Abstract

BackgroundCustomized birth weight charts take into account physiological maternal characteristics that are known to influence fetal growth to differentiate between physiological and pathological abnormal size at birth. It is unknown whether customized birth weight charts better identify newborns at risk of long-term adverse outcomes than population birth weight charts. We aimed to examine whether birth weight classification according to customized charts is superior to population charts at identification of newborns at risk of adverse cardio-metabolic and respiratory health outcomes.MethodsIn a population-based prospective cohort study among 6052 pregnant women and their children, we measured infant catch-up growth, overweight, high blood pressure, hyperlipidemia, liver steatosis, clustering of cardio-metabolic risk factors, and asthma at age 10. Small size and large size for gestational age at birth was defined as birth weight in the lowest or highest decile, respectively, of population or customized charts. Association with birth weight classification was assessed using logistic regression models.ResultsOf the total of 605 newborns classified as small size for gestational age by population charts, 150 (24.8%) were reclassified as appropriate size for gestational age by customized charts, whereas of the total of 605 newborns classified as large size for gestational age by population charts, 129 (21.3%) cases were reclassified as appropriate size for gestational age by customized charts. Compared to newborns born appropriate size for gestational age, newborns born small size for gestational age according to customized charts had increased risks of infant catch-up growth (odds ratio (OR) 5.15 (95% confidence interval (CI) 4.22 to 6.29)), high blood pressure (OR 2.05 (95% CI 1.55 to 2.72)), and clustering of cardio-metabolic risk factors at 10 years (OR 1.66 (95% CI 1.18 to 2.34)). No associations were observed for overweight, hyperlipidemia, liver steatosis, or asthma. Newborns born large-size for gestational age according to customized charts had higher risk of catch-down-growth only (OR 3.84 (95% CI 3.22 to 4.59)). The direction and strength of the observed associations were largely similar when we used classification according to population charts.ConclusionsSmall-size-for-gestational-age newborns seem to be at risk of long-term adverse cardio-metabolic health outcomes, irrespective of the use of customized or population birth weight charts.

Highlights

  • Customized birth weight charts take into account physiological maternal characteristics that are known to influence fetal growth to differentiate between physiological and pathological abnormal size at birth

  • Small-size-for-gestational-age newborns seem to be at risk of long-term adverse cardio-metabolic health outcomes, irrespective of the use of customized or population birth weight charts

  • Compared to newborns classified as appropriate size for gestational age (AGA) by customized charts, newborns classified as size for gestational age (SGA) by customized charts more often had heavier mothers and their mothers more often smoked throughout pregnancy

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Summary

Introduction

Customized birth weight charts take into account physiological maternal characteristics that are known to influence fetal growth to differentiate between physiological and pathological abnormal size at birth. Newborns classified as SGA or LGA by these population charts include those who have grown according to their physiological growth potential and end up constitutionally small or large at birth, and those who have fetal growth restriction or acceleration and end up pathologically small or large at birth. Maternal characteristics, such as age, height, body mass index (BMI), ethnicity and parity, and fetal sex are important determinants of fetal growth and cause nonpathological variation in birth weight [5, 6]. Previous studies assessing the superiority of customized over population charts to identify SGA and LGA newborns at risk of short-term adverse outcomes are scarce and show conflicting results [10,11,12,13]

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