title: Abdominal circumference is superior to body mass index in estimating musculoskeletal injury risk.
abstract: OBJECTIVE
  The purpose of this study was to compare body mass index (BMI) and abdominal circumference (AC) in discriminating individual musculoskeletal injury risk within a large population. We also sought to determine whether age or sex modulates the interaction between body habitus and injury risk.
  
  
  METHODS
  We conducted a retrospective cohort study involving 67,904 US Air Force personnel from 2005 to 2011. Subjects were stratified by age, sex, BMI, adjusted BMI, and AC. New musculoskeletal injuries were recorded relative to body habitus and time elapsed from the start of study.
  
  
  RESULTS
  Cox proportional hazards regression revealed increased HR for musculoskeletal injury in those with high-risk AC (males, >39 inches; females, >36 inches) compared with HR in those with low-risk AC (males, ≤35 inches; females, ≤32 inches) in all age categories (18-24 yr: HR = 1.567, 95% confidence interval (CI) = 1.327-1.849; 25-34 yr: HR = 2.089, 95% CI = 1.968-2.218; ≥35 yr: HR = 1.785, 95% CI = 1.651-1.929). HR for obese (BMI, ≥30 kg·m) compared with that for normal individuals (BMI, <25 kg·m) were less elevated. Kaplan-Meier curves showed a dose-response relation in all age groups but most prominently in 25- to 34-yr-old participants. Time to injury was consistently lowest in 18- to 24-yr-old participants. Score chi-square values, indicating comparative strength of each model for injury risk estimation in our cohort, were higher for AC than those for BMI or adjusted BMI within all age groups.
  
  
  CONCLUSIONS
  AC is a better predictor of musculoskeletal injury risk than BMI in a large military population. Although absolute injury risk is greatest in 18- to 24-yr-old participants, the effect of obesity on injury risk is greatest in 25- to 34-yr-old participants. There is a dose-response relation between obesity and musculoskeletal injury risk, an effect seen with both BMI and AC.
authors.affiliation: 1Sports Medicine Fellowship, National Capital Consortium, Uniformed Services University of the Health Sciences, Bethesda, MD; 2Air Force Medical Support Agency, Healthcare Informatics Division, San Antonio, TX; and 3Nellis Family Medicine Residency, Nellis Air Force Base, Las Vegas, NV.
authors.forename: Nathaniel S
authors.initials: NS
authors.lastname: Nye
authors.forename: David H
authors.initials: DH
authors.lastname: Carnahan
authors.forename: Jonathan C
authors.initials: JC
authors.lastname: Jackson
authors.forename: Carlton J
authors.initials: CJ
authors.lastname: Covey
authors.forename: Lee A
authors.initials: LA
authors.lastname: Zarzabal
authors.forename: Susan Y
authors.initials: SY
authors.lastname: Chao
authors.forename: Archie D
authors.initials: AD
authors.lastname: Bockhorst
authors.forename: Paul F
authors.initials: PF
authors.lastname: Crawford
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D015992:Body Mass Index; D005260:Female; D006801:Humans; D008297:Male; D008889:Military Personnel; D009141:Musculoskeletal System / Q000293:injuries*; D056128:Obesity, Abdominal / Q000150:complications*; D012189:Retrospective Studies; D018570:Risk Assessment; D012737:Sex Factors; D013997:Time Factors; D055105:Waist Circumference; D055815:Young Adult