A Comparison of UK Preterm Anthropometric Charts and INTERGROWTH-21st: Is It Time to Change Growth Charts?

Owen Martyn Bendor-Samuel1, Sanja Zivanovic2,3, David Odd4

  • 1Newborn Services, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK, owenmbs@gmail.com.

Neonatology
|May 13, 2020
PubMed

Insights

UK premature infant growth charts differ significantly from international INTERGROWTH-21st standards. This impacts accurate assessment of nutritional needs and requires further study for optimal infant care.

Area of Science:

  • Neonatalogy
  • Pediatric Growth Standards
  • Anthropometry

Background:

  • Current UK practice uses Neonatal and Infant Close Monitoring (NICM) charts for premature infants, which have known limitations.
  • The INTERGROWTH-21st Project offers international ante- and postnatal growth standards.
  • Accurate growth centile knowledge is crucial for assessing premature infant nutritional requirements.

Purpose of the Study:

  • To compare target centile measurements between INTERGROWTH-21st and UK NICM growth charts for premature infants.

Main Methods:

  • Retrospective analysis of anthropometric measurements (weight, head circumference) from premature neonates (24-32 weeks gestation).
  • Measurements plotted on both NICM and INTERGROWTH-21st charts at three time points.
  • Statistical comparison using paired-sample t test, Wilcoxon rank test, and mixed-effects linear regression.

Main Results:

  • INTERGROWTH-21st charts showed significantly greater centiles for weight and head circumference compared to UK NICM charts at all time points.
  • Average weight centile differences ranged from 9.1 to 16.4.
  • Differences were more pronounced in female infants, up to 6.9 centiles greater than males.

Conclusions:

  • UK NICM reference charts demonstrate significant divergence from INTERGROWTH-21st growth standards.
  • The selection of growth charts has potential implications for premature infants' long-term adult health.
  • Further prospective studies with larger datasets, including length and comprehensive population data, are warranted.
Abstract

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