| Title: | Automated abdominal aortic calcification, muscle health and incident falls: the UK Biobank Imaging Study |
| Journal: | Journal of Bone and Mineral Research |
| Published: | 21 May 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42166179/ |
| DOI: | https://doi.org/10.1093/jbmr/zjag084 |
Publication 19964
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Abstract
Emerging evidence suggests that vascular disease is linked with poorer muscle strength and higher falls risk. We evaluated the association between abdominal aortic calcification (AAC), scored using a well-established and validated 24-point machine learning algorithm (ML-AAC24), with magnetic resonance imaging-derived fat-free muscle volume (FFMV, n=33,640) and muscle fat infiltration (MFI, n=33,640), appendicular lean mass (ALM, n=36,526), handgrip strength (HGS, n=49,049), sarcopenia (n=35,834) and incident falls (n=48,482) in community-dwelling adults (mean age 64.6 ± 7.8 years, 50.9% women). ML-AAC24 was assessed on dual-energy X-ray absorptiometry (DXA)-derived lateral spine images and classified into established categories based on severity; low (<2), moderate (2-5) and high (≥6). Age and sex specific cut-points for low FFMV and sex-specific high MFI were based on previous work. Low ALM, weak HGS and sarcopenia were based on the revised European sarcopenia guidelines. The associations between ML-AAC24 extent, odds of having poorer muscle health measures and incident falls were tested in multivariable-adjusted logistic and Cox proportional hazards regressions, respectively. Individuals with moderate and high, compared to low ML-AAC24, had greater odds for low FFMV (1.58, 95%CI: 1.28-1.95 and 2.52, 95%CI: 1.88-3.38, respectively), high MFI (1.09, 95%CI: 1.01-1.18 and 1.45, 95%CI: 1.29-1.64, respectively), and low ALM (1.14, 95%CI: 1.04-1.24 and 1.28, 95%CI: 1.11-1.47, respectively). They also had higher odds for weak HGS (1.18, 95%CI: 1.07-1.29 and 1.24, 95%CI:1.09-1.42, respectively) and sarcopenia (1.40, 95%CI:1.12-1.76 and 1.69, 95%CI:1.24-2.29, respectively). Compared to low ML-AAC24, high ML-AAC24 was associated with greater hazards for an incident fall-related hospitalisation (1.31, 95%CI: 1.02-1.68). Greater ML-AAC24 extent, which can be opportunistically identified during routine bone density testing, was associated with poorer muscle composition and, function, sarcopenia and incident falls in community-dwelling adults. Such findings may explain previous reports between AAC and higher fall and fracture risk, supporting a nexus between vascular and musculoskeletal health.</p>
20 Authors
- Abadi K Gebre
- Cassandra Smith
- James Webster
- Afsah Saleem
- Syed Zulqarnain Gilani
- David Suter
- Yuandan Zhang
- Gustavo Duque
- Robin M Daly
- Emma L Duncan
- Namki Hong
- Parminder Raina
- Douglas P Kiel
- William D Leslie
- John T Schousboe
- John P Kemp
- Richard L Prince
- Nicholas C Harvey
- Joshua R Lewis
- Marc Sim
1 Application
| Application ID | Title |
|---|---|
| 93712 | Machine Learning on Densitometric Imaging for Novel Cardiometabolic & Musculoskeletal Health Phenotypes of Disease and their Developmental Origins |
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