The association between body mass index and white matter hyperintensities: a cross-sectional analysis in a Tibetan population
- 1Department of Neurology, Hospital of Chengdu Office of the People's Government of Xizang Autonomous Region
Abstract
Background: White matter hyperintensities (WMH), an imaging hallmark of cerebral small vessel disease (CSVD), show inconsistent associations with body mass index (BMI) that vary with ethnicity, sex and metabolic factors. We examined the relationship of BMI with WMH severity (Fazekas score) and with the spatial distribution of WMH in a high-altitude Tibetan population.
Methods: This cross-sectional study consecutively enrolled 499 participants hospitalized for cerebrovascular or neurological disorders between 2022 and 2025. Threshold-specific binary logistic regression, adjusted for confounders, was used to evaluate BMI–WMH associations across clinically defined severity thresholds.
Results: A burden-dependent inverse association between BMI and WMH severity was observed. For total WMH burden (Fazekas score), the inverse association was more pronounced at the higher threshold (0–2 vs. 3–6: OR = 0.939, 95% CI 0.882–0.999, p = 0.047) than at the lower threshold (0–1 vs. 2–6: OR = 0.968, 95% CI 0.910–1.030, p = 0.306). For PVWMH, the association varied across thresholds (0 vs. 1–3: OR = 0.984, 95% CI 0.920–1.052, p = 0.639; 0–1 vs. 2–3: OR = 0.942, 95% CI 0.884–1.003, p = 0.064; 0–2 vs. 3: OR = 0.864, 95% CI 0.787–0.949, p = 0.002). DSWMH showed a similar pattern (0 vs. 1–3: OR = 1.014, 95% CI 0.945–1.088, p = 0.706; 0–1 vs. 2–3: OR = 0.928, 95% CI 0.872–0.988, p = 0.019; 0–2 vs. 3: OR = 0.874, 95% CI 0.796–0.959, p = 0.005). For the number of involved anatomical regions, the OR estimates were consistently below 1.0, with the strongest estimate at the highest threshold (0–3 vs. 4–10: OR = 0.947, 95% CI 0.894–1.004, p = 0.067).
Conclusion: A burden-dependent inverse association was observed between BMI and severe WMH, strongest at the most severe WMH thresholds and particularly for periventricular WMH. These findings highlight the complex relationship between adiposity and cerebrovascular injury in high-altitude populations and underscore the need for longitudinal studies to clarify the temporal dynamics of this association.
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BibTeX
@article{yao2026association,
title = {{The association between body mass index and white matter hyperintensities: a cross-sectional analysis in a Tibetan population}},
author = {Shaoli Yao and Shi-min Bao and Yi-yin Xing and Zhen-rong Qi and Hui-ru Feng and Yuling Tan and Qi Zhang and Wei-hong Ge and Xiaorong Chen},
journal = {Frontiers in Neurology},
year = {2026},
month = oct,
doi = {10.3389/fneur.2026.1805682},
url = {https://www.frontiersin.org/articles/10.3389/fneur.2026.1805682/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - The association between body mass index and white matter hyperintensities: a cross-sectional analysis in a Tibetan population
AU - Shaoli Yao
AU - Shi-min Bao
AU - Yi-yin Xing
AU - Zhen-rong Qi
AU - Hui-ru Feng
AU - Yuling Tan
AU - Qi Zhang
AU - Wei-hong Ge
AU - Xiaorong Chen
PY - 2026
DA - 2026/10/22
JO - Frontiers in Neurology
DO - 10.3389/fneur.2026.1805682
UR - https://www.frontiersin.org/articles/10.3389/fneur.2026.1805682/full
AB - Background: White matter hyperintensities (WMH), an imaging hallmark of cerebral small vessel disease (CSVD), show inconsistent associations with body mass index (BMI) that vary with ethnicity, sex and metabolic factors. We examined the relationship of BMI with WMH severity (Fazekas score) and with the spatial distribution of WMH in a high-altitude Tibetan population. Methods: This cross-sectional study consecutively enrolled 499 participants hospitalized for cerebrovascular or neurological disorders between 2022 and 2025. Threshold-specific binary logistic regression, adjusted for confounders, was used to evaluate BMI–WMH associations across clinically defined severity thresholds. Results: A burden-dependent inverse association between BMI and WMH severity was observed. For total WMH burden (Fazekas score), the inverse association was more pronounced at the higher threshold (0–2 vs. 3–6: OR = 0.939, 95% CI 0.882–0.999, p = 0.047) than at the lower threshold (0–1 vs. 2–6: OR = 0.968, 95% CI 0.910–1.030, p = 0.306). For PVWMH, the association varied across thresholds (0 vs. 1–3: OR = 0.984, 95% CI 0.920–1.052, p = 0.639; 0–1 vs. 2–3: OR = 0.942, 95% CI 0.884–1.003, p = 0.064; 0–2 vs. 3: OR = 0.864, 95% CI 0.787–0.949, p = 0.002). DSWMH showed a similar pattern (0 vs. 1–3: OR = 1.014, 95% CI 0.945–1.088, p = 0.706; 0–1 vs. 2–3: OR = 0.928, 95% CI 0.872–0.988, p = 0.019; 0–2 vs. 3: OR = 0.874, 95% CI 0.796–0.959, p = 0.005). For the number of involved anatomical regions, the OR estimates were consistently below 1.0, with the strongest estimate at the highest threshold (0–3 vs. 4–10: OR = 0.947, 95% CI 0.894–1.004, p = 0.067). Conclusion: A burden-dependent inverse association was observed between BMI and severe WMH, strongest at the most severe WMH thresholds and particularly for periventricular WMH. These findings highlight the complex relationship between adiposity and cerebrovascular injury in high-altitude populations and underscore the need for longitudinal studies to clarify the temporal dynamics of this association.
SN - 1664-2295
ER -