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AimThe Triglyceride-Glucose (TyG) index, an indicator of insulin resistance, has been proposed as a predictor of cardiovascular diseases. However, its role in predicting stroke risk, particularly in low-income populations, is not well understood. This study aimed to investigate the predictive value of the TyG index for stroke incidence in a low-income Chinese population, with a focus on gender and age-specific differences.MethodsThis 10-year prospective cohort study included 3,534 participants aged ≥45 years from rural areas in northern China. Baseline data on demographic characteristics, lifestyle factors, and clinical measurements were collected. Participants were followed for stroke incidence, categorized into ischemic and hemorrhagic stroke. Multivariate logistic regression models were used to assess the association between the TyG index and stroke incidence, adjusting for potential confounders.ResultsDuring the follow-up period, 368 participants (10.4%) experienced a stroke, with 327 ischemic and 31 hemorrhagic strokes. TyG index was significantly associated with total and ischemic stroke incidence but not hemorrhagic stroke. After adjusting for confounding factors, for every one standard deviation increase in TyG index, the risk of stroke increased by 32% for overall stroke (RR: 1.32; 95% CI: 1.08-1.61; P=0.006) and 39% for ischemic stroke (RR: 1.39; 95% CI: 1.12-1.73; P=0.003). The risk of stroke in the highest TyG tertile levels (tertile 3) increased by 49% (RR: 1.49; 95% CI 1.11-1.99; P=0.007) for overall stroke, compared to those in the lowest tertile levels (tertile 1). For ischemic stroke, the risk of stroke increased by 53% (RR: 1.53; 95% CI 1.12-2.11; P=0.008) in the highest TyG tertile levels (tertile 3) compared to those in the lowest tertile levels (tertile 1).ConclusionThis 10-year prospective cohort study has established the TyG index as an independent predictor of both total and ischemic stroke incidence in a low-income Chinese population. The findings indicate that the TyG index is particularly effective in predicting stroke risk among women and older adults (≥60 years), but not for hemorrhagic stroke. These insights are crucial for improving clinical practice and stroke prevention strategies. |
