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Table 4 Analysis of the association between MetS and anthropometric indices and the predictive power for MetS in men and women aged 60–69 years

From: Identification of metabolic syndrome using phenotypes consisting of triglyceride levels with anthropometric indices in Korean adults

IndexM-60-69W-60-69
ORpAdj. ORAdj. pAUC-1AUC-2ORpAdj. ORAdj. pAUC-1AUC-2
Height1.18 (1.04–1.34).0131.17 (1.02–1.34).0290.5380.7881.03 (0.93–1.14).6081.1 (0.98–1.23).1010.4730.79
Weight2.4 (2.05–2.81)< .0012.71 (2.28–3.2)< .0010.7290.8261.67 (1.49–1.88)< .0011.79 (1.58–2.02)< .0010.6380.805
BMI2.58 (2.19–3.04)< .0012.95 (2.46–3.52)< .0010.740.8331.73 (1.54–1.94)< .0011.8 (1.6–2.04)< .0010.6480.808
ForeheadC1.599 (1.38–1.82)< .0011.65 (1.42–1.91)< .0010.6150.7981.24 (1.11–1.37)< .0011.22 (1.08–1.36)< .0010.5460.798
NeckC2.56 (2.17–3)< .0012.57 (2.16–3.06)< .0010.730.8271.97 (1.75–2.23)< .0011.87 (1.65–2.12)< .0010.6720.821
AxillaryC2.63 (2.23–3.1)< .0012.62 (2.2–3.11)< .0010.7410.8382.09 (1.85–2.36)< .0011.98 (1.74–2.25)< .0010.6920.824
ChestC2.84 (2.4–3.36)< .0012.87 (2.4–3.43)< .0010.7550.8452.17 (1.92–2.46)< .0012.06 (1.81–2.35)< .0010.7040.826
RibC3.34 (2.79–4)< .0013.38 (2.79–4.09)< .0010.7770.8522.18 (1.92–2.47)< .0012.05 (1.8–2.33)< .0010.7040.825
WaistC3.78 (3.11–4.59)< .0013.88 (3.17–4.76)< .0010.8050.8642.3 (2.02–2.61)< .0012.23 (1.96–2.55)< .0010.710.831
PelvicC2.28 (1.95–2.65)< .0012.43 (2.06–2.86)< .0010.7130.8191.84 (1.63–2.07)< .0011.81 (1.6–2.05)< .0010.6640.816
HipC2.21 (1.9–2.58)< .0012.25 (1.92–2.65)< .0010.7110.8211.58 (1.41–1.77)< .0011.55 (1.38–1.75)< .0010.6220.809
Waist_Hip2.81 (2.37–3.34)< .0012.97 (2.48–3.57)< .0010.7440.8322.09 (1.85–2.36)< .0012.09 (1.83–2.38)< .0010.6860.82
Waist_Pelvic2.51 (2.14–2.95)< .0012.44 (2.06–2.9)< .0010.7290.8261.79 (1.59–2.01)< .0011.73 (1.53–1.96)< .0010.6510.811
Forehead_Waist0.27 (0.22–0.33)< .0010.27 (0.21–0.33)< .0010.7790.8490.45 (0.39–0.51)< .0010.45 (0.39–0.51)< .0010.6950.827
Forehead_Rib0.35 (0.29–0.42)< .0010.35 (0.29–0.42)< .0010.7410.8310.48 (0.42–0.54)< .0010.5 (0.44–0.57)< .0010.6890.821
Forehead_Chest0.42 (0.36–0.5)< .0010.43 (0.36–0.51)< .0010.710.8230.48 (0.43–0.55)< .0010.5 (0.44–0.57)< .0010.6860.821
WHtR3.5 (2.9–4.22)< .0013.7 (3.03–4.53)< .0010.7890.8592.17 (1.92–2.46)< .0012.13 (1.87–2.43)< .0010.6990.829
TG2.98 (2.49–3.55)< .0013.05 (2.53–3.66)< .0010.7885.71 (4.58–7.13)< .0016.08 (4.81–7.68)< .0010.792
HW phenotype0.02 (0.01–0.04)< .0010.02 (0.01–0.04)< .0010.11 (0.09–0.15)< .0010.11 (0.08–0.14)< .001
  1. The results were obtained by binary logistic regression. M-60-69 men aged 60–69 years, W-60-69 women aged 60–69 years, Adj. p and OR adjustment for age, region, and education, OR odds ratio, AUC-1 AUC value of each index used to identify MetS, AUC-2 AUC value of phenotypes combining TG + one anthropometric index to identify MetS