BMC Gastroenterology (Jul 2024)

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

  • Jingjing Sun,
  • Chun Yan,
  • Jing Wen,
  • Fang Wang,
  • Han Wu,
  • Fang Xu

DOI
https://doi.org/10.1186/s12876-024-03303-x
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 10

Abstract

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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.

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