AzTrials
AzTrials

HealthyNCT03637855

Shape Up! Adults Study

An observational study of Healthy, run by University of Hawaii at 1 site in United States.

Completed

Finished. The study has ended and is not enrolling. Results may be posted on the official record.

Official record
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Trial summary

Identify the unique associations of body shape to body composition indices in a population that represents the variance of sex, age, BMI, and ethnicity found in the US population. Describe the precision and accuracy of 3DO scans to monitor change in body composition and metabolic health interventions. Read more about this study

Who is it for?
Ages 18 to 80 yearsHealthy volunteers can take part
Conditions the study is for
Healthy
How many people
696 participants
Where
1 siteUnited States
Study dates
1 Oct 2016to 31 Dec 2021
Phase
Observational
Are there results?
None posted in the registry

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 to 80 years
  • All sexes
  • Healthy volunteers accepted
  • Adult, Older adult

Study population: We will recruit a stratified sample of 720 participants, approximately 360 from each site, using the following equally-weighed stratifications: sex, age (18-40, 40-60, 60-80 years), BMI (less than 25, 25-30, 30 and above) and ethnicity (White, Black, Mexican-American, Asian and Native Hawaiian or Other Pacific Islander). Within this sample, we will include up to 36 participants with very low and high BMI by special recruitments from our facilities Anorexia Nervosa (AN) and bariatric surgery clinics. The remainder of the participants will be recruited as a sample of convenience using local advertisements around our facilities.

Who may be able to join

  • Healthy participants will be included in the study if they have a self-reported ability to:
  • walk one-quarter of a mile and climb 10 steps without difficulty,
  • perform activities of daily living (ADLs) without difficulty, and
  • have no life-threatening conditions or diseases that would alter their body composition from what is typical for their age, sex, ethnicity, and BMI.

Who cannot join

  • Participants will be excluded if they have any internal metal artifact (e.g. pacemakers, internal fixation, arthroplasty), amputation, physical impairment or previous fracture that would alter body composition assessment or are pregnant or breastfeeding.
  • All premenopausal females will be asked for a spot urine sample for pregnancy test prior to participation.
  • Those unwilling to comply with this will not be included.

Trial locations and contacts

1 site in 1 country.

United States1 site

  • University of Hawaii Cancer Center

    Honolulu, Hawaii, 96813

Other trials in United States

About this study

Official title: Optical Body Composition and Health Assessment (Shape Up! Adults) Study

Identify the unique associations of body shape to body composition indices in a population that represents the variance of sex, age, BMI, and ethnicity found in the US population.

Describe the precision and accuracy of 3DO scans to monitor change in body composition and metabolic health interventions.

Estimate the level of association of 3DO to common health indicators including metabolic risk factors (glucose, triglycerides, HDL-cholesterol, blood pressure, VAT, WC and strength) by gender, race, age, and BMI.

Investigate holistic, high-resolution descriptors of 3D body shape as direct predictors of body composition and metabolic risk using statistical shape models and Latent Class Analysis.

Conditions
Healthy

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Fat mass

    Measure fat mass and percent fat (arms, legs, trunk, and total) using Dual energy X-ray absorptiometry (DXA) data

    Measured: 1 day

  2. Lean mass

    Measure lean mass (arms, legs, trunk, and total) using Dual energy X-ray absorptiometry (DXA) data

    Measured: 1 day

  3. Bone mass

    Measure bone mass (arms, legs, lumbar spine, and total) and Bone Mineral Density (spine and total)

    Measured: 1 day

  4. Waist to Hip ratio (WHR) from manual tape measurement

    Manual physical anthropometry of waist and hip circumferences

    Measured: 1 day

  5. Automatic 3D optical (3DO) scan measurement

    Automated 3DO measurements generate the following: 476 girth, length, and volume measurements across the whole body.

    Measured: 1 day

  6. HUMAC NORM

    Will measure isokinetic strength of knee and back to assess muscle function

    Measured: 1 day

  7. Jamar hydraulic hand dynamometer

    Will measure grip strength to assess muscle function

    Measured: 1 day

  8. Fasting glucose levels

    Measure fasting glucose levels

    Measured: 1 day

  9. Fasting HbA1c levels

    Measure fasting HbA1c levels

    Measured: 1 day

  10. Fasting insulin levels

    Measure fasting insulin levels

    Measured: 1 day

  11. Fasting cholesterol levels

    Measure fasting cholesterol levels

    Measured: 1 day

  12. Fasting triglycerides levels

    Measure fasting triglycerides levels

    Measured: 1 day

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted20 Aug 2018
  2. Study start1 Oct 2016
  3. Primary completion31 Dec 2021
  4. Study completion31 Dec 2021

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Prospective
Enrolment
696 participants (actual)
IDs, dates and publications
ClinicalTrials.gov ID
NCT03637855
Sponsor's protocol ID
R01DK109008
Status last verified
May 2022
First submitted
19 Jul 2018
Last updated
9 May 2022
Results posted
No
Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No

Publications

  • Bennett JP, Wong MC, Liu YE, Quon BK, Kelly NN, Garber AK, Heymsfield SB, Shepherd JA. Trunk-to-leg volume and appendicular lean mass from a commercial 3-dimensional optical body scanner for disease risk identification. Clin Nutr. 2024 Oct;43(10):2430-2437. doi: 10.1016/j.clnu.2024.09.028. Epub 2024 Sep 16.

    PubMed 39305753

  • Marazzato F, McCarthy C, Field RH, Nguyen H, Nguyen T, Shepherd JA, Tinsley GM, Heymsfield SB. Advances in digital anthropometric body composition assessment: neural network algorithm prediction of appendicular lean mass. Eur J Clin Nutr. 2024 May;78(5):452-454. doi: 10.1038/s41430-023-01396-3. Epub 2023 Dec 23.

    PubMed 38142263

  • Garber AK, Bennett JP, Wong MC, Tian IY, Maskarinec G, Kennedy SF, McCarthy C, Kelly NN, Liu YE, Machen VI, Heymsfield SB, Shepherd JA. Cross-sectional assessment of body composition and detection of malnutrition risk in participants with low body mass index and eating disorders using 3D optical surface scans. Am J Clin Nutr. 2023 Oct;118(4):812-821. doi: 10.1016/j.ajcnut.2023.08.004. Epub 2023 Aug 19.

    PubMed 37598747

  • Wong MC, Bennett JP, Quon B, Leong LT, Tian IY, Liu YE, Kelly NN, McCarthy C, Chow D, Pujades S, Garber AK, Maskarinec G, Heymsfield SB, Shepherd JA. Accuracy and Precision of 3-dimensional Optical Imaging for Body Composition by Age, BMI, and Ethnicity. Am J Clin Nutr. 2023 Sep;118(3):657-671. doi: 10.1016/j.ajcnut.2023.07.010. Epub 2023 Jul 19.

    PubMed 37474106

  • McCarthy C, Tinsley GM, Yang S, Irving BA, Wong MC, Bennett JP, Shepherd JA, Heymsfield SB. Smartphone prediction of skeletal muscle mass: model development and validation in adults. Am J Clin Nutr. 2023 Apr;117(4):794-801. doi: 10.1016/j.ajcnut.2023.02.003. Epub 2023 Feb 8.

    PubMed 36822238

  • Wong MC, Bennett JP, Leong LT, Tian IY, Liu YE, Kelly NN, McCarthy C, Wong JMW, Ebbeling CB, Ludwig DS, Irving BA, Scott MC, Stampley J, Davis B, Johannsen N, Matthews R, Vincellette C, Garber AK, Maskarinec G, Weiss E, Rood J, Varanoske AN, Pasiakos SM, Heymsfield SB, Shepherd JA. Monitoring body composition change for intervention studies with advancing 3D optical imaging technology in comparison to dual-energy X-ray absorptiometry. Am J Clin Nutr. 2023 Apr;117(4):802-813. doi: 10.1016/j.ajcnut.2023.02.006. Epub 2023 Feb 14.

    PubMed 36796647

  • Wong MC, McCarthy C, Fearnbach N, Yang S, Shepherd J, Heymsfield SB. Emergence of the obesity epidemic: 6-decade visualization with humanoid avatars. Am J Clin Nutr. 2022 Apr 1;115(4):1189-1193. doi: 10.1093/ajcn/nqac005.

    PubMed 35030235

  • Panizza CE, Wong MC, Kelly N, Liu YE, Shvetsov YB, Lowe DA, Weiss EJ, Heymsfield SB, Kennedy S, Boushey CJ, Maskarinec G, Shepherd JA. Diet Quality and Visceral Adiposity among a Multiethnic Population of Young, Middle, and Older Aged Adults. Curr Dev Nutr. 2020 May 26;4(6):nzaa090. doi: 10.1093/cdn/nzaa090. eCollection 2020 Jun.

    PubMed 33959689

  • Lowe DA, Wu N, Rohdin-Bibby L, Moore AH, Kelly N, Liu YE, Philip E, Vittinghoff E, Heymsfield SB, Olgin JE, Shepherd JA, Weiss EJ. Effects of Time-Restricted Eating on Weight Loss and Other Metabolic Parameters in Women and Men With Overweight and Obesity: The TREAT Randomized Clinical Trial. JAMA Intern Med. 2020 Nov 1;180(11):1491-1499. doi: 10.1001/jamainternmed.2020.4153.

    PubMed 32986097

  • Harty PS, Sieglinger B, Heymsfield SB, Shepherd JA, Bruner D, Stratton MT, Tinsley GM. Novel body fat estimation using machine learning and 3-dimensional optical imaging. Eur J Clin Nutr. 2020 May;74(5):842-845. doi: 10.1038/s41430-020-0603-x. Epub 2020 Mar 16.

    PubMed 32203233

  • Ng BK, Sommer MJ, Wong MC, Pagano I, Nie Y, Fan B, Kennedy S, Bourgeois B, Kelly N, Liu YE, Hwaung P, Garber AK, Chow D, Vaisse C, Curless B, Heymsfield SB, Shepherd JA. Detailed 3-dimensional body shape features predict body composition, blood metabolites, and functional strength: the Shape Up! studies. Am J Clin Nutr. 2019 Dec 1;110(6):1316-1326. doi: 10.1093/ajcn/nqz218.

    PubMed 31553429

Questions about this trial

What is this clinical trial studying?

An observational study of Healthy, run by University of Hawaii at 1 site in United States.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 4 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: finished, as of the sponsor's last update on 9 May 2022. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.

How can a doctor refer a patient or contact the research team?

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Fat mass (time frame: 1 day). The study lists 12 primary outcomes in all. It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT03637855, which also lists 11 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 9 May 2022.

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