The greener the living environment, the better the health? Examining the effects of multiple green exposure metrics on physical activity and health among young students.

The sedentary and less active lifestyle of modern college students has a significant impact on the physical and mental well-being of the college community. Campus Green Spaces (GSs) are crucial in promoting physical activity and improving students' health. However, previous research has focused on evaluating campuses as a whole, without considering the diverse spatial scenarios within the campus environment. Accordingly, this study focused on the young people's residential scenario in university and constructed a framework including a comprehensive set of objective and subjective GSs exposure metrics. A systematic, objective exposure assessment framework ranging from 2D (GSs areas), and 2.5D (GSs visibility) to 3D (GSs volume) was innovatively developed using spatial analysis, deep learning technology, and unmanned aerial vehicle (UAV) measurement technology. Subjective exposure metrics incorporated GSs visiting frequency, GSs visiting duration, and GSs perceived quality. Our cross-sectional study was based on 820 university students in Nanjing, China. Subjective measures of GSs exposure, physical activity, and health status were obtained through self-reported questionnaires. The Generalized Linear Model (GLM) was used to evaluate the associations between GSs exposure, physical activity, and perceived health. Physical activity and social cohesion were considered as mediators, and path analysis based on Structural Equation Modeling (SEM) was used to disentangle the mechanisms linking GSs exposure to the health status of college students. We found that (1) 2D indicator suggested significant associations with health in the 100m buffer, and the potential underlying mechanisms were: GSs area → Physical activity → Social cohesion → Physical health → Mental health; GSs area → Physical activity → Social cohesion → Mental health. (2) Subjective GSs exposure indicators were more relevant in illustrating exposure-response relationships than objective ones. This study can clarify the complex nexus and mechanisms between campus GSs, physical activity, and health, and provide a practical reference for health-oriented campus GSs planning.

[A correlation study between body mass index and exercise capacity in patients with chronic systolic heart failure].

OBJECTIVE: To investigate the association between body mass index (BMI) and exercise capacity in patients with chronic systolic heart failure. METHODS: The elderly patients with chronic systolic heart failure were consecutively recruited from 2008 to 2011 in cardiovascular clinic of Zhejiang Hospital. All the participants underwent height and weight measurements and BMI was calculated with these two parameters. Cardiopulmonary exercise test were performed to achieve peak oxygen uptake (PVO(2)), oxygen uptake to body mass ratio (PKVO(2)), oxygen uptake to heart ratio (VO(2)/HR) and ventilation/carbon dioxide production (VO(2)/VCO(2)). RESULTS: A total of the 273 patients with chronic systolic heart failure included 6 underweight patients (BMI < 18.5 kg/m(2)), 113 normal weight patients (BMI 18.5 - < 24.0 kg/m(2)), 116 overweight patients (BMI 24.0 - < 28.0 kg/m(2)), and 38 obese patients (BMI ≥ 28 kg/m(2)). In both NYHA II and III/IV patients, unadjusted correlation analyses showed that BMI was positively related to PVO(2) and VO(2)/HR, and was inversely related to PKVO(2) and VE/VCO(2) (P < 0.05), respectively. Multiple stepwise regression analyses showed age, sex, BMI (P < 0.05) and left ventricular ejection fraction (LVEF) were independent determinants of PKVO(2), and age and BMI (P < 0.05) were independent determinants of VE/VCO(2). CONCLUSIONS: BMI is significantly associated with exercise capacity in patients with chronic systolic heart failure, and also independent determinant for the PKVO(2) and VE/VCO(2), respectively.

A Case-Control Study on Risk Factors of Pulmonary Infection in Patients with Type 2 Diabetes Mellitus and Its Implications for Clinical Intervention.

Objective: To analyze the risk factors of pulmonary infection in patients with type 2 diabetes mellitus (T2DM) and its implications for clinical intervention. Methods: One hundred and twenty-five patients with type 2 diabetes treated in our hospital from January 2019 to November 2021 were divided into simple T2DM group (n = 80) and infection group (n = 45) according to whether they were complicated with pulmonary infection or not. Sputum samples of patients with infection were collected and identified by bacterial culture. The general conditions (age, sex, body mass index, course of disease, and length of stay), pulmonary complications (chronic bronchitis, emphysema, and obstructive pulmonary disease,), blood glucose control (fasting blood glucose and glycosylated hemoglobin), and treatment (use of hormones and antibiotics and invasive operation) were compared between the two groups. Univariate and multivariate analyses were used to screen the risk factors of pulmonary infection in patients with T2DM. Results: A total of 45 patients were found to be infected in this study. 68 pathogenic bacteria were detected in the sputum samples, of which 42 were Gram-negative (61.76%), 22 were Gram-positive (35.35%), and 4 were fungi (5.88%). Gram-negative bacteria were mainly Klebsiella pneumoniae, accounting for 25.00%, followed by Pseudomonas aeruginosa, Acinetobacter baumannii, and Escherichia coli. Gram-positive bacteria were mainly Staphylococcus aureus, accounting for 17.65%, followed by Streptococcus pneumoniae and Staphylococcus haemolyticus. The main fungi were Candida albicans (4.41%). The age, the course of T2DM, and the duration of hospitalization in the coinfection group were significantly higher than those in the T2DM group (P < 0.05). There was no significant difference in other indexes (P > 0.05). The number of patients with chronic bronchitis, emphysema, and obstructive pulmonary disease in the coinfection group was significantly higher than that in the T2DM group. The fasting blood glucose and glycosylated hemoglobin in the coinfection group were significantly higher than those in the T2DM group. The number of patients using hormone and antimicrobial agents and invasive operation in the coinfection group was higher than that in the simple T2DM group, and the difference was statistically significant (P < 0.05). Multivariate analysis showed that age, course of T2DM, length of hospital stay, complicated pulmonary disease, glycosylated hemoglobin, use of hormones and antibiotics, and invasive operation were all risk factors of pulmonary infection in patients with T2DM (P < 0.05). Conclusion: Gram-negative bacteria are the main pathogens of T2DM complicated with pulmonary infection. Drug sensitivity test should be combined to understand the drug resistance of pathogenic bacteria and use drugs reasonably to patients. Among them, advanced age, long course of T2DM, long hospital stay, complicated pulmonary disease, high level of glycosylated hemoglobin, use of hormones and antibiotics, and invasive operation were all risk factors of pulmonary infection in patients with T2DM. In clinical treatment, under the premise of using insulin to control blood sugar in an appropriate range, antibiotics should be used reasonably, pulmonary complications should be treated actively, pulmonary ventilation function should be improved, and invasive operation should be avoided as far as possible, which can effectively prevent the occurrence of T2DM complicated with pulmonary infection.

Correlation Analysis and Intervention Study on Disturbance of Lipid Metabolism and Diabetic Peripheral Neuropathy.

OBJECTIVE: To explore the significance and clinical value of dynamic monitoring of lipid metabolism indexes in patients with diabetic peridiabetic lesions. METHODS: A total of 192 patients with type 2 diabetes (T2DM) treated in our hospital from October 2019 to July 2021 were divided into two groups according to whether they were complicated with peripheral neuropathy (DPN). The patients in the observation group were randomly assigned into group A (n = 45) and group B (n = 45) according to the method of random number table. The patients were assigned into control group (n = 102) and observation group (n = 90), and the patients in the observation group were randomly divided into two groups (n = 45). All the patients in the three groups were given routine hypoglycemic treatment, and group B was observed to dynamically monitor the indexes of lipid metabolism and regulate blood lipids on the basis of routine hypoglycemic treatment. The indexes of lipid metabolism, including total cholesterol (TC), triglyceride (TG), and high-density lipoprotein cholesterol (HDL-C)/low-density lipoprotein cholesterol (LDL-C), were detected before treatment. The receiver operating curve (ROC) was applied to elucidate the efficacy of TC, TG, and HDL-C and LDL-C in predicting peripheral neuropathy (DPN) in patients with T2DM. The indexes of lipid metabolism and neurological function of patients were determined after the treatment. The difference was considered to be statistically significant (P < 0.05). RESULTS: In contrast to the control, the serum levels of TG, TC, and LDL-C in the observation group were significantly higher, with HDL-C significantly lower. ROC curve analysis indicated that the area under the curve (AUC) of serum TG level to predict peripheral neuropathy in patients with T2DM was 0.753 (95% CI = 0.604 - 0.901, P = 0.007). When the Youden index reached the maximum (0.677), with corresponding sensitivity and specificity 77.18% and 82.58%, respectively, and the critical value was 2.31 mmol/L, the AUC of serum TC level for predicting peripheral neuropathy in patients with T2DM was 0.851 (95% CI = 0.735 ~ 0.967P < 0.001); when the Youden index reaches its maximum (0.750), with the sensitivity and specificity 84.44% and 92.06%, respectively, and the critical value is 4.52 mmol/L, the AUC of predicting peripheral neuropathy in patients with T2DM by serum LDL-C level was 0.799 (95% CI = 0.52 ~ 0.946, P = 0.001); when the Youden index reaches its maximum (0.706), with sensitivity and specificity 80.58% and 87.24%, respectively, and the critical value is 3.36 mmol/L, the AUC of serum HDL-C level for predicting DPN in patients with T2DM was 0.727 (95% CI = 0.568 ~ 0.886P = 0.014). When the Youden index reached the maximum (0.640), the sensitivity and specificity were 74.56% and 83.25%, respectively, the critical value is 1.51 mmol/L. The AUC in predicting DPN in patients with T2DM was 0.919 (95% CI = 0.839 ~ 0.978P < 0.001); when the Jordan index reached the maximum (0.786), the sensitivity and specificity were 91.75% and 95.82%, respectively. Compared with group A, the levels of serum TG, TC, and LDL-C in group B decreased significantly, while the level of HDL-C increased (P < 0.05). The motor nerve conduction velocity and sensory nerve conduction velocity of median nerve and peroneal nerve in group B were higher than those in group A (P < 0.05). CONCLUSION: Diabetic patients with severe lipid metabolic disorders have a higher risk of DPN. Combined detection of lipid metabolism indexes such as TC, TG, and HDL-C and LDL-C is effective in predicting diabetic patients with DPN. In clinic, through dynamic monitoring of lipid metabolism indexes, we can actively regulate the level of blood lipids in patients with T2DM, which can delay the occurrence and development of DPN to a certain extent, as well as improving the prognosis of patients with diabetes.