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Jonathan P. Bennett, PhD

Jonathan P. Bennett, PhD

Junior Researcher

Jon’s background (BS Biology, BS Psychology, MS Kinesiology) aims to build on the intersection of diet, exercise, and behavior on body composition and health. His research focuses on the application of multicompartment body composition modeling and its utility in a variety of medical settings as well as in athletes and across the lifespan. He chairs the Body Composition section of the International Society for Clinical Densitometry, and in May 2026 he moved from an RCUH postdoctoral researcher to a UH Junior Researcher — the role under which he serves as principal investigator on a Thrasher Research Fund award validating a tablet-based optical scanner for infant body composition. Jon’s PhD is in Nutritional Sciences; he moved to Hawaii with his cat, Milky, who retired from his career as a milkman to also pursue a PhD in dairy science.

Publications (34)

  • Visual demonstration of weight loss and health risk improvement with a dual GIP and GLP-1 receptor agonist
    Ramirez S, Yang R, Habibovic M, Kennedy S, Bennett JP, Shepherd JA, Thomas DM, Heymsfield SB
    International Journal of Obesity, 2025· doi:10.1038/s41366-025-01842-1
  • Comparing body composition techniques against an adapted multicompartment model in individuals with excess body weight
    Montenegro J, Bennett JP, Oliveira CLP, Berg A, Sharma AM, Mereu L, Shepherd J, Siervo M, Walter J, Prado CM
    Nutrition, 2025· doi:10.1016/j.nut.2025.113033
  • Association of body composition measures to muscle strength using DXA, D3Cr, and BIA in collegiate athletes
    Cataldi D, Bennett JP, Quon BK, Leong LT, Kelly TL, Binder AM, Evans JW, PRADO C, Heymsfield SB, Shepherd J
    Scientific Reports, 2025· doi:10.1038/s41598-025-87918-4
  • Improving Body Composition Analysis in Oncology: Do Measures From Multicompartment, 2C and CT Agree? Implications for Monitoring Sarcopenia Risk
    Bennett JP, Ford KL, Siervo M, González MC, Lukaski HC, Sawyer MB, Mourtzakis M, Deutz NE, Shepherd J, Prado CM
    Current Developments in Nutrition, 2024· doi:10.1016/j.cdnut.2024.102322
  • Accurate Prediction of 3D Humanoid Avatars for Anthropometric Modeling
    Heymsfield SB, McCarthy C, Wong M, Brown J, Bennett JP, Shepherd J
    Current Developments in Nutrition, 2024· doi:10.1016/j.cdnut.2024.103558
  • Accurate prediction of three-dimensional humanoid avatars for anthropometric modeling
    McCarthy C, Wong MC, Brown J, Ramirez S, Yang S, Bennett JP, Shepherd J, Heymsfield SB
    International Journal of Obesity, 2024· doi:10.1038/s41366-024-01614-3
  • Evaluation of body shape as a human body composition assessment in isolated conditions and remote environments
    Wong MC, Bennett JP, Leong LT, Liu YE, Kelly NN, Cherry JA, Kloza K, Li B, Iuliano S, Sibonga JD, Sawyer A, Ayton J, Shepherd J
    npj Microgravity, 2024· doi:10.1038/s41526-024-00412-5
  • Trunk-to-leg volume and appendicular lean mass from a commercial 3-dimensional optical body scanner for disease risk identification
    Bennett JP, Wong MC, Liu YE, Quon BK, Kelly NN, Garber AK, Heymsfield SB, Shepherd J
    Clinical Nutrition, 2024· doi:10.1016/j.clnu.2024.09.028
  • Advancing body composition assessment in patients with cancer: First comparisons of traditional versus multicompartment models
    Bennett JP, Ford KL, Siervo M, González MC, Lukaski HC, Sawyer MB, Mourtzakis M, Deutz NE, Shepherd J, Prado CM
    Nutrition, 2024· doi:10.1016/j.nut.2024.112494
  • Evaluation of visceral adipose tissue thresholds for elevated metabolic syndrome risk across diverse populations: A systematic review
    Bennett JP, Prado CM, Heymsfield SB, Shepherd J
    Obesity Reviews, 2024· doi:10.1111/obr.13767
  • Variations in bioelectrical impedance devices impact raw measures comparisons and subsequent prediction of body composition using recommended estimation equations
    Bennett JP, Cataldi D, Liu YE, Kelly NN, Quon BK, González MC, Heymsfield SB, Shepherd J
    Clinical Nutrition ESPEN, 2024· doi:10.1016/j.clnesp.2024.07.009
  • Medical imaging measurement of visceral adipose tissue thresholds associated with increased risk of cardiometabolic disease
    Bennett JP, Wong MC, Prado CM, Heymsfield SB, Shepherd J
    Journal of Clinical Densitometry, 2023· doi:10.1016/j.jocd.2023.101387
  • Accuracy and Precision of Multiple Laboratory and Field Methods to The Criterion In Vivo Five-Compartment Body Composition Model and Their Association with Muscle Strength in Collegiate Athletes of Varying States of Hydration: The Da Kine Protocol Study
    Cataldi D, Bennett JP, Wong MC, Quon BK, Liu YE, Kelly NN, Kelly TL, Schoeller DA, Heymsfield SB, Shepherd J
    medRxiv, 2023· doi:10.1101/2023.05.30.23290630
  • Association of Muscle Strength to Body Composition Measures using DXA, D 3 Cr, and BIA in Collegiate Athletes
    Cataldi D, Bennett JP, Quon BK, Leong LT, Kelly TL, Evans WJ, Prado CM, Heymsfield SB, Shepherd J
    medRxiv, 2023· doi:10.1101/2023.05.17.23288849
  • Reply to Y Lu et al.
    Bennett JP, Liu YE, Kelly NN, Quon BK, Wong MC, McCarthy C, Heymsfield SB, Shepherd J
    American Journal of Clinical Nutrition, 2023· doi:10.1016/j.ajcnut.2023.01.004
  • Predictors of visceral and subcutaneous adipose tissue and muscle density: The ShapeUp! Kids study
    Maskarinec G, Shvetsov YB, Wong MC, Cataldi D, Bennett JP, Garber AK, Buchthal SD, Heymsfield SB, Shepherd J
    Nutrition Metabolism and Cardiovascular Diseases, 2023· doi:10.1016/j.numecd.2023.12.014
  • Visceral adipose tissue reference data computed for GE HealthCare DXA from the National Health and Nutrition Examination Survey data set
    Bennett JP, Quon BK, Fan B, Liu E, Kazemi L, Villegas‐Valle RC, Ahgun R, Wu X, Zhou H, Lü Y, Shepherd J
    Obesity, 2023· doi:10.1002/oby.23888
  • Development and validation of a rapid multicompartment body composition model using 3-dimensional optical imaging and bioelectrical impedance analysis
    Bennett JP, Cataldi D, Liu YE, Kelly NN, Quon BK, Schoeller DA, Kelly TL, Heymsfield SB, Shepherd J
    Clinical Nutrition, 2023· doi:10.1016/j.clnu.2023.12.009
  • 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
    Garber AK, Bennett JP, Wong MC, Tian IY, Maskarinec G, Kennedy S, McCarthy C, Kelly NN, Liu YE, Machen VI, Heymsfield SB, Shepherd J
    American Journal of Clinical Nutrition, 2023· doi:10.1016/j.ajcnut.2023.08.004
  • Accuracy and precision of multiple body composition methods and associations with muscle strength in athletes of varying hydration: The Da Kine Study
    Cataldi D, Bennett JP, Wong MC, Quon BK, Liu YE, Kelly NN, Kelly TL, Schoeller DA, Heymsfield SB, Shepherd J
    Clinical Nutrition, 2023· doi:10.1016/j.clnu.2023.11.040
  • Accuracy and Precision of 3-dimensional Optical Imaging for Body Composition by Age, BMI, and Ethnicity
    Wong MC, Bennett JP, Quon BK, Leong LT, Tian IY, Liu YE, Kelly NN, McCarthy C, Chow DC, Pujades S, Garber AK, Maskarinec G, Heymsfield SB, Shepherd J
    American Journal of Clinical Nutrition, 2023· doi:10.1016/j.ajcnut.2023.07.010
  • Standardization of dual‐energy x‐ray visceral adipose tissue measures for comparison across clinical imaging systems
    Bennett JP, Fan B, Liu E, Kazemi L, Wu X, Zhou H, Lü Y, Shepherd J
    Obesity, 2023· doi:10.1002/oby.23885
  • Monitoring body composition change for intervention studies with advancing 3D optical imaging technology in comparison to dual-energy X-ray absorptiometry
    Wong MC, Bennett JP, Leong LT, Tian IY, Liu YE, Kelly NN, McCarthy C, Wong JM, Ebbeling CB, Ludwig DS, Irving BA, Scott MC, Stampley J, Davis B, Johannsen NM, Matthews R, Vincellette C, Garber AK, ...
    American Journal of Clinical Nutrition, 2023· doi:10.1016/j.ajcnut.2023.02.006
  • Smartphone prediction of skeletal muscle mass: model development and validation in adults
    McCarthy C, Tinsley GM, Yang S, Irving BA, Wong MC, Bennett JP, Shepherd J, Heymsfield SB
    American Journal of Clinical Nutrition, 2023· doi:10.1016/j.ajcnut.2023.02.003
  • Accuracy and Precision of 3D Optical Imaging for Body Composition and their Associations to Metabolic Markers by Age, BMI, and Ethnicity
    Wong MC, Bennett JP, Quon BK, Leong LT, Tian IY, Liu YE, Kelly NN, McCarthy C, Chow DC, Pujades S, Garber AK, Maskarinec G, Heymsfield SB, Shepherd J
    medRxiv, 2022· doi:10.1101/2022.11.02.22281819

See all 34 publications →

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