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©The Author(s) 2022.
World J Gastroenterol. Sep 28, 2022; 28(36): 5364-5379
Published online Sep 28, 2022. doi: 10.3748/wjg.v28.i36.5364
Published online Sep 28, 2022. doi: 10.3748/wjg.v28.i36.5364
Table 1 Baseline characteristics of the study subjects
Variable | Non-MAFLD, n = 352 | MAFLD, n = 512 | Statistics1 | P value |
Demographics | ||||
Sex | χ2 = 14.020 | < 0.001 | ||
Male | 230 (65.3) | 394 (77.0) | ||
Female | 122 (34.7) | 118 (23.0) | ||
Age in yr | 37.750 ± 10.736 | 41.240 ± 10.852 | t = -4.634 | < 0.001 |
Age ≥ 40 yr | 115 (32.7) | 254 (49.6) | χ2 = 24.461 | < 0.001 |
Age < 40 yr | 237 (67.3) | 258 (40.4) | ||
Smoking history | 81 (23.0) | 174 (34.0) | χ2= 12.073 | < 0.001 |
Drinking history | 76 (21.6) | 145 (28.3) | χ2= 4.962 | 0.027 |
Anthropometrics | ||||
WC in cm | 86.240 ± 9.893 | 96.790 ± 8.618 | t = -16.219 | < 0.001 |
BMI in kg/m2 | 24.436 ± 3.169 | 28.028 ± 3.221 | t = -16.228 | < 0.001 |
SBP in mmHg | 125.880 ± 14.883 | 133.610 ± 16.859 | t = -6.908 | < 0.001 |
DBP in mmHg | 77.500 ± 11.658 | 82.950 ± 12.525 | t = -6.461 | < 0.001 |
Laboratory tests | ||||
ALT in U/L | 21.0 (15.0, 30.0) | 34.0 (24.0, 54.0) | Z = -12.276 | < 0.001 |
AST in U/L | 19.0 (17.0, 23.0) | 23.0 (19.0, 29.0) | Z = -9.058 | < 0.001 |
TC in mmol/L | 4.539 ± 0.847 | 4.783 ± 0.902 | t = -4.104 | < 0.001 |
TG in mmol/L | 1.1 (0.7, 1.5) | 1.8 (1.3, 2.6) | Z = -13.650 | < 0.001 |
HDL-C in mmol/L | 1.351 ± 0.283 | 1.191 ± 0.256 | t = 8.321 | < 0.001 |
LDL-C in mmol/L | 2.645 ± 0.708 | 2.906 ± 0.884 | t = -4.568 | < 0.001 |
FBG in mmol/L | 5.2 (4.9, 5.4) | 5.4 (5.1, 5.9) | Z = -7.637 | < 0.001 |
SUA in μmol/L | 332.722 ± 86.289 | 377.836 ± 85.859 | t = -7.590 | < 0.001 |
AIP | -0.11 (-0.30, 0.08) | 0.20 (0.03, 0.39) | Z = -14.006 | < 0.001 |
Table 2 Multivariate logistic regression of atherogenic index of plasma for the risk of metabolic-associated fatty liver disease
Variable | β | SE | Wald χ2 | P value | OR (95%CI) | |
Model 1 | AIP level (per change in SD) | 3.918 | 0.318 | 151.599 | < 0.001 | 50.286 (26.953-93.819) |
Quartiles of AIP | ||||||
A1 (≤ -0.1265) | - | - | - | - | 1 (Ref) | |
A2 (-0.1265-0.0947) | 1.241 | 0.209 | 35.108 | < 0.001 | 3.460 (2.295-5.217) | |
A3 (0.0947-0.3023) | 2.323 | 0.226 | 105.794 | < 0.001 | 10.204 (6.554-15.885) | |
A4 (> 0.3022) | 2.826 | 0.245 | 132.611 | < 0.001 | 16.882 (10.436-27.311) | |
Model 2 | AIP level (per change in SD) | 3.889 | 0.32 | 147.414 | < 0.001 | 48.874 (26.087-91.569) |
Quartiles of AIP | ||||||
A1 (≤ -0.1265) | - | - | - | - | 1 (Ref) | |
A2 (-0.1265-0.0947) | 0.847 | 0.241 | 12.347 | < 0.001 | 3.218 (2.124-4.876) | |
A3 (0.0947-0.3023) | 1.690 | 0.260 | 42.107 | < 0.001 | 9.774 (6.256-15.270) | |
A4 (> 0.3022) | 2.103 | 0.281 | 55.913 | < 0.001 | 16.514 (10.176-26.799) | |
Model 3 | AIP level (per change in SD) | 2.784 | 0.362 | 59.147 | < 0.001 | 16.184 (7.961-32.902) |
Quartiles of AIP | ||||||
A1 (≤ -0.1265) | - | - | - | - | 1 (Ref) | |
A2 (-0.1265-0.0947) | 0.847 | 0.241 | 12.347 | < 0.001 | 2.334 (1.455-3.744) | |
A3 (0.0947-0.3023) | 1.690 | 0.260 | 42.107 | < 0.001 | 5.421 (3.253-9.032) | |
A4 (> 0.3022) | 2.103 | 0.281 | 55.913 | < 0.001 | 8.194 (4.721-14.22) | |
Model 4 | AIP level (per change in SD) | 2.519 | 0.371 | 46.230 | < 0.001 | 12.420 (6.008-25.675) |
Quartiles of AIP | ||||||
A1 (≤ -0.1265) | - | - | - | - | 1 (Ref) | |
A2 (-0.1265-0.0947) | 0.828 | 0.249 | 11.088 | 0.001 | 2.288 (1.4063-725) | |
A3 (0.0947-0.3023) | 1.642 | 0.268 | 37.636 | < 0.001 | 5.167 (3.058-8.732) | |
A4 (> 0.3022) | 1.969 | 0.289 | 46.343 | < 0.001 | 7.160 (4.062-12.62) |
Table 3 Results analysis of the receiver operating characteristic curves
Variable | AUC (95%CI) | P value | Sensitivity (%) | Specificity (%) | Youden index | Cutoff value |
Total | ||||||
AIP | 0.780 (0.751-0.807) | < 0.0001 | 75.20 | 69.89 | 0.4508 | 0.0340 |
WC in cm | 0.790 (0.761-0.817) | < 0.0001 | 85.94 | 58.52 | 0.4446 | 88.00 |
BMI in kg/m2 | 0.788 (0.759-0.814) | < 0.0001 | 83.20 | 59.09 | 0.4229 | 25.10 |
A-W-B | 0.833 (0.807-0.858)1,2,3 | < 0.0001 | 86.13 | 68.47 | 0.5460 | 0.5019 |
Male | ||||||
AIP | 0.755 (0.719-0.788) | < 0.0001 | 75.89 | 64.78 | 0.4067 | 0.0821 |
WC in cm | 0.770 (0.735-0.803) | < 0.0001 | 72.59 | 67.39 | 0.3998 | 92.50 |
BMI in kg/m2 | 0.773 (0.738-0.805) | < 0.0001 | 72.34 | 68.70 | 0.4103 | 26.32 |
A-W-B | 0.814 (0.781-0.843)1,2,3 | < 0.0001 | 82.99 | 65.65 | 0.4865 | 0.5932 |
Female | ||||||
AIP | 0.819 (0.764-0.865) | < 0.0001 | 82.2 | 70.49 | 0.5270 | -0.1390 |
WC in cm | 0.820 (0.765-0.866) | < 0.0001 | 81.36 | 69.67 | 0.5103 | 85.50 |
BMI in kg/m2 | 0.804 (0.748-0.852) | < 0.0001 | 88.98 | 58.20 | 0.4718 | 23.34 |
A-W-B | 0.874 (0.826-0.914)1,2,3 | < 0.0001 | 78.81 | 83.61 | 0.6242 | 0.4105 |
Age ≥ 40 yr | ||||||
AIP | 0.726 (0.678-0.771) | < 0.0001 | 71.26 | 66.96 | 0.3822 | 0.0367 |
WC in cm | 0.736 (0.688-0.780) | < 0.0001 | 82.68 | 52.17 | 0.3485 | 88.00 |
BMI in kg/m2 | 0.736 (0.688-0.780) | < 0.0001 | 71.26 | 66.96 | 0.3822 | 26.03 |
A-W-B | 0.787 (0.742-0.828)1,2,3 | < 0.0001 | 77.56 | 69.57 | 0.4712 | 0.5574 |
Age < 40 yr | ||||||
AIP | 0.816 (0.779-0.849) | < 0.0001 | 73.64 | 77.22 | 0.5086 | 0.0814 |
WC in cm | 0.824 (0.787-0.856) | < 0.0001 | 89.15 | 61.60 | 0.5075 | 88.00 |
BMI in kg/m2 | 0.820 (0.783-0.853) | < 0.0001 | 83.72 | 66.24 | 0.4997 | 25.31 |
A-W-B | 0.863 (0.830-0.892)1,2,3 | < 0.0001 | 89.92 | 71.73 | 0.6165 | 0.4947 |
BMI ≥ 28 kg/m2 | ||||||
AIP | 0.579 (0.519-0.638) | 0.0849 | 25.63 | 90.91 | 0.1654 | 0.4140 |
WC in cm | 0.597 (0.688-0.780) | 0.0303 | 36.97 | 79.55 | 0.1652 | 104.50 |
BMI in kg/m2 | 0.648 (0.589-0.704) | 0.0005 | 65.13 | 68.18 | 0.3331 | 29.38 |
A-W-B | 0.644 (0.585-0.700)1 | 0.0007 | 43.28 | 84.09 | 0.2737 | 0.9009 |
BMI < 28 kg/m2 | ||||||
AIP | 0.783 (0.747-0.816)3 | < 0.0001 | 69.71 | 76.30 | 0.4601 | 0.0340 |
WC in cm | 0.754 (0.717-0.789) | < 0.0001 | 78.1 | 63.31 | 0.4141 | 87.50 |
BMI in kg/m2 | 0.733 (0.695-0.768) | < 0.0001 | 77.37 | 59.42 | 0.3679 | 24.56 |
A-W-B | 0.822 (0.789-0.852)1,2,3 | < 0.0001 | 80.66 | 72.08 | 0.5273 | 0.4531 |
Table 4 Establishment of the logistic regression prediction model A-W-B combined with the atherogenic index of plasma, waist circumference, and body mass index
Variable | β | SE | Wald χ2 | P value | OR (95%CI) |
AIP | 2.560 | 0.345 | 55.017 | < 0.001 | 12.939 (6.578-25.45) |
WC | 0.049 | 0.017 | 7.951 | 0.005 | 1.050 (1.015-1.087) |
BMI | 0.170 | 0.051 | 11.087 | 0.001 | 1.186 (1.073-10311) |
Constant | -8.782 | 1.003 | 76.689 |
Table 5 Spearman’s correlation analysis results between various indicators (r value)
Variable | AIP | WC | BMI | A-W-B |
SBP in mmHg | 0.299b | 0.358b | 0.362b | 0.392b |
DBP in mmHg | 0.327b | 0.325b | 0.315b | 0.375b |
ALT in U/L | 0.470b | 0.455b | 0.451b | 0.530b |
AST in U/L | 0.306b | 0.307b | 0.304b | 0.351b |
TC in mmol/L | 0.193b | 0.070a | 0.056 | 0.132b |
TG in mmol/L | 0.954b | 0.455b | 0.430b | 0.763b |
HDL-C in mmol/L | -0.617b | -0.365b | -0.373b | -0.543b |
LDL-C in mmol/L | 0.253b | 0.128b | 0.105b | 0.190b |
FBG in mmol/L | 0.294b | 0.280b | 0.274b | 0.334b |
SUA in μmol/L | 0.462b | 0.375b | 0.358b | 0.469b |
Table 6 Data comparison between training set and validation set
Variable | Training set, n = 864 | Validation set, n = 131 | P value |
Sex, female | 240 (27.8) | 38 (29.0) | 0.770 |
Age in yr | 39.820 ± 10.934 | 39.660 ± 10.861 | 0.885 |
Smoking history | 255 (29.5) | 38 (29.0) | 0.906 |
Drinking history | 221 (25.6) | 24 (18.3) | 0.072 |
WC in cm | 92.490 ± 10.522 | 93.690 ± 10.759 | 0.057 |
BMI in kg/m2 | 26.563 ± 3.653 | 27.055 ± 3.772 | 0.155 |
SBP in mmHg | 130.460 ± 16.517 | 129.090 ± 16.822 | 0.386 |
DBP in mmHg | 80.730 ± 12.464 | 78.560 ± 12.192 | 0.063 |
ALT in U/L | 28.0 (19.0, 42.0) | 28.0 (19.0, 43.0) | 0.837 |
AST in U/L | 21.0 (18.0, 26.0) | 22.0 (18.0, 26.0) | 0.612 |
TC in mmol/L | 4.683 ± 0.888 | 4.607 ± 0.865 | 0.349 |
TG in mmol/L | 1.5 (1.0, 2.2) | 1.6 (1.0, 2.5) | 0.307 |
HDL-C in mmol/L | 1.256 ± 0.279 | 1.241 ± 0.293 | 0.533 |
LDL-C in mmol/L | 2.800 ± 0.826 | 2.763 ± 0.769 | 0.651 |
FBG in mmol/L | 5.3 (5.0, 5.7) | 5.2 (4.9, 5.8) | 0.326 |
SUA in μmol/L | 359.434 ± 88.800 | 342.901 ± 88.448 | 0.052 |
AIP | 0.09 (-0.13, 0.30) | 0.12 (-0.13, 0.33) | 0.306 |
- Citation: Duan SJ, Ren ZY, Zheng T, Peng HY, Niu ZH, Xia H, Chen JL, Zhou YC, Wang RR, Yao SK. Atherogenic index of plasma combined with waist circumference and body mass index to predict metabolic-associated fatty liver disease. World J Gastroenterol 2022; 28(36): 5364-5379
- URL: https://www.wjgnet.com/1007-9327/full/v28/i36/5364.htm
- DOI: https://dx.doi.org/10.3748/wjg.v28.i36.5364