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Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories
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. Ba...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3429388/ https://www.ncbi.nlm.nih.gov/pubmed/22952435 http://dx.doi.org/10.1371/journal.pmed.1001289 |
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author | Pedersen, Jon Liu, Jing |
author_facet | Pedersen, Jon Liu, Jing |
author_sort | Pedersen, Jon |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3429388 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-34293882012-09-05 Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories Pedersen, Jon Liu, Jing PLoS Med Research Article 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. Public Library of Science 2012-08-28 /pmc/articles/PMC3429388/ /pubmed/22952435 http://dx.doi.org/10.1371/journal.pmed.1001289 Text en © 2012 Pedersen, Liu http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Pedersen, Jon Liu, Jing Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories |
title | Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories |
title_full | Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories |
title_fullStr | Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories |
title_full_unstemmed | Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories |
title_short | Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories |
title_sort | child mortality estimation: appropriate time periods for child mortality estimates from full birth histories |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3429388/ https://www.ncbi.nlm.nih.gov/pubmed/22952435 http://dx.doi.org/10.1371/journal.pmed.1001289 |
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