title: Development of Novel Methods to Define Deficits in Appendicular Lean Mass Relative to Fat Mass.
abstract: BACKGROUND
  Recent studies suggest that adjustment of measures of lean mass for adiposity improves associations with physical function. Our objective was to develop and test a method to adjust appendicular lean mass for adiposity.
  
  
  METHODS
  Whole-body DXA data in 14,850 adults in the National Health and Nutrition Examination Survey were used to generate sex-, and race-specific standard deviation scores (Z-Scores relative to age and T-scores relative to 25 year-olds) for appendicular lean mass index (ALMI, kg/m2) and fat mass index (FMI, kg/m2). Correlations between ALMI and FMI Z- and T-Scores were assessed within demographic categories. Fat-adjusted ALMI (ALMIFMI) scores were determined using residual methods. Sarcopenia was defined as a T-Score <-2.0 and low lean for age as a Z-Score <-1.0. Correlations with physical function were assessed in an at-risk population.
  
  
  RESULTS
  Positive associations between ALMI and FMI Z- and T-Scores were significant (R >0.50; p<0.001) within all demographic categories. The impact of a unit greater FMI Z-score on ALMI Z-score was less in the elderly, men, white subjects, and among individuals with lower FMI (all tests for interaction p<0.001). There was fair agreement between ALMI and ALMIFMI estimates of sarcopenia and low lean for age [Kappa: 0.46, 0.52, respectively (p<0.0001)]. Elderly subjects were likely to be re-classified as sarcopenic while young subjects were likely to be re-classified as normal using ALMIFMI. ALMIFMI T-scores resulted in approximately twice the number of subjects defined as sarcopenic, compared with ALMI T-Scores. (1299 v. 534). Among rheumatoid arthritis patients, ALMIFMI Z-scores correlated with physical function (Health Assessment Questionnaire: rho = -0.22, p = 0.04; Short Physical Performance Battery: rho = 0.27, p = 0.01); however, the ALMI Z-Score did not.
  
  
  CONCLUSIONS
  Adjustment of ALMI for the confounding association with FMI impacts the definition of lean mass deficits. These methods provide a practical tool for investigators and clinicians based on population-based reference data.
authors.affiliation: Division of Endocrinology and Diabetes, Golisano Children's Hospital, University of Rochester, Rochester, United States of America.
authors.forename: David
authors.initials: D
authors.lastname: Weber
authors.affiliation: Children's Hospital of Philadelphia, Philadelphia, United States of America.|Department of Pediatrics and Medicine, Stanford University, Stanford, United States of America.
authors.forename: Jin
authors.initials: J
authors.lastname: Long
authors.affiliation: Department of Pediatrics and Medicine, Stanford University, Stanford, United States of America.
authors.forename: Mary B
authors.initials: MB
authors.lastname: Leonard
authors.affiliation: Children's Hospital of Philadelphia, Philadelphia, United States of America.
authors.forename: Babette
authors.initials: B
authors.lastname: Zemel
authors.affiliation: Philadelphia Veterans Affairs Medical Center, Philadelphia, United States of America.|University of Pennsylvania, School of Medicine, Philadelphia, United States of America.|Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, United States of America.
authors.forename: Joshua F
authors.initials: JF
authors.lastname: Baker
mesh_terms: D050154:Adiposity; D000328:Adult; D001835:Body Weight; D005260:Female; D006801:Humans; D008297:Male; D055948:Sarcopenia / Q000175:diagnosis / Q000473:pathology / Q000503:physiopathology