Table 4 Potential candidate predictors of subclinical atherosclerosis in males (n = 55) assessed using univariable logistic regression.

From: Gender differences in fasting and postprandial metabolic traits predictive of subclinical atherosclerosis in an asymptomatic Chinese population

Category

Variables

Univariate logistic regression

Multivariable logistic regression

OR (95% CI)

P value

OR (95% CI)

P value

Inflammatory

Diff TNFα Conc. t60–t120 min

0.629 (0.385, 1.026)

0.0635

  

Diff TNFα Conc. t60–t240 min

0.622 (0.366, 1.058)

0.0800

0.511 (0.268, 0.975)

0.0418

TNFα iAUC t0–t240 min

0.997 (0.993, 1.000)

0.0700

TNFα iAUC t0–t360 min

0.998 (0.996, 1.000)

0.0619

Diff TNFα Conc. from fasting to Cmax

0.658 (0.407, 1.065)

0.0883

Insulin sensitivity

Diff Insulin Conc. t0–t45 min

0.987 (0.972, 1.002)

0.0913

Diff Insulin Conc. t30–t45 min

0.981 (0.96, 1.003)

0.0910

0.969 (0.943, 0.996)

0.0232

ln Adiponectin Conc. t120 min

0.242 (0.054, 1.079)

0.0628

ln Adiponectin Conc. t360 min

0.255 (0.055, 1.178)

0.0802

Total cholesterol

Diff Cholesterol Conc. t0–t60 min

0.020 (< 0.001, 0.676)

0.0294

Diff Cholesterol Conc. t0–t360 min

0.077 (0.004, 1.600)

0.0976

Cholesterol iAUC t0–t60 min

0.807 (0.684, 0.953)

0.0115

Cholesterol iAUC t0–t120 min

0.908 (0.842, 0.979)

0.0115

0.884 (0.805, 0.970)

0.0091

Cholesterol iAUC t0–t240 min

0.943 (0.898, 0.989)

0.0162

Cholesterol iAUC t0–t360 min

0.966 (0.940, 0.993)

0.0143

Diff Cholesterol Conc. from fasting to Cmax

0.008 (< 0.001, 0.427)

0.0172

Demographic characteristics

Age

1.167 (1.010, 1.350)

0.0368

Framingham Score

1.317 (1.041, 1.666)

0.0217

1.477 (1.088, 2.006)

0.0124

  1. Odds ratios are expressed per standard deviation increase in each continuous risk factor. Highlighted variables are independent risk predictors of subclinical atherosclerosis admitted by stepwise selection into the multivariable logistic regression models. OR, Odds ratio; CI, Confidence interval; TNFa, Tumor necrosis factor alpha; iAUC, incremental area under curve; Cmax, Peak concentration; Other demographic characteristics such as BMI, Diastolic blood pressure, Systolic blood pressure, waist circumference, weight, fasting glucose, fasting LDL-C, fasting HDL-C, fasting Triglyceride, fasting total cholesterol, age and Framingham score were also examined. Variables not listed in table have p > 0.10 in the univariate logistic regression models.
  2. Significant values are in bold.
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