International Journal of Data Science and Analysis

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Modeling Covariates of Infant and Child Mortality in Kenya

Received: 22 May 2019    Accepted: 09 July 2019    Published: 04 August 2020
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Abstract

Mortality of children under the age of five has been target of public health policies. There has been a significant decline in under-five mortality in the twenty first century in almost all countries several studies have been conducted to identify covariates of Infant and Child Mortality in Kenya but none of these used recent data and none has included HIV/AIDs as a risk factor. This study aims at examining bio-demographic, socio-economic and environmental mortality in Kenya. Two methods of the logistic regression and survival analysis method are used. The results of the study show that HIV status of the mother and lengths of the preceding birth interval were significantly associated with both Infant and Child Mortality. Other significant covariates include birth order, age of the mother at birth of the child, sex of the child, education of the mother and father and wealth index.

DOI 10.11648/j.ijdsa.20200603.13
Published in International Journal of Data Science and Analysis (Volume 6, Issue 3, June 2020)
Page(s) 90-98
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

Infant, Mortality, Covariates

References
[1] Akanni A. O and Fulasi “Determinants of Child Mortality in Rural Nigeria,” World Rural Observations 4 (2): 38–45.
[2] Clara Lemani (2013) University of Cape town.
[3] Cornelius Mwisa Mutangili published on Population Studies and Research Institute University of Nairobi Kenya.
[4] Daniel Mwangi Muriithi: American Journal of Theoretical and Applied Statistics Vol. 4 – No. 5. Pp 404–413.
[5] Eduardo V., Lara Misegades" International Journal of Epidemiology '2005 34: 61-68 Vol. 34 no. 1.
[6] Ghosh, R and Bharati 2010"Determinants of infant and child mortality in periurbban areas of kolkala city India"Asoa -pacific journal of public health 22.
[7] Hisham. E. M and Clifford, O (2008) "Socio-economic Determinants of Infant Mortality in Kenya".
[8] Kayonde, G A 2012 Risk Factors and Predictive Model for under-five Mortality in Nigeria. Biomed Central, Pregnancy and Child Birth. 12 (10).
[9] Mustafa, H. E and C Odimegwu. 2008 "Socio economic determinants of infant mortality in Kenya. Analysis of kenya DHS 2003" Humanities and social sciences 2 (2) 1-16.
[10] Mutinga, C. S 2007. Environmental determinants of child mortality in kenya. katajanokanlaituri 6B, 00160 Helsinki Finland 6B: world institute for.
[11] Mwangi Wambugu University of Nairobi (2012) Nairobi. Unpublished thesis.
[12] Newel, M. H, Brahmhatt and P. D Ghys 2004,"child mortality and HIV infection in Africa: review", AIDS 18 (2): 527-534.
[13] Ndirangu, J. M. Newel, C Thorne and R Bland 2012 Treating H. I. V infected mother reduces under five years of age mortality to levels seen in children of H. I. V uninfected mothers in rural south Africa "Antiviral therapy."17: 81-90.
[14] Souza, E. M. 2012 "The impact of HIV on fertility in Malawi" unpublished thesis university of cape town.
[15] USAID (2014) written by Joy Fishel, Ruilin Ren Bernard Barrere.
[16] UNICEF (2011), HIV and AIDS estimates Geneva, Switzerland.
Author Information
  • Department Statistics and Actuarial Science, Jommo Kenyatta University of Agriculture and Technology, Nairobi, Kenya

  • Department Statistics and Actuarial Science, Moi University, Eldoret, Kenya

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    Stephen Muthii Wanjohi, Daniel Mwangi Muriithi. (2020). Modeling Covariates of Infant and Child Mortality in Kenya. International Journal of Data Science and Analysis, 6(3), 90-98. https://doi.org/10.11648/j.ijdsa.20200603.13

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    ACS Style

    Stephen Muthii Wanjohi; Daniel Mwangi Muriithi. Modeling Covariates of Infant and Child Mortality in Kenya. Int. J. Data Sci. Anal. 2020, 6(3), 90-98. doi: 10.11648/j.ijdsa.20200603.13

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    AMA Style

    Stephen Muthii Wanjohi, Daniel Mwangi Muriithi. Modeling Covariates of Infant and Child Mortality in Kenya. Int J Data Sci Anal. 2020;6(3):90-98. doi: 10.11648/j.ijdsa.20200603.13

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  • @article{10.11648/j.ijdsa.20200603.13,
      author = {Stephen Muthii Wanjohi and Daniel Mwangi Muriithi},
      title = {Modeling Covariates of Infant and Child Mortality in Kenya},
      journal = {International Journal of Data Science and Analysis},
      volume = {6},
      number = {3},
      pages = {90-98},
      doi = {10.11648/j.ijdsa.20200603.13},
      url = {https://doi.org/10.11648/j.ijdsa.20200603.13},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijdsa.20200603.13},
      abstract = {Mortality of children under the age of five has been target of public health policies. There has been a significant decline in under-five mortality in the twenty first century in almost all countries several studies have been conducted to identify covariates of Infant and Child Mortality in Kenya but none of these used recent data and none has included HIV/AIDs as a risk factor. This study aims at examining bio-demographic, socio-economic and environmental mortality in Kenya. Two methods of the logistic regression and survival analysis method are used. The results of the study show that HIV status of the mother and lengths of the preceding birth interval were significantly associated with both Infant and Child Mortality. Other significant covariates include birth order, age of the mother at birth of the child, sex of the child, education of the mother and father and wealth index.},
     year = {2020}
    }
    

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    JO  - International Journal of Data Science and Analysis
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    AB  - Mortality of children under the age of five has been target of public health policies. There has been a significant decline in under-five mortality in the twenty first century in almost all countries several studies have been conducted to identify covariates of Infant and Child Mortality in Kenya but none of these used recent data and none has included HIV/AIDs as a risk factor. This study aims at examining bio-demographic, socio-economic and environmental mortality in Kenya. Two methods of the logistic regression and survival analysis method are used. The results of the study show that HIV status of the mother and lengths of the preceding birth interval were significantly associated with both Infant and Child Mortality. Other significant covariates include birth order, age of the mother at birth of the child, sex of the child, education of the mother and father and wealth index.
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