Shift Workers' Health Behavior Action Program Across Europe
NCT07631767
Behavior, Body Weight
Bremen, Germany
View Trial DetailsNCT Number: NCT07776678
The purpose of this study is to evaluate body composition across a variety of medical, professional, and commercial devices, including: bioelectrical impedance analysis (BIA) devices, 3-dimensional optical imaging (3DO), manual anthropometry measurements, dual-energy X-ray absorptiometry (DXA), magnetic resonance imaging (MRI), and blood tests. The secondary study purpose is to compare body composition measurements from BIA devices, 3DO, and manual anthropometry measurements within a 1-week period for a subset of the study population.
The study plans to enroll 300 healthy (having no life-threatening conditions or diseases; male and female) participants, 18 years of age or older.
Interested in participating?
Request Info18 year and older
All sexes
Observational
Exponent Phoenix, Phoenix, Arizona, United States
Obesity is a disease of excess and abnormal distribution of adipose tissue. Even though negative metabolic outcomes of obesity are driven by adipose tissue, investigators still use body weight (comprised of both fat and fat-free mass) in the calculation of body mass index (weight in kg divided by height in meters squared) to define, subclassify and monitor treatment in people with obesity. Despite this traditional focus on body weight, body composition is an important consideration in the management of people with obesity.
Clinical trials and clinical research often use DXA and MRI to quantify changes in body composition; however these methods are expensive and not easily implemented. It is desirable to monitor fat mass and other body composition outcomes in individuals with obesity taking weight loss medications as well as when new weight management therapeutic drugs are developed.
Most weight loss medications are associated with loss of both fat mass and fat-free mass with the "quality of weight loss" defined as the proportion of weight lost as fat mass, equal to 60-75%. Recognizing that loss of fat-free mass during weight loss is undesirable, several companies are developing lean mass preserving weight loss agents. For these agents, stepping on a weight scale will no longer be an accurate measure of benefit; loss in fat is offset by gains in lean, rendering body weight changes as an inaccurate measure of weight loss quality. Therefore, the application of body composition measurements will be required for patients, physicians, and payors to monitor treatment in people with obesity. In order for this to occur, investigators need scalable body composition measurements for fat mass.
Bioelectrical impedance analysis (BIA) offers a more scalable approach as the time, cost and footprint of BIA devices make them appropriate for a physician's office and for clinical research trials. Traditionally, BIA devices have been deemed to possess insufficient accuracy for body composition quantification. While this decreased accuracy was an obstacle for first generation weight loss medications with less weight loss, it is possible that with the newer generation of weight loss medications that confer greater weight loss, BIA may be adequate to measure changes in body composition occurring over time in individuals losing weight. Additionally, notable technological innovation has occurred in the field of bioimpedance, with several new devices possessing improved hardware and software as compared to previously evaluated analyzers. As such, these devices are expected to outperform traditional BIA systems.
Other accessible technologies that are practical to apply in clinical research and practice have appeared in recent publications. These include three-dimensional optical systems (3DO) housed in smartphones and multi-omics blood tests capable of estimating various body compartments. To the extent that BIA and these newer technologies can serve as useful sufficiently reproducible phenotypic measures of a person's body composition remains largely unknown. In addition to the dichotomy of fat mass vs fat-free mass, not all fat mass is created equal. Superficial or subcutaneous fat mass is thought to be metabolically healthy whereas visceral central fat is thought to be metabolically unhealthy. Furthermore, visceral fat is associated with long-term morbidity and mortality. Therefore, another dimension of body composition is the proportion of fat in the visceral vs subcutaneous compartments.
Currently, MRI is the gold standard method to measure visceral fat. Some BIA analyzers provide estimations of visceral fat, and digital anthropometry derived from 3D scanning can also be used in visceral fat estimation equations. As such, an additional goal of this project is to determine if visceral fat can be accurately estimated in the real-world using BIA or 3DO. Currently there are two major manufacturers of DXA devices, Hologic and General Electric (GE). Accuracy and precision data for body composition measures using DXA have been published. For BIA, there are several different manufacturers including InBody, Tanita, Seca, and Impedimed. Likewise, several companies produce 3DO smartphone systems, and one company provides multi omics blood evaluations for body composition. It is not known which of these devices and measurement platforms (if any) have adequate accuracy to measure body composition. The overall goal of this project is to bring measurement of body composition to the real world to improve the diagnosis, classification, and monitoring of treatment in people with obesity, both in clinical research trials and medical practice. Adipose or fat mass needs to become a new "vital sign." This project could have a large impact on the treatment of people with obesity. Accurate implementation of body composition analysis in the real world could lead to the development of treatment goals for obesity based on either total fat mass and/or visceral fat mass.
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Time frame: 4 Weeks
Agreement between bioimpedance and 3-dimensional optical imaging derived estimates of total fat mass and DXA-derived reference measurements.
Time frame: 4 Weeks
Agreement between bioimpedance and 3-dimensional optical imaging derived estimates of fat-free mass and DXA-derived reference measurements.
Time frame: 4 Weeks
Agreement between bioimpedance and 3-dimensional optical imaging derived estimates of percent body fat and DXA-derived reference measurements.
Time frame: 4 Weeks
Agreement between bioimpedance and 3-dimensional optical imaging derived estimates of visceral adipose tissue and MRI-derived reference measurements.
Time frame: 4 Weeks
Agreement between blood-based proteomics-derived fat-free mass and DXA-derived fat-free mass, assessed using the prespecified agreement analyses.
Time frame: 4 Weeks
Description: Agreement between blood-based proteomics-derived total fat mass and DXA-derived total fat mass, assessed using the prespecified agreement analyses.
Time frame: 4 Weeks
Agreement between blood-based proteomics-derived percent body fat and DXA-derived percent body fat, assessed using the prespecified agreement analyses.
Time frame: 4 Weeks
Agreement between blood-based proteomics-derived visceral adipose tissue and MRI-derived visceral adipose tissue, assessed using the prespecified agreement analyses
Time frame: 4 Weeks
Classification performance of bioimpedance (BIA), 3-dimenisonal optics imaging (3DO), and blood-based methods for obesity and elevated visceral adipose tissue (VAT) status, assessed using area under the receiver operating characteristic curve (AUC) based on prespecified thresholds.
Time frame: 4 Weeks
Regression models will be used to evaluate the effects of prespecified demographic and anthropometric covariates, including age, sex, and BMI, on measurement error between candidate body composition methods and the corresponding DXA or MRI reference method.
Time frame: 1 Week
Intraclass correlation coefficients with 95% confidence intervals will be calculated for repeated BIA measurements obtained during the protocol-specified repeat-visit window of 2-7 days.
Time frame: 1 Week
Intraclass correlation coefficients with 95% confidence intervals will be calculated for repeated 3DO measurements obtained during the protocol-specified visit window of 2-7 days.
Time frame: 1 Week
Technical error of measurement will be calculated for repeated BIA measurements obtained during the protocol-specified repeat-visit window of 2-7 days.
Time frame: 1 Week
Technical error of measurement will be calculated for repeated 3DO measurements obtained during the protocol-specified repeat-visit window of 2-7 days
Time frame: 4 Weeks
Exploratory models incorporating 3DO-derived geometric and anthropometric features will be evaluated for estimation of visceral adipose tissue relative to MRI-derived reference measurements using regression-based predictive performance measures.
Contact information is provided by the study sponsor or research team.
Ariel Dowling, PhD
CONTACT
Steven Heymsfield, MD
CONTACT
Foundation for the National Institutes of Health
Other
Redefining Evaluation of Adiposity and Leanness: Broadening Objective Diagnostics for Obesity (REAL-BODY)
Acronym: REAL-BODY
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View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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