摘要BACKGROUND:This study aims to explore the causal relationship of body weight,body mass index(BMI),and waist circumference(WC)with the risk of cardiac arrest(CA)using two-sample Mendelian randomization(MR).METHODS:Data were summarized using genome-wide association studies(GWAS).Two-sample MR analyses were performed using the inverse variance weighting(IVW)method,the weighted median method,and the MR-Egger analysis.Heterogeneity test and sensitivity analysis were performed using Cochran's Q test and the leave-one-out method,respectively.The Steiger test was used to detect reverse causality.Bayesian model-averaged MR was used to identify the most influential risk factors.RESULTS:A total of 13 GWAS data were collected for BMI,body weight and WC.IVW analyses showed a positive correlation of body weight,BMI,and WC with CA(all OR>1 and P<0.05),with MR-Egger and weighted median methods confirming the IVW findings.No horizontal pleiotropy or heterogeneity was observed.Sensitivity analysis indicated that no single nucleotide polymorphism(SNP)caused significant changes in overall causality.Bayesian model-averaged MR was also used to rank causality based on marginal inclusion probability(MIP),and the corresponding model-averaged causal estimate(MACE)were confirmed,which indicated that WC(GWAS ID:ukb-b-9405)was the highest-ranked risk factor(MIP=0.119,MACE=0.011);its posterior probability was 0.057.A total of 14 sex-specific GWAS data on weight,BMI,and WC were analyzed in relationship with CA,and the MR results showed no significant effects of sex-specific factors.CONCLUSION:Body weight,BMI,and WC are causally associated with an increased risk of CA,with WC identified as the most important risk factor.