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. 2023 Jul 28;21(1):10.
doi: 10.1186/s12963-023-00309-7.

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

Daniel J Erchick  1 , Seema Subedi  2 , Andrea Verhulst  3 , Michel Guillot  3   4 , Linda S Adair  5 , Aluísio J D Barros  6 , Bernard Chasekwa  7 , Parul Christian  2 , Bruna Gonçalves C da Silva  6 , Mariângela F Silveira  6 , Pedro C Hallal  6 , Jean H Humphrey  2 , Lieven Huybregts  8   9 , Simon Kariuki  10 , Subarna K Khatry  11 , Carl Lachat  9 , Alicia Matijasevich  12 , Peter D McElroy  13 , Ana Maria B Menezes  6 , Luke C Mullany  2 , Tita Lorna L Perez  14 , Penelope A Phillips-Howard  15 , Dominique Roberfroid  15 , Iná S Santos  6 , Feiko O Ter Kuile  16 , Thulasiraj D Ravilla  17 , James M Tielsch  18 , Lee S F Wu  2 , Joanne Katz  2
Affiliations

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

Daniel J Erchick et al. Popul Health Metr. .

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.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Distribution of age at death and loss to follow-up in neonatal or infant period by study. A Graphs include live births with complete vital registration data: India 2000: n = 14,147; Nepal 1999 n = 4130; Nepal 2011 n = 32,010; Philippines 1983: n = 3070 observations with complete data (n = 79 live births excluded for missing vital event data). All four of these studies were pregnancy cohorts. B Graphs include live births with complete vital registration data: Burkina 2004: n = 1321; Burkina 2006: n = 1102; Kenya 1992: n = 2332; Zimbabwe 1997: n = 14,108. Burkina Faso 2004 and 2006 and Kenya 1992 were pregnancy cohorts; Zimbabwe 1997 was a birth cohort. C Graphs include live births with complete vital registration data: Brazil 1993: n = 5248; Brazil 2004: n = 4219; Brazil 2015: n = 4270. Brazil 2015 was a pregnancy cohort; Brazil 1993 and 2004 were birth cohorts
Fig. 1
Fig. 1
Distribution of age at death and loss to follow-up in neonatal or infant period by study. A Graphs include live births with complete vital registration data: India 2000: n = 14,147; Nepal 1999 n = 4130; Nepal 2011 n = 32,010; Philippines 1983: n = 3070 observations with complete data (n = 79 live births excluded for missing vital event data). All four of these studies were pregnancy cohorts. B Graphs include live births with complete vital registration data: Burkina 2004: n = 1321; Burkina 2006: n = 1102; Kenya 1992: n = 2332; Zimbabwe 1997: n = 14,108. Burkina Faso 2004 and 2006 and Kenya 1992 were pregnancy cohorts; Zimbabwe 1997 was a birth cohort. C Graphs include live births with complete vital registration data: Brazil 1993: n = 5248; Brazil 2004: n = 4219; Brazil 2015: n = 4270. Brazil 2015 was a pregnancy cohort; Brazil 1993 and 2004 were birth cohorts
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References

    1. United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). Levels & trends in child mortality: report 2020, estimates developed by the United Nations Inter-Agency Group for Child Mortality Estimation. United Nations Children’s Fund; 2020.
    1. Mikkelsen L, Phillips DE, AbouZahr C, et al. A global assessment of civil registration and vital statistics systems: monitoring data quality and progress. Lancet Lond Engl. 2015;386(10001):1395–1406. doi: 10.1016/S0140-6736(15)60171-4. - DOI - PubMed
    1. United Nations Statistics Division. Quality of vital statistics obtained from civil registration. United Nations https://unstats.un.org/unsd/demographic-social/crvs/
    1. Guillot M, Gerland P, Pelletier F, Saabneh A. Child mortality estimation: a global overview of infant and child mortality age patterns in light of new empirical data. PLOS Med. 2012;9(8):e1001299. doi: 10.1371/journal.pmed.1001299. - DOI - PMC - PubMed
    1. Guillot M, Prieto J, Verhulst A, Gerland P. Modeling age patterns of under-5 mortality: results from a log-quadratic model applied to high-quality vital registration data. Published online August 31, 2020. - PMC - PubMed

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