Body Composition
Conditions
Keywords
Body composition, Bioimpendance analysis, Physical activity, Nutrition
Brief summary
Body composition measurement is an important tool for assessing the physical condition of sick or healthy people, as well as for monitoring changes in body composition and physical performance during diet and/or training. Many people self-monitor their body composition using portable and inexpensive assessment tools, but most of them have not been tested for accuracy and precision. This study aims to assess the accuracy and precision of a new portable impedancemeter scale to measure body composition in comparison with proven techniques, such as 4-electrode electrical bioimpedance analysis and dual X-ray absorptiometry.
Detailed description
This is an observational, prospective, cross-sectional study to evaluate the accuracy and precision of the new HAG-B19 in healthy Western adults. A stratified sampling method is used to recruit a heterogeneous sample of 160 subjects, covering a wide range of ages and body compositions according to gender specific BMI distributions in the population. Volunteers who signed the informed consent form are included in the study. A financial compensation of 50.- CHF is given to each participant (100.- to the 16 participants subjected to the DEXA measurements). The body composition of each subject (FM, LBM and FM%) is assessed with sequential measurements using 3 HAG-B19 and 3 Nutriguard-M® devices (Data Input, Germany). FM% values measured by HAG-B19 are compared to values by Nutriguard-M® to assess the accuracy and precision of HAG-B19 (main objective). Intra- and inter-device variability are obtained by comparing the 3 repeated measurements and the 3 HAG-B19 devices (secondary objective). In a subgroup of 16 individuals, the FM% values measured by HAG-B19 are compared to DEXA measurements (secondary objective). Pearson correlations and Bland-Altman graphs are performed to assess the agreement of the measurements between the devices and paired t-tests are used to determine if there is a bias between the devices. The significance of the statistical analysis is fixed at p \<0.05.
Interventions
DEVICEBody composition measurement with HAG-BIA scale
Bio-impendance analysis
Sponsors
Prof. Claude Pichard
Study design
Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
20 Years to 60 Years
Healthy volunteers
Yes
Inclusion criteria
Healthy Caucasians/Hispanics adults who signed the informed consent form (healthy defined as no chronic disease, no hospitalisation for the last 6 months, no physical disability)
Exclusion criteria
* BMI \<18.5 or ≥ 30 kg/m2 * No informed consent form signed * Inability to understand the procedures of the study, e.g. due to language problems, psychological disorders, dementia, etc. of the participant. * Medication impacting fluid and electrolyte balance (diuretics or calcium channel blocker) * Moderate to intense level physical activity 2-3 h before measurement * Pregnancy
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Accuracy of percent fat mass measurement | 6 months | Comparison between HAG-B19 and Nutriguard-M measurement |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Intra- and inter-device variability of percent fat mass measurement | 6 months | Comparison of measurements within and between three HAG-B19 devices. |
| Accuracy of percent fat mass measurement compared to gold standard | 6 months | Comparison between HAG-B19 and DEXA in 10 percents of participants |
Countries
Switzerland
Outcome results
None listed