Gastric cancer (GC) is the fourth most common type of cancer and the second leading cause of cancer-related deaths worldwide. To detect the spatial trends of GC risk based on hospital-diagnosed patients, this study presented a selection probability model and integrated it into the Bayesian spatial statistical model. Then, the spatial pattern of GC risk in Shanxi Province in north central China was estimated. In addition, factors influencing GC were investigated mainly using the Bayesian Lasso model. The spatial variability of GC risk in Shanxi has the conspicuous feature of being 'high in the south and low in the north'. The highest GC relative risk was 1.291 (95% highest posterior density: 0.789(-)4.002). The univariable analysis and Bayesian Lasso regression results showed that a diverse dietary structure and increased consumption of beef and cow milk were significantly (p