American Journal of Theoretical and Applied Statistics

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Analysis of Determinants of Antenatal Care Services Utilization in Nairobi County Using Logistic Regression Model

Received: 14 July 2015    Accepted: 24 July 2015    Published: 01 August 2015
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Abstract

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.

DOI 10.11648/j.ajtas.20150405.12
Published in American Journal of Theoretical and Applied Statistics (Volume 4, Issue 5, September 2015)
Page(s) 322-328
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Antenatal Care, Nairobi, Logistic Regression, Variables, Covariates

References
[1] Edward Nketiah‐Amponsah, Bernardin Senadza, Eric Arthur, (2013) "Determinants of utilization of antenatal care services in developing countries: Recent evidence from Ghana", African Journal of Economic and Management Studies, Vol. 4 Iss: 1, pp.58 - 73
[2] Hosmer D.W and Lemeshow S, (2000), Applied Logistic Regression 2nd Ed. John Wiley & Sons, Inc. Canada. PP1-17
[3] Kamal, S.M.M. (2009). Factors Affecting Utilization of Skilled Maternity care Services among Married Adolescents in Bangladesh, Asian Population Studies, PP.153-170
[4] Koblinsky,O Campbell and J Heichelheim: Bull World Health Organ, (1999), 77:399-406
[5] MOH, 2006. Essential Obstetric Care Manual. s.l.:s.n.Nairobi-Kenya: MOH Kenya
[6] Ntambue et al (2012). Determinants of maternal health utilization in uurban settings of Democratic Republic of Congo: A case study of Lubumbashi City. BMC Pregnancy and Childbirth
[7] Pell C, Meñaca A, Were F, Afrah NA, Chatio S, Manda-Taylor L, et al. (2013) Factors Affecting Antenatal Care Attendance: Results from Qualitative Studies in Ghana, Kenya and Malawi. PLoS ONE 8(1): e53747. doi:10.1371/journal.pone.0053747
[8] Ronsmans, C. and Graham, W. J., (2006). Maternal mortality: who, when, where, and why. The Lancet, September. PP 1189-1200.
[9] Shiferaw et al (2013). Why do women prefer home births in Ethopia? BMC Pregnancy and Childbirth
[10] Singh, S., Darroch, J. E., Ashford, L. S. and Vlassoff, M., (2009). Adding It Up: The Costs and Benefi ts of Investing in Family Planning and Maternal and Newborn Health, New York: Guttmacher Institute and United Nations Population Fund.
[11] Tabachnick, B and Fidell, L. (1996). Using Multivariate Statistics, 3rd edition. Harper Collins.
[12] UNECA/AUC/AfDB, (2010). Assessing Progress in Africa towards the Millennium Development Goals, New York: ECA; AU; ADBG; UNDP.
[13] United Nations (2008). The Millenium Development Goals Report, New York.
[14] WHO, (2003). Antenatal care in developing countries: promises, achievements and missed opportunities: an analysis of trends, levels and differentials, 1990-2001. WHO Press
[15] WHO (2007). Maternal mortality in 2005: estimates developed by WHO, UNICEF, UNFPA, and the World Bank. Geneva: WHO
Author Information
  • Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya

  • Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya

  • Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya

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    Kennedy Sakaya Barasa, Anthony Kibira Wanjoya, Anthony Gichuhi Waititu. (2015). Analysis of Determinants of Antenatal Care Services Utilization in Nairobi County Using Logistic Regression Model. American Journal of Theoretical and Applied Statistics, 4(5), 322-328. https://doi.org/10.11648/j.ajtas.20150405.12

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    Kennedy Sakaya Barasa; Anthony Kibira Wanjoya; Anthony Gichuhi Waititu. Analysis of Determinants of Antenatal Care Services Utilization in Nairobi County Using Logistic Regression Model. Am. J. Theor. Appl. Stat. 2015, 4(5), 322-328. doi: 10.11648/j.ajtas.20150405.12

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    AMA Style

    Kennedy Sakaya Barasa, Anthony Kibira Wanjoya, Anthony Gichuhi Waititu. Analysis of Determinants of Antenatal Care Services Utilization in Nairobi County Using Logistic Regression Model. Am J Theor Appl Stat. 2015;4(5):322-328. doi: 10.11648/j.ajtas.20150405.12

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  • @article{10.11648/j.ajtas.20150405.12,
      author = {Kennedy Sakaya Barasa and Anthony Kibira Wanjoya and Anthony Gichuhi Waititu},
      title = {Analysis of Determinants of Antenatal Care Services Utilization in Nairobi County Using Logistic Regression Model},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {4},
      number = {5},
      pages = {322-328},
      doi = {10.11648/j.ajtas.20150405.12},
      url = {https://doi.org/10.11648/j.ajtas.20150405.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajtas.20150405.12},
      abstract = {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.},
     year = {2015}
    }
    

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    T1  - Analysis of Determinants of Antenatal Care Services Utilization in Nairobi County Using Logistic Regression Model
    AU  - Kennedy Sakaya Barasa
    AU  - Anthony Kibira Wanjoya
    AU  - Anthony Gichuhi Waititu
    Y1  - 2015/08/01
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    DO  - 10.11648/j.ajtas.20150405.12
    T2  - American Journal of Theoretical and Applied Statistics
    JF  - American Journal of Theoretical and Applied Statistics
    JO  - American Journal of Theoretical and Applied Statistics
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    EP  - 328
    PB  - Science Publishing Group
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    UR  - https://doi.org/10.11648/j.ajtas.20150405.12
    AB  - 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.
    VL  - 4
    IS  - 5
    ER  - 

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