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A comparison of different approaches for fitting centile curves to birthweight data

S R Bonellie1, G M Raab

  • 1Department of Mathematics, Napier University, Edinburgh, U.K.

Statistics in Medicine
|December 30, 1996
PubMed

Insights

This study compares statistical methods for creating centile charts to identify infants small for gestational age. Findings help improve clinical assessment of intra-uterine growth retardation using Scottish birth data.

Area of Science:

  • Perinatal epidemiology
  • Biostatistics
  • Clinical growth assessment

Background:

  • Centile charts are crucial for identifying infants small for gestational age (SGA).
  • Intra-uterine growth retardation (IUGR) is a significant concern in perinatal health.
  • Various statistical methods exist for constructing these charts, each with different assumptions.

Purpose of the Study:

  • To compare different statistical approaches for constructing centile charts.
  • To evaluate methods for identifying infants with potential intra-uterine growth retardation.
  • To utilize a comprehensive dataset of Scottish live births for this comparison.

Main Methods:

  • Comparison of distribution-free methods (empirical centile smoothing) versus parametric methods (assuming Normal distribution).
  • Utilized a large dataset of live births in Scottish hospitals (1980-1992).
  • Analysis focused on charts plotted by week of gestational age.

Main Results:

  • The study provides a comparative analysis of various centile chart construction techniques.
  • The effectiveness of different statistical methods in identifying SGA infants was assessed.
  • Data from the Scottish Health Service's SMR2 forms provided a robust basis for comparison.

Conclusions:

  • The choice of statistical method impacts the accuracy of centile charts for SGA assessment.
  • This comparison aids in selecting optimal methods for clinical use in identifying potential IUGR.
  • The findings contribute to refining perinatal growth monitoring standards.

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