Dataset Information

Quality of vital event data for infant mortality estimation in prospective, population-based studies: an analysis of secondary data from Asia, Africa, and Latin America.

ABSTRACT:

Introduction

Infant and neonatal mortality estimates are typically derived from retrospective birth histories collected through surveys in countries with unreliable civil registration and vital statistics systems. Yet such data are subject to biases, including under-reporting of deaths and age misreporting, which impact mortality estimates. Prospective population-based cohort studies are an underutilized data source for mortality estimation that may offer strengths that avoid biases.

Methods

We conducted a secondary analysis of data from the Child Health Epidemiology Reference Group, including 11 population-based pregnancy or birth cohort studies, to evaluate the appropriateness of vital event data for mortality estimation. Analyses were descriptive, summarizing study designs, populations, protocols, and internal checks to assess their impact on data quality. We calculated infant and neonatal morality rates and compared patterns with Demographic and Health Survey (DHS) data.

Results

Studies yielded 71,760 pregnant women and 85,095 live births. Specific field protocols, especially pregnancy enrollment, limited exclusion criteria, and frequent follow-up visits after delivery, led to higher birth outcome ascertainment and fewer missing deaths. Most studies had low follow-up loss in pregnancy and the first month with little evidence of date heaping. Among studies in Asia and Latin America, neonatal mortality rates (NMR) were similar to DHS, while several studies in Sub-Saharan Africa had lower NMRs than DHS. Infant mortality varied by study and region between sources.

Conclusions

Prospective, population-based cohort studies following rigorous protocols can yield high-quality vital event data to improve characterization of detailed mortality patterns of infants in low- and middle-income countries, especially in the early neonatal period where mortality risk is highest and changes rapidly.

SUBMITTER: Erchick DJ

PROVIDER: S-EPMC10375772 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Publications

Quality of vital event data for infant mortality estimation in prospective, population-based studies: an analysis of secondary data from Asia, Africa, and Latin America.

Erchick Daniel J DJ Subedi Seema S Verhulst Andrea A Guillot Michel M Adair Linda S LS Barros Aluísio J D AJD Chasekwa Bernard B Christian Parul P da Silva Bruna Gonçalves C BGC Silveira Mariângela F MF Hallal Pedro C PC Humphrey Jean H JH Huybregts Lieven L Kariuki Simon S Khatry Subarna K SK Lachat Carl C Matijasevich Alicia A McElroy Peter D PD Menezes Ana Maria B AMB Mullany Luke C LC Perez Tita Lorna L TLL Phillips-Howard Penelope A PA Roberfroid Dominique D Santos Iná S IS Ter Kuile Feiko O FO Ravilla Thulasiraj D TD Tielsch James M JM Wu Lee S F LSF Katz Joanne J

Population health metrics 20230728 1

<h4>Introduction</h4>Infant and neonatal mortality estimates are typically derived from retrospective birth histories collected through surveys in countries with unreliable civil registration and vital statistics systems. Yet such data are subject to biases, including under-reporting of deaths and age misreporting, which impact mortality estimates. Prospective population-based cohort studies are an underutilized data source for mortality estimation that may offer strengths that avoid biases.<h4> ...[more]

PMID: 37507749

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Dataset Information

Quality of vital event data for infant mortality estimation in prospective, population-based studies: an analysis of secondary data from Asia, Africa, and Latin America.

Introduction

Methods

Results

Conclusions

Publications

Quality of vital event data for infant mortality estimation in prospective, population-based studies: an analysis of secondary data from Asia, Africa, and Latin America.

Similar Datasets

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