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.
Objective To explore the relationship between grip strength and knee joint pain in middle-aged and elderly population. Method The research data in middle-aged and elderlypopulation was obtained from the CHARLS database between 2011and 2020. The relationship between average grip strength and knee pain in 2011 were analyzed, and follow up was conducted on the occurrence of knee joint pain. According to whether the knee joint is painful, the population who participated in the “Knee Joint Pain Symptoms” survey in 2011 were divided into the knee joint pain free group and the knee joint pain group. According to the follow-up data, the population who participated in the “Knee Pain Symptoms” survey in 2011 and had no knee pain were divided into a group without knee pain and a group with knee pain. Use logistic regression to analyze the correlation between average grip strength and knee pain. Apply a restrictive cubic spline model to analyze the dose-response relationship between average grip strength and knee joint pain occurrence. ResultsA total of 12 307 cases were included in 2011. The results of multiple logistic regression analysis showed that average grip strength was associated with knee joint pain. The incidence of knee joint pain increases with a decrease in average grip strength. During the 9-year follow-up period, a total of 9 667 cases were included. The results of multiple logistic regression analysis showed that average grip strength was correlated with the occurrence of knee joint pain. Compared to the group with the highest average grip strength, the low grip strength group had an increased risk of developing knee joint pain. The results of the restricted cubic spline analysis showed that the continuous changes in average grip strength were strongly correlated with knee joint pain in a linear dose-response relationship. As the average grip strength level increases, the incidence of knee joint pain decreases. Conclusion There is a correlation between average grip strength and knee joint pain. The risk of knee joint pain is higher with low average grip strength.
