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Is body mass index a useful measure of excess body fatness in adolescents and young adults with Down syndrome?

Authors

  • L. G. Bandini,

    Corresponding author
    1. Eunice Kennedy Shriver Center, University of Massachusetts Medical School, Waltham, MA, USA
    2. Department of Health Sciences, Boston University, Boston, MA, USA
      Dr Linda Bandini, Eunice Kennedy Shriver Center, University of Massachusetts Medical School, 200 Trapelo Road, Waltham, MA 02452, USA (e-mail: linda.bandini@umassmed.edu).
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  • R. K. Fleming,

    1. Eunice Kennedy Shriver Center, University of Massachusetts Medical School, Waltham, MA, USA
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  • R. Scampini,

    1. Eunice Kennedy Shriver Center, University of Massachusetts Medical School, Waltham, MA, USA
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  • J. Gleason,

    1. Eunice Kennedy Shriver Center, University of Massachusetts Medical School, Waltham, MA, USA
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  • A. Must

    1. Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, USA
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Dr Linda Bandini, Eunice Kennedy Shriver Center, University of Massachusetts Medical School, 200 Trapelo Road, Waltham, MA 02452, USA (e-mail: linda.bandini@umassmed.edu).

Abstract

Background  To determine the validity of body mass index (BMI) to identify excess fatness in youth with Down syndrome (DS).

Methods  Using the Centers for Disease Control and Prevention (CDC) growth reference, we defined overweight (≥85th percentile) and obesity (≥95th percentile) based on participants' age- and sex-specific BMI z-scores, calculated from measured height and weight. Percentage body fat was measured by dual-energy X-ray absorptiometry. We determined sensitivity, specificity, positive predictive value, negative predictive value and efficiency of BMI percentiles to identify excess adiposity relative to elevated percentage body fat cut-offs developed from the Pediatric Rosetta Body Composition project in 32 youth (20 boys/12 girls), ages 13–21 years with Down syndrome.

Results  For adolescents with Down syndrome using the cut-off points of 95th percentile for BMI (obesity), sensitivity and specificity were 71% and 96% respectively. Positive predictive value was 83% and negative predictive value was 92%. Overall efficiency was 91%. Sensitivity and specificity for BMI cut-offs above the 85th percentile (overweight) were 100% and 60% respectively. The positive predictive value was 41% and negative predictive value was 100%. Overall efficiency was 69%.

Conclusion  On the whole, the obesity (≥95th percentile) cut-off performs better than the overweight cut-off (85th–94th percentile) in identifying elevated fatness in youth with DS.

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