Objective To construct a One Health-based performance evaluation indicator system for integrated interventions for schistosomiasis in the elimination phase, clarify the dimensions and connotations of intervention performance evaluation, and provide methodological reference for subsequent real-world performance evaluation in schistosomiasis control. Methods On the basis of literature analysis, a preliminary indicator system was developed through group discussion and expert consultation. Nineteen experts in schistosomiasis control were invited to participate in two rounds of Delphi consultation. Expert response rate, degree of consensus, coordination of opinions, and authority were assessed. The indicators were optimized and refined according to the scoring results and expert feedback, and the analytic hierarchy process was used to determine the normalized weights of indicators at each level. Results Through literature analysis, group discussion, and expert consultation, a preliminary performance evaluation indicator system for integrated interventions for schistosomiasis was developed, consisting of 4 first-level indicators, 8 second-level indicators, and 20 third-level indicators. The response rates of the two rounds of expert consultation were both 100.00%. In the first round, the ranges of the experts’ judgment coefficient, familiarity coefficient, and authority coefficient were 0.88 ~ 1.00, 0.74 ~ 0.99, and 0.82 ~ 0.99, respectively; in the second round, the corresponding ranges were 0.88 ~ 0.98, 0.73 ~ 0.98, and 0.81 ~ 0.98, respectively. In the first round, Kendall’s coefficients of concordance for the rationality, importance, and operability of the indicators were 0.201, 0.252, and 0.221, respectively; in the second round, the corresponding values were 0.267, 0.319, and 0.296, respectively. The Kendall’s coefficients of concordance in both rounds were statistically significant (χ² = 112.063, 140.415, 123.386, 121.939, 145.393, and 135.072, all P < 0.05). After optimization and revision, the final indicator system consisted of 4 first-level indicators, 7 second-level indicators, and 14 third-level indicators. Among the first-level indicators, the normalized weights of “health performance”, “economic performance”, “ecological performance”, and “social performance” were 40.44%, 13.88%, 11.67%, and 34.01%, respectively. Among the second-level indicators, the normalized weights of “disease burden level” and “promotion of health equity” were both 100.00%; those of “resource consumption” and “production capacity” were both 50.00%; and those of “water and soil regulation”, “atmospheric environmental regulation”, and “species conservation” were all 33.33%. Conclusions A One Health-based performance evaluation indicator system was constructed for integrated interventions for schistosomiasis in the elimination phase. The system incorporates performance evaluation indicators across multiple dimensions, including health, economic, ecological, and social domains, and provides a tool for evaluating the performance of cross-sector collaborative governance in integrated schistosomiasis interventions.

OBJECTIVES: This study evaluated the association between obesity and glaucoma in middle-aged and older people. A population-based retrospective cohort study was conducted using data from the China Health and Retirement Longitudinal Study. METHODS: Glaucoma was assessed via self-reports. Multivariate logistic regression analysis and a Cox proportional hazards model were used to assess the relationship between obesity and glaucoma risk. RESULTS: Older males living in urban areas who were single, smokers, and non-drinkers were found to have a significantly higher incidence of glaucoma (all p<0.05). Diabetes, hypertension, and kidney disease were also associated with higher glaucoma risk, while dyslipidemia was associated with lower risk (all p<0.05). After the model was adjusted for demographic, socioeconomic, and health-related variables, obesity was significantly associated with a 10.2% decrease in glaucoma risk according to the Cox proportional hazards model (hazard ratio, 0.90; 95% confidence interval [CI], 0.83 to 0.97) and an 11.8% risk reduction in the multivariate logistic regression analysis (odds ratio, 0.88; 95% CI, 0.80 to 0.97). A further subgroup analysis showed that obesity was associated with a reduced risk of glaucoma in people living in rural areas, in smokers, and in those with kidney disease (all p<0.05). Obesity also reduced glaucoma risk in people with diabetes, hypertension, or dyslipidemia more than in healthy controls (all p<0.05). CONCLUSIONS This cohort study suggests that obesity was associated with a reduced risk of glaucoma, especially in rural residents, smokers, and people with kidney disease. Obesity exerted a stronger protective effect in people with diabetes, hypertension, or dyslipidemia than in healthy people.

The Traditional Chinese Medical Pulse Instrument uses the HKG-07B infrared pulse sensor to get pulse signal from the body. It makes full use of the TMS320VC5402 chip to realize time-frequency domain parameters extracting, classification and identification of the pulse signal. The system can store a plenty of pulse signal and realize data communication with the PC via the USB interface. According to acquisition and classification of pulse signal experiments of 200 subjects, the results show that the recognition rate of pulse signal can reach to 87.4%. It is applicable to the clinical diagnosis and detection of the pulse signal and home healthcare.
Equipment Design ; Humans ; Medicine, Chinese Traditional ; methods ; Signal Processing, Computer-Assisted ; Software Design