Table reports the demographic, anthropometric, and metabolic characteristics of the 588 participants (347 males [59%] and 241 females) stratified by the degree of ultrasonographic liver steatosis. Owing to the study design, approximately half (52%, n = 305) of the analytic sample had suspected liver disease (SLD). Overall, 256 (44%) of the study participants had intermediate or severe steatosis.
Measurements of the 588 study subjects.
56% of the individuals (n = 332) had normal liver while 20% (n = 118) had intermediate steatosis and 24% (n = 138) had severe steatosis. Liver steatosis was more common in males (none = 48%, intermediate = 23%, severe = 29%) than in females (none = 69%, intermediate = 16%, severe = 15%; p < 0.001). The distribution of liver steatosis in anti-HbsAg-positive group (n = 23) was: none = 19, intermediate = 1, severe = 3; the corresponding numbers for HCV-RNA-positive group (n = 60) were 42, 12, 6.
Weight, BMI, WC, ALT, AST, GGT, ethanol intake, glucose, triglycerides and LAP showed an increasing trend for increasing degree of liver steatosis (p
≤ 0.006). 33 participants had diabetes and 8 of these had normal liver, 8 intermediate steatosis and 17 severe steatosis. The median (25th
percentile) values of LAP in 173 subjects aged 25 to 49 years and in 407 aged 50+ years were 26 (16, 47) and 37 (23, 63) as compared to NHANES III population estimates of 30 (16, 57) and 53 (31, 85) [15
Table reports the proportional-odds logistic models used to evaluate the association between lnLAP and liver steatosis. Because the Dionysos Nutrition and Liver Study is a cross-sectional study with matching of subjects performed on the basis of SLD, sex and age [11
], we tested whether the addition of these variables had any effect on the ability of lnLAP to identify liver steatosis.
Proportional-odds logistic regression models.
shows that for every increase in 1 unit of lnLAP, the odds of more severe vs.
less severe liver steatosis was 4.45 (95%CI 3.42 to 5.79, p
< 0.001). However, the fit of Model 1 was not good, as detected by the Hosmer-Lemeshow statistic for the binary logistic model aiming to discriminate none vs.
intermediate and severe liver steatosis (p
= 0.008). Model 2
added sex and age to lnLAP and showed an independent effect of sex but not of age on liver steatosis. Model 3
removed the non-significant age term from Model 2 and offered "strong evidence" of improvement as compared to Model 1 (ΔBIC = -6). Model 3 also fitted well according to the Hosmer-Lemeshow statistics. Model 4
added SLD to the predictors of Model 2. As the effect of age was still not significant in Model 4, Model 5
evaluated the degree to which the addition of SLD ameliorated the fit of Model 3
. There was only "weak evidence" of improvement of Model 5 vs. Model 3
(ΔBIC = -2), which is clearly not counterbalanced by the difficulties in evaluating SLD in epidemiological studies outside the field of hepatology. The AUROC were similar for all models suggesting no advantage in using the more complex models. However, the AUROC does not address the issue of model calibration so that it must be interpreted in the light of the results of the other tests [31
Because ethanol intake was higher in males than in females, we tested whether it could be partly responsible for the sex-related difference in the liver steatosis-lnLAP association by adding it (g/day) to Models 1-5
but found no association between it and liver steatosis (data not shown). This finding was not unexpected owing to our previous demonstration that alcohol intake was not a predictor of binary fatty liver in this population [12
] and with the independent observation made by the RISC Study that FLI and alcohol intake are not associated [13
Another possible explanation for the sex-related difference in the liver steatosis-lnLAP association could be that we measured WC at the midpoint between the last rib and the iliac crest [11
] while LAP was developed from the NHANES data using waist measured at level of the iliac crest [15
]. While these alternative WC measurement protocols provide similar values in men, in women the iliac-crest site may overestimate WC by about 1.8 cm as compared to the site midway between the last rib and iliac crest [33
]. We tried to take into account this difference by subtracting 1.8 cm from the WC of our women and refitting Models 1-5
(data not shown). The results were virtually unchanged as compared to those provided in Table . This was not unexpected because the relationship between WC and health outcomes is fairly stable independently from the measurement site [34
Owing to this evidence, we choose Model 3
, based on lnLAP and sex, as the most efficient and practical model for predicting liver steatosis in our study population. Figures and displays sex-specific probabilities of 3-level liver steatosis as nomograms that illustrate the continuous relationship of liver steatosis to lnLAP. The Additional file 1
reports the probability of 3-level liver steatosis for increments of 0.1 units in lnLAP in separate tables for males and females.
Probability of liver steatosis as detected by the natural logarithm of the lipid accumulation product in males. Abbreviations: lnLAP = natural logarithm of LAP.
Probability of liver steatosis as detected by the natural logarithm of the lipid accumulation product in females. Abbreviations: lnLAP = natural logarithm of LAP.