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NCT03637855

Shape Up! Adults Study

Completed Last updated 9 May 2022
What this trial tests

trial in Healthy in 696 participants. Completed in 31 December 2021.

Timeline
1 October 2016
Primary endpoint
31 December 2021
31 December 2021

Quick facts

Lead sponsorUniversity of Hawaii
StatusCompleted
Study typeOBSERVATIONAL
Enrollment696
Start date1 October 2016
Primary completion31 December 2021
Estimated completion31 December 2021
Sites1 location across United States

Conditions studied

Sponsor

University of Hawaii

Who can join

Adults 18 to 80, any sex, with Healthy. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

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.

Publications & conference data

8 peer-reviewed publications reference this trial (live from Europe PMC):

  1. 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.
    Lowe DA, Wu N, Rohdin-Bibby L, Moore AH, et al · · 2020 · cited 375× · PMID 32986097 · DOI 10.1001/jamainternmed.2020.4153
  2. Detailed 3-dimensional body shape features predict body composition, blood metabolites, and functional strength: the Shape Up! studies.
    Ng BK, Sommer MJ, Wong MC, Pagano I, et al · · 2019 · cited 72× · PMID 31553429 · DOI 10.1093/ajcn/nqz218
  3. Improved strength prediction combining clinically available measures of skeletal muscle mass and quality.
    Bourgeois B, Fan B, Johannsen N, Gonzalez MC, et al · · 2019 · cited 53× · PMID 30371008 · DOI 10.1002/jcsm.12353
  4. Assessment of clinical measures of total and regional body composition from a commercial 3-dimensional optical body scanner.
    Bennett JP, Liu YE, Quon BK, Kelly NN, et al · · 2022 · cited 37× · PMID 34915272 · DOI 10.1016/j.clnu.2021.11.031
  5. Novel body fat estimation using machine learning and 3-dimensional optical imaging.
    Harty PS, Sieglinger B, Heymsfield SB, Shepherd JA, et al · · 2020 · cited 36× · PMID 32203233 · DOI 10.1038/s41430-020-0603-x
  6. Anthropometric evaluation of a 3D scanning mobile application.
    Smith B, McCarthy C, Dechenaud ME, Wong MC, et al · · 2022 · cited 31× · PMID 35491718 · DOI 10.1002/oby.23434
  7. Predicting 3D body shape and body composition from conventional 2D photography.
    Tian IY, Ng BK, Wong MC, Kennedy S, et al · · 2020 · cited 27× · PMID 32978970 · DOI 10.1002/mp.14492
  8. Smartphone prediction of skeletal muscle mass: model development and validation in adults.
    McCarthy C, Tinsley GM, Yang S, Irving BA, et al · · 2023 · cited 25× · PMID 36822238 · DOI 10.1016/j.ajcnut.2023.02.003

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Other recruiting trials for Healthy

Currently open trials in the same condition.

Other University of Hawaii trials

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Data sources for this page

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