| Title: | Association between metabolic syndrome and incident stroke: insights from the UK Biobank |
| Journal: | Frontiers in Neurology |
| Published: | 13 Apr 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42057935/ |
| DOI: | https://doi.org/10.3389/fneur.2026.1803011 |
| URL: | https://public-pages-files-2025.frontiersin.org/journals/neurology/articles/10.3389/fneur.2026.1803011/pdf |
Publication 18017
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Abstract
Background: Metabolic syndrome (MetS) is a cluster of metabolic abnormalities associated with increased cardiovascular risk. This study examined the association between MetS and incident stroke in the UK Biobank.</p>
Methods: This population-based prospective cohort study included 329,887 participants free of stroke at baseline. MetS was defined as the presence of at least three of the following components: elevated waist circumference, elevated blood glucose, elevated blood pressure, elevated triglycerides, and reduced high-density lipoprotein cholesterol. Incident all-cause stroke was identified using hospital inpatient records, death registries, and self-reported data, whereas ischemic and hemorrhagic stroke were identified using hospital records and death registries only. Cox proportional hazards models were used to evaluate the associations of MetS, its individual components, and the number of MetS components with incident stroke.</p>
Results: Over a median follow-up of 14.1 years, 6,716 incident stroke cases were recorded. MetS was associated with a higher risk of incident all-cause stroke (HR, 1.35; 95% CI, 1.28-1.42) and ischemic stroke (HR, 1.50; 95% CI, 1.41-1.60), but not hemorrhagic stroke (HR, 1.07; 95% CI, 0.96-1.20). Stroke risk increased with the number of MetS components. All individual MetS components were significantly associated with incident all-cause stroke, with elevated blood pressure showing the strongest association.</p>
Conclusion: MetS was significantly associated with incident all-cause stroke and ischemic stroke, but not hemorrhagic stroke, in this UK population.</p>
5 Authors
- Yan Zhou
- Jicun Zhu
- HuiMin Liu
- Qiang Zhang
- Jiajun Chen
1 Application
| Application ID | Title |
|---|---|
| 772449 | Integrating Multi-Omics and Imaging Data for Mechanistic Insights and Risk Prediction in Disease Pathogenesis |
Enabling scientific discoveries that improve human health