Hyperuricemia (HUA) is an escalating public health challenge, yet systematic epidemiological data regarding its distribution across different high-altitude gradients remain limited. A multicenter, cross-sectional survey was conducted involving 1264 Tibetan residents across three altitudinal gradients: Nyingchi (~2900m), Lhasa-Shigatse (~3700m), and Ngari (~4300m). Logistic regression and Restricted Cubic Spline (RCS) models were employed to identify independent risk factors and explore their non-linear risk trajectories. The overall crude HUA prevalence was 22.6%, demonstrating a marked sex disparity (45.8% in males vs. 5.4% in females). HUA prevalence exhibited a non-linear spatial distribution, peaking in the highest-altitude region (Ngari). Multivariate analysis identified male sex, hypertension, body mass index (BMI) ≥24 kg/m², dyslipidemia, high altitude polycythemia and elevated serum creatinine (Scr) as independent risk factors. RCS models revealed significant non-linear continuous increases in HUA risk associated with elevated BMI and Scr levels. Conclusion: HUA prevalence in high-altitude Tibetan populations is associated with regional effects and metabolic factors. Public health strategies incorporating weight management and routine metabolic monitoring may be beneficial for this population. HUA prevalence in high-altitude Tibetan populations is associated with regional effects and metabolic factors. Public health strategies incorporating weight management and routine metabolic monitoring may be beneficial for this population. Not applicable.
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Yin et al. (2026) studied this question.
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