Severity and stroke type according to waist-Hip ratio, body mass index and waist circumference
- PMID: 40828254
- DOI: 10.1007/s00702-025-02996-y
Severity and stroke type according to waist-Hip ratio, body mass index and waist circumference
Abstract
The aim of this study was to explore the effect of waist-to-hip ratio (WHR), body mass index (BMI) and waist circumference (WC) on stroke severity. A population-based cross-sectional, observational prospective cohort study was conducted from 2022 to 2023 in Bosnia and Herzegovina. A total of 440 subjects were included in the cohort divided into two groups. The first group consisted of 220 patients with stroke (S), and the second group from 220 subjects without S (control, C). We measured the WHR, BMI and WC. The National Institutes of Health Stroke Scale was used to assess the S severity. The largest number of subjects of both groups have BMI in the category of increased body weight, (57.7% of patients with, and 56.8% of subjects without S). The average BMI (in kg/m2) was slightly higher in the S group and amounted to 28.2 ± 4.2 in comparison to the C with the average BMI of 27.6 ± 3.9. The average WHR was almost identical in both groups (0.55 ± 0.07 in S group, 0.55 ± 0.06 in C). The largest number of patients (n = 140, 63.6%) had a moderate to severe S. The largest WC (in cm) had patients with a hemorrhagic S (HS) 96.4 ± 15.5, compared to patients with thrombotic S (TS) 94.9 ± 11.9, and embolic S (ES) 94.5 ± 10.2. The average BMI was slightly higher in ES group (28.5 ± 2.8) in comparison to HS (28.4 ± 5.9) and TS (28.1 ± 4.2). WHR was almost identical in all three types of S. In conclusion, WHR, BMI and WC may be good risk factors for stroke risk assessment.
Keywords: Body mass index; Stroke; Waist circumference; Waist to hip ratio.
© 2025. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
Conflict of interest statement
Declarations. Conflict of interest: The authors report no disclosures relevant to the manuscript.
References
-
- Aigner A, Grittner U, Rolfs A et al (2017) Contribution of established stroke risk factors to the burden of stroke in young adults. Stroke 48(7):1744–1751. https://doi.org/10.1161/STROKEAHA.117.016599 - DOI - PubMed
-
- Aparicio HJ, Demissie S, Himali JJ et al (2019) Abdominal obesity predicts stroke risk in the Framingham study. Abstract TMP55/MP55. Presented at: International Stroke Conference; Feb. 6–8, Honolulu
-
- Bazzano LA, Gu D, Whelton MR et al (2010) Body mass index and risk of stroke among Chinese men and women. Ann Neurol 67(1):11–20. https://doi.org/10.1002/ana.21950 - DOI - PubMed - PMC
-
- Bjerkreim AT, Khanevski AN, Thomassen L et al (2019) Five-year readmission and mortality differ by ischemic stroke subtype. J Neurol Sci 403:31–37. https://doi.org/10.1016/j.jns.2019.06.007 - DOI - PubMed
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