Influence of Geographical Segregation on Fertility of Women in Kisumu East Sub County, Kisumu County, Kenya

Abstract

Fertility and geographical segregation are some of the major factors influencing human population growth. High fertility stagnates development by draining resources. The fertility rate of Kisumu East Sub County is rated at 4.8 exceeding the average for the county, national and the global which is 4.2, 3.4 and 2.3 respectively. The purpose of this study is to assess the influence of geographical segregation on fertility of women. This study was guided by Becker's economics theory of fertility and Hägerstrand theory of Spatial diffusion. The households was the unit of analysis and a sample size of 384 was obtained as determined by the Fisher’s formula. Cross-sectional descriptive research design was used. 384 women respondents aged between 18-49 were selected using cluster and snowball sampling techniques. Quantitative data such as descriptive statistics: percentages, means and standard deviation was analysed using SPSS version 22. Inferential statistics: chi-square, gamma statistics, spearman’s rank, multiple logistic regressions, multiple correlation coefficient and multinomial logistic regression were used to analyse the data. Qualitative data was analysed by coding, creating categories, themes and patterns then evaluating the usefulness of the information in answering the research questions. Piloted tool revealed a spearman-brown reliability coefficient of .721. All the tests of significance were conducted at ?=0.05. According to the multinomial logistic regression, the influence of cultural norms on first and last child birth remained statistically significant. Sharing common centres and mean number of children born per woman showed strong positive relationship (r = 0.675). Daily and weekly social interactions showed a strong positive significant linear correlation with fertility (r =0.732, p = 0.03). Spearman rank correlation indicated a strong positive and statistically significant linear correlation (r =0.50, p = 0.04) between social interactions and number of children born. Gamma statistic coefficient of 0.493 indicated moderately strong positive association between levels of geographical concentrations and number of children born. Number of children born correlated negatively (r =-0.612, p=0.02) with low geographical concentration. Multiple correlation coefficient analysis showed adjusted R square value of 0.673 indicating that the predictability of number of children born per woman from the combined influence of high and low geographical concentration was significant. The findings of this study will provide knowledge on aspects of geographical segregations influencing fertility among women and will give useful information to reproductive health planners and policy makers on fertility issues in Kisumu East Sub County. Therefore, the study recommends wider adoption of reproductive family health awareness and economic empowerment among women to help reduce the number of children born per woman.