Ambient ozone pollution impairs glucose homeostasis and contributes to renal function decline: Population-based evidence.

Particulate matter pollution could increase the risk of kidney disease, while evidence for ozone exposure is less well-established. Here, we aimed to evaluate the effect of ozone pollution on renal function and explore mechanisms. We first conducted a cross-sectional study based on Wuhan Chronic Disease Cohort Study baseline information. We recruited 2699 eligible participants, estimated their residential ozone concentrations, collected fasting peripheral blood samples for biochemical analysis and calculated the estimated glomerular filtration rate (eGFR). The linear regression model was applied to evaluate the long-term association between ozone pollution and eGFR. Then, we recruited another 70 volunteers as a panel with 8 rounds follow-up visits. We calculated the eGFR and measured fasting blood glucose and lipid levels. The linear mixed-effect model along with mediation analysis were performed to confirm the short-term association and explore potential mechanisms, respectively. For the long-term association, a 10.95 µg/m3 increment of 3-year ozone exposure was associated with 2.96 mL/min/1.73 m2 decrease in eGFR (95%CI: -4.85, -1.06). Furthermore, the drinkers exhibited a pronounced declination of eGFR (-7.46 mL/min/1.73 m2, 95%CI: -11.84, -3.08) compared to non-drinkers in relation to ozone exposure. Additionally, a 19.02 µg/m3 increase in 3-day ozone concentrations was related to 2.51 mL/min/1.73 m2 decrease in eGFR (95%CI: -3.78, -1.26). Hyperglycemia and insulin resistance mediated 12.2% and 16.5% of the aforementioned association, respectively. Our findings indicated that higher ozone pollution could affect renal function, and the hyperglycemia and insulin resistance linked to ozone might be the underlying mechanisms.

Associations between cold spells of different time types and coronary heart disease severity.

Limited evidence showed the association between cold spells and the severity of coronary heart disease (CHD). This study was to investigate the association between cold spells with their different time types and CHD severity. We collected data on CHD patients admitted to the Zhongnan Hospital, Wuhan, China from 2016 to 2021. CHD severity was quantified using the SYNTAX score and transformed into a binomial variable. Daily mean, maximum and minimum temperature were collected during the study period. We first used daily mean temperature to find the optimum definition among multiple thresholds and durations. The daily maximum and minimum temperatures were used to define different types of cold spells (daytime, nighttime and compound) based on the optimum definition. Annual cold spell days were included to assess individual exposure to cold spells. Logistic regression models were performed to fit the association between cold spell days and CHD severity stratified by different tertiles of PM2.5 and NDVI. In this study, 1937 CHD patients were included. The cold spell defined as at least four consecutive days with daily mean temperature below the 5th percentile exhibited the optimum model. We found that a 4-day increase in cold spell days was associated with more severe CHD (OR = 1.170, 95% CI: 1.074, 1.282). Such an association was more pronounced under higher levels of PM2.5 by OR = 1.270 (1.086, 1.494) and lower levels of greenness by OR = 1.240 (1.044, 1.476). Compared with daytime and compound cold spells, nighttime cold spells showed the strongest association with CHD severity by OR = 1.141 (1.026, 1.269). This study showed that exposure to cold spells was positively associated with CHD severity, especially the nighttime cold spells. The association between cold spells and CHD severity was more significant in high levels of PM2.5 and low levels of greenness.

Associations of fine particulate matter and its metal constituents with blood pressure: A panel study during the seventh World Military Games.

Evidence is needed to elucidate the association of blood pressure (BP) changes with metal constituents in fine particulate matter (PM2.5). Therefore, we designed a longitudinal panel study enrolling 70 healthy students from Wuhan University in the context of the seventh World Military Games (the 7th WMG) from September 2019 to January 2020. A total of eight visits were conducted before, during, and after the 7th WMG. During every visit, each participant was asked to carry a personal PM2.5 monitor to measure hourly PM2.5 levels for three consecutive days. Questionnaire investigation and physical examination were completed on the fourth day. We analyzed ten metal constituents of ambient PM2.5 collected from the fixed station, and blood pressure was recorded during each visit. The linear mixed-effects models were performed to evaluate associations of metal constituents and blood pressure measurements. We observed a dramatic variation of PM2.5 concentration ranging from 7.38 to 132.04 µg/m3. A 10 µg/m3 increment of PM2.5 was associated with an increase of 0.64 mmHg (95% CI: 0.44, 0.84) in systolic BP (SBP), 0.40 mmHg (0.26, 0.54) in diastolic BP (DBP), 0.31 mmHg (0.15, 0.47) in pulse pressure (PP) and 0.44 mmHg (0.26, 0.62) in mean artery pressure (MAP), respectively. For metal constituents in PM2.5, robust positive associations were observed between BP and selenium, manganese, arsenic, cadmium, and thallium. For example, for an IQR (0.93 ng/m3) increment of selenium, SBP and MAP elevated by 0.98 mmHg (0.09, 1.87) and 0.71 mmHg (0.03, 1.39), respectively. Aluminum was found to be robustly associated with decreased SBP, DBP, and MAP. The study indicated that exposure to PM2.5 total mass and metal constituents including selenium, manganese, arsenic, cadmium, and thallium were associated with the elevated BP.

Association of Short-Term Exposure to PM2.5 with Blood Lipids and the Modification Effects of Insulin Resistance: A Panel Study in Wuhan.

Results of previous studies about the acute effects of fine particulate matter (PM2.5) on blood lipids were inconsistent. This study aimed to quantify the short-term effects of PM2.5 on blood lipids and estimate the modifying role of insulin resistance, reflected by the homeostasis model assessment of insulin resistance (HOMA-IR). From September 2019 to January 2020, the study recruited 70 healthy adults from Wuhan University for a total of eight repeated data collections. At each visit, three consecutive days were monitored for personal exposure to PM2.5, and then a physical examination was carried out on the fourth day. The linear mixed-effect models were operated to investigate the impact of PM2.5 over diverse exposure windows on blood lipids. With the median of the HOMA-IR 1.820 as the cut-off point, participants were assigned to two groups for the interaction analyses. We found the overall mean level (standard deviation, SD) of PM2.5 was 38.34 (18.33) µg/m3. Additionally, with a 10 µg/m3 rise in PM2.5, the corresponding largest responses in triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), as well as high-density lipoprotein cholesterol (HDL-C), were −0.91% (95% confidence interval (CI): −1.63%, −0.18%), −0.33% (95% CI: −0.64%, −0.01%,), −0.94% (95% CI: −1.53%, −0.35%), and 0.67% (95% CI: 0.32%, 1.02%), respectively. The interaction analyses revealed that a significantly greater reduction in the four lipids corresponded to PM2.5 exposure when in the group with the lower HOMA-IR (<1.820). In conclusion, short-term PM2.5 exposure over specific time windows among healthy adults was associated with reduced TG, TC, as well as LDL-C levels, and elevated HDL-C. Additionally, the association of PM2.5−lipids may be modulated by insulin resistance.

Short-term exposure to fine particulate matter and its constituents may affect renal function via oxidative stress: A longitudinal panel study.

Exposure to fine particulate matter (PM2.5) has been reported to increase the risks of chronic kidney disease. However, limited research has assessed the effect of PM2.5 and its constituents on renal function, and the underlying mechanism has not been well characterized. We aimed to evaluate the association of PM2.5 and its constituents with kidney indicators and to explore the roles of systematic oxidative stress and inflammation in the association. We conducted a longitudinal panel study among 35 healthy adults before-, intra- and after-the 2019 Wuhan Military World Games. We repeatedly measured 6 renal function parameters and 5 circulating biomarkers of oxidative stress and inflammation at 6 rounds of follow-ups. We monitored hourly personal PM2.5 concentrations with 3 consecutive days and measured 10 metals (metalloids) and 16 polycyclic aromatic hydrocarbons (PAHs) components. The linear mixed-effect models were applied to examine the association between PM2.5 and renal function parameters, and the mediation analysis was performed to explore potential bio-pathways. PM2.5 concentrations across Wuhan showed a slight decrease during the Military Games. We observed significant associations between elevated blood urea nitrogen (BUN) levels and PM2.5 and its several metals and PAHs components. For an interquartile range (IQR) increase of PM2.5, BUN increased 0.42 mmol/L (95% CI: 0.14 to 0.69). On average, an IQR higher of lead (Pb), cadmium (Cd), arsenic (As), selenium (Se), thallium (Tl) and Indeno (1,2,3-cd) pyrene (IPY) were associated with 0.90, 0.65, 0.29, 0.27, 0.26 and 0.90 mmol/L increment of BUN, respectively. Moreover, superoxide dismutase was positively associated with PM2.5 and mediated 18.24% association. Our research indicated that exposure to PM2.5 might affect renal function by activating oxidative stress pathways, in which the constituents of Pb, Cd, As, Se, Tl and IPY might contribute to the associations.

Effect of urinary catheter removal on different time after hysterectomy: a network meta-analysis.

INTRODUCTION AND HYPOTHESIS: The optimal timing for removing urinary catheters is controversial for patients undergoing total hysterectomy. This study aimed to evaluate the optimal time for removing urinary catheters post-hysterectomy. METHODS: We searched multiple databases from inception till December 31, 2020, for all randomized trials evaluating the timing of catheter removal following hysterectomy. All studies were evaluated by two investigators independently depending on inclusion and exclusion criteria. Network meta-analysis (NMA) was conducted on the data using Stata 14.0 software. RESULTS: A total of 12 articles involving 1814 patients were ultimately included. This study showed removing urinary catheters 12.1 to 24 h (pooled OR = 2.67; 95% CI, 1.53­4.67) and 36.1 to 48 h (pooled OR = 8.11;95% CI, 3.78­17.36) post-hysterectomy increased the risk of urinary tract infection (UTI) compared with immediate catheter removal. Timing of catheter removal in other groups following hysterectomy accompanied a reduced risk of urinary retention (UR) versus immediate catheter removal (P < 0.05). Removal of the urinary catheter from 36.1 to 48 h was most likely to lead to UTI. The maximum SUCRA value of immediate catheter removal after hysterectomy was 99.3% for UR. Catheter removal 24.1 to 36 h after hysterectomy was the best time for preventing UR. CONCLUSION: Removal of the catheter immediately after hysterectomy may be the optimal time for preventing UTI with increased risk of UR, whereas removal time of the urinary catheters within 6 h post-hysterectomy combined with postoperative urination monitoring might be more beneficial than other removal times following hysterectomy.

Acute effect of fine particulate matter on blood pressure, heart rate and related inflammation biomarkers: A panel study in healthy adults.

Epidemiological evidence of short-term fine particulate matter (PM2.5) exposure on blood pressure (BP), heart rate (HR) and related inflammation biomarkers has been inconsistent. We aimed to explore the acute effect of PM2.5 on BP, HR and the mediation effect of related inflammation biomarkers. A total of 32 healthy college students were recruited to perform 4 h of exposure at two sites with different PM2.5 concentrations in Wuhan between May 2019 and June 2019. The individual levels of PM2.5 concentration, BP and HR were measured hourly for each participant. Blood was drawn from each participant after each visit and we measured the levels of inflammation markers, including serum high-sensitivity C-reactive protein and plasma fibrinogen. Linear mixed-effect models were to explore the acute effect of PM2.5 exposure on BP, HR, and related inflammation biomarkers. In addition, we evaluated related inflammation biomarkers as the mediator in the association of PM2.5 and cardiovascular health indicators. The results showed that a 10 µg/m3 increment in PM2.5 concentration was associated with an increase of 0.84 (95% CI: 0.54, 1.15) beats/min (bpm) in HR and a 3.52% (95% CI: 1.60%, 5.48%) increase in fibrinogen. The lag effect model showed that the strongest effect on HR was observed at lag 3 h of PM2.5 exposure [1.96 bpm (95% CI: 1.19, 2.75)], but for fibrinogen, delayed exposure attenuated the association. Increased fibrinogen levels may account for 39.07% (P = 0.44) of the elevated HR by PM2.5. Null association was observed when it comes to short-term PM2.5 exposure and BP. Short-term exposure to PM2.5 was associated with elevated HR and increased fibrinogen levels. But our finding was not enough to suggest that exposure to PM2.5 might induce adverse cardiovascular effects by the pathway of inflammation.