title: Dual energy X-ray absorptiometry spine scans to determine abdominal fat in postmenopausal women.
abstract: Body composition may be a better predictor of chronic disease risk than body mass index (BMI) in older populations.
  
  
  
  We sought to validate spine fat fraction (%) from dual energy X-ray absorptiometry (DXA) spine scans as a proxy for total abdominal fat.
  
  
  
  Total body DXA scan abdominal fat regions of interest (ROI) that have been previously validated by magnetic resonance imaging were assessed among healthy, postmenopausal women who also had antero-posterior spine scans (n = 103). ROIs were (1) lumbar vertebrae L2-L4 and (2) L2-Iliac Crest (L2-IC), manually selected by two independent raters, and (3) trunk, auto-selected by DXA software. Intra-class correlation coefficients evaluated intra and inter-rater reliability on a random subset (N = 25). Linear regression models, validated by bootstrapping, assessed the relationship between spine fat fraction (%) and total abdominal fat (%) ROIs.
  
  
  
  Mean age, BMI, and total body fat were 66.1 ± 4.8 y, 25.8 ± 3.8 kg/m2and 40.0 ± 6.6%, respectively. There were no significant differences within or between raters. Linear regression models adjusted for several participant and scan characteristics were equivalent to using only BMI and spine fat fraction. The model predicted L2-L4 (Adj. R2: 0.83) and L2-IC (Adj. R2: 0.84) abdominal fat (%) well; the adjusted R2for trunk fat (%) was 0.78. Model validation demonstrated minimal over-fitting (Adj. R2: 0.82, 0.83, and 0.77 for L2-L4, L2-IC, and trunk fat, respectively).
  
  
  
  The strong correlation between spine fat fraction and DXA abdominal fat measures make it suitable for further development in postmenopausal chronic disease risk prediction models. Am. J. Hum. Biol. 28:918-926, 2016. © 2016Wiley Periodicals, Inc.
authors.affiliation: Department of Medicine, University of Arizona Cancer Center, Tucson, Arizona, 85724-5024.|Department of Nutritional Sciences, University of Arizona, Tucson, Arizona, 85721.
authors.forename: J W
authors.initials: JW
authors.lastname: Bea
authors.affiliation: Department of Nutritional Sciences, University of Arizona, Tucson, Arizona, 85721.
authors.forename: R M
authors.initials: RM
authors.lastname: Blew
authors.affiliation: Department of Nutritional Sciences, University of Arizona, Tucson, Arizona, 85721.
authors.forename: S B
authors.initials: SB
authors.lastname: Going
authors.affiliation: University of Arizona Mel and Enid Zuckerman College of Public Health, Tucson, Arizona, 85724.
authors.forename: C-H
authors.initials: CH
authors.lastname: Hsu
authors.affiliation: Department of Nutritional Sciences, University of Arizona, Tucson, Arizona, 85721.
authors.forename: M C
authors.initials: MC
authors.lastname: Lee
authors.affiliation: Department of Nutritional Sciences, University of Arizona, Tucson, Arizona, 85721.
authors.forename: V R
authors.initials: VR
authors.lastname: Lee
authors.affiliation: Division of Research, Kaiser Permanente Northern California, Oakland, California, 94612.
authors.forename: B J
authors.initials: BJ
authors.lastname: Caan
authors.affiliation: Division of Research, Kaiser Permanente Northern California, Oakland, California, 94612.
authors.forename: M L
authors.initials: ML
authors.lastname: Kwan
authors.affiliation: Department of Physiology, University of Arizona, Tucson, Arizona, 85721.
authors.forename: T G
authors.initials: TG
authors.lastname: Lohman
mesh_terms: D050153:Abdominal Fat / Q000000981:diagnostic imaging*; D015502:Absorptiometry, Photon / Q000379:methods*; D000368:Aged; D001130:Arizona; D015992:Body Mass Index; D005260:Female; D006801:Humans; D008875:Middle Aged; D017698:Postmenopause; D015203:Reproducibility of Results
keywords: adiposity; body composition; body mass index; obesity; risk prediction