Objective:To investigate the epidemiological characteristics of herpangina (HA) and its correlation with the incidence of hand, foot and mouth disease (HFMD) in children aged ≤6 years in Yinzhou District of Ningbo from 2017 to 2022.Methods:Epidemiological characteristics of HA in children aged ≤6 years were analyzed based on the electronic medical record data and public health management data from 2017 to 2022 collected from the Health Information Platform of Yinzhou. The incidence of HFMD was calculated using the infectious disease reporting data from the public health management data. Autoregressive integrated moving average model and cross-correlation function were used to evaluate the correlation between the incidence of HA and HFMD.Results:From 2017 to 2022, a total of 25 385 cases of HA were detected in children aged ≤6 years in Yinzhou, the male-to-female ratio of the cases was 1.12∶1. The average annual incidence of HA was 4 986.67/100 000, with the highest incidence in 2018 (10 477.09/100 000) and the lowest incidence in 2020 (870.88/100 000). The incidence peak of HA was during June to July. The incidence of HA was higher in age group 1 year (7 950.45/100 000) than in other age groups. The incidences of HA in Yunlong, Jiangshan and Xiaying were higher, with the incidence of 8 764.31/100 000, 8 377.58/100 000 and 7 965.31/100 000, respectively. The correlation coefficients between the incidence of HA and HFMD at lag day 0, 7, 12 and 18 were 0.199, 0.139, 0.090 and 0.086, respectively (all P<0.05). Conclusions:From 2017 to 2022, the incidence of HA was high in children aged ≤6 years in Yinzhou with obvious seasonality and area difference. The incidence of HA was correlated with the incidence of HFMD and the incidence of HFMD had certain lags. The comprehensive prevention and control of HA and HFMD should be further strengthened by prioritizing HA surveillance and implementing integrated surveillance and management of HA and HFMD.

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.

Objective:To understand the current status of gastroscopy in diagnosing gastric lesions in general population, and to recommend the optimal age for the first gastroscopy and intervals for repeated gastroscopy.Methods:The gastroscopy records of residents aged 18-80 years in Yinzhou District of Ningbo, Zhejiang Province, between April 2010 and December 2021 were analyzed retrospectively. The detections of gastric lesions across different years, age and genders were described. Goodness of fit tests were applied to compare the differences in detection rates of different lesions in first-time endoscopy in different age groups and different populations. Generalized additive models were used to fit the trend of age specific gastric lesion detection rate explore the optimal age for gastroscopy. The appropriate gastroscopy intervals were determined according to the progress of the gastric lesions detected in repeated gastroscopy.Results:A total of 237 751 participants with 344 398 gastroscopy records were included in analyses. A total of 5 597 cases of chronic atrophic gastritis (CAG), 9 796 cases of intestinal metaplasia (IM), 165 cases of low-grade intraepithelial neoplasia (LGIN), 52 cases of high-grade intraepithelial neoplasia (HGIN) and 435 cases of gastric cancer were detected by the first gastroscopy. The overall detection rate of gastric lesions increased significantly in age group 45-70 years, and remained stable after 70 years old, with LGIN and HGIN showing notable increases at 50 and 55 years old, respectively. Repeated gastroscopy detected CAG, IM, LGIN, and HGIN at a higher rate compared with the first gastroscopy. Normal/superficial gastritis progressed in 3-5 years, whereas CAG or more severe lesions progressed in 1-6 years.Conclusion:Gastroscopy is recommended for general population aged 45 years and above. Furthermore, gastroscopy can be performed every 3-5 years for individuals with normal endoscopy results and once a year for patients with CAG or more severe gastric lesions.

Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.

Objective:To construct a risk prediction model for diabetes kidney disease (DKD).Methods:Patients newly diagnosed with type 2 diabetes mellitus (T2DM) between January 1, 2015, and December 31, 2022, were selected as study subjects from the Yinzhou Regional Health Information Platform in Ningbo City. The Lasso method was used to screen the risk factors, and the DKD risk prediction model was established using Cox proportional hazard regression models. Bootstrap 500 resampling was applied for internal validation.Results:The study included 49 706 subjects, with an median ( Q1, Q3) age of 60.00 (50.00, 68.00) years old, and 55% were male. A total of 4 405 subjects eventually developed DKD. Age at first diagnosis of T2DM, BMI, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, past medical history (hyperuricemia, rheumatic diseases), triglycerides, and estimated glomerular filtration rate were included in the final model. The final model's C-index was 0.653, with an average of 0.654 after Bootstrap correction. The final model's area under the receiver operating characteristic curve for predicting 4-year, 5-year, and 6-year was 0.657, 0.659, and 0.664, respectively. The calibration curve was closely aligned with the ideal curve. Conclusions:This study constructed a DKD risk prediction model for newly diagnosed T2DM patients based on real-world data that is simple, easy to use, and highly practical. It provides a reliable basis for screening high-risk groups for DKD.

Objective To analyze and verify the factors influencing the prediction model of suicidal ideation of burn patients in hospital based on international scale.Methods The clinical data of 194 burn patients treated in hospi-tal were retrospectively analyzed.General data questionnaire,ISI,HAMD,HAMA,ASDS and BSHS-B were used to evaluate the influencing factors of suicidal ideation.According to the presence or absence of suicidal ideation,the patients were divided into the suicidal ideation group and the non-suicidal ideation group.The baseline data be-tween the groups were compared,univariate screening of meaningful variables was conducted,and multivariate Lo-gistic regression modeling was further conducted.ROC analysis evaluated model differentiation,and internal verifi-cation was conducted.Results According to the baseline data analysis results,there were no statistically signifi-cant differences in age,BMI,years of education,smoking history,estimated percentage of burned area,head and neck burns,hip and perineal burns,and pain scores in the suicidal ideation group(21/194)compared with the non-suicidal ideation group(173/194).Gender(P=0.047),presence or absence of trunk burn(P=0.022),severity of burn(moderate burn:P=0.002;severe burn:P=0.458;extremely severe burn:P=0.169),ISI score(P=0.001),HAMD score(P=0.001),HAMA score(P＜0.001),ASDS score(P=0.003),BSHS-B score(P=0.011)had statistical significance.Multivariate Logistic regression analysis showed that the severity of burn(moderate burn:OR=0.103,P=0.009;severe burn:OR=0.351,P=0.223;extremely severe burn:OR=0.103,P=0.095)and HAMA score(OR=1.136,P=0.007)were independent influencing factors for burn patients with suicidal ideation.The Logistic regression prediction model was established by two independent influ-encing factors.ROC analysis results showed that the model had good differentiation(AUC=0.880,95％CI:0.808-0.952,P＜0.001)and the internal verification accuracy was 79.38％.Conclusion The prediction model built on the basis of two independent influencing factors,burn severity and HAMA score,has a good predic-tion accuracy,which is helpful for clinicians to intervene as soon as possible for burn patients with suicidal ideation in hospital,in order to reduce the incidence and enrich clinical psychological research.

Objective: To investigate the incidence density of adult sleep disorders (SD) in Yinzhou District, Ningbo City, Zhejiang Province from 2017 to 2023, so as to provide insights into formulating the control measures of SD. Methods: The electronic health records of permanent residents aged 18 years and over in Yinzhou District from 2017 to 2023 were collected through the Yinzhou Regional Health Information Platform. New cases of SD were diagnosed for the first time a year after establishing health records. The incidence density was estimated using Poisson distribution. The temporal, population and regional distribution characteristics of new cases of SD were analyzed using a descriptively epidemiological method. Results: From 2017 to 2023, there were 1 255 129 permanent residents aged 18 years and over in Yinzhou District, with a total observed person-time of 6 292 884 person-years and a median of 5.67 (interquartile range, 3.74) person-years. There were 165 490 new cases of SD, including 67 095 males (40.54%) and 98 385 females (59.46%). The incidence density of SD in Yinzhou District from 2017 to 2023 was 26.30/1 000 person-years, with no significant trend observed (P>0.05). The incidence density of SD was higher in females than in males (29.63/1 000 person-years vs. 22.57/1 000 person-years, P<0.05). The highest incidence density of SD was observed in individuals aged 70 to <80 years (63.30/1 000 person-years), and the lowest was in individuals aged 18 to <30 years (7.24/1 000 person-years). The incidence density of SD in individuals aged 30 years and over was higher than that in individuals aged 18 to <30 years (all P<0.05). The incidence density of SD was 32.03/1 000 person-years in individuals with junior high school education or below, which was higher than individuals with senior high school/technical secondary school education (25.93/1 000 person-years) and college degree and above (18.87/1 000 person-years, all P<0.05). Dongliu Street, Dongjiao Street, and Baihe Street had relatively higher incidence densities of SD, at 45.11/1 000 person-years, 42.87/1 000 person-years and 40.16/1 000 person-years, respectively. Conclusions From 2017 to 2023, there was no significant trend in the incidence density of SD in Yinzhou District. Higher incidence density were observed in females, the elderly, and individuals living in central urban areas.

The objective of this study is to assess the current status of vaccination against respiratory disease among the elderly aged ≥60 and analyze the factors influencing vaccination rates at both service provider and recipient levels in Zhejiang Province. Using a stratified random sampling method, a questionnaire survey was conducted from September 2022 to January 2023 among elderly people aged ≥60 in 30 townships/streets in Zhejiang Province, as well as immunization planning staff at the provincial, municipal, county/district, and township/street levels. Logistic regression models were used to analyze the factors related to vaccination among elderly people in Zhejiang Province. Based on the Zhejiang Provincial Comprehensive Management Information System for Vaccine and Vaccination, the systematic coverage rates of influenza vaccine and pneumonia vaccine for the elderly were 21.76% and 4.57%, respectively. Multivariate logistic regression analysis indicated that advanced age ( OR=1.74, 95% CI: 1.51-1.99), knowing that influenza is more severe than the common cold ( OR=1.67, 95% CI: 1.37-2.04) and having heard of the influenza vaccine ( OR=9.78, 95% CI: 7.03-13.59) were motivating factors for elderly to receive influenza vaccines. Advanced age ( OR=1.71, 95% CI: 1.43-2.06), knowing the serious consequences of pneumonia in the elderly ( OR=1.93, 95% CI: 1.47-2.55) and knowing that pneumonia vaccines can prevent pneumonia ( OR=6.36, 95% CI: 4.84-8.36) were motivating factors for elderly to receive pneumonia vaccines. Zhejiang Immunization Program staff believed that the main reasons why the elderly aged ≥60 would not be vaccinated against influenza or pneumonia were that they felt they would not get sick (55.52% and 56.35% respectively), it would not be serious if get sick (47.73% and 37.46% respectively), lacking trust in vaccine efficacy and safety (38.31% and 43.69% respectively). Vaccination rates for influenza and pneumonia vaccines among the elderly aged ≥60 in Zhejiang Province are suboptimal. Advanced age, awareness of the severity of respiratory diseases and awareness of vaccines against such diseases are related factors for elderly individuals to receive influenza and pneumonia vaccines.

Objective To assess the association between Metformin use and the risk of dementia in patients with type 2 diabetes mellitus(T2DM).Methods The research data came from the big medical data platform of Yinzhou District,and we constructed a cohort of T2DM patients who had initiated treatment of Metformin or sulfonylurea since January 1,2009.The inverse probability of treatment weighting(IPTW)was used to control the baseline confounding factors,and the Cox regression model was used to estimate the HR(95%CI)of the association between Metformin use and dementia risk.Results The incidence rate of dementia in new users of Metformin(41181 persons)and sulfonylureas(38092 persons)was 128.4 per 100000 person years and 142.3 per 100000 person years respectively.Compared with sulfonylureas,the crude analysis with no adjustment for confounding factors showed that there was a negative association between the use of Metformin and the incidence of dementia,with an HR(95%CI)0.930(0.800～1.090).After adjusting for potential confounders with IPTW,Metformin was not significantly associated with the risk of dementia HR(95%CI)1.040(0.890～1.220).The subgroup analysis results for different baseline characteristics were consistent with the primary analysis results,and there were no statistically significant associations between Metformin and dementia incidence risk in all subgroups.Conclusions There is no significant association between the use of Metformin and the risk of dementia in T2DM patients in the Yinzhou District.

The objective of this study is to assess the current status of vaccination against respiratory disease among the elderly aged ≥60 and analyze the factors influencing vaccination rates at both service provider and recipient levels in Zhejiang Province. Using a stratified random sampling method, a questionnaire survey was conducted from September 2022 to January 2023 among elderly people aged ≥60 in 30 townships/streets in Zhejiang Province, as well as immunization planning staff at the provincial, municipal, county/district, and township/street levels. Logistic regression models were used to analyze the factors related to vaccination among elderly people in Zhejiang Province. Based on the Zhejiang Provincial Comprehensive Management Information System for Vaccine and Vaccination, the systematic coverage rates of influenza vaccine and pneumonia vaccine for the elderly were 21.76% and 4.57%, respectively. Multivariate logistic regression analysis indicated that advanced age ( OR=1.74, 95% CI: 1.51-1.99), knowing that influenza is more severe than the common cold ( OR=1.67, 95% CI: 1.37-2.04) and having heard of the influenza vaccine ( OR=9.78, 95% CI: 7.03-13.59) were motivating factors for elderly to receive influenza vaccines. Advanced age ( OR=1.71, 95% CI: 1.43-2.06), knowing the serious consequences of pneumonia in the elderly ( OR=1.93, 95% CI: 1.47-2.55) and knowing that pneumonia vaccines can prevent pneumonia ( OR=6.36, 95% CI: 4.84-8.36) were motivating factors for elderly to receive pneumonia vaccines. Zhejiang Immunization Program staff believed that the main reasons why the elderly aged ≥60 would not be vaccinated against influenza or pneumonia were that they felt they would not get sick (55.52% and 56.35% respectively), it would not be serious if get sick (47.73% and 37.46% respectively), lacking trust in vaccine efficacy and safety (38.31% and 43.69% respectively). Vaccination rates for influenza and pneumonia vaccines among the elderly aged ≥60 in Zhejiang Province are suboptimal. Advanced age, awareness of the severity of respiratory diseases and awareness of vaccines against such diseases are related factors for elderly individuals to receive influenza and pneumonia vaccines.