Abstract

BackgroundLow birthweight (LBW) (< 2500 g) is a significant determinant of infant morbidity and mortality worldwide. In low-income settings, the quality of birthweight data suffers from measurement and recording errors, inconsistent data reporting systems, and missing data from non-facility births. This paper describes birthweight data quality and the prevalence of LBW before and after implementation of a birthweight quality improvement (QI) initiative in Amhara region, Ethiopia.MethodsA comparative pre-post study was performed in selected rural health facilities located in West Gojjam and South Gondar zones. At baseline, a retrospective review of delivery records from February to May 2018 was performed in 14 health centers to collect birthweight data. A birthweight QI initiative was introduced in August 2019, which included provision of high-quality digital infant weight scales (precision 5 g), routine calibration, training in birth weighing and data recording, and routine field supervision. After the QI implementation, birthweight data were prospectively collected from late August to early September 2019, and December 2019 to June 2020. Data quality, as measured by heaping (weights at exact multiples of 500 g) and rounding to the nearest 100 g, and the prevalence of LBW were calculated before and after QI implementation.ResultsWe retrospectively reviewed 1383 delivery records before the QI implementation and prospectively measured 1371 newborn weights after QI implementation. Heaping was most frequently observed at 3000 g and declined from 26% pre-initiative to 6.7% post-initiative. Heaping at 2500 g decreased from 5.4% pre-QI to 2.2% post-QI. The percentage of rounding to the nearest 100 g was reduced from 100% pre-initiative to 36.5% post-initiative. Before the QI initiative, the prevalence of recognized LBW was 2.2% (95% confidence interval [CI]: 1.5–3.1) and after the QI initiative increased to 11.7% (95% CI: 10.1–13.5).ConclusionsA QI intervention can improve the quality of birthweight measurements, and data measurement quality may substantially affect estimates of LBW prevalence.

Highlights

  • Low birthweight (LBW) (< 2500 g) is a significant determinant of infant morbidity and mortality worldwide

  • The health centers were chosen as prospective sites for the parent Enhancing Nutrition and Antenatal Infection Treatment (ENAT) study, and the populations were selected based on high rates of maternal malnutrition, risk of fetal growth restriction, and need for nutrition interventions

  • Quality of birthweight data Birthweight data from 1383 and 1371 live births were collected from delivery registers in phase 1 and phase 2 studies, respectively

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Summary

Introduction

Low birthweight (LBW) (< 2500 g) is a significant determinant of infant morbidity and mortality worldwide. In low-income settings, the quality of birthweight data suffers from measurement and recording errors, inconsistent data reporting systems, and missing data from non-facility births. Measuring newborn weight at birth is crucial to provide special care for LBW infants, monitor the burden of LBW in the population, evaluate access to interventions aimed to improve antenatal care, and planning appropriate actions to accelerate the reduction of neonatal morbidity and mortality [6]. In LMICs, the quality of birthweight data suffers from measurement and recording errors, inconsistent data reporting systems, and missing data from non-facility births [1]. The Every Newborn Action Plan endorsed by the World Health Assembly prioritizes measurement improvement, with a focus on strengthening routine facility-based data, to track the national 2030 milestones (≤ 12 neonatal deaths and ≤ 12 stillbirths per 1000 live births) [9]. Notwithstanding, the recent global and national LBW estimates conducted by Blencowe and colleagues could not provide an estimated LBW prevalence from Ethiopia, due to lack of adequate birthweight data quality [1]

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