Z score prediction model for assessment of bone mineral content in pediatric diseases

J Bone Miner Res. 2001 Sep;16(9):1658-64. doi: 10.1359/jbmr.2001.16.9.1658.


The objective of this study was to develop an anthropometry-based prediction model for the assessment of bone mineral content (BMC) in children. Dual-energy X-ray absorptiometry (DXA) was used to measure whole-body BMC in a heterogeneous cohort of 982 healthy children, aged 5-18 years, from three ethnic groups (407 European- American [EA], 285 black, and 290 Mexican-American [MA]). The best model was based on log transformations of BMC and height, adjusted for age, gender, and ethnicity. The mean +/- SD for the measured/predicted in ratio was 1.000 +/- 0.017 for the calibration population. The model was verified in a second independent group of 588 healthy children (measured/predicted In ratio = 1.000 +/- 0.018). For clinical use, the ratio values were converted to a standardized Z score scale. The whole-body BMC status of 106 children with various diseases (42 cystic fibrosis [CF], 29 juvenile dermatomyositis [JDM], 15 liver disease [LD], 6 Rett syndrome [RS], and 14 human immunodeficiency virus [HIV]) was evaluated. Thirty-nine patients had Z scores less than -1.5, which suggest low bone mineral mass. Furthermore, 22 of these patients had severe abnormalities as indicated by Z scores less than -2.5. These preliminary findings indicate that the prediction model should prove useful in determining potential bone mineral deficits in individual pediatric patients.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Absorptiometry, Photon / methods
  • Adolescent
  • Age Factors
  • Body Height
  • Bone Density
  • Bone and Bones / physiopathology*
  • Child
  • Child, Preschool
  • Cohort Studies
  • Cystic Fibrosis / physiopathology
  • Dermatomyositis / physiopathology
  • Female
  • HIV Infections / physiopathology
  • Humans
  • Linear Models*
  • Liver Diseases / physiopathology
  • Male
  • Models, Biological*
  • Pediatrics
  • Population Surveillance* / methods
  • Predictive Value of Tests
  • Rett Syndrome / physiopathology
  • Sex Factors