Z Score Prediction Model for Assessment of Bone Mineral Content in Pediatric Diseases*

Authors

  • Kenneth J. Ellis,

    Corresponding author
    1. U.S. Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
    • Address reprint requests to: Kenneth J. Ellis, Ph.D., Body Composition Laboratory, U.S. Department of Agriculture/Agricultural Research, Service Children's Nutrition Research Center, 1100 Bates Street, Houston, TX 77030–2600, USA
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  • Roman J. Shypailo,

    1. U.S. Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
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  • Dana S. Hardin,

    1. Department of Pediatrics, University of Texas Health Science Center, Houston, Texas, USA
    2. Texas Children's Hospital, Houston, Texas, USA
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  • Maria D. Perez,

    1. U.S. Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
    2. Texas Children's Hospital, Houston, Texas, USA
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  • Kathleen J. Motil,

    1. U.S. Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
    2. Texas Children's Hospital, Houston, Texas, USA
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  • William W. Wong,

    1. U.S. Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
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  • Steven A. Abrams

    1. U.S. Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
    2. Texas Children's Hospital, Houston, Texas, USA
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  • *

    This work is a publication of the USDA/ARS Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, and Texas Children's Hospital, Houston, TX. The contents of this publication do not necessarily reflect the views or policies of the USDA, nor does mention of trade names, commercial products, or organizations imply endorsement

Abstract

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 ln 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 ln 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.

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