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
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...
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BMJ Publishing Group
2022-07-01
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Series: | BMJ Open |
Online Access: | https://bmjopen.bmj.com/content/12/7/e060105.full |
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author | Joanne Katz James M Tielsch Luke C Mullany Diwakar Mohan Subarna K Khatry Seema Subedi Scott L Zeger Elizabeth A Hazel |
author_facet | Joanne Katz James M Tielsch Luke C Mullany Diwakar Mohan Subarna K Khatry Seema Subedi Scott L Zeger Elizabeth A Hazel |
author_sort | Joanne Katz |
collection | DOAJ |
description | 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. |
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language | English |
last_indexed | 2024-03-12T21:40:33Z |
publishDate | 2022-07-01 |
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spelling | doaj.art-914d787658334d17bd771b55ef6439512023-07-27T01:45:07ZengBMJ Publishing GroupBMJ Open2044-60552022-07-0112710.1136/bmjopen-2021-060105Development 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 NepalJoanne Katz0James M Tielsch1Luke C Mullany2Diwakar Mohan3Subarna K Khatry4Seema Subedi5Scott L Zeger6Elizabeth A Hazel7International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USADepartment of Global Health, George Washington University School of Public Health and Health Services, Washington, District of Columbia, USADepartment of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USAInternational Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USANepal Nutrition Intervention Project Sarlahi, Kathmandu, NepalDepartment of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USAInternational Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USADepartment of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USAObjectives 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.https://bmjopen.bmj.com/content/12/7/e060105.full |
spellingShingle | Joanne Katz James M Tielsch Luke C Mullany Diwakar Mohan Subarna K Khatry Seema Subedi Scott L Zeger Elizabeth A Hazel 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 BMJ Open |
title | 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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
url | https://bmjopen.bmj.com/content/12/7/e060105.full |
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