Evidence map›Paper›PMID 40051020›Full record

Trial reportObesity (Silver Spring, Md.)2025

Musculoskeletal characteristics in older adults with overweight or obesity: INVEST in Bone Health trial baseline analysis.

S Delanie Lynch, Marjorie Howard, Daniel P Beavers, Leon Lenchik, Ryan Barnard, Joshua R Stapleton, Erica Lawrence, Peggy M Cawthon, Fang-Chi Hsu, Kristen M Beavers and 1 more

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Obesity (Silver Spring, Md.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04076618 (Incorporating Nutrition, Vests, Education, and Strength Training in Bone Health), which is not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04076618 nacompletednot on this map

Incorporating Nutrition, Vests, Education, and Strength Training in Bone Health (INVEST in Bone Health)

TypeinterventionalSponsorWake Forest University Health SciencesRan2020 to 2024Enrolled150ConditionsWeight Loss, Bone HealthArmsVest, Resistance Exercise Training, weight loss program
3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

S Delanie LynchDepartment of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.ORCID https://orcid.org/0000-0003-4074-4410
Marjorie HowardDepartment of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.
Daniel P BeaversDepartment of Statistical Sciences, Wake Forest University, Winston-Salem, North Carolina, USA.
Leon LenchikDepartment of Radiology, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.
Ryan BarnardDepartment of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.
Joshua R StapletonDepartment of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.
Erica LawrenceDepartment of Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.
Peggy M CawthonCalifornia Pacific Medical Center Research Institute, San Francisco, California, USA.
Fang-Chi HsuDepartment of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.
Kristen M BeaversDepartment of Health and Exercise Science, Wake Forest University, Winston-Salem, North Carolina, USA.ORCID https://orcid.org/0000-0002-7786-4195
Ashley A WeaverDepartment of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.ORCID https://orcid.org/0000-0002-4383-0106

Funding

Wake Forest Claude D. Pepper OAIC - RenewalP30AG021332 · NIA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Denise Kathryn Houston · 2002 to 2026
$36.4M
Wake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3M
Incorporating Nutrition, Vests, Education, and Strength Training in Bone Health (INVEST in Bone Health)R01AG059186 · NIA · WAKE FOREST UNIVERSITY · PI BEAVERS, KRISTEN MARIE · 2019 to 2023
$3.0M
Effect of protein supplementation during weight loss on older adult bone healthK25AG058804 · NIA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI WEAVER, ASHLEY · 2019 to 2023
$672k
INVESTigations of Muscle and Bone Health: Developing Automated Approaches for CT-Based AnalysesF31AG086010 · NIA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI LYNCH, DELANIE · 2024 to 2025
$99k
Jason Pharmaceuticals, Inc., a wholly owned subsidiary of Medifast, Inc.National Center for Advancing Translational Sciences (NCATS) UL1TR001420NCATS NIH HHS UL1 TR001420NIA NIH HHS F31 AG086010NIA NIH HHS F31AG086010NIA NIH HHS K25 AG058804NIA NIH HHS K25AG058804NIA NIH HHS P30 AG021332NIA NIH HHS P30AG021332NIA NIH HHS R01 AG059186NIA NIH HHS R01AG059186
6 · The paper itself

Abstract

objectiveThe objective of this study was to examine associations of computed tomography (CT)-derived musculoskeletal measures with demographics and traditional musculoskeletal characteristics.

methodsThe Incorporating Nutrition, Vests, Education, and Strength Training (INVEST) in Bone Health trial (NCT04076618) acquired a battery of musculoskeletal measures in 150 older-aged adults living with overweight or obesity. At baseline, CT (i.e., volumetric bone mineral density, cortical thickness, muscle radiomics, and muscle/intermuscular adipose tissue [IMAT] area and density), dual-energy x-ray absorptiometry (DXA; i.e., areal bone mineral density, total body fat mass, appendicular lean mass, and lean body mass), and strength assessments (i.e., grip and knee extensor strength) were collected, along with demographic and clinical characteristics. Analyses employed linear regression and mixed-effects models along with factor analysis for dimensionality reduction of the radiomics data.

resultsParticipants were older-aged (mean [SD] age: 66 [5] years), mostly female (75%), and were living with overweight or obesity (mean [SD] BMI: 33.6 [3.3] kg/m

conclusionsMachine learning-derived CT metrics correlated strongly with DXA and muscle strength, with higher BMI linked to greater IMAT and poorer muscle quality.

Indexed as

ObesityOverweightAbsorptiometry, PhotonAgedBody CompositionBody Mass IndexBone DensityFemaleHand StrengthHumansMaleMiddle AgedMuscle, SkeletalMuscle StrengthTomography, X-Ray Computed

Identifiers

PMID40051020
PMCPMC12353373

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.