Objective: To analyze the epidemiological characteristics and spatial-temporal clustering of hepatitis E in Jinhua City, Zhejiang Province from 2010 to 2025, so as to provide evidence for formulating targeted hepatitis E prevention and control measures. Methods: Data of reported hepatitis E cases in Jinhua City from 2010 to 2025, including gender, age and occupation, were collected through the Epidemiological Investigation System of China Disease Prevention and Control Information System. Descriptive epidemiological methods were used to analyze the temporal, population and regional distribution characteristics of hepatitis E. The average annual percent change (AAPC) was used to analyze the changing trend of reported incidence of hepatitis E. Spatial autocorrelation and spatial-temporal scan analysis were used to analyze the spatial-temporal clustering of hepatitis E. Results: A total of 2 555 hepatitis E cases were reported in Jinhua City from 2010 to 2025, with an average annual reported incidence of 2.65/105. The overall trend of reported incidence had no statistical significance (AAPC=-1.233%, 95%CI: -6.027%-3.782%, P>0.05). Cases were reported every month, and the number of reported cases was relatively high from January to May, with 1 302 cases (50.96%). The average annual reported incidence of hepatitis E among males was 3.47/105, which was higher than the female counterpart of 1.73/105 (P<0.05). The number of hepatitis E reported cases was relatively high in the groups aged 40-<50 years and 50-<60 years, with 544 cases (21.29%) and 671 cases (26.26%), respectively. The average annual reported incidence of hepatitis E was relatively high in the groups aged 60-<70 years and 70-<80 years, with 5.18/105 and 4.41/105, respectively. The number of hepatitis E reported cases was relatively high among farmers, with 1 512 cases (59.18%). Lanxi City had a relatively high average annual reported incidence of hepatitis E, at 4.53/105. Hepatitis E in Jinhua City showed positive spatial correlation in 2013, 2014, 2022, 2023 and 2025 (all P<0.05), exhibiting a spatially clustered distribution.The high-high clusters were mainly distributed in some townships (subdistricts) of Wucheng District, Lanxi City, Dongyang City, Pan'an County and Wuyi County. Class Ⅰ cluster of hepatitis E in Jinhua City from 2010 to 2025 was Choucheng Subdistrict of Yiwu City, with the clustering period from January 2011 to December 2018. Conclusions The reported incidence of hepatitis E in Jinhua City remained at a moderate level, with a gentle overall trend from 2010 to 2025. Hepatitis E peaked in winter and spring. Males, middle-aged and elderly people, and farmers were high-risk populations. Lanxi City and Yiwu City were high-risk areas.

Objective: To investigate the value of the Chinese visceral adiposity index (CVAI) in predicting hypertension risk, so as to provide a tool for the early assessment of hypertension risk. Methods: Health examination individuals aged ≥18 years were selected from four medical institutes in Jinhua City, Zhejiang Province in 2022. Data on basic information, lifestyle, disease history, body mass index, waist circumference, blood pressure, and blood biochemical indicators were collected through questionnaire surveys and physical examinations. CVAI was calculated to assess levels of visceral fat accumulation, divided by quartiles into Q1, Q2, Q3, and Q4 groups. The relationship between CVAI and hypertension was analyzed using a multivariable logistic regression model, and their dose-response relationship was examined using a restricted cubic spline model. The value of CVAI in predicting hypertension risk was evaluated using receiver operating characteristic (ROC) curve. Results: A total of 23 791 individuals were enrolled, with a median age of 68.00 (interquartile range, 14.00) years. Among them, 10 178 (42.78%) were males and 13 613 (57.22%) were females. The median CVAI was 111.40 (interquartile range, 48.23). Hypertension was identified in 15 563 cases, with a prevalence of 65.42%. After adjusting for lifestyle, disease history, and blood biochemical indicators, the multivariable logistic regression analysis revealed that hypertension risk in the CVAI Q2, Q3, and Q4 groups were 2.012 (95%CI: 1.865-2.170), 3.059 (95%CI: 2.826-3.311), and 5.099 (95%CI: 4.672-5.565) times that of the Q1 group, respectively. The restricted cubic spline model revealed a non-linear relationship between CVAI and hypertension risk (Pnon linearity<0.05). Hypertension risk increased more rapidly when the CVAI was ≥81.03. The area under the ROC curve for CVAI in predicting hypertension risk was 0.691, with an optimal cutoff value of 106.01, which falls within the Q2 group. Conclusions There was a nonlinear dose-response relationship between CVAI and hypertension. CVAI can predict the risk of hypertension, and 106.01 can serve as an early warning threshold for risk screening.