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Study protocol for WHO and UNICEF estimates of global, regional, and national preterm birth rates for 2010 to 2019

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PLOS ONE
卷 16, 期 10, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0258751

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  1. Children's Investment Fund Foundation

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This study aims to update global, regional, and national preterm birth estimates from 2010 to 2019 by searching national administrative data sources and conducting a systematic review of studies. The accurate measurement of preterm birth is challenging due to incomplete data and limited gestational age assessment in many countries. The updated estimates will be vital for understanding the global burden of preterm birth and guiding policies and programs, particularly in high neonatal mortality settings.
Background Preterm birth is a leading cause of death among children under five years. Previous estimates indicated global preterm birth rate of 10.6% (14.8 million neonates) in 2014. We aim to update preterm birth estimates at global, regional, and national levels for the period 2010 to 2019. Methods Preterm birth is defined as a live birth occurring before 37 completed gestational weeks, or <259 days since a woman's last menstrual period. National administrative data sources for WHO Member States with facility birth rates of >= 80% in the most recent year for which data is available will be searched. Administrative data identified for these countries will be considered if >= 80% of UN estimated live births include gestational age information to define preterm birth. For countries without eligible administrative data, a systematic review of studies will be conducted. Research studies will be eligible if the reported outcome is derived from an observational or intervention study conducted at national or sub-national level in population- or facility-based settings. Risk of bias assessments will focus on gestational age measurement method and coverage, and inclusion of special subgroups in published estimates. Covariates for inclusion will be selected a priori based on a conceptual framework of plausible associations with preterm birth, data availability, and quality of covariate data across many countries and years. Global, regional and national preterm birth rates will be estimated using a Bayesian multilevel-mixed regression model. Discussion Accurate measurement of preterm birth is challenging in many countries given incomplete or unavailable data from national administrative sources, compounded by limited gestational age assessment during pregnancy to define preterm birth. Up-to-date modelled estimates will be an important resource to measure the global burden of preterm birth and to inform policies and programs especially in settings with a high burden of neonatal mortality.

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