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Copyright ©The Author(s) 2018.
World J Hepatol. Oct 27, 2018; 10(10): 695-701
Published online Oct 27, 2018. doi: 10.4254/wjh.v10.i10.695
Table 1 Studies evaluating the anthropometric indicators as predictors of non-alcoholic fatty liver disease
Ref.CountryPopulation (n)Age (yr)Anthropometric indicatorNAFLD diagnosis
Yoo et al[14]South KoreaNAFLD (77)20-88WC and WHtRTomography
Non-NAFLD (379)
Zheng et al[9]ChinaNAFLD (250)36.6 ± 11.1WHR, BMI, WC and WHtRLiver biopsy
Non-NAFLD (240)37.3 ± 10.2
Ju et al[10]South KoreaNAFLD (2553)42.5 ± 5.1BMI and WCUltrasonography
Non-NAFLD (6606)41.6 ± 4.9
Cuthbertson et al[8]England and GermanyNAFLD (168)50.3 ± 11.9LAPProton magnetic resonance spectroscopy
Non-NAFLD (168)48.6 ± 10.9
Monteiro et al[16]BrazilObese with NAFLD (45)11-17WCUltrasonography
Obese without NAFLD (100)
Zhang et al[17]ChinaNAFLD (362)7-18WHtR, BMI and WCUltrasonography
Non-NAFLD (6867)
Motamed et al[11]IranNAFLD (2048)48.6 ± 12.7WHtR, WHR, ABSI, BRIUltrasonography
Non-NAFLD (2824)39.0 ± 15.4
Özhan et al[18]TurkeyObese without NAFLD (130)11.6 ± 2.7WHtRUltrasonography
Obese with NAFLD (202)12.1 ± 2.6
Lin et al[19]TaiwanNAFLD (167)18.8 ± 1.9WHtR, WHRUltrasonography
Non-NAFLD (1043)15.1 ± 2.8
Lee et al[15]United StatesBlack (94) and White (58)14.7 ± 1.8WCProton magnetic resonance spectroscopy
overweight and obese adolescents14.5 ± 1.5
Dai et al[20]ChinaNAFLD (12150)18-94LAPUltrasonography
Non-NAFLD (28309)
Table 2 Cut-offs and areas under the ROC curve, sensitivity and specificity of anthropometric indicators to determine non-alcoholic fatty liver disease
Ref.IndicatorTotal
Women
Men
AUC (95%CI)Cut-offs pointSens (%)Spec (%)AUC (95%CI)Cut-offs pointSens (%)Spec (%)AUC (95%CI)Cut-offs pointSens (%)Spec (%)
Yoo et al[14]WHtR0.80 (0.74-0.86)0.5390630.72 (0.63-0.81)0.527165
WC0.79 (0.73-0.86)8484620.74 (0.65-0.83)897564
Zheng et al[9]WHR0.916 (0.86-0.97)0.899966
BMI0.854 (0.78-0.93)24.229664
WC0.876 (0.81-0.94)82.59568
WHtR0.878 (0.82-0.94)0.499664
Ju et al[10]WC0.821 (0.801-0.840)80.3950.759 (0.746-0.773)84.945
BMI0.83 (0.811-0.850)22.7150.76 (0.747-0.773)24.465
Cuthbertson et al[8]LAP0.78 (0.73-0.83)0.77 (0.69-0.85)0.74 (0.66-0.82)
Monteiro et al[16]WC0.72 (0.636-0.804)66.7640.7330.7040.5670.6
Zhang et al[17]WHtR0.95 (0.94-0.96)0.4785.292.5
WC0.94 (0.92-0.95)80186.287.4
BMI0.93 (0.91-0.94)80186.287.6
Motamed et al[11]WHtR0.8566 (0.8419-0.8714)0.5883.371.70.8457 (0.8320-0.8593)0.53382.770.8
BRI0.8566 (0.8419-0.8714)583.371.70.8457 (0.8320-0.8593)482.770.8
WHR0.7673 (0.7487-0.7860)0.8018 (0.7862-0.8173)
ABSI0.6598 (0.6382-0.6814)0.6539 (0.6351-0.6727)
Özhan et al[18]WHtR0.6248.473.8
Lin et al[19]WHtR0.80 (0.76-0.83)0.46970.176.9
WHR0.755 (0.714-0.795)
1Lee et al[15]WC0.847101.59380
Dai et al[20]LAP0.887 (0.882-0.892)2382790.843 (0.837-0.849)30.57775