Evidence map›Paper›PMID 37574110›Full record

ArticleOsteoarthritis and cartilage2023

Associations between weight change, knee subcutaneous fat and cartilage thickness in overweight and obese individuals: 4-Year data from the osteoarthritis initiative.

Gabby B Joseph, Melia Takakusagi, Gino Arcilla, John A Lynch, Valentina Pedoia, Sharmila Majumdar, Nancy E Lane, Michael C Nevitt, Charles E McCulloch, Thomas M Link

Open access · bronzeAbstract read
In one paragraph

Article in Osteoarthritis and cartilage, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 25% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Gabby B JosephDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, United States. Electronic address: gabby.joseph@ucsf.edu.
Melia TakakusagiDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, United States.
Gino ArcillaDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, United States.
John A LynchDepartment of Epidemiology and Biostatistics, University of California, San Francisco, United States.
Valentina PedoiaDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, United States.
Sharmila MajumdarDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, United States.
Nancy E LaneDepartment of Rheumatology, University of California, Davis, United States.
Michael C NevittDepartment of Epidemiology and Biostatistics, University of California, San Francisco, United States.
Charles E McCullochDepartment of Epidemiology and Biostatistics, University of California, San Francisco, United States.
Thomas M LinkDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, United States.
University of California, San Francisco · USUniversity of California, Davis · US

Funding

Understanding the mechanisms by which weight change affects progression of knee osteoarthritis in obese and overweight individuals: An analysis of the Osteoarthritis Initiative DatasetR01AR078917 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GABRIELLE JOSEPH, THOMAS M LINK · 2021 to 2026
$3.4M
The Study of Muscle, Mobility and Aging with Knee OAR01AG070647 · NIA · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Nancy E Lane · 2021 to 2026
$2.5M
Impact of Weight loss on Knee Joint Biochemical and Structural DegenerationR01AR064771 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LINK, THOMAS M · 2014 to 2019
$1.6M
NIAMS NIH HHS R01 AR064771NIAMS NIH HHS R01 AR078917NIA NIH HHS R01 AG070647
6 · The paper itself

Abstract

objectiveTo assess (i) the impact of changes in body weight on changes in joint-adjacent subcutaneous fat (SCF) and cartilage thickness over 4 years and (ii) the relation between changes in joint-adjacent SCF and knee cartilage thickness.

designIndividuals from the Osteoarthritis Initiative (total=399) with > 10% weight gain (n=100) and > 10% weight loss (n=100) over 4 years were compared to a matched control cohort with less than 3% change in weight (n=199). 3.0T Magnetic Resonance Imaging (MRI) of the right knee was performed at baseline and after 4 years to quantify joint-adjacent SCF and cartilage thickness. Linear regression models were used to evaluate the associations between the (i) weight change group and 4-year changes in both knee SCF and cartilage thickness, and (ii) 4-year changes in knee SCF and in cartilage thickness. Analyses were adjusted for age, sex, baseline body mass index (BMI), tibial diameter (and weight change group in analysis (ii)).

resultsIndividuals who lost weight over 4-years had significantly less joint-adjacent SCF (beta range, medial/lateral joint sides: 2.2-4.2 mm, p < 0.001) than controls; individuals who gained weight had significantly greater joint-adjacent SCF than controls (beta range: -1.4 to -3.9 mm, p < 0.001). No statistically significant associations were found between weight change and cartilage thickness change. However, increases in joint-adjacent SCF over 4 years were significantly associated with decreases in cartilage thickness (p = 0.04).

conclusionsWeight change was associated with joint-adjacent SCF, but not with change in cartilage thickness. However, 4-year increases in joint-adjacent SCF were associated with decreases in cartilage thickness independent of baseline BMI and weight change group.

Indexed as

Cartilage, ArticularOsteoarthritis, KneeHumansKnee JointMagnetic Resonance ImagingObesityOverweightSubcutaneous FatCartilage thicknessKnee subcutaneous fatMRIWeight change

Identifiers

PMID37574110
PMCPMC10848315
OpenAlexW4385798153

What OpenQuestion holds

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Registered trials

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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.