Evidence map›Paper›PMID 39376216›Full record

ArticleFrontiers in dementia2024

Interactions between muscle volume and body mass index on brain structure in the UK Biobank.

Alicia Lu, Stephanie Than, Richard Beare, Alexandra La Hood, Taya Annabelle Collyer, Velandai Srikanth, Chris Moran

Abstract read
In one paragraph

Article in Frontiers in dementia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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.

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

3 citing papers in PubMed.

  1. Relationship between cardiac index and brain volume in the UK Biobank.Cerebral circulation - cognition and behavior · 2026
    Article
  2. Review
  3. Review
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

7 authors.

Alicia LuPeninsula Clinical School, School of Translational Medicine, Monash University, Frankston, VIC, Australia.
Stephanie ThanPeninsula Clinical School, School of Translational Medicine, Monash University, Frankston, VIC, Australia.
Richard BearePeninsula Clinical School, School of Translational Medicine, Monash University, Frankston, VIC, Australia.
Alexandra La HoodDepartment of Geriatric Medicine, Peninsula Health, Mornington, VIC, Australia.
Taya Annabelle CollyerPeninsula Clinical School, School of Translational Medicine, Monash University, Frankston, VIC, Australia.
Velandai SrikanthPeninsula Clinical School, School of Translational Medicine, Monash University, Frankston, VIC, Australia.
Chris MoranPeninsula Clinical School, School of Translational Medicine, Monash University, Frankston, VIC, Australia.

Funding

Identifying lifelong factors that impact brain health and outcomes in type 1 diabetes: The Cognition and Longitudinal Assessments of Risk Factors over 30 Years (CLARiFY) Diabetes Complications StudyR01DK129320 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI FELDMAN, EVA LUCILLE · 2021 to 2025
$2.3M
NIDDK NIH HHS R01 DK129320Wellcome Trust
6 · The paper itself

Abstract

Background: Low skeletal muscle volume may increase dementia risk through mechanisms affecting brain structure. However, it is unclear whether this relationship exists outside of sarcopenia and/or varies by other factors. We aimed to study the interplay between skeletal muscle volume and factors, such as age, sex, and body mass index (BMI), in explaining brain structure at midlife in a cohort without sarcopenia. Methods: We used abdominal and brain magnetic resonance imaging (MRI) data from a population-based cohort enrolled in the UK Biobank. The following measures were derived: thigh fat-free muscle volume (FFMV), total brain volume (TBV), gray matter volume (GMV), white matter volume (WMV), total hippocampal volume (THV), and white matter hyperintensity volume (WMHV). Participants below sex-based grip strength thresholds suggesting probable sarcopenia were excluded. Linear regression analysis was used to study the interaction or mediation effects of age, sex, and BMI on the associations between FFMV and brain volumes. Results: Data were available for 20,353 participants (median age 64 years, 53% female). We found interactions between thigh FFMV, BMI, and age (all Conclusion: Greater thigh muscle volume correlates with better brain volumes at midlife in people without sarcopenia, but this relationship weakens with greater age and BMI. Further study is required to investigate the underlying mechanisms to understand which components of body composition are potentially modifiable risk factors for dementia.

Indexed as

body compositionbrain structurebrain volumesobesityskeletal muscle volumeUK Biobank

Identifiers

PMID39376216
PMCPMC11456486

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.