The causal relationship between triglycerides and myocardial infarction (MI) was investigated using Mendelian randomization (MR) studies. Triglycerides were the exposure factor, and MI served as the outcome variable. Inverse variance weighting was used as the main analysis method, MR-Egger, and weight median as other analysis methods for MR analysis. In addition, heterogeneity test, level multivariate analysis, and sensitivity analysis were carried out. Inverse variance weighting results showed that the increase in triglyceride level affected the incidence of MI (OR = 1.287; 95% CI = 1.185-1.398; P = 1.988 × 10-9). Consistently, the results from all 3 methods indicated a statistically significant increase in the risk of MI with higher triglyceride levels (P < .05). The results showed that patients with high triglyceride levels had a higher incidence of MI, suggesting that MI should be prevented in the high triglyceride population.
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