Abstract
Introduction: The correct interpretation of DXA data is critical to the diagnosis and management of children with suspected bone disease. This study examines the various influences on bone mineral content (BMC), as measured by dual-energy X-ray absorptiometry (DXA). Materials and methods: Six hundred and forty-six healthy school children and forty-three children with chronic diseases, aged 5–18 years, had their lumbar spine and whole body measured using a Lunar DPX-L DXA scanner. Results: Stepwise linear regression identified lean body mass (LBM) as the strongest single predictor of BMC in the lumbar spine and the total body. A significant gender difference was observed in the relationship between BMC and LBM with girls having significantly more bone per unit LBM from 9 years of age in the spine and 13 years of age in the total body. To investigate the relationship between LBM and BMC in children with chronic disease, a two-stage algorithm based upon calculation of Z scores from the normative data was applied. Stage 1 assessed LBM for height and stage 2 assessed BMC for LBM. Ten children with spinal muscular atrophy had a mean LBM for height Z score of −1.8(1.4) but a mean BMC for LBM Z score of 1.2(1.3) indicating their primary abnormality was reduced muscle mass (sarcopenia) with no evidence of osteopenia. In contrast, 21 children with osteogenesis imperfecta had a mean LBM for height Z score of 0.4(1.7) but a mean BMC for LBM Z score of −2.5(1.8) indicating normal LBM for size but significantly reduced BMC for LBM (i.e. osteopenia) confirming a primary bone abnormality. A third group consisting of 12 children with low trauma fractures demonstrated little evidence of sarcopenia [mean LBM for height Z score −1.1(2.1)] but significant osteopenia [mean BMC for LBM Z score −1.9(1.5)]. Conclusion: The results from this study demonstrate how the relationship between height and lean body mass, and lean body mass and bone mineral content can be a useful method of diagnosing osteoporosis in children and how the relationships can be used to identify if the primary abnormality is in muscle or bone.
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