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Updated: Mar 12, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study
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Construction of Lambda, Mu, Sigma Values for Determining Mid-Upper Arm Circumference z Scores in U.S. Children Aged 2

Susan M Abdel-Rahman1, Charlie Bi2, Kristi Thaete3

  • 11 University of Missouri, Kansas City-School of Medicine and Section of Therapeutic Innovation, Division of Clinical Pharmacology, Toxicology, and Therapeutic Innovation, Children's Mercy Hospital, Kansas City, Missouri, USA.

Nutrition in Clinical Practice : Official Publication of the American Society for Parenteral and Enteral Nutrition
|November 19, 2016
PubMed

Insights

New Lambda Mu Sigma (LMS) values enable mid-upper arm circumference (MUAC) z-score calculations for U.S. children up to 18 years. This advances malnutrition assessment, improving pediatric nutrition monitoring.

Area of Science:

  • Pediatric Nutrition
  • Anthropometry
  • Growth Monitoring

Background:

  • Mid-upper arm circumference (MUAC) is a key indicator for malnutrition, outperforming BMI z scores in predicting morbidity and mortality.
  • A consensus recommends MUAC z scores for U.S. children, but data for those over 5 years were lacking.

Purpose of the Study:

  • To generate Lambda Mu Sigma (LMS) values for calculating MUAC z scores in U.S. children aged 2 months to 18 years.
  • To provide essential data for comprehensive pediatric nutrition assessment.

Main Methods:

  • Utilized National Health and Nutrition Examination Survey (1999-2012) anthropometric data (n=28,995) for model development.
  • Constructed smoothed centiles and validated using independent U.S. MUAC datasets (n=1438).
  • Assessed goodness-of-fit using visual and statistical methods, including detrended quantile-quantile plots and Q statistics.

Main Results:

  • Generated LMS curves demonstrated excellent fit to the raw data across all age groups, including infants under 12 months.
  • The derived curves aligned with existing CDC percentiles.
  • The distribution of z scores closely approximated the expected 0 ± 1 across all age groups.

Conclusions:

  • The developed LMS values provide a reliable method for clinicians to calculate MUAC z scores for U.S. children.
  • This facilitates improved nutritional status monitoring and early identification of malnutrition in pediatric populations.
Abstract

Keywords:
adolescentchildgrowth curveinfantmalnutritionnutrition assessment

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