ObjectiveTo investigate the guidance centers for promoting equalization of basic public health services in Sichuan province, in order to provide evidence for construction and development. MethodsBy questionnaire survey, we collected relevant information and data about the guidance centers at all levels in Sichuan province. The EpiData 3.0 was used to establish a database and the SPSS 16.0 was used to analyze data. ResultsA total of 202 guidance centers had been set up in Sichuan province. All disciplines of the basic public health services were covered by these centers. There were 2 020 technicians, whose average age was 41.37, more had college degree, and intermediate professional title. 54.5% of the guidance centers didn't work together, and there were 92.7% part-time technicians. Only 40% city and 20% county guidance centers got working funds. The average working funds of province, city and county were 890 000 yuan per year, 101 000 yuan per year and 89 000 yuan per year, respectively. ConclusionThe guidance centers of Sichuan province at all levels have effectively promoted the basic public health services project, but we should improve and perfect the management mechanism and guarantee mechanism.
ObjectiveTo establish a hypertension prediction model for middle-aged and elderly people in China and to use the basic public health service database for performance validation. MethodsThe literature related to hypertension was retrieved from the internet. Using meta-analysis to assess the effect value of influencing factors. Statistically significant factors, which were also combined in the database, were extracted as the predictors of the models. The predictors’ effect values were logarithmarithm-transformed as the parameters of the Logit function model and the risk score model. Participants who were never diagnosed with hypertension at the physical examination of health service project of Hongguang Town Health Center in Pidu District of Chengdu from January 1, 2017, to January 1, 2022, were considered as the external validation group. ResultsA total of 15 original studies were involved in the meta-analysis and 11 statistically significant influencing factors for hypertension were identified, including age, female, systolic blood pressure, diastolic blood pressure, BMI, central obesity, triglyceride, smoking, drinking, history of diabetes and family history of hypertension. Of 4997 qualified participants, 684 individuals were identified with hypertension during the five-years follow-up. External validation indicated an AUC of 0.571 for the Logit function model and an AUC of 0.657 for the risk score model. ConclusionIn this study, we developed two different prediction models based on the results of meta-analysis. National basic public health service database is used to verify the models. The risk score model has a better prediction performance, which may help quickly stratify the risk class of the community crowd and strengthen the primary-level assistance system.