A Comparative Analysis of Factors Explaining Fertility Differentials in Nyeri and Mandera Counties in Kenya

Abstract

The study’s objective was to determine and explain the effects of the socio-economic, cultural and proximate factors influencing fertility differentials in Nyeri and Mandera counties in Kenya. Two subsets of the 2014 Kenya Demographic and Health Survey data, containing 521 women for Mandera County and 698 women for Nyeri County were used for analysis. This study analysed the effects of ten explanatory variables, consisting of five background variables and five proximate determinant variables, on rate of childbearing in each county. The explanatory variables analysed were wealth index, education level, place of residence, age at first marriage and religion. The proximate variables: were marital status, ever use of modern contraceptives, experience of child mortality, age at first birth and ideal number of children. Rate of childbearing was measured by a composite variable consisting of children ever born and respondent age. The study applied descriptive statistics to describe the study variables and Poisson regression analysis to determine the effects of predictor variables on the outcome variable. Bivariate Poisson regression models were used to screen the independent variables considered in this study. Multivariate Poisson regression models fitted involved only the significant explanatory variables at bivariate analysis stage in both or either of the two counties. The results of the bivariate regression established that except for religion, all the selected background and proximate variables had significant effect on the rate of childbearing in both or either of the two counties. The results of multivariate regression revealed that age at first birth and experience of child death were common across the two although with varied effects, marital status was only unique in Mandera while wealth index, use of modern contraception and ideal number of children were unique in Nyeri. Experience of child death and low use of modern contraceptives were attributed to high fertility in Mandera while improved wealth status accounted for low fertility in Nyeri. In view of these, key interventions to reduce childhood mortality, reposition family planning and increase wealth creation are recommended. Also, further studies should be undertaken using datasets containing information on proximate factors that were not analysed in this study due to various limitations.