![]() ![]() The study sample was characterized using descriptive statistics. Metabolic factors were included both continuously and dichotomized according to the definition of the metabolic syndrome, following the Adult Treatment Panel III criteria ( 24): (i) fasting glucose > 5.6 mmol/L and/or antidiabetic drug use (ii) waist circumference > 102 cm (male individuals) or >88 cm (female individuals) (iii) TG ≥ 1.7 mmol/L and/or lipid-lowering drug use (iv) HDL-C < 1.04 mmol/L in female individuals or < 1.30 mmol/L in male individuals and/or lipid-lowering drug use and (5) hypertension based on a systolic blood pressure(SBP) ≥ 130 mm Hg, diastolic blood pressure ≥ 85 mm Hg, and/or antihypertensive drug use. Viral hepatitis was determined on hepatitis B surface antigen and anti-hepatitis C, analyzed by automatic immunoassay (Roche Diagnostic GmbH, Mannheim, Germany). ![]() Homeostatic model assessment of insulin resistance (HOMA-IR) was based on glucose and insulin levels. Glucose, HDL-C, triglycerides (TG), aspartate aminotransaminase, alanine aminotransferase (ALT), and gamma-glutamyl transpeptidase were analyzed by automatic enzyme procedures, and insulin was analyzed with automatic immunoassay (Roche, Diagnostic GmbH, Mannheim, Germany). Systemic corticosteroids, amiodarone, methotrexate, and tamoxifen were defined as steatogenic drugs.ĭuring fasting state, blood samples were collected from the participants. Medication use was based on a digital linkage with the pharmacy of the participant. ![]() Based on the same FFQ, coffee consumption, total caloric intake, and an overall diet quality score were calculated ( 23). Excessive alcohol use was defined as >30 g/d for male individuals and >20 g/d for female individuals based on FFQ or interview data ( 20). Alcohol intake frequency and quantity were assessed during a home interview and with a validated self-administered FFQ. Trained interviewers administered questionnaires at the participants' home to ensure completion and correct interpretation. In this study, we investigated the association between objectively measured physical activity and ultrasound-based NAFLD with emphasis on different intensities of physical activity, sedentary behavior, and the impact of metabolic health in these associations.Īt the study location, research assistants measured anthropometrics, which included waist circumference. Therefore, it remains unclear whether physical activity is directly associated with NAFLD ( 11) or is effectuated by improvements in body composition and metabolic health ( 12). Because such parameters are part of the algorithm, adjusting for and exploring the role of those variables in the association between physical activity and NAFLD is impossible, even in case of sufficient sample size and extensive data available. Third, these algorithms often include parameters (i.e., body mass index, waist circumference, fasting glucose, and high-density lipoprotein cholesterol ), which are directly linked with physical activity, which may therefore be mediators or confounders ( 17, 18). Second, using serological algorithms instead of imaging to define steatosis is of concern because it lacks sensitivity and specificity. This type of continuous activity tracking is an objective approach and not subject to recall bias and differs significantly from conventional, self-reported information ( 16). This limitation might be resolved by the recent progression in technology that has resulted in compact devices, which can accurately measure physical activity time and intensity over longer periods on a large scale ( 15). First, physical activity measurement was often self-reported. Most studies to date that have been investigating the association between physical activity and NAFLD were hampered by several challenges. However, specific advice on physical activity duration and intensity is lacking. In addition, previous studies demonstrated a beneficial association between physical activity and NAFLD to some extent ( 9– 14). Many studies have therefore investigated the potential of dietary intake and composition in steatosis regression ( 5, 8). ![]() These beneficial effects are driven by improved insulin resistance, stimulation of fat metabolism, and increased mitochondrial function ( 5, 7). Weight loss and improvements in metabolic health are important targets in prevention and disease management in fact, NAFLD and even fibrosis can regress if 5% weight reduction is accomplished ( 5, 6). Moreover, the disease burden of NAFLD is expected to further increase in the following decades because of the rapid increase in adiposity and metabolic syndrome ( 3, 4). Nonalcoholic fatty liver disease (NAFLD) has become the most prevalent chronic liver disease in the western world and is associated with severe hepatic and extrahepatic comorbidities and mortality ( 1, 2). ![]()
0 Comments
Leave a Reply. |