Non-Alcoholic Fatty Liver Disease, Body Composition, Electric Impedance
Conditions
Keywords
Non-Alcoholic Fatty Liver Disease, Body Composition, Electric Impedance
Brief summary
This is a prospective observational study which will recruit up to 1200 participants over a two-year period to investigate whether non-invasive methods such as bioelectrical impedance analysis parameters and urine metabolic profile are predictors for pediatric non-alcoholic liver disease.
Detailed description
Obesity is associated with non-alcoholic fatty liver in children. Currently, body mass index is used for stratification risk for non-alcoholic fatty liver disease in children. However, body mass index represents the adjusted weight status for height and may not be a perfect surrogate for body fatness. This study assumes that a combination of body measures including parameters of bioelectrical impedance analysis and hand grip strength may better represented body fatness and healthy status than body mass index. Moreover, non-alcoholic fatty liver disease is strongly associated with the metabolic syndrome and non-invasive urine metabolic profile may be used to predict the disease status. The aim of this study will be to develop non-invasive methods using body measures and urine metabolic profile to predict pediatric fatty liver disease. This study will recruit 1200 apparently healthy children at Year 1 to Year 6 in the primary schools in Taiwan within a two-year period. A series of tests including body measures, bioelectrical impedance analysis, hand grip strength and urine metabolomics by nuclear magnetic resonance will be performed in each participant. These data will be used as features to predict the results of Fibroscan test.
Interventions
DIAGNOSTIC_TESTFibroscan
Controlled attenuation parameter and liver stiffness measurement are measured.
DIAGNOSTIC_TESTBioelectrical impedance analysis
Body composition measures including fat mass, fat-free mass, percentage body fat in total body and body segments are obtained.
DIAGNOSTIC_TESTUrine unclear magnetic resonance metabolomics
Metabolites in the urine are estimated by 600 MHz nuclear magnetic resonance.
DIAGNOSTIC_TESTHand grip strength
Hand grip strength in both hands is measured by hand-held dynamometer.
Sponsors
Ministry of Science and Technology, Taiwan
Chang Gung Memorial Hospital
Study design
Observational model
CASE_ONLY
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
6 Years to 13 Years
Inclusion criteria
* Apparently healthy male or female children * Students in Year 1 to Year 6 of primary schools
Exclusion criteria
* Unknown liver disease * Metal implant or splint * Pacemaker implantation * Limb defect or injury * Pregnancy
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Correlation between bioelectrical impedance analysis parameters and the degree of fatty liver | 24 months | Correlation body composition parameters by bioelectrical impedance analysis and controlled attenuation parameter by Fibroscan |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Correlation between urine metabolites and the degree of fatty liver | 24 months | Correlation between urine metabolites by nuclear magnetic resonance and controlled attenuation value parameter by Fibroscan |
Countries
Taiwan
Contacts
Primary ContactLi-Wen Lee, MD, PhD
Outcome results
None listed