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Child Mortality Estimation: Consistency of Under-Five Mortality Rate Estimates Using Full Birth Histories and Summary Birth Histories

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  • Romesh Silva

Abstract

Romesh Silva assesses and analyzes differences in direct and indirect methods of estimating under-five mortality rates using data collected from full and summary birth histories in Demographic and Health Surveys from West Africa, East Africa, Latin America, and South/Southeast Asia. Background: Given the lack of complete vital registration data in most developing countries, for many countries it is not possible to accurately estimate under-five mortality rates from vital registration systems. Heavy reliance is often placed on direct and indirect methods for analyzing data collected from birth histories to estimate under-five mortality rates. Yet few systematic comparisons of these methods have been undertaken. This paper investigates whether analysts should use both direct and indirect estimates from full birth histories, and under what circumstances indirect estimates derived from summary birth histories should be used. Methods and Findings: Usings Demographic and Health Surveys data from West Africa, East Africa, Latin America, and South/Southeast Asia, I quantify the differences between direct and indirect estimates of under-five mortality rates, analyze data quality issues, note the relative effects of these issues, and test whether these issues explain the observed differences. I find that indirect estimates are generally consistent with direct estimates, after adjustment for fertility change and birth transference, but don't add substantial additional insight beyond direct estimates. However, choice of direct or indirect method was found to be important in terms of both the adjustment for data errors and the assumptions made about fertility. Conclusions: Although adjusted indirect estimates are generally consistent with adjusted direct estimates, some notable inconsistencies were observed for countries that had experienced either a political or economic crisis or stalled health transition in their recent past. This result suggests that when a population has experienced a smooth mortality decline or only short periods of excess mortality, both adjusted methods perform equally well. However, the observed inconsistencies identified suggest that the indirect method is particularly prone to bias resulting from violations of its strong assumptions about recent mortality and fertility. Hence, indirect estimates of under-five mortality rates from summary birth histories should be used only for populations that have experienced either smooth mortality declines or only short periods of excess mortality in their recent past. Background: In 1990, 12 million children died before they reached their fifth birthday. Faced with this largely avoidable loss of young lives, in 2000, world leaders set a target of reducing under-five mortality (death) to one-third of its 1990 level by 2015 as Millennium Development Goal 4 (MDG 4); this goal, together with seven others, aims to eradicate extreme poverty globally. To track progress towards MDG 4, experts need accurate estimates of the global and country-specific under-five mortality rate (U5MR, the probability of a child dying before age five). The most reliable sources of data for U5MR estimation are vital registration systems—national records of all births and deaths. Unfortunately, developing countries, which are where most childhood deaths occur, rarely have such records, so full or summary birth histories provide the data for U5MR estimation instead. In full birth histories (FBHs), which are collected through household surveys such as those conducted by Demographic and Health Surveys (DHS), women are asked for the date of birth of all their children and the age at death of any children who have died. In summary birth histories (SBHs), which are collected through household surveys and censuses, women are asked how many children they have had and how many are alive at the time of the survey. Why Was This Study Done?: “Direct” estimates of U5MRs can be obtained from FBHs because FBHs provide detailed information about the date of death and the exposure of children to the risk of dying. By contrast, because SBHs do not contain information on children's exposure to the risk of dying, “indirect” estimates of U5MR are obtained from SBHs using model life tables (mathematical models of the variation of mortality with age). Indirect estimates are often also derived from FBHs, but few systematic comparisons of direct and indirect methods for U5MR estimation have been undertaken. In this study, Romesh Silva investigates whether direct and indirect methods provide consistent U5MR estimates from FBHs and whether there are any circumstances under which indirect methods provide more reliable U5MR estimates than direct methods. What Did the Researcher Do and Find?: The researcher used DHS data from West Africa, East Africa, Latin America, and South/Southeast Asia to quantify the differences between direct and indirect estimates of U5MR calculated from the same data and analyzed possible reasons for these differences. Estimates obtained using a version of the “Brass” indirect estimation method were uniformly higher than those obtained using direct estimation. Indirect and direct estimates generally agreed, however, after adjustment for changes in fertility—the Brass method assumes that country-specific fertility (the number of children born to a woman during her reproductive life) remains constant—and for birth transference, an important source of data error in FBHs that arises because DHS field staff can lessen their workload by recording births as occurring before a preset cutoff date rather than after that date. Notably, though, for countries that had experienced political or economic crises, periods of excess mortality due to conflicts, or periods during which the health transition had stalled (as countries become more affluent, overall mortality rates decline and noncommunicable diseases replace infectious diseases as the major causes of death), marked differences between indirect and direct estimates of U5MR remained, even after these adjustments. What Do These Findings Mean?: Because the countries included in this study do not have vital registration systems, these findings provide no information about the validity of either direct or indirect estimation methods for U5MR estimation. They suggest, however, that for countries where there has been a smooth decline in mortality or only short periods of excess mortality, both direct and indirect methods of U5MR estimation work equally well, after adjustment for changes in fertility and for birth transference, and that indirect estimates add little to the insights provided into childhood mortality by direct estimates. Importantly, the inconsistencies observed between the two methods that remain after adjustment suggest that indirect U5MR estimation is more susceptible to bias (systematic errors that arise because of the assumptions used to estimate U5MR) than direct estimation. Thus, indirect estimates of U5MR from SBHs should be used only for populations that have experienced either smooth mortality declines or only short periods of excess mortality in their recent past. Additional Information: Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001296.

Suggested Citation

  • Romesh Silva, 2012. "Child Mortality Estimation: Consistency of Under-Five Mortality Rate Estimates Using Full Birth Histories and Summary Birth Histories," PLOS Medicine, Public Library of Science, vol. 9(8), pages 1-14, August.
  • Handle: RePEc:plo:pmed00:1001296
    DOI: 10.1371/journal.pmed.1001296
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    Cited by:

    1. Eoghan Brady & Kenneth Hill, 2017. "Testing survey-based methods for rapid monitoring of child mortality, with implications for summary birth history data," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-10, April.
    2. Katie Wilson & Jon Wakefield, 2021. "Child mortality estimation incorporating summary birth history data," Biometrics, The International Biometric Society, vol. 77(4), pages 1456-1466, December.
    3. Wazir Asif & Goujon Anne, 2021. "Exploratory Assessment of the Census of Pakistan Using Demographic Analysis," Journal of Official Statistics, Sciendo, vol. 37(3), pages 719-750, September.
    4. Andrea Verhulst, 2016. "Child mortality estimation: An assessment of summary birth history methods using microsimulation," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 34(39), pages 1075-1128.
    5. Leontine Alkema & Jin Rou New & Jon Pedersen & Danzhen You & all members of the UN Inter-agency Group for Child Mortality Estimation and its Technical Advisory Group, 2014. "Child Mortality Estimation 2013: An Overview of Updates in Estimation Methods by the United Nations Inter-Agency Group for Child Mortality Estimation," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-13, July.
    6. Muhammad Asif Wazir & Anne Goujon, 2019. "Assessing the 2017 Census of Pakistan Using Demographic Analysis: A Sub-National Perspective," VID Working Papers 1906, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna.
    7. Anne J Rerimoi & Momodou Jasseh & Schadrac C Agbla & Georges Reniers & Anna Roca & Ian M Timæus, 2019. "Under-five mortality in The Gambia: Comparison of the results of the first demographic and health survey with those from existing inquiries," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-14, July.
    8. Sory Toure & John Weeks & David Lopez-Carr & Douglas Stow, 2020. "Evaluating links between dynamic urban landscapes and under-five child mortality in Accra, Ghana," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(20), pages 589-614.
    9. Yempabou Bruno Lankoandé & Bruno Masquelier & Pascal Zabre & Hélène Bangré & Géraldine Duthé & Abdramane B. Soura & Gilles Pison & Sié Ali, 2022. "Estimating mortality from census data: A record-linkage study of the Nouna Health and Demographic Surveillance System in Burkina Faso," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 46(22), pages 653-680.

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