Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories

Pedersen, Jon; Liu, Jing

doi:10.1371/journal.pmed.1001289

Cited by 74 publications

(76 citation statements)

References 12 publications

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“…For countries that lack vital information reporting systems or have insufficient information to estimate mortality indicators, methods have increasingly adopted estimation procedures based on complete birth histories collected from women of reproductive age in household surveys [19-21]. …”

Section: Discussionmentioning

confidence: 99%

Correction of vital statistics based on a proactive search of deaths and live births: evidence from a study of the North and Northeast regions of Brazil

Szwarcwald

Frias

Júnior

et al. 2014

Popul Health Metrics

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BackgroundIn the last 20 years, Brazil has undergone dramatic changes in terms of socioeconomic development and health care. In the first decade of the 2000s, the Ministry of Health (MoH) developed a series of programs focused on reducing infant mortality, including the Family Health Program as a national policy for primary care. In this paper, we propose a method to correct underreporting of deaths and live births. After vital statistics are corrected, infant mortality trends are analyzed for the period 2000–2010 by macro-geographical region.MethodsA proactive search of live births and deaths was carried out in the Amazon and Northeast regions in 2010 to find vital events that occurred in 2008 and were not reported to the Ministry of Health. The probabilistic sample of 133 municipalities was stratified by adequacy of vital information reporting. For each municipality, the adequacy analysis was based on the reported age-standardized mortality rate per 1,000 population and the ratio between reported and estimated live births. Correction factors were estimated by strata based on additional vital events found in the proactive search. The procedure was generalized to correct municipal vital statistics for the period 2000–2010.ResultsIn the proactive search, 35% of non-reported deaths were found within the health system (hospitals and other health establishments), but 28% were found in non-official sources, like illegal cemeteries. In areas of extreme poverty and unreliable vital information, the estimated completeness of infant death reporting was only 33%. After correction of vital information, the estimated infant mortality rate decreased from 26.1 in 2000 to 16.0 in 2010, with an annual rate of decrease of 4.7%, greater than the required rate to achieve the Millennium Development Goal. Among Brazilian regions, the Northeast showed the largest decrease, from 38.4 to 20.1 per 1,000 live births.ConclusionsThe proactive search for vital events was shown to be a good strategy both in terms of understanding local irregularities and for correcting vital statistics. The methodology could be applied in other countries to routinely assess the pattern and extent of birth and death under-registration in order to improve the utility of these data to inform health policies.

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Section: Discussionmentioning

confidence: 99%

Correction of vital statistics based on a proactive search of deaths and live births: evidence from a study of the North and Northeast regions of Brazil

Szwarcwald

Frias

Júnior

et al. 2014

Popul Health Metrics

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show abstract

“…For these series, values for sampling errors are imputed (see Section 3.4.2). All mortality rates, ratios of mortality rates, and corresponding standard errors were calculated from the survey microdata using the software CMRJack (Pedersen and Liu 2012), a software package that produces mortality estimates and standard errors for surveys with complete birth histories or summary birth histories. Estimates are obtained based on the methodology outlined in Pedersen and Liu (2012).…”

Section: Source Typesmentioning

confidence: 99%

“…All mortality rates, ratios of mortality rates, and corresponding standard errors were calculated from the survey microdata using the software CMRJack (Pedersen and Liu 2012), a software package that produces mortality estimates and standard errors for surveys with complete birth histories or summary birth histories. Estimates are obtained based on the methodology outlined in Pedersen and Liu (2012). The retrospective time period covered by mortality estimates is optimized to capture short-term fluctuations while still ensuring that the estimates have a coefficient of variation of less than 10%.…”

Section: Source Typesmentioning

confidence: 99%

Global estimation of neonatal mortality using a Bayesian hierarchical splines regression model

Alexander¹,

Alkema²

2018

DemRes

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In recent years, much of the focus in monitoring child mortality has been on assessing changes in the under-five mortality rate (U5MR). However, as the U5MR decreases, the share of neonatal deaths (within the first month) tends to increase, warranting increased efforts in monitoring this indicator in addition to the U5MR. A Bayesian splines regression model is presented for estimating neonatal mortality rates (NMR) for all countries. In the model, the relationship between NMR and U5MR is assessed and used to inform estimates, and spline regression models are used to capture country-specific trends. As such, the resulting NMR estimates incorporate trends in overall child mortality while also capturing data-driven trends. The model is fitted to 195 countries using the database from the United Nations Interagency Group for Child Mortality Estimation, producing estimates from 1990, or earlier if data are available, until 2015. The results suggest that, above a U5MR of 34 deaths per 1000 live births, at the global level, a 1 per cent increase in the U5MR leads to a 0.6 per cent decrease in the ratio of NMR to U5MR. Below a U5MR of 34 deaths per 1000 live births, the proportion of deaths under-five that are neonatal is constant at around 54 per cent. However, the relationship between U5MR and NMR varies across countries. The model has now been adopted by the United Nations Inter-agency Group for Child Mortality Estimation.

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“…17 Although recent studies suggest short time windows may be appropriate with larger DHS surveys, 5-year windows were used throughout. 18 …”

Section: Under-5 Mortalitymentioning

confidence: 99%

“…The DHS methodologists developed a sophisticated approach for estimating standard errors by using block jackknife to account for the complexity in the statistics and study designs. 18,32 The uncertainty in the monthly estimates may bias trend measurements. However, an analysis of DHS surveys suggests that differences .15% in under-5 mortality between consecutive surveys signals true trends (the threshold is lower in bigger surveys).…”

Section: Figurementioning

confidence: 99%

Changes in Child Mortality Over Time Across the Wealth Gradient in Less-Developed Countries

2014

PEDIATRICS

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Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories

Abstract: Jon Pedersen and Jing Liu examine the feasibility and potential advantages of using one-year rather than five-year time periods along with calendar year-based estimation when deriving estimates of child mortality.

Cited by 74 publications

References 12 publications

Correction of vital statistics based on a proactive search of deaths and live births: evidence from a study of the North and Northeast regions of Brazil

Correction of vital statistics based on a proactive search of deaths and live births: evidence from a study of the North and Northeast regions of Brazil

Global estimation of neonatal mortality using a Bayesian hierarchical splines regression model

Changes in Child Mortality Over Time Across the Wealth Gradient in Less-Developed Countries

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