate that against the initial purpose of spacing births, most Kenyan women
tend to use contraceptives basically to terminate births after getting enough children as security
against child loss, hence contraception was found more popular among women with many
children. It is no wonder that under-five mortality has been singled out by this study as a barrier
to success of contraception in fertility reduction attempt.
Most of the independent variables considered in this study tended to have more impact in
the rural areas. In the absence of proximate determinant (contraception), the variation in CEB
explained by all the independent variables together was 63.9% and 72.8% respectively for urban
and rural areas. Together with contraception, the variation explained rose to 65.9% in the urban
and 73.4% in the rural, showing greater impact of contraception in the urban. However,
demographic variables explained the bulk of the observed explained variations in CEB, 63 .3%
for urban and 72.3% for rural. It is an interesting finding of this study that while urban areas had
the advantage of better education, late age at marriage, fewer incidences of child loss and limited
attachment to ethnic dictates which are characteristic of low fertility, the scenario was relatively
different in the rural where fertility was found higher and attributed to low level of education,
greater concentration of the married and high parity women (aged 35+ years), early age at
marriage, more deaths to children aged below five years, affiliation to ethnic and religious beliefs
and practices, being far (60+ minutes) away from the nearest FP outlet, and minimal use of
contraception.
One major conclusion that can be derived from the study results is that secondary+
education is paramount in fertility reduction. Thus, this study recommends increase in school
enrolment for girls, and creation of more employment and training opportunities in the rural
areas. Further, efforts should be made to promote Reproductive Health Education in schools to
enable the youth to understand the dangers of high population and to develop a more positive
attitude towards limitation of family size as a primary step to development | en_US |
