The impact of growth curve changes in assessing premature infant growth

J Perinatol. 2014 Jan;34(1):49-53. doi: 10.1038/jp.2013.114. Epub 2013 Sep 19.


Objective: To assess the impact of using the recently published WHO growth standard, based on healthy, breastfed infants in multiple countries that excluded prematurely born infants, versus the Infant Health Development Program (IHDP) growth reference constructed from premature infants, on the interpretation of the growth of premature infants after hospital discharge.

Study design: A retrospective cohort was constructed of infants born at gestational age ≤35 weeks who initially presented for care at one of the 32 outpatient sites between 2006 and 2008 (N=2297). Kappa statistics measured overall agreement and agreement in ever classifying infants <5th percentile or ≥ 95th percentile for age between the WHO and IHDP. Logistic regression models identified factors associated with growth curve disagreement in classifying infants at the extremes of growth.

Result: The WHO and IHDP growth curves showed moderate agreement for all measurements (κ=0.40-0.52). When the curves disagreed on whether an infant was <5th percentile for weight (8.3% of cohort) or length (13.6% of cohort), the WHO curve classified the infant in this category over 90% of the time. For head circumference, the IHDP curve classified more infants below the 5th percentile. Gestational age <30 weeks was associated with growth curve disagreement for weight and length <5th percentile.

Conclusion: Choice of growth curve affects the assessment of growth and the classification of underweight status. Longitudinal studies are needed to determine which assessment identifies the greatest number of premature infants at risk for long-term growth issues.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Body Height
  • Body Weight
  • Female
  • Gestational Age
  • Growth Charts*
  • Head / anatomy & histology
  • Humans
  • Infant, Newborn
  • Infant, Premature / growth & development*
  • Logistic Models
  • Male
  • Retrospective Studies
  • Thinness / diagnosis