9 research outputs found
Association between body fat composition measures and anthropometry by sex in MESA.
<p>Regression equation for body fat composition by anthropometry and sex: Ln body fat composition = β0<sub>1</sub> + β0<sub>2</sub>(sex) + β1(X) + β2(X<sup>2</sup>) + β3(sex*X). Intercept = β0<sub>1</sub> + β0<sub>2</sub>, Linear = β1 <b>+</b> β3, Quadratic = β2, P-value for difference by sex = p-value for β3. Centering: height—160cm, weight—50kg, BMI—20 kg/m<sup>2</sup>, waist—100cm, hip—100cm, waist to hip—0.7, waist to height—0.4.</p><p>Association between body fat composition measures and anthropometry by sex in MESA.</p
Lowess of Visceral Fat and Subcutaneous Fat by Sex in 1851 Adults in the MESA Body Composition ancillary Study.
<p>Lowess of Visceral Fat and Subcutaneous Fat by Sex in 1851 Adults in the MESA Body Composition ancillary Study.</p
Characteristics (Mean (SD) or Percentile) of 1851 Adults<sup>a</sup> Aged 45–84 in the MESA Body Composition Ancillary Study by Body Composition Quartile<sup>b</sup>.
<p>a. Participants on Thiazolidinediones and observations with Cook's Distance >0.025 excluded.</p><p>b. Quartile cutoffs are equivalent to 97.7, 138.2, 193.6 cm<sup>2</sup> visceral fat170.7, 235.1, 311.1 cm<sup>2</sup> subcutaneous fat on the original scale</p><p>c. Diabetes diagnosed as ≥126 mg/dl fasting glucose</p><p>Characteristics (Mean (SD) or Percentile) of 1851 Adults<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0139559#t001fn001" target="_blank"><sup>a</sup></a> Aged 45–84 in the MESA Body Composition Ancillary Study by Body Composition Quartile<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0139559#t001fn002" target="_blank"><sup>b</sup></a>.</p
Association Between Body Fat Composition Measures and Anthropometry by Race/Ethnicity in MESA.
<p>Regression equation for body fat composition by anthropometry and race/ethnicity: Ln body fat composition = β0<sub>1</sub> + β0<sub>2</sub>(race) + β1(X) + β2(X<sup>2</sup>) + β3(race*X). Intercept = β0<sub>1</sub> + β0<sub>2</sub>, Linear = β1 <b>+</b> β3, Quadratic = β2, P-value for difference by race = <i>P</i>-value for overall F-test. Centering: height—160cm, weight—50kg, BMI—20 kg/m<sup>2</sup>, waist—100cm, hip—100cm, waist to hip—0.7, waist to height—0.4.</p><p>Association Between Body Fat Composition Measures and Anthropometry by Race/Ethnicity in MESA.</p
SNPs representing loci associated with circulating SHBG concentrations.
<p>All SNPs are on the+strand and positions are based on build 36. EAF = ‘effect allele frequency’. Beta units are per-allele effect estimates in natural log transformed nmol/L. Sex column gives the sex with the largest per-allele beta estimate. Missing values for conditional SNPs as sex-specific conditional analysis was not performed.</p
Allelic heterogeneity at the <i>SHBG</i> gene locus.
<p>There was significant allelic heterogeneity at the SHBG gene locus. The nine independent signals identified in the SHBG gene are shown in relation to their position within the gene. All positions based on build 36. Not all genes are shown.</p
Statistically independent signals at the <i>SHBG</i> gene locus.
<p>All SNPs are on the+strand and positions are based on build 36. EAF = ‘effect allele frequency’. Beta units are per-allele effect estimates in natural log transformed nmol/L. ‘Full model’ SNPs were all included in a single regression model, where the effect estimates for each SNP are adjusted for the effect of the others in the model.</p><p>‘Conditional’ SNPs are SNPs with low pair-wise LD (HapMap r<sup>2</sup><0.01) that were identified after conditioning on the full model SNPs.</p
Manhattan plot of the autosomal SNPs identified in the GWA meta-analysis.
<p>The Manhattan plot depicts the SNPs identified in the GWAS analysis labeled with the nearest gene on the plot. The SNP identified on the X chromosome, rs1573036, at Xq22.3, is not included in this figure.</p