Maternal and Child Health Journal

, Volume 17, Issue 8, pp 1355–1358 | Cite as

Variations in Under-Five Mortality Estimates in Nigeria: Explanations and Implications for Program Monitoring and Evaluation

  • Henry Victor Doctor
Methodological Notes


Millennium Development Goal (MDG) 5 aims at reducing under-five mortality by two-thirds between 1990 and 2015. However, monitoring this goal is a challenging task. With an estimated 162 million people in 2011, Nigeria is Africa’s most populous country with generally poor maternal and child health indicators. Maternal mortality ratio was estimated at 545 deaths per 100,000 live births in 2008 and recent data show that under-five mortality rates have varied tremendously. This paper provides a synthesis of the data collection and estimation procedures used by the two major sources of child mortality data in Nigeria (the Multiple Indicator Cluster Surveys; and Demographic and Health Surveys) and the importance of reflecting on these dynamics in order to utilize the mortality estimates in program monitoring and evaluation. While efforts to seek explanations for the unstable trends in mortality rates are ongoing, this study calls for stakeholders to seek studies that employ more detailed and robust disaggregation methods that take into account the relative impact of socio-demographic, medical, and public health variables on mortality rates. This will be crucial in assessing the effectiveness of selected interventions in reducing mortality. Further, the study encourages collection, use, and triangulation of health and demographic surveillance system (HDSS) and other available data which could assist in monitoring progress towards achieving MDGs since HDSS as well as census or survey data would provide an opportunity to measure and evaluate interventions through longitudinal follow-up of populations.


Child mortality Demographic surveillance Household surveys Monitoring and evaluation Nigeria 


  1. 1.
    National Population Commission (Nigeria), IF Macro. (2008). Nigeria demographic and health survey. Abuja, Nigeria: National Population Commission and ICF Macro.Google Scholar
  2. 2.
    National Bureau of Statistics, UNICEF, and UNFPA. (2011). Nigeria Multiple Indicator Cluster Survey. Abuja, Nigeria: National Bureau of Statistics, UNICEF, and UNFPA, 2012.Google Scholar
  3. 3.
    UNICEF, WHO, World Bank, and United Nations Population Division. (2011). Levels and trends in child mortality: 2011 Report on estimates developed by the UN Inter-agency group for child mortality estimation. New York: UNICEF.Google Scholar
  4. 4.
    United Nations. (1983). Manual X: Indirect techniques for demographic estimation. New York: Department of International Economic and Social Affairs. Population Studies, No. 81. ST/ESA/SER.A/81.Google Scholar
  5. 5.
    Rutstein, S. O., & Rojas, G. (2006). Guide to DHS statistics. Calverton, MD: Demographic and Health Surveys, ORC Macro.Google Scholar
  6. 6.
    Sullivan, K., Hossain, S. M., & Woodruff, B. A. (2010). Mortality rate and confidence interval estimation in humanitarian emergencies. Disasters, 34(1), 164–175.PubMedCrossRefGoogle Scholar
  7. 7.
    Knezevic, A. (2012, September 24). Overlapping confidence intervals and statistical significance. StatNews. No. 73; 2008; Accessed at:
  8. 8.
    Bishai, D., & Opun, M. (2009). Are infant mortality rate declines exponential? The general pattern of 20th century infant mortality rate decline. Population Health Metrics, 7, 13.PubMedCrossRefGoogle Scholar
  9. 9.
    Kintner, H. J. (1994). Infant mortality decline in Germany, 1871–1925: The roles of changes in variables and changes in the structure of relations. GENUS, L(3–4), 117–132.Google Scholar
  10. 10.
    Cornia, G. A., & Mwabu, G. (1997). Health status and health policy in sub Saharan Africa: A long-term perspective. Helinski: World Institute for Development Economics Research.Google Scholar
  11. 11.
    Bangha, M., Diagne, A., Bawah, A., & Sankoh, O. (2010). Monitoring the millennium development goals: The potential role of the INDEPTH network. Global Health Action, 3, 5517.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.Department of Population and Family Health, Mailman School of Public HealthColumbia UniversityNew YorkUSA

Personalised recommendations