Objective To perform an epidemiological investigation on the incidence of hyperuricemia (HUA) in young people in coastal areas, and to construct a nomogram prediction model for the occurrence of HUA in this population. Methods A total of 13,647 young people undergoing physical examination in the First People's Hospital of Qinzhou, Guangxi, from February 2019 to February 2022 were selected as the study subjects, their clinical data were collected and they were followed up for a year, and the HUA incidence in this population was calculated, and the study subjects were divided into an HUA group or a non-HUA group according to the occurrence of HUA in the physical examination 1 year later. The clinical data of the two groups were compared, the multivariate logistic regression model was used to analyze the influencing factors for HUA in young people in coastal areas, and a nomogram prediction model for HUA in this population was constructed. Hosmer-Lemeshow test, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to evaluate the model's predictive performance. Results Among the 13,647 young people undergoing physical examination, 3,169 were diagnosed with HUA, which made an overall HUA incidence of 23.22%. There were statistically significant differences in gender, prevalence of diabetes mellitus, prevalence of hypertension, alcohol consumption history, meat consumption, body mass index (BMI), systolic blood pressure, diastolic blood pressure, triacylglycerol, glycosylated hemoglobin, serum creatinine, alanine transaminase, aspartate transaminase, and high-density lipoprotein cholesterol (HDL-C) between the two groups (all P<0.05). The results of multivariate logistic regression analysis showed that gender, prevalence of hypertension, alcohol consumption history, meat consumption, BMI, TG, serum Cr, and HDL-C were influencing factors for HUA in young people in coastal areas (all P<0.05). The results of the Hosmer-Lemeshow test showed that the prediction results of the nomogram model constructed on the basis of the abovementioned influencing factors fitted well with the actual observations, the area under the ROC curve of the model for predicting the occurrence of HUA in young people in coastal areas was 0.891 (95%CI: 0.837-0.946), and the DCA curve showed a quite high net benefit of the model for predicting HUA. Conclusion The incidence of HUA in young people in coastal areas is quite high, and gender, prevalence of hypertension, alcohol consumption history, meat consumption, BMI, triacylglycerol, serum creatinine, and HDL-C are the influencing factors for HUA in young people in coastal areas. Constructed on the basis of the abovementioned influencing factors, the nomogram model can effectively predict the occurrence of HUA in this population, with good clinical utility. 

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