BACKGROUND & AIMS: The prevalence of non-alcoholic fatty liver disease (NAFLD) appears to increase with age. However, limited data are available concerning the prevalence of NAFLD in the elderly. Our aim was to determine the prevalence and risk factors of NAFLD in an elderly population. METHODS: This study was based on participants in the population-based Rotterdam Study. Each participant was interviewed and had a clinical examination at the research center, including a fasting blood collection, liver ultrasonography, and anthropometric assessment. Ordinal and logistic regression analysis was used to assess associations between covariables and (severity of) NAFLD. RESULTS: Data from 2811 participants (mean age 76.4 ± 6.0 years) were analyzed. The prevalence of NAFLD was 35.1%. The prevalence of NAFLD decreased with advancing age (p<0.001). In logistic regression analysis, age (OR 0.97; 95% CI 0.95-0.99; p<0.001), total physical activity level (OR 0.98, 95% CI 0.96-0.99; p=0.005), pack years of smoking (OR 1.01, 95% CI 1.00-1.01; p=0.02), waist circumference >88 cm for women and > 102 cm for men (OR 4.89; CI 4.00-5.96; p<0.001), fasting glucose ≥ 100 mg/dl or drug treatment for elevated blood glucose (OR 2.11, 95% CI 1.72-2.59; p<0.001), blood pressure ≥ 130/85 mmHg or drug treatment for elevated blood pressure (OR 1.80, 95% CI 1.08-3.01; p=0.03), and triglycerides ≥ 150 mg/dl or treatment with serum lipid reducing agents (OR 1.56, 95% CI 1.28-1.91; p<0.001) were associated with NAFLD. CONCLUSIONS: NAFLD is common in the elderly, although the prevalence decreases with advancing age. Further studies are warranted exploring potential factors contributing to this apparent positive selection effect in the elderly.
BACKGROUND & AIMS: The prevalence of non-alcoholic fatty liver disease (NAFLD) appears to increase with age. However, limited data are available concerning the prevalence of NAFLD in the elderly. Our aim was to determine the prevalence and risk factors of NAFLD in an elderly population. METHODS: This study was based on participants in the population-based Rotterdam Study. Each participant was interviewed and had a clinical examination at the research center, including a fasting blood collection, liver ultrasonography, and anthropometric assessment. Ordinal and logistic regression analysis was used to assess associations between covariables and (severity of) NAFLD. RESULTS: Data from 2811 participants (mean age 76.4 ± 6.0 years) were analyzed. The prevalence of NAFLD was 35.1%. The prevalence of NAFLD decreased with advancing age (p<0.001). In logistic regression analysis, age (OR 0.97; 95% CI 0.95-0.99; p<0.001), total physical activity level (OR 0.98, 95% CI 0.96-0.99; p=0.005), pack years of smoking (OR 1.01, 95% CI 1.00-1.01; p=0.02), waist circumference >88 cm for women and > 102 cm for men (OR 4.89; CI 4.00-5.96; p<0.001), fasting glucose ≥ 100 mg/dl or drug treatment for elevated blood glucose (OR 2.11, 95% CI 1.72-2.59; p<0.001), blood pressure ≥ 130/85 mmHg or drug treatment for elevated blood pressure (OR 1.80, 95% CI 1.08-3.01; p=0.03), and triglycerides ≥ 150 mg/dl or treatment with serum lipid reducing agents (OR 1.56, 95% CI 1.28-1.91; p<0.001) were associated with NAFLD. CONCLUSIONS: NAFLD is common in the elderly, although the prevalence decreases with advancing age. Further studies are warranted exploring potential factors contributing to this apparent positive selection effect in the elderly.
Authors: Albert Hofman; Guy G O Brusselle; Sarwa Darwish Murad; Cornelia M van Duijn; Oscar H Franco; André Goedegebure; M Arfan Ikram; Caroline C W Klaver; Tamar E C Nijsten; Robin P Peeters; Bruno H Ch Stricker; Henning W Tiemeier; André G Uitterlinden; Meike W Vernooij Journal: Eur J Epidemiol Date: 2015-09-19 Impact factor: 8.082
Authors: M Arfan Ikram; Guy G O Brusselle; Sarwa Darwish Murad; Cornelia M van Duijn; Oscar H Franco; André Goedegebure; Caroline C W Klaver; Tamar E C Nijsten; Robin P Peeters; Bruno H Stricker; Henning Tiemeier; André G Uitterlinden; Meike W Vernooij; Albert Hofman Journal: Eur J Epidemiol Date: 2017-10-24 Impact factor: 8.082
Authors: In Hee Kim; Jun Xu; Xiao Liu; Yukinori Koyama; Hsiao-Yen Ma; Karin Diggle; Young-Hyun You; Jan M Schilling; Dilip Jeste; Kumar Sharma; David A Brenner; Tatiana Kisseleva Journal: Age (Dordr) Date: 2016-08-30