Under-five mortality remains a public health challenge in South Africa and other developing countries where children are likely to die before reaching five years. This paper aimed to identify factors associated with under-five mortality in South Africa taking into account clustering using the 1998 South African Demographic and Health Survey data. Survival analysis techniques were used to understand under-five mortality and its determinants. Frailty models incorporating family and community frailty effects were implemented. The results revealed that preceding birth interval, birth type, breastfeeding and dwelling unit type were significant determinants of under-five mortality. The findings further confirmed that children belonging to the same family and children belonging to the same community shared certain unobserved characteristics that put them at risk of death.
United Nations, “Programme of Action for the International Conference on Population Development,” 2014.
United Nations, “United Nations Millenium Declarations. Resolution adopted by the General Assembly,” 2000.
United Nations, “The Millennium Development Goals Report 2015,” 2015.
United Nations, “Resolution adopted by the General Assembly on 25 September 2015,” 2015.
G.A. Kayode, V.T. Adekanmbi, and O.A. Uthman, “Risk factors and a predictive model for under-five mortality in Nigeria: evidence from Nigeria demographic and health survey,” BMC Pregranancy & Childbirth, vol. 12, no. 10, 2012.
United Nations For Children’s Fund, “Levels and Trends in Child Mortality: 2015,” 2015.
P. Buwembo, and N.J. Bomela, “Factors associated with under-five mortality in South Africa: Trends 1997-2002,” 2010.
B. Houle, A. Stein, K. Kahn, S. Madhavan, M. Collinson, S.M. Tollman, and S.J. Clark, “Household context and child mortality in rural South Africa: the effects of birth spacing, shared mortality, household composition and socio-economic status,” International Journal of Epidemiology, vol. 42, pp. 1444-1454, 2013.
K.A. Kyei, “Socio-economic factors affecting under five mortality in South Africa – An investigative study,” Journal of Emerging Trends in Economics and Management Science, vol. 2, no. 2, pp. 104-110, 2011.
N. Mckerrow, and M. Mulaudzi, “Child mortality in South Africa: Using existing data,” South African Health Review 2010. December 2010.
R. Baker, “Differential in child mortality in Malawi. Malawi Research Database” 1999.
R.R. Ettarh, and J. Kimani, “Determinants of under-five mortality in rural and urban Kenya,” The International Electronic Journal of Rural and Remote Health Research Education, Practice and Policy, vol. 12, no. 1812, pp. 1-9, March 2012.
South African Department of Health, “South African Demographic and Health Survey 1998: Preliminary Report,” 1998.
D.R. Cox, “Regression models and Life-Tables,” Journal of the Royal Statistical Society. Vol. 34, no. 2, pp. 187-220. 1972.
M. Cleves, W. Gould, R.R. Gutierrez, and Y.V. Marchenko, An introduction to survival analysis using Stata. Texas: Stata Press, 2010.
G. Guo, and G. Rodriguez, “Estimating a multivariate proportional hazards model for clustered data using the EM Algorithm, with an application to child survival in Guatemala,” American Statistical Association, vol. 87, no. 420, pp. 969-976, 1992.
F. Niregire, A. Wangombe, and T.O.N. Achia, “Use of shared frailty model to identify the determinants of child mortality in Rwanda,” Rwanda Journal, vol. 20, no. C, pp. 89-105, 2011.
W.M. Bolstad, and S.O. Manda, “Investigating child mortality in Malawi using family and community random effects: A Bayesian analysis,” American Statistical Association, vol. 96, no. 453, pp. 12-19, March 2001.
K. Mani, S.N. Dwivedi, and R.M. Pandey, “Determinants of under-five mortality in rural empowered action group states in India: An application of Cox Frailty Model,” International Journal of MCH and AIDS, vol. 1, no. 1, pp. 60-72, 2012.
V. Rondeau, Y. Mazroui, and J.R. Gonzalez, “Frailtypack: An R package for the analysis of correlated survival data with frailty models using penalized likelihood estimation or parametrical estimation,” Journal of Statistical Software, vol. 47, no. 4, pp. 1-31, 2012.
G. Grover, and D. Seth, “Application of frailty models on advanced liver disease using gamma as frailty distribution,” Statistical Research Letters, vol. 4, no. 3, pp. 42-50, 2010.
S.O. Manda, “Birth intervals, breastfeeding and determinants of childhood mortality in Malawi,” Social Science Medicine, vol. 48, pp. 301-312, 1999.
Statistics South Africa., “Census 2011: Fact sheet,” 2011.
D.W.R. Omariba, F.Rajulton, and R. Beaujot, “Correlated mortality of siblings in Kenya: The role of state dependence,” Demographic Research, vol. 18, no. 11, pp. 311-336, 2008.
R. Singh, and V. Tripathi, “Under-five mortality among mothers employed in agriculture: findings from a nationally representative sample,” PeerJ, January 2015.
A.H. Chowdhury, “Determinants of under-five mortality in Bangladesh,” Open Journal of Statistics, vol. 3, no. 3, pp. 213-219. June 2013.
This work is licensed under a Creative Commons Attribution 4.0 International License.