前瞻性、基于人群的研究中婴儿死亡率估计的生命事件数据质量：亚洲、非洲和拉丁美洲二次数据分析。
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.
机构信息
Department of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD, 21205, USA.
Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA.
出版信息
Popul Health Metr. 2023 Jul 28;21(1):10. doi: 10.1186/s12963-023-00309-7.
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.
简介
婴儿和新生儿死亡率的估计通常来自于通过调查在民事登记和生命统计系统不可靠的国家收集的回顾性出生史。然而，这些数据可能存在偏差，包括死亡漏报和年龄误报，这会影响死亡率的估计。基于人群的前瞻性队列研究是一种用于死亡率估计的未充分利用的数据来源，它可能具有避免偏差的优势。
方法
我们对儿童健康流行病学参考组的数据进行了二次分析，包括 11 项基于人群的妊娠或出生队列研究，以评估生命事件数据用于死亡率估计的适宜性。分析是描述性的，总结了研究设计、人群、方案和内部检查，以评估它们对数据质量的影响。我们计算了婴儿和新生儿死亡率，并将其与人口与健康调查（DHS）数据进行了比较。
结果
这些研究产生了 71760 名孕妇和 85095 名活产儿。具体的现场方案，特别是妊娠登记、有限的排除标准和分娩后频繁的随访访问，导致了更高的出生结局确定率和更少的死亡漏报。大多数研究在妊娠和第一个月的随访丢失率较低，几乎没有日期堆积的证据。在亚洲和拉丁美洲的研究中，新生儿死亡率（NMR）与 DHS 相似，而撒哈拉以南非洲的几项研究的 NMR 低于 DHS。婴儿死亡率因研究和地区而异，来源也不同。
结论
遵循严格方案的前瞻性、基于人群的队列研究可以产生高质量的生命事件数据，以改善对中低收入国家婴儿详细死亡率模式的描述，特别是在新生儿期死亡率最高且变化最快的时期。
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