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Identification of a High Visceral Adiposity Phenotype: A Cluster Analysis-Based Stratification of NAFLD Risk in the
Zhongjun Shen1,2,3, Qian Zhang1,3, Jingjin Tao1,2,3
1Department of Clinical Laboratory, Peking University Third Hospital, Beijing, People's Republic of China.
Background:
Non-alcoholic fatty liver disease (NAFLD), the most prevalent chronic liver disease globally, is closely linked to obesity and metabolic dysregulation. However, the relative contributions of overall adiposity versus body fat distribution patterns to NAFLD pathogenesis, particularly in the elderly population, remain incompletely understood.
Objective:
This study aimed to investigate the association between cluster-derived body composition phenotypes and NAFLD risk, and identify independent risk factors for NAFLD.
Methods:
This cross-sectional study enrolled 239 elderly participants. Body composition parameters (whole-body and regional fat percentages, visceral adipose tissue (VAT) area, fat-free mass) were measured via dual-energy X-ray absorptiometry (DXA). Participants were divided into NAFLD and non-NAFLD groups by abdominal ultrasonography. Inter-group comparisons were performed with Student's t-tests and chi-square tests. Cluster analysis was applied to identify distinct body composition phenotypes. Univariate and multivariate logistic regression were used to screen independent NAFLD risk factors, and ROC curve analysis evaluated the model's predictive performance.
Results:
The NAFLD group showed more prominent central obesity (P<0.001) and higher fat-free mass (P<0.001) than the non-NAFLD group, with no difference in total body fat percentage. Three phenotypes were identified: high total fat with limb-dominant distribution (C1), high visceral fat with central obesity (C2), and low total fat with symmetrical distribution (C3). C2 had the worst metabolic profile and highest NAFLD prevalence (60.5%), significantly higher than C1 (27.5%) and C3 (30.3%). Multivariate analysis identified lower HDL-C, higher BMI, elevated trunk-to-leg fat ratio, and higher albumin as independent NAFLD predictors; the four-indicator combined model had optimal predictive performance (AUC=0.803).
Conclusion:
In the elderly, visceral fat accumulation and central fat distribution, rather than overall adiposity itself, are key body composition features linked to NAFLD. The high visceral fat central obesity phenotype correlates with the highest metabolic risk and NAFLD prevalence, and the trunk-to-leg fat ratio is a robust NAFLD predictor.
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