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The LMS method for constructing normalized growth standards.

T J Cole1

  • 1MRC Dunn Nutrition Unit, Cambridge, UK.

European Journal of Clinical Nutrition
|January 1, 1990
PubMed
Summary
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The LMS method offers normalized growth centile standards for assessing child growth status using SD scores. This statistical approach effectively handles skewed data, simplifying the creation and application of growth charts.

Area of Science:

  • Pediatrics
  • Biostatistics
  • Anthropometry

Background:

  • Child growth assessment commonly uses Standard Deviation (SD) scores.
  • Existing methods may struggle with skewed data distributions in measurements like height and weight.

Purpose of the Study:

  • To introduce and illustrate the LMS method for creating normalized growth centile standards.
  • To provide a flexible approach for assessing child growth, accommodating skewed data.

Main Methods:

  • The LMS method utilizes a power transformation to normalize skewed data.
  • Smooth curves (L, M, S) are generated to represent trends in skewness, median, and coefficient of variation across age groups.
  • These curves enable the conversion of measurements into precise SD scores and the generation of centile charts.

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Main Results:

  • The LMS method effectively normalizes skewed anthropometric data.
  • Generated L, M, and S curves provide a comprehensive basis for growth standard construction.
  • The method allows for the accurate calculation of SD scores, even for extreme measurements.

Conclusions:

  • The LMS method simplifies the assessment of child growth status through normalized centile standards.
  • It offers a robust solution for dealing with skewed distributions in pediatric measurements.
  • This approach is valuable for both developing and implementing accurate growth standards.