title: Construction of Lambda, Mu, Sigma Values for Determining Mid-Upper Arm Circumference z Scores in U.S. Children Aged 2 Months Through 18 Years.
abstract: BACKGROUND
  Mid-upper arm circumference (MUAC) has proven highly predictive of morbidity and mortality associated with malnutrition better, in some cases, than other growth indicators, including body mass index (BMI) z scores and weight-for-height z scores. A recent consensus statement recommended the inclusion of MUAC and MUAC z scores in the nutrition assessment of children in the United States; however, the requisite data to permit z score calculations for children aged >5 years have not been published.
  
  
  OBJECTIVE
  This investigation was designed to generate lambda mu sigma (LMS) values to permit the calculation of MUAC z scores in U.S. children 2 months through 18 years of age.
  
  
  METHODS
  Anthropometric data from the Centers for Disease Control and Prevention (CDC) National Health and Nutrition Examination Survey (1999-2012) were used for model development (n = 28,995). Smoothed centiles were constructed and compared with previously described CDC percentiles. Independently collected MUAC data from 2 different U.S. studies were used for external validation (n = 1438).
  
  
  METHODS
  Goodness-of-fit was assessed visually and statistically by examining detrended quantile-quantile plots, Q statistics, and the distribution of z scores.
  
  
  RESULTS
  The curves generated in this investigation fit the raw data well with no systematic bias and no sacrifice in fit for children aged <12 months. The curves were consistent with those published by the CDC, and the distribution z scores approximated 0 ± 1 in all age groups.
  
  
  CONCLUSIONS
  These LMS values derived in this investigation can be used by clinicians to generate MUAC z scores for U.S. children.
authors.affiliation: 1 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.
authors.forename: Susan M
authors.initials: SM
authors.lastname: Abdel-Rahman
authors.affiliation: 2 Bioinformatics and Intelligent Computing, Division of Clinical Pharmacology, Toxicology, and Therapeutic Innovation, Children's Mercy Hospital, Kansas City, Missouri, USA.
authors.forename: Charlie
authors.initials: C
authors.lastname: Bi
authors.affiliation: 3 Nutrition Services, Children's Mercy Hospital, Kansas City, Missouri, USA.
authors.forename: Kristi
authors.initials: K
authors.lastname: Thaete
mesh_terms: D000293:Adolescent; D041923:Adolescent Development; D017195:Adolescent Nutritional Physiological Phenomena; D001132:Arm; D049628:Body Size; D002648:Child; D002657:Child Development; D002664:Child Nutritional Physiological Phenomena; D002675:Child, Preschool; D015331:Cohort Studies; D005260:Female; D057238:Growth Charts; D006801:Humans; D007223:Infant; D007227:Infant Nutritional Physiological Phenomena; D008297:Male; D008954:Models, Biological; D015596:Nutrition Assessment; D009749:Nutrition Surveys; D009752:Nutritional Status; D012727:Sex Characteristics; D014481:United States
keywords: adolescent; child; growth curve; infant; malnutrition; nutrition assessment