To explore the relationship between seasonal influenza and the environment, the principal task is to make data on influenza and environment for effective management. This paper focuses on the design and implementation of spatial database system for seasonal influenza in mainland China. Firstly, it proposed the influential environmental factors for seasonal influenza and collected the influenza surveillance data from China Influenza Surveillance System and relevant environmental data by remote sensing as well as meteorological monitoring. Then, it introduced the schema and technological processes of influenza spatial database systems. It took ArcSDE and Oracle 9i as the database platforms and adopted three-layer development model. Finally, it realized the system by programming in the C# environment with ArcEngine. The database system provides uniform spatial reference for spatial analysis of seasonal influenza and environmental factors, which is a basis for influenza-environmental modeling and influenza epidemic early-alerting.
OBJECTIVE To study the association of functional bladder capacity with the severity of bedwetting in children with nocturnal enuresis. METHODS A questionnaire investigation was performed in 1 500 children with nocturnal enuresis and the functional bladder capacity was examined by B-ultrasound. RESULTS The ratio of males to females was 1.3:1. The majority of patients (87%) were in an age range of 5-10 years, followed by the 10-14 years group (12%), and the 15-18 years group (1%). Six hundred and thirty-seven patients (42.4%) showed a decreased functional bladder capacity (less than 50% of normal level). The patients were classified into four groups according to the severity of bedwetting (from severe to mild): > or =2 times per night (n=53, 3.5%), > or =7 times per week (n=969, 64.6%), 3-6 times per week (n=380, 25.3%) and 1-2 times per week (n=98, 6.5%). The incidence of the reduction in functional bladder capacity in the above four groups was 79.2%, 48.3%, 29.7% and 14.3% respectively and a significant difference was noted among the four groups. CONCLUSIONS Most of children with nocturnal enuresis showed decreased functional bladder capacity. Functional bladder capacity is associated with the severity of bedwetting in children with nocturnal enuresis.
Background Although it is known that obesity is inseparable from diabetes, many anthropometric indices are used for determining obesity. At the same time, research on the predictive indices of diabetes in Chinese minority populations is lacking. Therefore, this study determines the relationship between different anthropometric indices and diabetes, and identifies the best index and best cut-off values for predicting diabetes. Method In total, 11,035 Dong and Miao ethnic participants (age: 30–79 years) from the China Multi-Ethnic Cohort study were included. The logistic regression model was used to examine the relationship between the different anthropometric indices and diabetes risk. The receiver operating characteristic curve and the area under the curve (AUC) were used to identify the best predictor of diabetes. Results In multivariate adjusted logistic regression models, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), and visceral adiposity index (VAI) were positively correlated with diabetes risk. Among Chinese Dong men and women and Miao men, WHR had the largest AUC (0.654/0.719/0.651). Among Miao women, VAI had the largest AUC(0.701). The best cut-off values of WHR for Dong men and women and Miao men were 0.94, 0.92, and 0.91, respectively. The best cut-off value of VAI for Miao women was 2.20. Conclusion Obesity indicators better predict diabetes in women than men. WHR may be the best predictor of diabetes risk in both sex of Dong ethnicity and Miao men, and VAI may be the best predictor of diabetes risk in Miao women.
Heavy metal exposure has well-established health risks, but its impact on all-cause mortality through renal function remains unclear. This study used data from 1,342 participants aged≥60 years in the National Health and Nutrition Examination Survey (2005-2018). A cross-sectional design was employed, with heavy metal composite scores derived using least absolute shrinkage and selection operator regression. Multivariate Cox proportional hazards models assessed the relationship between heavy metal exposure and all-cause mortality, while mediation analysis evaluated the role of estimated glomerular filtration rate (eGFR). The average participant age was 69.4 years. Higher composite metal exposure scores (CMES) were associated with older age, higher smoking rates, and increased blood lead (Pb) and cadmium (Cd) levels. CMES was significantly associated with mortality (adjusted HR=1.75, 95% CI:1.04-2.96), with Kaplan-Meier curves showing lower survival in participants with higher CMES (p=0.02). Pb and Cd levels were independently associated with increased mortality risk. eGFR was negatively correlated with mortality (adjusted HR=0.98, 95% CI: 0.97-0.99) and mediated 23.7% of the CMES-mortality relationship. These findings suggest that heavy metal exposure increases mortality risk, partly through impaired renal function.
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