Objective: To explore the spatial-temporal interaction effect within a Bayesian framework and to probe the ecological influential factors for tuberculosis. Methods: Six different statistical models containing parameters of time, space, spatial-temporal interaction and their combination were constructed based on a Bayesian framework. The optimum model was selected according to the deviance information criterion (DIC) value. Coefficients of climate variables were then estimated using the best fitting model. Results: The model containing spatial-temporal interaction parameter was the best fitting one, with the smallest DIC value (−4,508,660). Ecological analysis results showed the relative risks (RRs) of average temperature, rainfall, wind speed, humidity, and air pressure were 1.00324 (95% CI, 1.00150–1.00550), 1.01010 (95% CI, 1.01007–1.01013), 0.83518 (95% CI, 0.93732–0.96138), 0.97496 (95% CI, 0.97181–1.01386), and 1.01007 (95% CI, 1.01003–1.01011), respectively. Conclusions: The spatial-temporal interaction was statistically meaningful and the prevalence of tuberculosis was influenced by the time and space interaction effect. Average temperature, rainfall, wind speed, and air pressure influenced tuberculosis. Average humidity had no influence on tuberculosis.

(1) Background: Evidence regarding scarlet fever and its relationship with meteorological, including air pollution factors, is not very available. This study aimed to examine the relationship between ambient air pollutants and meteorological factors with scarlet fever occurrence in Beijing, China. (2) Methods: A retrospective ecological study was carried out to distinguish the epidemic characteristics of scarlet fever incidence in Beijing districts from 2013 to 2014. Daily incidence and corresponding air pollutant and meteorological data were used to develop the model. Global Moran’s I statistic and Anselin’s local Moran’s I (LISA) were applied to detect the spatial autocorrelation (spatial dependency) and clusters of scarlet fever incidence. The spatial lag model (SLM) and spatial error model (SEM) including ordinary least squares (OLS) models were then applied to probe the association between scarlet fever incidence and meteorological including air pollution factors. (3) Results: Among the 5491 cases, more than half (62%) were male, and more than one-third (37.8%) were female, with the annual average incidence rate 14.64 per 100,000 population. Spatial autocorrelation analysis exhibited the existence of spatial dependence; therefore, we applied spatial regression models. After comparing the values of R-square, log-likelihood and the Akaike information criterion (AIC) among the three models, the OLS model (R² = 0.0741, log likelihood = −1819.69, AIC = 3665.38), SLM (R² = 0.0786, log likelihood = −1819.04, AIC = 3665.08) and SEM (R² = 0.0743, log likelihood = −1819.67, AIC = 3665.36), identified that the spatial lag model (SLM) was best for model fit for the regression model. There was a positive significant association between nitrogen oxide (p = 0.027), rainfall (p = 0.036) and sunshine hour (p = 0.048), while the relative humidity (p = 0.034) had an adverse association with scarlet fever incidence in SLM. (4) Conclusions: Our findings indicated that meteorological, as well as air pollutant factors may increase the incidence of scarlet fever; these findings may help to guide scarlet fever control programs and targeting the intervention.

Research on the relationship between metabolic syndrome (MetS), its components and eating speed is limited in China. The present study aimed to clarify the association between MetS, its components and eating speed in a Beijing adult population. This cross-sectional study included 7972 adults who were 18–65 years old and who received health check-ups at the Beijing Physical Examination Center in 2016. Logistic regression was conducted to explore the associations between MetS, its components and eating speed. The prevalence of MetS in this population was 24.65% (36.02% for males and 10.18% for females). Eating speed was significantly associated with a high risk for MetS, elevated blood pressure, and central obesity for both genders. Eating speed was associated with a high risk for elevated triglycerides and with a reduction in high-density lipoprotein in males, and eating speed was associated with a high risk for elevated fasting plasma glucose in females. Compared with slow eating speed, the multivariate-adjusted odds ratios of medium eating speed and fast eating speed for MetS were 1.65 (95% confidence interval 1.32–2.07) and 2.27 (95% confidence interval 1.80–2.86) for all subjects, 1.58 (95% confidence interval 1.21–2.07) and 2.21 (95% confidence interval 1.69–2.91) for males, and 1.75 (95% confidence interval 1.15–2.68) and 2.27 (95% confidence interval 1.46–3.53) for females, respectively. Eating speed is positively associated with MetS and its components. Future recommendations aiming to prevent MetS and its components may focus on eating speed.

Air pollutants are common modifiable risk factors for arthritis. To explore the longitudinal effects of air pollution on arthritis based on a cohort study in middle-aged and elder people of China. Data was obtained from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018. A total of 7449 participants aged 45 years and older were involved in our study. The generalized linear mixed models were conducted to examine the separate and joint effects of household air pollution and outdoor air pollution on arthritis, respectively. We found a strong significant association between air pollution and arthritis incidence. Individuals cooking primarily with solid fuel were more likely in higher risk of arthritis compared with cleaner fuel (OR= 1.15; 95% CI: 1.08-1.23). The group-based trajectory model identified four trajectory groups, compared with group "High-Decreasing rapidly", adjusted ORs of incident arthritis for group "Middle-Decreasing moderately", "Low-Decreasing slowly" and "Low-Stably" were 1.36 (95% CI, 1.03-1.79), 1.36 (95% CI, 1.01-1.83) and 1.81 (95% CI, 1.30-2.52), respectively. These associations were generally higher in participants younger than 65 years. In addition, solid fuel use and PM_2.5 exposure had additive and multiplicative effects on arthritis. The results suggested that solid fuel use and long-term PM_2.5 exposure were associated with a higher incidence of arthritis. Therefore, it is necessary to restrict solid fuel use to reduce household air pollution and make stronger environmental protection policies to reduce PM_2.5 concentration.

Background: Epidemiological evidences regarding the association between the use of non-steroidal anti-inflammatory drugs (NSAIDs) and the risk of prostate cancer (PC) is still controversial. Therefore, we conducted a meta-analysis to explore the controversy that exists. Methods: Electronic databases including Medline, EMBASE, Web of Science, Cochrane Library, BIOSIS, Scopus, CBM, CNKI, WANFANG, and CQVIP were used to search for and identify eligible studies published until December 31, 2017. Pooled effect estimates for the relative risk (RR) were computed through fixed-effects or random-effects models as appropriate. Publication bias was evaluated by Egger's and Begg's tests and potential sources of heterogeneity were investigated in subgroup analyses. Results: A total of 43 observational studies were eligible for this meta-analysis. A protective effect was identified for the intake of any NSAIDs on the risk of PC (pooled RR = 0.89, 95% CI = 0.81–0.98). Moreover, the long-term intake of NSAIDs (≥5 years rather than ≥4 years) was associated with reduced PC incidence (pooled RR = 0.882, 95% CI = 0.785–0.991). Aspirin intake was also associated with a 7.0% risk reduction of PC (pooled RR = 0.93, 95% CI = 0.89–0.96). The inverse association became stronger for advanced PC and PC with a Gleason score ≥7 compared to the association with total PC. Interestingly, it was the daily dose (≥1 pill/day) rather than, long-term aspirin intake (≥4 or ≥5 years) that was associated with reduced PC incidence (pooled RR = 0.875, 95% CI = 0.792–0.967). The pooled effects for non-aspirin NSAIDs demonstrated no significantly adverse or beneficial effects on total PC, advanced PC, or PC with Gleason score ≥7, though all pooled RRs were >1. Conclusions: Our findings suggested a protective effect of the intake of any NSAIDs on the risk of PC, especially in those who took the NSAIDs for a long period. Moreover, aspirin intake was also associated with a decreased risk of PC, and there was a dose related association between aspirin intake and the risk of PC, while no significant effects of long-term aspirin intake were found on the PC incidence.

Past studies have demonstrated that goal-directed fluid therapy (GDFT) may be more marginal than previously believed. However, beneficial effects of alpha-1 adrenergic agonists combined with appropriate fluid administration is getting more and more attention. This study aimed to systematically review the effects of goal-directed fluid therapy (GDFT) combined with the application of alpha-1 adrenergic agonists on postoperative outcomes following noncardiac surgery. This meta-analysis included randomized controlled trials (RCTs) on GDFT combined with the application of alpha-1 adrenergic agonists in patients undergoing noncardiac surgery. The primary outcomes included the postoperative mortality rate and length of hospital stay (LOS). The secondary outcome indexes were the incidence of postoperative complications and recovery of postoperative gastrointestinal (GI) function. The traditional pairwise meta-analysis was conducted to compare the effect of fluid therapy. The quality of included RCTs was evaluated according to the Cochrane Collaboration’s risk-of-bias tool. Also, the publication bias was detected using funnel plots, Egger’s regression test, and Begg’s adjusted rank correlation test. The meta-analysis was conducted using the RevMan 5.3 and Stata 14.0 software. Thirty-two eligible RCTs were included in this meta-analysis. Perioperative GDFT combined with the application of alpha-1 adrenergic agonists was associated with a significant reduction in LOS (P = 0.002; I2 = 69%), and overall complication rates (P = 0.04; I2 = 41%). It facilitated gastrointestinal function recovery, as demonstrated by shortening the time to first flatus by 6.30 h (P < 0.00001; I2 = 91%) and the time to toleration of solid food by 1.69 days (P < 0.00001; I2 = 0%). Additionally, there was no significant reduction in short-term mortality in the GDFT combined with alpha-1 adrenergic agonists group (P = 0.05; I2 = 0%). This systematic review of available evidence suggested that the use of perioperative GDFT combined with alpha-1 adrenergic agonists might facilitate recovery in patients undergoing noncardiac surgery.