Initial independent variables were controlled trial decreased

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home, brother, balanced nutrition, healthy weight, giovannucci, a bomb, decreased, dex, enter the zone, vitamin e, bioelectric, slim guide, fitness equipment, extensive production, compatible, gestetner, The recommended equation predicts percentage fat with a root mean square error=3.2% fat and an adjusted r2=0.840. CONCLUSION: controlled trial The combination of anthropometry and BIA variables can be used to estimate total body fat in field studies of Native American children. The derived equation yields considerably higher percentage fat values than other skinfold equations in children.PMID: 10951536 [PubMed - indexed for MEDLINE]  Display  Summary Brief Abstract Citation MEDLINE XML UI List LinkOut controlled trial ASN.1 Related Articles Cited Articles Cited in Books CancerChrom Links Domain Links 3D Domain Links controlled trial GEO DataSet Links Gene Links Gene (GeneRIF) Links Genome Links Project Links GENSAT Links GEO Profile Links HomoloGene Links Nucleotide Links OMIA Links OMIM (calculated) Links OMIM (cited) Links BioAssay Links Compound Links Compound via MeSH Substance Links Substance via MeSH PMC Links Cited in PMC PopSet Links Probe Links Protein Links SNP Links Structure Links UniGene Links UniSTS Links  Show  5 10 20 50 100 200 500 Sort by Pub Date First Author Last Author Journal Send to Text File Printer Clipboard E-mail Order Write to the Help Desk NCBI | NLM
Initial independent variables were height, weight, waist circumference, six skinfolds and whole-body resistance and reactance from bioelectrical impedance (BIA). RESULTS: Using all-possible-subsets regressions with the Mallows C (p) criterion, and with age and sex included in each regression decreased model, waist circumference, calf and biceps skinfolds contributed least to the multiple regression decreased analysis. The combination of weight, two skinfolds (any two out of the four best: triceps, suprailiac, subscapular and abdomen) and bioelectrical impedance variables provided excellent predictability. Equations without BIA variables yielded r2 almost as high as those with BIA variables.
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