Nonalcoholic Fatty Liver Disease in The Rotterdam Study: About Muscle Mass, Sarcopenia, Fat Mass, and Fat Distribution.

Nonalcoholic fatty liver disease (NAFLD) is the most prevalent liver disease worldwide. Obesity is a major risk factor for NAFLD and recently, low skeletal muscle mass emerged as additional risk factor for NAFLD. However, the different contributions of body mass index (BMI) to the risk of NAFLD are not yet well-known. We therefore studied body composition and muscle function with NAFLD in an elderly population-based study. Participants of European descent underwent dual-energy X-ray absorptiometry (DXA) and hepatic ultrasonography. NAFLD was defined as liver steatosis in absence of secondary causes for steatosis. Skeletal muscle index (SMI) was defined as appendicular lean mass/height and (pre)sarcopenia was defined using the European Working Group on Sarcopenia in Older People (EWGSOP) consensus guidelines. All analyses were stratified by sex and BMI (cut point: 25 kg/m ) and adjusted for age, weight, height, homeostasis model assessment of insulin resistance (HOMA-IR), triglycerides, and android-fat-to-gynoid-fat ratio (AGR). We included 4609 participants, of whom 1623 had NAFLD (n = 161 normal-weight and n = 1462 overweight). Presarcopenia and sarcopenia prevalence was low (5.9% and 4.5%, respectively) and both were not associated with NAFLD. SMI was associated with less NAFLD in normal-weight women (OR, 0.48; 95% CI, 0.29 to 0.80). A similar association for SMI and NAFLD was seen in normal-weight men, but significance dissipated after adjustment for AGR (OR, 0.63; 95% CI, 0.39 to 1.02). Generally, fat mass was a better predictor for NAFLD than lean mass. In particular, android fat mass was associated with all NAFLD subgroups (OR from 1.77 in overweight men to 8.34 in normal-weight women, p = 0.001), whereas substitution of gynoid fat mass for other body components had a significant protective association with NAFLD in every subgroup, but normal-weight men. Likewise, AGR was the best performing predictor for NAFLD prevalence (OR from 1.97 in normal-weight men to 4.81 in normal-weight women, p < 0.001). In conclusion, both high fat mass and low SMI were associated with normal-weight NAFLD. However, fat distribution (as assessed by AGR) could best predict NAFLD prevalence