An observational study in Obesity & Overweight, sponsored by Foundation for the National Institutes of Health. Recruiting at 3 sites in United States. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-10-26.
Sponsored by Foundation for the National Institutes of Health · Observational
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.
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.
11,522 studies on the registry are indexed under Obesity; 2,033 are open to participants now.
This study's planned enrollment of 300 is above the median of 114 across 2,154 observational studies indexed under Obesity.
Browse Obesity studies →Foundation for the National Institutes of Health is the lead sponsor of 10 studies on the registry; 2 are open to participants now.
Counted across the registry records on this site, refreshed daily.
A diverse sample of adults will be recruited for participation in the US. Stratification will occur based on sex and BMI, with additional targets to promote recruitment of a variety of ages and adequate representation of racial and ethnic categories. For race and ethnicity, the goal will be to obtain a distribution approximately equal to the demographics of the United States, with selective oversampling employed as needed. For BMI, the following percentages will be used as approximate goals for the sample (18.50-19.99, None; 20.00-24.99, 20%; 25.00-29.99, 35%; 30.00-34.99, 25%; 35.00-39.99, 13.30%; 40.00-44.99, 6.70%; ≥45, None). However, the distribution of BMI and other demographic characteristics will be monitored as the study progresses in case adjustment is needed.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Weight in kilograms divided by height in metres squared. Example: 70 kg and 1.75 m gives 70 ÷ (1.75 × 1.75) ≈ 22.9.
What counts as overweight or obesity differs between countries (some use lower cut-offs), so go by the range the study states.
A reason a treatment, test or procedure should not be given to a particular person, such as an allergy, another illness or a medicine they take.
The human immunodeficiency virus, which weakens the immune system.
Many studies now accept people whose HIV is controlled on treatment, judged by the viral load and the CD4 count. Check the limits this study sets.
The New York Heart Association’s four classes of how much heart failure limits physical activity.
Studies set their own limit — many outside heart failure leave out class III–IV, while heart failure studies may ask for a particular class. Check the class this study names.
Malignancy means cancer. Criteria about another or earlier malignancy ask whether you have had a different cancer, usually within a set number of years.
Some are commonly allowed, such as treated skin cancers other than melanoma and early cancers removed completely — check the exceptions this study lists.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
BMI (body mass index)
Weight in kilograms divided by height in metres squared. Example: 70 kg and 1.75 m gives 70 ÷ (1.75 × 1.75) ≈ 22.9.
What counts as overweight or obesity differs between countries (some use lower cut-offs), so go by the range the study states.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Contraindication
A reason a treatment, test or procedure should not be given to a particular person, such as an allergy, another illness or a medicine they take.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
HIV
The human immunodeficiency virus, which weakens the immune system.
Many studies now accept people whose HIV is controlled on treatment, judged by the viral load and the CD4 count. Check the limits this study sets.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
NYHA class (heart failure)
The New York Heart Association’s four classes of how much heart failure limits physical activity.
Studies set their own limit — many outside heart failure leave out class III–IV, while heart failure studies may ask for a particular class. Check the class this study names.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Cancer (malignancy)
Malignancy means cancer. Criteria about another or earlier malignancy ask whether you have had a different cancer, usually within a set number of years.
Some are commonly allowed, such as treated skin cancers other than melanoma and early cancers removed completely — check the exceptions this study lists.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Modality-reference agreement for total fat mass (kg)
Agreement between bioimpedance and 3-dimensional optical imaging derived estimates of total fat mass and DXA-derived reference measurements.
Time frame: 4 Weeks
Modality-reference agreement for fat-free mass (kg)
Agreement between bioimpedance and 3-dimensional optical imaging derived estimates of fat-free mass and DXA-derived reference measurements.
Time frame: 4 Weeks
Modality-reference agreement for percent body fat (%)
Agreement between bioimpedance and 3-dimensional optical imaging derived estimates of percent body fat and DXA-derived reference measurements.
Time frame: 4 Weeks
Modality-reference agreement for visceral adipose tissue (VAT; kg or volume)
Agreement between bioimpedance and 3-dimensional optical imaging derived estimates of visceral adipose tissue and MRI-derived reference measurements.
Time frame: 4 Weeks
Agreement of blood-based proteomics-derived fat-free mass with DXA-derived fat-free mass (kg)
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
Agreement of blood-based proteomics-derived total fat mass with DXA-derived total fat mass (kg)
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 of blood-based proteomics-derived percent body fat with DXA-derived percent body fat (%)
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 of blood-based proteomics-derived visceral adipose tissue with MRI-derived visceral adipose tissue
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
Obesity and elevated visceral adipose tissue classification
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-based assessment of demographic and anthropometric effects on modality-reference measurement error
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: 4 Weeks
Between-day reliability of BIA measurements assessed by intraclass correlation coefficient (ICC)
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
Between-day reliability of 3DO measurements assessed by intraclass correlation coefficient (ICC)
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
Between-day reliability of BIA measurements assessed by technical error of measurement (TEM)
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
Between-day reliability of 3DO measurements assessed by technical error of measurement (TEM)
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: 1 Week
Exploratory predictive performance of novel 3DO-derived geometric and anthropometric features for visceral adipose tissue
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.
Time frame: 4 Weeks
Started Jun 2026 (actual). Primary completion is estimated for Nov 2026, 5 months after the start.
Of 791 non-industry observational studies under Obesity, half reached primary completion within 40 months of starting (the median), counting those still running; a quarter within 17 and three quarters within 106. This study's planned 5 months is below that.
Counting every sponsor, half of 836 studies reached it within 39 months; a quarter within 17 and three quarters within 96.
How these figures are worked out, and which studies are left out of them.
From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗
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Foundation for the National Institutes of Health