Skeletal muscle mass and abdominal obesity are independent predictors of hepatic steatosis and interact to predict ten-year cardiovascular disease incidence: Data from the ATTICA cohort study.

Background & Aims: Sarcopenia and sarcopenic obesity may be associated with nonalcoholic fatty liver disease (NAFLD). This study examined the association between low skeletal muscle mass, with or without central obesity, with NAFLD, as well as their interaction on predicting 10-year incidence of cardiovascular disease (CVD).

Methods: This was a post-hoc analysis of the ATTICA study. At baseline, 3042 participants from the Attica region of Greece were recruited; 2020 completed the 10-year follow-up visit for CVD. NAFLD was assessed through hepatic steatosis index (HSI). Skeletal muscle mass index (SMI) was calculated to assess skeletal muscle mass. SMI was studied in tertiles, stratified by sex; the first tertile corresponds to the lowest SMI, the second to middle, and the third to highest SMI. Abnormal waist circumference was defined as ≥102 cm for men and ≥88 cm for women. The combined 10-year endpoint was the development of a fatal or nonfatal CVD event. Logistic regression analysis was used to assess the association between NAFLD prevalence and SMI as well as Cox regression analysis to assess the interaction of both variables on the incidence of CVD over 10 years.

Results: Higher rates of NAFLD were observed in the first (45%) compared to the second [33%; odds ratio (OR): 0.50, 95% confidence interval (95%CI): 0.41-0.61] and the third (22%; OR: 0.24, 95%CI: 0.19-0.29) SMI tertile. This association remained robust after multiple adjustments; significance was marginally lost, when waist circumference was added to the model. When SMI and waist circumference were evaluated jointly, participants with moderate/high SMI and normal waist circumference had the lowest and those with low SMI and abnormal waist circumference the highest NAFLD rate (24.3 and 60.5%, respectively; P < 0.001). Ten-year CVD incidence was gradually lower from the first (22.8%) to second (16.1%) and third SMI tertile (8.2%) (P < 0.001). The hazard ratio (HR) for the third vs. the first SMI tertile for predicting CVD in fully adjusted model was 0.69 (95%CI: 0.46, 1.00). The unadjusted HR for NAFLD predicting CVD was 3.00 (95%CI: 2.28-3.95). Finally, there was a significant interaction among NAFLD, SMI and waist circumference (P = 0.04) in determining the 10-year CVD incidence; the association between NAFLD and 10-year CVD remained significant for the participants with low SMI and normal or abnormal waist circumference, but not those with moderate/high SMI and normal or abnormal waist circumference.

Conclusions: Increasing SMI and lower abdominal obesity are independently associated with lower rates of NAFLD, and the two interact as key determinants of NAFLD. Low SMI and central obesity are independent predictors of CVD and were shown to interact with NAFLD in determining 10-year CVD risk.