Shape Up! Adults Study

NCT03637855 | Completed DMC

• 1 other identifier: R01DK109008
• Study Type: observational
• Target: 696
• Locations: 1 country
• Sites: 1

Brief 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. 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

Outcome Measures

Primary Outcomes (12)

• Fat mass

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

  1 day

• Lean mass

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

  1 day

• Bone mass

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

  1 day

• Waist to Hip ratio (WHR) from manual tape measurement

  Manual physical anthropometry of waist and hip circumferences

  1 day

• Automatic 3D optical (3DO) scan measurement

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

  1 day

• HUMAC NORM

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

  1 day

• Jamar hydraulic hand dynamometer

  Will measure grip strength to assess muscle function

  1 day

• Fasting glucose levels

  Measure fasting glucose levels

  1 day

• Fasting HbA1c levels

  Measure fasting HbA1c levels

  1 day

• Fasting insulin levels

  Measure fasting insulin levels

  1 day

• Fasting cholesterol levels

  Measure fasting cholesterol levels

  1 day

• Fasting triglycerides levels

  Measure fasting triglycerides levels

  1 day

Other Outcomes (10)

• Fat loss

  24 weeks

• Changes in lean mass

  24 weeks

• Changes in WHR

  24 weeks

Eligibility Criteria

• Age: 18 Years - 80 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

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.

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• University of Hawaii: lead

Study Sites (1)

University of Hawaii Cancer Center

Honolulu, Hawaii, 96813, United States

Location

Related Publications (10)

• 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.

  PMID: 38142263 DERIVED

• 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.

  PMID: 37598747 DERIVED

• 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.

  PMID: 37474106 DERIVED

• 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.

  PMID: 36822238 DERIVED

• 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.

  PMID: 36796647 DERIVED

• 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.

  PMID: 35030235 DERIVED

• 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.

  PMID: 33959689 DERIVED

• 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.

  PMID: 32986097 DERIVED

• 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.

  PMID: 32203233 DERIVED

• 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.

  PMID: 31553429 DERIVED

Study Officials

• John Shepherd, PhD

  University of Hawaii Cancer Research Center

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 19, 2018
• First Posted: August 20, 2018
• Study Start: October 1, 2016
• Primary Completion: December 31, 2021
• Study Completion: December 31, 2021
• Last Updated: May 9, 2022

Record last verified: 2022-05

Locations

US (1)