Adapting the log quadratic model to estimate age- and cause-specific mortality among neonates

Authors

Jamie Perin, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Li Liu, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Luke C. Mullany, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
James M. Tielsch, Department of Global Health, Milken Institute School of Public Health, George Washington University, Washington, DC, United States of America.
Andrea Verhulst, Institut National d'Études Démographiques, Aubervilliers, France.
Michel Guillot, Institut National d'Études Démographiques, Aubervilliers, France.
Joanne Katz, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.

Document Type

Journal Article

Publication Date

1-1-2024

Journal

PloS one

Volume

19

Issue

7

DOI

10.1371/journal.pone.0304841

Abstract

INTRODUCTION: Estimates for cause-specific mortality for neonates are generally available for all countries for neonates overall (0 to 28 days). However, cause-specific mortality is generally not being estimated at higher age resolution for neonates, despite evidence of heterogeneity in the causes of deaths during this period. We aimed to use the adapted log quadratic model in a setting where verbal autopsy was the primary means of determining cause of death. METHODS: We examined the timing and causes of death among a cohort of neonates in rural Nepal followed as part of the Nepal Oil Massage Study (NOMS). We adapted methods defined by Wilmoth et al (2012) and Guillot et al. (2022) to estimate age and cause-specific mortality among neonates. We used cross validation to estimate the accuracy of this model, holding out each three month period. We took the average cross validation across hold out as our measure of model performance and compared to a standard approach which did not account for the heterogeneity in cause-specific mortality rate within this age group. RESULTS: There were 957 neonates in the NOMS cohort with known age and cause of death. We estimated an average cross-validation error of 0.9 per 1000 live births for mortality due to prematurity in the first week, and 1.1 for mortality due to birth asphyxia, compared to the standard approach, having error 7.4 and 7.8 per 1000 live births, respectively. Generally mortality rates for less common causes such as congenital malformations and pneumonia were estimated with higher cross-validation error. CONCLUSIONS: The stability and precision of these estimates compare favorably with similar estimates developed with higher quality cause-specific mortality surveillance from China, demonstrating that reliably estimating causes of mortality at high resolution is possible for neonates in low resources areas.

APA Citation

Perin, Jamie; Liu, Li; Mullany, Luke C.; Tielsch, James M.; Verhulst, Andrea; Guillot, Michel; and Katz, Joanne, "Adapting the log quadratic model to estimate age- and cause-specific mortality among neonates" (2024). GW Authored Works. Paper 5289.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/5289

Department

Global Health