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. 2024 Jul 10;24(1):221.
doi: 10.1186/s12876-024-03303-x.

Association between different obesity patterns and the risk of NAFLD detected by transient elastography: a cross-sectional study

Jingjing Sun  1 , Chun Yan  1 , Jing Wen  1 , Fang Wang  1 , Han Wu  1 , Fang Xu  2
Affiliations

Association between different obesity patterns and the risk of NAFLD detected by transient elastography: a cross-sectional study

Jingjing Sun et al. BMC Gastroenterol. .

Abstract

Background: Obesity has become a major global public health challenge. Studies examining the associations between different obesity patterns and the risk of nonalcoholic fatty liver disease (NAFLD) are limited. This study aimed to investigate the relationships between different obesity patterns and the risk of NAFLD in a large male population in the US.

Methods: Data from the 2017 to March 2020 National Health and Nutrition Examination Survey (NHANES) were utilized. Liver steatosis and fibrosis were assessed with FibroScan using the controlled attenuation parameter (CAP) and liver stiffness measurements (LSM). Steatosis was identified with a CAP value of 248 dB/m or higher. Abdominal obesity was defined by a waist circumference (WC) of 102 cm or more for males and 88 cm or more for females. Overweight was defined as a body mass index (BMI) of 24.0 kg/m2 and above. General obesity was identified with a BMI of 28.0 kg/m2 or higher. Obesity status was categorized into four types: overweight, general obesity, abdominal obesity, and combined obesity. Multivariate logistic regression, adjusting for potential confounders, was used to examine the link between obesity patterns and NAFLD risk. Subgroup analysis further explored these associations.

Results: A total of 5,858 adults were included. After multivariable adjustment, compared to the normal weight group, the odds ratios (ORs) [95% confidence interval (CI)] for NAFLD in individuals with overweight, general obesity, abdominal obesity, and combined obesity were 6.90 [3.74-12.70], 2.84 [2.38-3.39], 3.02 [2.02-4.51], and 9.53 [7.79-11.64], respectively. Subgroup analysis showed the effect of different obesity patterns on NAFLD risk was stable among individuals with different clinical conditions. In the fully adjusted multivariate logistic regression model, WC was positively associated with NAFLD risk (OR: 1.48; 95% CI: 1.42-1.53; P < 0.001). WC also demonstrated strong discriminatory ability for NAFLD in Receiver Operating Characteristic (ROC) analysis, achieving an Area Under the Curve (AUC) of 0.802.

Conclusions: Different patterns of obesity are risk factors for NAFLD. An increase in WC significantly increased NAFLD risk. More attention should be paid to preventing different patterns of obesity among adults.

Keywords: Cross-sectional; Hepatic fibrosis; NAFLD; Obesity patterns; Transient elastography.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Flowchart for the selection of the participants of the present study
Fig. 2
Fig. 2
Subgroup analyses for the risks of NAFLD in different obesity pattern groups compared with the normal-weight group. A general obesity vs normal-weight group; B overweight vs normal-weight group; C abdominal obesity vs normal-weight group; D compound obesity vs normal-weight group
Fig. 3
Fig. 3
Restricted cubic spline analysis between waist circumference and the risk of NAFLD and the Receiver operating characteristic curve. A Restricted cubic spline analysis for the association between waist circumference and the risk of NAFLD; B Receiver operating characteristic curve of waist circumference for discriminating NAFLD risk
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References

    1. Festi D, Colecchia A, Sacco T, Bondi M, Roda E, Marchesini G. Hepatic steatosis in obese patients: clinical aspects and prognostic significance. Obesity reviews : an official journal of the International Association for the Study of Obesity. 2004;5(1):27–42. doi: 10.1111/j.1467-789X.2004.00126.x. - DOI - PubMed
    1. Younossi ZM, Stepanova M, Younossi Y, et al. Epidemiology of chronic liver diseases in the USA in the past three decades. Gut. 2020;69(3):564–568. doi: 10.1136/gutjnl-2019-318813. - DOI - PubMed
    1. Younossi ZM, Blissett D, Blissett R, et al. The economic and clinical burden of nonalcoholic fatty liver disease in the United States and Europe. Hepatology (Baltimore, MD) 2016;64(5):1577–1586. doi: 10.1002/hep.28785. - DOI - PubMed
    1. Teng ML, Ng CH, Huang DQ, et al. Global incidence and prevalence of nonalcoholic fatty liver disease. Clin Mol Hepatol. 2023;29(Suppl):S32–s42. doi: 10.3350/cmh.2022.0365. - DOI - PMC - PubMed
    1. Marchesini G, Bugianesi E, Forlani G, et al. Nonalcoholic fatty liver, steatohepatitis, and the metabolic syndrome. Hepatology (Baltimore, MD) 2003;37(4):917–923. doi: 10.1053/jhep.2003.50161. - DOI - PubMed

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