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.
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.
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DOI：
10.1186/s12963-023-00309-7
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发表时间：
2023-07-28
影响因子：
3.3
通讯作者：
Katz, Joanne
中科院分区：
文献类型：
--
作者：
Erchick, Daniel J.;Subedi, Seema;Verhulst, Andrea;Guillot, Michel;Adair, Linda S.;Barros, Aluisio J. D.;Chasekwa, Bernard;Christian, Parul;da Silva, Bruna Goncalves C.;Silveira, Mariangela F.;Hallal, Pedro C.;Humphrey, Jean H.;Huybregts, Lieven;Kariuki, Simon;Khatry, Subarna K.;Lachat, Carl;Matijasevich, Alicia;McElroy, Peter D.;Menezes, Ana Maria B.;Mullany, Luke C.;Perez, Tita Lorna L.;Phillips-Howard, Penelope A.;Roberfroid, Dominique;Santos, Ina S.;ter Kuile, Feiko O.;Ravilla, Thulasiraj D.;Tielsch, James M.;Wu, Lee S. F.;Katz, Joanne
婴儿和新生儿死亡率估计通常是根据在民事登记和生命统计系统不可靠的国家通过调查收集的回顾性出生史得出的。然而，这些数据存在偏见，包括少报死亡人数和谎报年龄，从而影响死亡率估计。基于人群的前瞻性队列研究是一种未充分利用的死亡率估计数据源，它可能提供避免偏倚的优势。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用性。分析是描述性的，总结了研究设计、人群、方案和内部检查，以评估其对数据质量的影响。我们计算了婴儿和新生儿的死亡率，并与人口与健康调查（DHS）的数据进行了比较。研究对象包括71,760名孕妇和85,095名活产婴儿。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，导致更高的出生结局确定和更少的失踪死亡。大多数研究在怀孕和第一个月的随访损失很少，没有证据表明日期堆积。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新生儿死亡率（NMR）低于DHS。婴儿死亡率因研究和地区而异。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，以改善低收入和中等收入国家婴儿详细死亡模式的特征，特别是在死亡风险最高且变化迅速的新生儿早期。在线版本包含补充材料，可在10.1186/s12963-023-00309-7获得。
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. 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. 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. 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. The online version contains supplementary material available at 10.1186/s12963-023-00309-7.
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影响因子：
7.1
作者：
Roberfroid, Dominique;Huybregts, Lieven;Kolsteren, Patrick
通讯作者：
Kolsteren, Patrick
影响因子：
3.7
作者：
Liu, Li;Kalter, Henry D.;Black, Robert E.
通讯作者：
Black, Robert E.
影响因子：
8
作者：
Lee, Anne C. C.;Mullany, Luke C.;Darmstadt, Gary L.
通讯作者：
Darmstadt, Gary L.
影响因子：
3.6
作者：
Marinda, Edmore;Humphrey, Jean H.;Ward, Brian J.
通讯作者：
Ward, Brian J.
DOI：
10.1186/s41043-016-0072-y
发表时间：
2016-10-21
期刊：
Journal of health, population, and nutrition
影响因子：
--
作者：
Gernand AD;Paul RR;Ullah B;Taher MA;Witter FR;Wu L;Labrique AB;West KP Jr;Christian P
通讯作者：
Christian P