Understanding the Correlates of Under-five Mortality in Sudan Using Survey Survival Models

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Dawit Getnet Ayele
Ali Satty
Temesgen Zewotir


Under-five mortality is among the major public health problems in developing countries, the rate of which is an important factor for a country’s development. For this reason, under-five mortality status is an important outcome to measure for children’s health. This study uses the Cox proportional-hazards model to identify risk factors associated with under-five mortality in Sudan. This study uses the 2014 Sudan Multiple Indicator Cluster Survey (MICS) conducted by the Central Bureau of Statistics in collaboration with several national institutions. The survival Cox proportional-hazards model was used to identify factors that affect under-five child mortality in Sudan. The results show that the weight of a child at birth is positively associated with the under-five child mortality rate. Under-five children who have both small and large weights at birth are at a higher risk of dying before reaching five years. Based on demographic factors associated with under-five mortality, our analysis showed that mothers who were married at the time of the survey are most likely to have higher under-five child mortality as compared to formerly married mothers. In addition to this, that mother’s age at the time of the birth is significantly associated with under-five mortality. Based on the result, the lack of important policies targeting the reduction of socioeconomic inequalities between rural and urban areas is the major problem of public health interventions to improve child health and survival in Sudan.

Multiple indicator cluster survey, Cox model, risk factor, proportional-hazards model, joint effect.

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How to Cite
Ayele, D. G., Satty, A., & Zewotir, T. (2020). Understanding the Correlates of Under-five Mortality in Sudan Using Survey Survival Models. Asian Journal of Research in Infectious Diseases, 5(1), 55-68. https://doi.org/10.9734/ajrid/2020/v5i130160
Original Research Article


Hug L, Alexander M, You D, Alkema L, for Child UI-aG: National, regional, and global levels and trends in neonatal mortality between 1990 and 2017, with scenario-based projections to 2030: a systematic analysis. The Lancet Global Health. 2019;7(6):e710-e720.

UN DESA: The Millennium Development Goals Report; 2015. Available:https://doi.org/10.18356/6cd11401-en. United Nations Department of Economic Social Affairs; 2016.

Li V: Reducing child mortality in Sudan by preventing diarrheal disease. The Journal of Global Health; 2014.

Makome GK, Nayak A, Machel B: Study 10-Year Strategic Review - Children and Conflict in a Changing World. New York. United Nations Children’s Fund: 244; 2009.

Kapungwe AK: Quality of child health care and under-five mortality in Zambia:A case study of two districts In Luapula Province. Demographic Research 2005, 12(12):301-322.

Abdeldafie SY. Under 5 Children Mortality in Sudan: Situation Analysis. International Journal of Innovative Research in Medical Science. 2018;3(1):1669 to 1671-1669 to 1671.

Susuman AS: Child Mortality Rate in Ethiopia. Iran J Public Health 2012, 41.

Ayele DG, Zewotir TT, Mwambi HG: Survival analysis of under-five mortality using Cox and frailty models in Ethiopia. Journal of Health, Population and Nutrition 2017, 36 (1):(1):25.

Abu IN: The Prevalence and Determinants of Under-Five Mortality in Benue State, Nigeria. SAGE Open access 2015.

Ayele DG, Zewotir T, Mwambi H: Indirect child mortality estimation technique to identify trends of under-five mortality in Ethiopia. Afr Health Sci 2016, 16.

Ayele DG, Zewotir TT: Comparison of under-five mortality for 2000, 2005 and 2011 surveys in Ethiopia. BMC public health 2016, 16(1):930.

Gebretsadik S, Gabreyohannes E: Determinants of Under-Five Mortality in High Mortality Regions of Ethiopia: An Analysis of the 2011 Ethiopia Demographic and Health Survey Data. International Journal of Population Research 2016.

Cox DR: Regression models and life‐tables. Journal of the Royal Statistical Society: Series B (Methodological) 1972, 34(2):187-202.

Cox DR, Oakes D: Analysis of Survival Data. London: Chapman & Hall; 1984.

Central Bureau of Statistics (CBS), UNICEF Sudan: Multiple Indicator Cluster Survey 2014 of Sudan, Final Report. In. Khartoum, Sudan: UNICEF and Central Bureau of Statistics (CBS); February 2016.

Kaldewei C: Determinants of Infant and Under-Five Mortality—The Case of Jordan. Technical note, February 2010.

Hosmer Jr DW, Lemeshow S, May S: Applied survival analysis: regression modeling of time-to-event data, vol. 618: Wiley-Interscience; 2008.

Kalbfleisch JD, Prentice RL. The statistical analysis of failure time data, vol. 360: John Wiley & Sons; 2011.

Heeringa SG, West BT, Berglund PA. Applied survey data analysis: Chapman and Hall/CRC; 2017.

Berglund P. Getting the Most out of the SAS® Survey Procedures: Repeated Replication Methods, Subpopulation Analysis, and Missing Data Options in SAS® v9.2. SAS Global Forum 2008; 2008.

Rust K. Variance estimation for complex estimators in sample surveys. Journal of Official Statistics. 1985;1(4):381.

Kish L. Survey Sampling. In. New York, NY: John Wily & Sons; 1995.

Allison PD: Survival analysis using SAS: a practical guide: Sas Institute; 2010.

Singer JD, Willett JB. It’s about time: Using discrete-time survival analysis to study duration and the timing of events. Journal of educational statistics 1993, 18(2):155-195.

Kessler RC, Berglund P, Chiu WT, Demler O, Heeringa S, Hiripi E, Jin R, Pennell BE, Walters EE, Zaslavsky A: The US national comorbidity survey replication (NCS‐R): design and field procedures. International Journal of Methods in Psychiatric Research. 2004;13(2):69-92.

Heeringa S: National Comorbidity Survey (NCS): Procedures for sampling error estimation. Survey Design and Analysis Unit, Survey Research Center, University of Michigan; 1996.

Breslow NE: Analysis of survival data under the proportional hazards model. International Statistical Review/Revue Internationale de Statistique. 1975:45-57.

Mortality rate, under-5 (per 1,000 live births)

Ayele DG, Zewotir TT, Mwambi HG: Structured additive regression models with spatial correlation to estimate under-five mortality risk factors in Ethiopia. BMC Public Health. 2015; 15(1):268.

Black RE, Morris SS, Bryce J: Where and why are 10 million children dying every year? The lancet. 2003:361(9376):2226-2234.

Ayele DG, Zewotir TT: Childhood mortality spatial distribution in Ethiopia. Journal of Applied Statistics 2016, 43(15):2813-2828.

Ayiko R, Antai D, Kulane A: Trends and determinants of under-five mortality in Uganda. East African journal of public health 2009, 6(2):136-140.

Adebayo SB, Fahrmeir L: Analysing child mortality in Nigeria with geoadditive discrete‐time survival models. Statistics in Medicine. 2005;24(5):709-728.

Mosley WH, Chen LC. An analytical framework for the study of child survival in developing countries. Population and Development Review. 1984;10:25-45.

Asefa M, Drewett R, Tessema F: A birth cohort study in South-West Ethiopia to identify factors associated with infant mortality that are amenable for intervention. Ethiopian Journal of Health Development. 2000;14(2):161-168.

Mustafa H: Socioeconomic determinants of infant mortality in Kenya; 2008.

Machado CJ, Hill K: Early infant morbidity in the city of Sao Paulo, Brazil. Population Health Metrics. 2003;1(1):7.

Ettarh R, Kimani J: Determinants of under-five mortality in rural and urban Kenya. Rural & Remote Health. 2012;12(1).