Frontiers in Cardiovascular Medicine (Sep 2024)

Association between fatty liver index and cardiometabolic multimorbidity: evidence from the cross-sectional national health and nutrition examination survey

  • Xinsheng Gu,
  • Di Gao,
  • Xinjian Zhou,
  • Yueyou Ding,
  • Wenrui Shi,
  • Jieun Park,
  • Shaohui Wu,
  • Yue He

DOI
https://doi.org/10.3389/fcvm.2024.1433807
Journal volume & issue
Vol. 11

Abstract

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BackgroundMetabolic dysfunction associated steatotic liver disease (MASLD) contributes to the cardiometabolic diseases through multiple mechanisms. Fatty liver index (FLI) has been formulated as a non-invasive, convenient, and cost-effective approach to estimate the degree of MASLD. The current study aims to evaluate the correlation between FLI and the prevalent cardiometabolic multimorbidity (CMM), and to assess the usefulness of FLI to improve the detection of the prevalent CMM in the general population.Methods26,269 subjects were enrolled from the National Health and Nutrition Examination Survey 1999–2018. FLI was formulated based on triglycerides, body mass index, γ -glutamyltransferase, and waist circumference. CMM was defined as a history of 2 or more of diabetes mellitus, stroke, myocardial infarction.ResultsThe prevalence of CMM was 10.84%. With adjustment of demographic, anthropometric, laboratory, and medical history covariates, each standard deviation of FLI leaded to a 58.8% risk increase for the prevalent CMM. The fourth quartile of FLI had a 2.424 times risk for the prevalent CMM than the first quartile, and a trend towards higher risk was observed. Smooth curve fitting showed that the risk for prevalent CMM increased proportionally along with the elevation of FLI. Subgroup analysis demonstrated that the correlation was robust in several conventional subpopulations. Receiver-operating characteristic curve analysis revealed an incremental value of FLI for detecting prevalent CMM when adding it to conventional cardiometabolic risk factors (Area under the curve: 0.920 vs. 0.983, P < 0.001). Results from reclassification analysis confirmed the improvement from FLI.ConclusionOur study demonstrated a positive, linear, and robust correlation between FLI and the prevalent CMM, and our findings implicate the potential usefulness of FLI to improve the detection of prevalent CMM in the general population.

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