Analysis of Regional Proximate Determinants of Fertility in Kenya
Abstract
This study set out to analyze regional fertility variations in Kenya focusing on the proximate
determinants using the 2003 KDHS. The four proximate determinants by Bongaarts are: nonmarriage,
contraceptive use, sterility and postpartum non-susceptibility on fertility in the regions.
A modification of the model by John Stover (1998) was used to take into account the impact of
non marital childbearing and secondary sterility. The contribution of each proximate determinant
is studied across the regions using both methods and a comparison is then made within the
regions and also between both methods.
In the high fertility region the highest inhibiting factor was lactation, followed by late and non
marriage, then sterility and lastly contraception. For the low fertility region, late and non
marriage have the highest fertility inhibiting effect, then lactation followed by contraceptive and
lastly sterility. In the control region late and non marriage had the highest inhibiting effect, then
lactation then sterility and lastly contraception. The contribution made by fertility outside
marriage is high in the control region followed by the low fertility region.
Overall the results show that the index of marriage decreased with the increase in the level of
education, the same effect was observed for the index of contraception. The impact oflactation is
very high in the rural areas while the impact of the index of marriage effect is very high in the
urban areas. Births outside marriage are very high in the urban areas and among the women with
no education. In general the effect of marriage and lactation in inhibiting fertility is high in all
the regions with contraceptive use and sterility being low.
The analysis of the levels of the proximate variables showed that the reducing effect of the three
main intermediate variables varied within the regions. The reducing effect of lactation was
almost the same in the high and low fertility region. Contraception had the lowest reducing effect
in all the regions while marriage had a higher reducing effect in the low fertility region then the
control region and lastly the high fertility region.
The key policy implication of this study is to include empowerment of women through education
which will in turn lead to inhibition of fertility. The relevant stakeholders in the family planning
programmes should intensify the distribution of contraceptives and come up with strategies that
will make their services accessible to everyone.
This study recommends further research to establish other factors that influence fertility
variations regionally. It recommends other method of analysis that can elicit other fertility
inhibiting patterns that could support the findings
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The University of NairobiPublisher
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