Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2012;9(8):e1001289.
doi: 10.1371/journal.pmed.1001289. Epub 2012 Aug 28.

Child mortality estimation: appropriate time periods for child mortality estimates from full birth histories

Jon Pedersen  1 , Jing Liu
Affiliations

Child mortality estimation: appropriate time periods for child mortality estimates from full birth histories

Jon Pedersen et al. PLoS Med. 2012.

Abstract

Background: Child mortality estimates from complete birth histories from Demographic and Health Surveys (DHS) surveys and similar surveys are a chief source of data used to track Millennium Development Goal 4, which aims for a reduction of under-five mortality by two-thirds between 1990 and 2015. Based on the expected sample sizes when the DHS program commenced, the estimates are usually based on 5-y time periods. Recent surveys have had larger sample sizes than early surveys, and here we aimed to explore the benefits of using shorter time periods than 5 y for estimation. We also explore the benefit of changing the estimation procedure from being based on years before the survey, i.e., measured with reference to the date of the interview for each woman, to being based on calendar years.

Methods and findings: Jackknife variance estimation was used to calculate standard errors for 207 DHS surveys in order to explore to what extent the large samples in recent surveys can be used to produce estimates based on 1-, 2-, 3-, 4-, and 5-y periods. We also recalculated the estimates for the surveys into calendar-year-based estimates. We demonstrate that estimation for 1-y periods is indeed possible for many recent surveys.

Conclusions: The reduction in bias achieved using 1-y periods and calendar-year-based estimation is worthwhile in some cases. In particular, it allows tracking of the effects of particular events such as droughts, epidemics, or conflict on child mortality in a way not possible with previous estimation procedures. Recommendations to use estimation for short time periods when possible and to use calendar-year-based estimation were adopted in the United Nations 2011 estimates of child mortality.

PubMed Disclaimer

Conflict of interest statement

The authors have declared the following competing interests: Stanton-Hill Research supported this study. Kenneth Hill of Stanton-Hill Research is also the chair of the Technical Advisory Group (TAG) to the UN Inter Agency group of Child Mortality Estimation. There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS Medicine policies on sharing data and materials, as detailed online in the guide for authors.

Figures

Figure 1
Figure 1. Effects of choice of period on estimates.
The figure shows a cosine curve (green lines) with a 5-y periodicity and average estimates based on 1- to 5-y periods (blue lines).
Figure 2
Figure 2. 5 q 0 and confidence intervals for the Rwanda 2000 DHS survey.
Estimates based on years before the survey.
Figure 3
Figure 3. Distribution of coefficient of variation of 5 q 0 by length of period of estimation.
Only estimates for periods 20 y or less before the survey were included. Two extreme outliers have been excluded from the graph.
Figure 4
Figure 4. Mean number of contiguous years before survey allowing estimates with coefficient of variation less than 10%, by sample size, estimation period, and total fertility rate (births per woman).
Estimates based on years before the survey. The number of surveys used for the estimates in each panel is indicated in the upper left corner of each.
Figure 5
Figure 5. Mean number of contiguous years before survey allowing estimates with coefficient of variation less than 5%, by sample size, estimation period, and total fertility rate (births per woman).
Estimates based on years before the survey. Estimates based on calendar years. The number of surveys used for the estimates in each panel is indicated in the upper left corner of each.
Figure 6
Figure 6. Estimates of 5 q 0 and confidence intervals for Mali 2001 DHS survey.
Sample size 12,439 households; total fertility rate 6.8 (births per woman). Estimates based on years before the survey.
Figure 7
Figure 7. Estimates of 5 q 0 and confidence intervals for Kazakhstan 1999 DHS survey.
Sample size 5,841households; total fertility rate 2.0 (births per woman). Estimates based on years before the survey.
Figure 8
Figure 8. Estimates of 5 q 0 and confidence intervals for Moldova 2005 DHS survey.
Sample size 11,095 households; total fertility rate 1.7 (births per woman). Estimates based on calendar years.
Figure 9
Figure 9. Estimates of 5 q 0 and confidence intervals for Zimbabwe 1999 DHS survey.
Sample size 6,372 households; total fertility rate 4.0 (births per woman). Estimates based on calendar years.
Figure 10
Figure 10. Trends in 5 q 0 in Rwanda 2000 and 2005 DHS surveys using estimation periods based on years before the survey.
Figure 11
Figure 11. Trends in 5 q 0 in Rwanda 2000 and 2005 DHS surveys using calendar-year estimation periods.
See this image and copyright information in PMC

References

    1. Measure DHS (1996) Sampling manual, DHS-III basic documentation No 6. Calverton: Macro International.
    1. Hill K, You D, Inoue M, Oestergaard MZ (2012) Child Mortality Estimation: Accelerated progress in reducing global child mortality, 1990–2010. PLoS Med 9: e1001303 doi:10.1371/journal.pmed.1001303. - DOI - PMC - PubMed
    1. United Nations (1993) Sampling errors in household surveys. New York: United Nations Department for Economic and Social Information and Policy Analyses.
    1. Ward D (2007) Data and metadata reporting and presentation handbook: Paris: Organisation for Economic Co-operation and Development.
    1. Särndal C-E, Swensson B, Wretman J (1992) Model assisted survey sampling. New York: Springer-Verlag. 694 p.

Publication types