BODY COMPOSITION ASSESSMENT IN SPINAL CORD INJURY

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The Hypothesis of this protocol: Regression equations compared to the gold standard 4-Compartment Modeling using Dual-energy X-Ray Absorptiometry (DXA), Bioelectrical Impedance Analysis (BIA), and anthropometric measures can provide relatively quick and inexpensive measures of obesity in SCI which will be highly correlated with the secondary conditions listed below. Percent Body Fat will be highly correlated with visceral fat in persons with SCI, and both measures will be highly correlated with mediators of lipogenic atherosclerosis Specific Aims include: The specific objectives for the current proposal are to compare several measures of body composition assessment with the gold standard (4-Compartment Modeling) and to develop regression equations that can be utilized in the clinical setting to estimate risk for metabolic syndrome and atherosclerosis. Specific objectives to be addressed in the current proposal are: To compare different methods of body composition analyses with the gold standard 4-compartment monitoring to determine accuracy and validity of those alternative, but less labor-intensive techniques. To assess the relationship between per cent body fat, visceral fat, and markers of the metabolic syndrome, including fasting glucose, insulin sensitivity, hypertension, dyslipidemia, Plasminogen Activator Inhibitor-1 (PAI-1), Thrombin- Activatable Fibrinolysis Inhibitor (TAFI), and high-sensitivity C-Reactive Protein (hsCRP) To develop body composition regression equations that can be easily utilized in a clinical setting to estimate risk for the metabolic syndrome in persons with SCI. To cross-validate the derived regression equations against the gold standard 4-compartment model in an independent group of persons with SCI.