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. 2022 Jul 12;12(7):e060105.
doi: 10.1136/bmjopen-2021-060105.

Development of an imputation model to recalibrate birth weights measured in the early neonatal period to time at delivery and assessment of its impact on size-for-gestational age and low birthweight prevalence estimates: a secondary analysis of a pregnancy cohort in rural Nepal

Elizabeth A Hazel  1 , Luke C Mullany  2 , Scott L Zeger  2 , Diwakar Mohan  2 , Seema Subedi  2 , James M Tielsch  3 , Subarna K Khatry  4 , Joanne Katz  2
Affiliations

Development of an imputation model to recalibrate birth weights measured in the early neonatal period to time at delivery and assessment of its impact on size-for-gestational age and low birthweight prevalence estimates: a secondary analysis of a pregnancy cohort in rural Nepal

Elizabeth A Hazel et al. BMJ Open. .

Abstract

Objectives: In low-income countries, birth weights for home deliveries are often measured at the nadir when babies may lose up of 10% of their birth weight, biasing estimates of small-for-gestational age (SGA) and low birth weight (LBW). We aimed to develop an imputation model that predicts the 'true' birth weight at time of delivery.

Design: We developed and applied a model that recalibrates weights measured in the early neonatal period to time=0 at delivery and uses those recalibrated birth weights to impute missing birth weights.

Setting: This is a secondary analysis of pregnancy cohort data from two studies in Sarlahi district, Nepal.

Participants: The participants are 457 babies with daily weights measured in the first 10 days of life from a subsample of a larger clinical trial on chlorhexidine (CHX) neonatal skin cleansing and 31 116 babies followed through the neonatal period to test the impact of neonatal massage oil type (Nepal Oil Massage Study (NOMS)).

Outcome measures: We developed an empirical Bayes model of early neonatal weight change using CHX trial longitudinal data and applied it to the NOMS dataset to recalibrate and then impute birth weight at delivery. The outcomes are size-for-gestational age and LBW.

Results: When using the imputed birth weights, the proportion of SGA is reduced from 49% (95% CI: 48% to 49%) to 44% (95% CI: 43% to 44%). Low birth weight is reduced from 30% (95% CI: 30% to 31%) to 27% (95% CI: 26% to 27%). The proportion of babies born large-for-gestational age increased from 4% (95% CI: 4% to 4%) to 5% (95% CI: 5% to 5%).

Conclusions: Using weights measured around the nadir overestimates the prevalence of SGA and LBW. Studies in low-income settings with high levels of home births should consider a similar recalibration and imputation model to generate more accurate population estimates of small and vulnerable newborns.

Keywords: maternal medicine; neonatology; public health.

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Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Probability of return to birth weight (BW) and 95% CIs, chlorhexidine trial. Babies that did not return to their BW in the 10-day period were censored.
Figure 2
Figure 2
Comparison of measured weight and imputed weight in grams by the timing of the weight measurement in days after delivery, Nepal Oil Massage Study dataset.
See this image and copyright information in PMC

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