Dataset Information

Low vitamin D status is associated with nonalcoholic Fatty liver disease independent of visceral obesity in Korean adults.

ABSTRACT:

Objective

To investigate the association between serum 25-hydroxyvitamin D [25(OH)D] levels and nonalcoholic fatty liver disease (NAFLD) independent of visceral obesity in Koreans and to examine whether the associations differ according to the presence of diabetes or insulin resistance.

Research design and methods

A total of 1081 adults were enrolled from a population-based cohort in Ansan city. Serum 25(OH)D concentrations were measured in all subjects. Insulin resistance was measured by homeostasis model assessment of insulin resistance (HOMA-IR). Using computed tomography, NAFLD was diagnosed if the liver attenuation index (LAI, the difference between the mean hepatic and splenic attenuation) was <5 Hounsfield Units.

Results

In subjects with diabetes (n = 282), 25(OH)D levels were negatively associated with waist circumference, fasting insulin, HOMA-IR, triglyceride levels, and visceral abdominal fat, and were positively associated with LAI after adjusting for age, sex, season, exercise, and vitamin supplementation. In subjects without diabetes, only triglyceride level was negatively associated with 25(OH)D. The adjusted odds ratio (OR) for NAFLD increased sequentially across decreasing quartiles of 25(OH)D in subjects with diabetes even after adjusting for visceral fat [Q1 vs. Q4; OR for NAFLD 2.5 (95% CI:1.0-6.2)]. In contrast, no significant difference in OR was observed in subjects without diabetes. When we classified non-diabetic subjects by HOMA-IR, an increase in the OR for NAFLD across decreasing quartiles of 25(OH)D was observed in the high HOMA-IR (≥2.5) group [n = 207, Q1 vs. Q4; OR 3.8(1.4-10.3)], but not in the low HOMA-IR (<2.5) group [n = 592, OR 0.8 (0.3-1.9)].

Conclusions

Low vitamin D status is closely associated with NAFLD, independent of visceral obesity in subjects with diabetes or insulin resistance.

SUBMITTER: Seo JA

PROVIDER: S-EPMC3793981 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Objective: This study aimed to distinguish the risk variables of nonalcoholic fatty liver disease (NAFLD) and to construct a prediction model of NAFLD in visceral fat obesity in Japanese adults. Methods This study is a historical cohort study that included 1,516 individuals with visceral obesity. All individuals were randomly divided into training group and validation group at 70% (n = 1,061) and 30% (n = 455), respectively. The LASSO method and multivariate regression analysis were performed for selecting risk factors in the training group. Then, overlapping features were selected to screen the effective and suitable risk variables for NAFLD with visceral fatty obesity, and a nomogram incorporating the selected risk factors in the training group was constructed. Then, we used the C-index, calibration plot, decision curve analysis, and cumulative hazard analysis to test the discrimination, calibration, and clinical meaning of the nomogram. At last, internal validation was used in the validation group. Results We contract a nomogram and validated it using easily available and cost-effective parameters to predict the incidence of NAFLD in participants with visceral fatty obesity, including ALT, HbA1c, body weight, FPG, and TG. In training cohort, the area under the ROC was 0.863, with 95% CI: 0.84–0.885. In validation cohort, C-index was 0.887, with 95%CI: 0.857–0.888. The decision curve analysis showed that the model's prediction is more effective. Decision curve analysis of the training cohort and validation cohort showed that the predictive model was more effective in predicting the risk of NAFLD in Japanese patients with visceral fatty obesity. To help researchers and clinicians better use the nomogram, our online version can be accessed at https://xy2yyjzyxk.shinyapps.io/NAFLD/. Conclusions Most patients with visceral fatty obesity have a risk of NALFD, but some will not develop into it. The presented nomogram can accurately identify these patients at high risk.