Analysis of Determinants of Antenatal Care Services Utilization in Nairobi County Using Logistic Regression Model
American Journal of Theoretical and Applied Statistics
Volume 4, Issue 5, September 2015, Pages: 322-328
Received: Jul. 14, 2015;
Accepted: Jul. 24, 2015;
Published: Aug. 1, 2015
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Kennedy Sakaya Barasa, Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Anthony Kibira Wanjoya, Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Anthony Gichuhi Waititu, Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Objectives: The aim of this study is to assess antenatal care service utilization and determine the factors associated with antenatal care non attendance in Nairobi County. Methods: The study used data that was collected in the county by use of questionnaires in which a total of 306 mothers participated. Data Analysis: The data was analyzed using R-software version 3.0.2, and the report was represented in form of tables. Here, Logistic regression model was used to model some of effects of the demographic and socio-economic independent variables. Results: The study found out that the independent variables, age, employment status, education level, parity and husband’s education level were the determinants of antenatal care service utilization in Nairobi County. The relationship between the covariates and antenatal care service utilization were significant at α=0.05 Conclusions: The study suggested that mothers in Nairobi County should be educated or enlightened on matters that concern antenatal health care utilization so as to increase the percentage of those mothers that attend the health facilities.
Kennedy Sakaya Barasa,
Anthony Kibira Wanjoya,
Anthony Gichuhi Waititu,
Analysis of Determinants of Antenatal Care Services Utilization in Nairobi County Using Logistic Regression Model, American Journal of Theoretical and Applied Statistics.
Vol. 4, No. 5,
2015, pp. 322-328.
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