Childhood mortality is still a public health issue in Sub-Saharan Africa, with Kenya being among the countries that experience the highest rate of children dying before reaching the age of five. Under-5 child mortality (U5CM) is heavily influenced by demographic, environmental, and socio-economic factors. The study aimed to examine the risk factors of under-5 child mortality in Kenya. The data were based on birth histories from the Kenya Demographic and Health Surveys (KDHS) conducted in 2014. The relative contribution of factors such as the mother's education, mother's occupation, household wealth, place of residence, region, and sex of the child to the variability in the under-five child mortality was assessed using Kaplan-Meier and Cox hazard methods. The outcome variable for the study was the child’s survival before the age of 5 and age at death. All children born in the period between 2009 and 2014 (n=83,591) were included in the study. Within the observation period, a total of 6,123 child deaths were recorded. The under-5 mortality rate in Kenya was strongly associated with the mother's education, region, place of residence, preceding birth interval, birth order, the total number of children ever born, mother's occupation, and type of toilet facility. The results indicated that a child born in Nyanza is twice more likely to die than that born in the Central region of Kenya. Male children had a higher risk of dying before the age of five than their female counterparts. The risk of experiencing U5CM increased among children born in rural areas compared to those born in urban areas. The study findings provide evidence in support of prioritizing interventions aiming at improving maternal and child healthcare. The findings also suggest that programs aimed at empowering women and boosting health knowledge among mothers should be scaled up. Furthermore, implementing socio-economic development interventions that reduce regional disparities is a recommendation that the central government should consider. Finally, national and local governments should commit resources to guarantee that modern contraceptives are available and used to increase child spacing.
| Published in | International Journal of Statistical Distributions and Applications (Volume 7, Issue 2) |
| DOI | 10.11648/j.ijsd.20210702.14 |
| Page(s) | 57-71 |
| 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), 2021. Published by Science Publishing Group |
Under-Five Child Mortality, Survival Models, Cox-proportional Hazard, Kaplan-Meier, Kenya Demographic and Health Survey
| [1] | Bay G, Miller T, Faijer DJ. WHO: Levels and trends in child mortality. Report 2013. 2013; 30. |
| [2] | Hill K, Bicego G. Childhood Mortality in Kenya: An Examination of Trends and Determinants in the Late 1980s to Mid 1990s. |
| [3] | Hamel MJ, Adazu K, Obor D, et al. A reversal in reductions of child mortality in Western Kenya, 2003-2009. Am J Trop Med Hyg [Internet]. The American Society of Tropical Medicine and Hygiene; 2011 [cited 2021 Jun 10]; 85 (4): 597–605. Available from: /pmc/articles/PMC3183762/. |
| [4] | Schultz TP. Studying the impact of household economic and community variables on child mortality. Child Surviv Strateg Res. Cambridge University Press; Population & Development Review, supplement to v. 10; 1984: 215–235. |
| [5] | Mosley WH, Chen LC. An analytical framework for the study of child survival in developing countries. Child Surviv Strateg Res. Cambridge University Press; Population & Development Review, supplement to vol. 10; 1984: 25–45. |
| [6] | Rutstein SO. Factors associated with trends in infant and child mortality in developing countries during the 1990s [Internet]. Bull. World Health Organ. 2000. Available from: http://www.who.int/bulletin/tableofcontents/. |
| [7] | Davanzo J, Razzaque A, Rahman M, et al. The Effects of Birth Spacing on Infant and Child Mortality, Pregnancy Outcomes, and Maternal Morbidity and Mortality in Matlab, Bangladesh THE EFFECTS OF BIRTH SPACING ON INFANT AND CHILD MORTALITY, PREGNANCY OUTCOMES, AND MATERNAL MORBIDITY AND MORTALITY IN MATLAB, BANGLADESH*. 2004. |
| [8] | Kibet MK. Comparative study of infant and child mortality: The case of Kenya and South Africa. African Popul Stud [Internet]. Stellenbosch University; 2013 [cited 2021 Jun 10]; 24 (1–2): 1–2. Available from: http://aps.journals.ac.za. |
| [9] | Rutstein SO. Effects of preceding birth intervals on neonatal, infant and under-five years mortality and nutritional status in developing countries: Evidence from the demographic and health surveys. Int J Gynecol Obstet [Internet]. John Wiley and Sons Ltd; 2005 [cited 2021 Jun 10]; 89 (SUPPL. 1): S7–S24. Available from: https://obgyn.onlinelibrary.wiley.com/doi/full/10.1016/j.ijgo.2004.11.012. |
| [10] | Kumar P, File G. Infant and child mortality in Ethiopia: A statistical analysis approach. Ethiop J Educ Sci [Internet]. African Journals Online (AJOL); 2011 [cited 2021 Jun 10]; 5 (2). Available from: https://www.ajol.info/index.php/ejesc/article/view/65373. |
| [11] | Mutunga CJ. Environmental Determinants of Child Mortality in Kenya. Heal Inequal Dev [Internet]. Palgrave Macmillan UK; 2011 [cited 2021 Jun 10]. p. 89–110. Available from: https://link.springer.com/chapter/10.1057/9780230304673_5. |
| [12] | Wardlaw T, Jensen L, Moreira Daniels webSite L, Cassidy S, Yuen D, Rao Gupta G. Committing to Child Survival: A Promise Renewed UNICEF Country Offices contributed to the review of country example text. Policy and communications advice and support were provided by [Internet]. 2012 [cited 2021 Jun 10]. Available from: www.apromiserenewed.org. |
| [13] | Hobcraft JN, Mcdonald JW, Rutstein SO. Socio-economic factors in Infant and child mortality: A cross-national comparison. Popul Stud (NY). 1984; 38 (2): 193–223. |
| [14] | Stallings RY. Child morbidity and treatment patterns [Internet]. 2004 Dec. Available from: http://www.measuredhs.com. |
| [15] | Ngome E. Demographic, Socio-Economic and Psychosocial Determinants of Current and Consistent Condom Use among Adolescents in Botswana. World J AIDS. Scientific Research Publishing, Inc,; 2016; 06 (04): 137–156. |
| [16] | Mutunga CJ. A Service of zbw Environmental determinants of child mortality in Kenya Standard-Nutzungsbedingungen [Internet]. [cited 2021 Jun 10]. Available from: www.econstor.eu. |
| [17] | Uaps 2007 [Internet]. [cited 2021 Jun 10]. Available from: https://uaps2007.princeton.edu/abstracts/70670. |
| [18] | Fayehun OA. Household Environmental Health Hazards and Child Survival in Sub-Saharan Africa [WP74] [Internet]. 2010. Available from: www.measuredhs.com. |
| [19] | Buttenheim AM. The sanitation environment in urban slums: Implications for child health. Popul Environ. 2008; 30 (1–2): 26–47. |
| [20] | Ilinca S, Giorgio L Di, Salari P, Chuma J. Socio-economic inequality and inequity in use of health care services in Kenya: Evidence from the fourth Kenya household health expenditure and utilization survey [Internet]. Int. J. Equity Health. BioMed Central Ltd.; 2019 [cited 2021 Jun 10]. p. 1–13. Available from: https://doi.org/10.1186/s12939-019-1106-z. |
| [21] | Malderen C Van, Oyen H Van, Speybroeck N. Contributing determinants of overall and wealth-related inequality in under-5 mortality in 13 African countries. J Epidemiol Community Health. 2013; 67 (8): 667–676. |
| [22] | Nasejje JB, Mwambi HG, Achia TNO. Understanding the determinants of under-five child mortality in Uganda including the estimation of unobserved household and community effects using both frequentist and Bayesian survival analysis approaches Biostatistics and methods. BMC Public Health [Internet]. BioMed Central Ltd.; 2015 [cited 2021 Jun 10]; 15 (1): 1–12. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-015-2332-y. |
| [23] | Basu AM, Stephenson R. Low levels of maternal education and the proximate determinants of childhood mortality: A little learning is not a dangerous thing. Soc Sci Med [Internet]. Elsevier Ltd; 2005 [cited 2021 Jun 10]; 60 (9): 2011–2023. Available from: https://pubmed.ncbi.nlm.nih.gov/15743650/. |
| [24] | Ezeh OK, Agho KE, Dibley MJ, Hall J, Page AN. Determinants of neonatal mortality in Nigeria: Evidence from the 2008 demographic and health survey. BMC Public Health [Internet]. BioMed Central Ltd.; 2014 [cited 2021 Jun 10]; 14 (1): 1–10. Available from: http://www.biomedcentral.com/1471-2458/14/521. |
APA Style
Elda Naliaka Watulo, Anthony Kibera Wanjoya. (2021). Childhood Mortality in Kenya: Survival Analysis of 2014 Kenya Demographic and Health Survey Data. International Journal of Statistical Distributions and Applications, 7(2), 57-71. https://doi.org/10.11648/j.ijsd.20210702.14
ACS Style
Elda Naliaka Watulo; Anthony Kibera Wanjoya. Childhood Mortality in Kenya: Survival Analysis of 2014 Kenya Demographic and Health Survey Data. Int. J. Stat. Distrib. Appl. 2021, 7(2), 57-71. doi: 10.11648/j.ijsd.20210702.14
AMA Style
Elda Naliaka Watulo, Anthony Kibera Wanjoya. Childhood Mortality in Kenya: Survival Analysis of 2014 Kenya Demographic and Health Survey Data. Int J Stat Distrib Appl. 2021;7(2):57-71. doi: 10.11648/j.ijsd.20210702.14
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.ijsd.20210702.14,
author = {Elda Naliaka Watulo and Anthony Kibera Wanjoya},
title = {Childhood Mortality in Kenya: Survival Analysis of 2014 Kenya Demographic and Health Survey Data},
journal = {International Journal of Statistical Distributions and Applications},
volume = {7},
number = {2},
pages = {57-71},
doi = {10.11648/j.ijsd.20210702.14},
url = {https://doi.org/10.11648/j.ijsd.20210702.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsd.20210702.14},
abstract = {Childhood mortality is still a public health issue in Sub-Saharan Africa, with Kenya being among the countries that experience the highest rate of children dying before reaching the age of five. Under-5 child mortality (U5CM) is heavily influenced by demographic, environmental, and socio-economic factors. The study aimed to examine the risk factors of under-5 child mortality in Kenya. The data were based on birth histories from the Kenya Demographic and Health Surveys (KDHS) conducted in 2014. The relative contribution of factors such as the mother's education, mother's occupation, household wealth, place of residence, region, and sex of the child to the variability in the under-five child mortality was assessed using Kaplan-Meier and Cox hazard methods. The outcome variable for the study was the child’s survival before the age of 5 and age at death. All children born in the period between 2009 and 2014 (n=83,591) were included in the study. Within the observation period, a total of 6,123 child deaths were recorded. The under-5 mortality rate in Kenya was strongly associated with the mother's education, region, place of residence, preceding birth interval, birth order, the total number of children ever born, mother's occupation, and type of toilet facility. The results indicated that a child born in Nyanza is twice more likely to die than that born in the Central region of Kenya. Male children had a higher risk of dying before the age of five than their female counterparts. The risk of experiencing U5CM increased among children born in rural areas compared to those born in urban areas. The study findings provide evidence in support of prioritizing interventions aiming at improving maternal and child healthcare. The findings also suggest that programs aimed at empowering women and boosting health knowledge among mothers should be scaled up. Furthermore, implementing socio-economic development interventions that reduce regional disparities is a recommendation that the central government should consider. Finally, national and local governments should commit resources to guarantee that modern contraceptives are available and used to increase child spacing.},
year = {2021}
}
TY - JOUR T1 - Childhood Mortality in Kenya: Survival Analysis of 2014 Kenya Demographic and Health Survey Data AU - Elda Naliaka Watulo AU - Anthony Kibera Wanjoya Y1 - 2021/06/28 PY - 2021 N1 - https://doi.org/10.11648/j.ijsd.20210702.14 DO - 10.11648/j.ijsd.20210702.14 T2 - International Journal of Statistical Distributions and Applications JF - International Journal of Statistical Distributions and Applications JO - International Journal of Statistical Distributions and Applications SP - 57 EP - 71 PB - Science Publishing Group SN - 2472-3509 UR - https://doi.org/10.11648/j.ijsd.20210702.14 AB - Childhood mortality is still a public health issue in Sub-Saharan Africa, with Kenya being among the countries that experience the highest rate of children dying before reaching the age of five. Under-5 child mortality (U5CM) is heavily influenced by demographic, environmental, and socio-economic factors. The study aimed to examine the risk factors of under-5 child mortality in Kenya. The data were based on birth histories from the Kenya Demographic and Health Surveys (KDHS) conducted in 2014. The relative contribution of factors such as the mother's education, mother's occupation, household wealth, place of residence, region, and sex of the child to the variability in the under-five child mortality was assessed using Kaplan-Meier and Cox hazard methods. The outcome variable for the study was the child’s survival before the age of 5 and age at death. All children born in the period between 2009 and 2014 (n=83,591) were included in the study. Within the observation period, a total of 6,123 child deaths were recorded. The under-5 mortality rate in Kenya was strongly associated with the mother's education, region, place of residence, preceding birth interval, birth order, the total number of children ever born, mother's occupation, and type of toilet facility. The results indicated that a child born in Nyanza is twice more likely to die than that born in the Central region of Kenya. Male children had a higher risk of dying before the age of five than their female counterparts. The risk of experiencing U5CM increased among children born in rural areas compared to those born in urban areas. The study findings provide evidence in support of prioritizing interventions aiming at improving maternal and child healthcare. The findings also suggest that programs aimed at empowering women and boosting health knowledge among mothers should be scaled up. Furthermore, implementing socio-economic development interventions that reduce regional disparities is a recommendation that the central government should consider. Finally, national and local governments should commit resources to guarantee that modern contraceptives are available and used to increase child spacing. VL - 7 IS - 2 ER -
Information
Email: