Background A small number of studies suggested that air pollution was associated with idiopathic pulmonary fibrosis (IPF) exacerbation, incidence and mortality. However, no studies to date were conducted in regions where air pollution is substantial. We aimed to investigate whether there are associations between acute increases in air pollution and hospitalization of patients with a confirmed primary diagnosis of IPF in Beijing. Methods Daily count of IPF hospitalizations (International Classification of Disease-10th Revision, J84.1) was obtained from an administrative database for 2013–2017 while daily city-wide average concentrations of PM10, PM2.5, NO2, Ozone, SO2 were obtained from 35 municipal monitoring stations for the same period. The association between daily IPF hospitalization and average concentration of each pollutant was analyzed with a generalized additive model estimating Poisson distribution. Results Daily 24-h mean PM2.5 concentration during 2013–2017 was 76.7 μg/m3. The relative risk (RR) of IPF hospitalization per interquartile range (IQR) higher (72 μg/m3) in PM2.5 was 1.049 (95% CI 1.024–1.074) and 1.031 (95% CI 1.007–1.056) for lag0 and moving averages 0–1 days respectively. No significant associations were observed for other lags. Statistically significant positive associations were also observed at lag0 with SO2, Ozone and NO2 (in men only). Positive associations were seen at moving averages 0–30 days for PM10 (RR per 86 μg/m3: 1.021, 95% CI 0.994–1.049), NO2 (RR per 30 μg/m3: 1.029, 95% CI 0.999–1.060), and SO2 (RR per 15 μg/m3: 1.060 (95% CI 1.025–1.097), but not with PM2.5 or Ozone. Conclusions Despite improvement in air quality since the implementation of clean air policy in 2013, acute exposure to higher levels of air pollution is significantly associated with IPF hospitalization in Beijing. Air quality policy should be continuously enforced to protect vulnerable IPF populations as well as the general public.
Background and Objective: Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. We aimed to evaluate the temporal trends in hospitalization and mortality from acute exacerbation of COPD (AECOPD) and the associated financial costs over a 10-year period in Beijing, China. Methods: Hospital admission records from 2008 to 2017 for all patients aged ≥20 years with a primary discharge diagnosis of AECOPD were retrieved from the Beijing Public Health Information Center Database. Joinpoint regression was used to analyze trends and calculate the annual percentage change (APC) and average annual percent change (AAPC) for AECOPD hospitalization and mortality. Results: A total of 337,802 AECOPD cases were recorded from 2008 to 2017. An inverse U-shaped trend in the AECOPD hospitalization rate was observed, showing an increase from 150.2 per 100,000 inhabitants in 2008 to 218.7 per 100,000 inhabitants in 2014 (APC: 5.5%, 95% CI: 2.9-8.2), before declining to 161.13 per 100,000 inhabitants in 2017 (APC: −9.7%, 95% CI: −16.0 to-2.9). In-hospital mortality from AECOPD decreased significantly from 3.91% to 2.21% (AAPC: −11.4%, 95% CI: −15.5 to−7.0). A decline in the median length of hospital stay from 13.0 days in 2008 to 12.0 days in 2017 (P trend < 0.001) was accompanied by a decrease in the use of mechanical ventilation from 2012 to 2017 (P trend < 0.001). However, the total hospitalization cost per case increased from 15953.5 yuan (USD $2281.4) to 19874.5 yuan ($2842.1) during the same period. Conclusion: AECOPD remains a heavy burden on the health care system in Beijing. Strategies to better manage COPD and reduce hospitalizations from AECOPD are needed.
INTRODUCTION Varenicline is an effective smoking cessation medicine. However, the possible adverse neuropsychiatric events reported by Food and Drug Administration for varenicline may cause safety problems for professional drivers. We aimed to investigate its safety and impacts on driving behaviors among taxi drivers in Beijing, China. METHODS An observational cohort study was conducted in a smoking cessation clinic in Beijing, China, between September 2017 and April 2018. Smokers with varenicline for smoking cessation were included and categorized into taxi-driver smokers (n=103) and non-taxi-driver smokers (n=119). All participants received varenicline up to 12 weeks and five standardized counseling sessions. Treatmentrelated adverse events (AEs) were collected in all participants and their impacts on driving behaviors were assessed in taxi-driver smokers. Multiple logistic regression analysis was used to examine potential risk factors for vareniclinerelated somnolence/fatigue. RESULTS The incidence of most treatment-related AEs was similar between taxidriver smokers and non-taxi-driver smokers, but treatment-related somnolence/ fatigue was more frequently reported in taxi-driver smokers (18.4% vs 6.7%; p=0.008). Most taxi-driver smokers (87.4%) reported that treatment-related AEs did not affect their driving behaviors, and no traffic accident was reported during treatment. CONCLUSIONS Varenicline appears to be a well-tolerated smoking cessation aid for Beijing taxi drivers and has less impact on driving behaviors. However, taxidriver smokers were more likely to report somnolence/fatigue during varenicline treatment and physicians should pay more attention to this occupational population.
INTRODUCTIONHealthcare information systems (HIS) are used to aid healthcare providers delivering brief smoking cessation interventions. However, evidence regarding the effectiveness of intervention models in developing countries remains limited. A smoking cessation intervention model based on a decision support tool embedded in HIS (an ‘e-information model’, including Ask, Advise, Assess, Inform, Refer and Print components) was applied in a large urban general hospital in Beijing, China. The current study was a preliminary evaluation of the implementation and effectiveness of this model.METHODSWe conducted a retrospective investigation in the outpatient department of the hospital in the period June–July 2017. Using a paper questionnaire, patients’ self-reported receipt of the e-information model in the past 2 months and their plans to quit within 1 month were collected. Multivariate logistic regression analysis was used to examine the association between receiving the e-information model and patients’ plans to quit.RESULTSAmong 656 currently smoking patients, the proportion of patients receiving the Ask, Advise, Assess, Refer and Print components were 73.2%, 65.4%, 49.8%, 16.0% and 10.4%, respectively. The results revealed a dose-response relationship between the number of components received and the proportion of patients planning to quit (p-trend=0.006). The likelihood of patients planning to quit within 1 month was highest among those receiving all five components (OR=2.79, 95% CI: 1.31–5.94). Moreover, a simplified model composed of two or three components also revealed a potential effect on increasing the proportion of patients planning to quit.CONCLUSIONSThe e-information model was applied effectively in the study hospital and appeared to encourage patients to plan to quit smoking. This model could be generalized to other hospitals in China and other developing countries. However, many components of this model were less utilized, and comprehensive measures will be required to improve its application in the future.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.