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Ambient Temperature and Outpatient Visits for Acute Exacerbation of Chronic Bronchitis in Shanghai: A Time Series Analysis 被引量:8

Ambient Temperature and Outpatient Visits for Acute Exacerbation of Chronic Bronchitis in Shanghai: A Time Series Analysis
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摘要 The association between ambient temperature and acute exacerbation of chronic bronchitis (AECB) was still unknown. Therefore, we performed an epidemiological study in a large hospital of Shanghai to explore the relationship about temperature and outpatient visit for AECB. We adopted a quasi-Poisson generalized additive models and distributed lag nonlinear models to estimate the accumulative effects of temperature on AECB across multiple days. We found significant non-linear effects of cold temperature on hospital visits for AECB, and the potential effect of cold temperature might last more than 2 weeks. The relative risks of extreme cold (first percentiles of temperature throughout the study period) and cold (10th percentile of temperature) temperature over lags 0-14 d were 2.98 [95% confidence intervals (CI): 1.77, 5.04] and 1.63 (95% Ch 1.21, 2.19), compared with the 25th percentile of temperature. However, we found no positive association between hospital visits and hot weather. This study showed that exposure to both extreme cold and cold temperatures were associated with increased outpatient visits for AECB in a large hospital of Shanghai. The association between ambient temperature and acute exacerbation of chronic bronchitis (AECB) was still unknown. Therefore, we performed an epidemiological study in a large hospital of Shanghai to explore the relationship about temperature and outpatient visit for AECB. We adopted a quasi-Poisson generalized additive models and distributed lag nonlinear models to estimate the accumulative effects of temperature on AECB across multiple days. We found significant non-linear effects of cold temperature on hospital visits for AECB, and the potential effect of cold temperature might last more than 2 weeks. The relative risks of extreme cold (first percentiles of temperature throughout the study period) and cold (10th percentile of temperature) temperature over lags 0-14 d were 2.98 [95% confidence intervals (CI): 1.77, 5.04] and 1.63 (95% Ch 1.21, 2.19), compared with the 25th percentile of temperature. However, we found no positive association between hospital visits and hot weather. This study showed that exposure to both extreme cold and cold temperatures were associated with increased outpatient visits for AECB in a large hospital of Shanghai.
出处 《Biomedical and Environmental Sciences》 SCIE CAS CSCD 2015年第1期76-79,共4页 生物医学与环境科学(英文版)
基金 supported by the National Clinical key subject construction funds(occupational disease program) the National Basic Research Program(973 program)of China(2011CB503802) Gong-Yi Program of China Ministry of Environmental Protection(201209008) China Medical Board Collaborating Program(13-152) Public Welfare Research Program of National Health Family Planning Commission of China(201402022)
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  • 1Luber G, McGeehin M. Climate change and extreme heat events. Am J Prev Med, 2008; 35, 429-35.
  • 2Braga AL, Zanobetti A, Schwartz J. The effect of weather on respiratory and cardiovascular deaths in 12 U.S. Cities. Environ Health Perspect, 2002; 110, 859-63.
  • 3Mannino DM, Buist AS. Gobal burden of copd: Risk factors, prevalence, and future trends. Lancet, 2007; 370, 765-73.
  • 4Anthonisen NR, Manfreda J, Warren CP, et al. Antibiotic therapy in exacerbations of chronic obstructive pulmonary disease. Ann Intern Med, 1987; 106, 196-204.
  • 5Chen RJ, Wang CC, Meng X, et al. Both low and high temperature may increase the risk of stroke mortality. Neurology, 2013; 81, 1064-70.
  • 6Peng RD, Dominici F, Louis TA. Model choice in time series studies of air pollution and mortality. J Roy Stat Soc a Sta, 2006; 169, 179-98.
  • 7Gasparrini A. Distributed lag linear and non-linear models in r: The package dlnm. J Stat Softw, 2011; 43, 1-20.
  • 8Wang C, Chen R, Kuang X, et al. Temperature and daily mortality in Suzhou, China: A time series analysis. Sci Total Environ, 2014; 466, 985-90.
  • 9Ma W, Yang C, Tan J, et al. Modifiers of the temperature-mortality association in Shanghai, China. Int J 8iometeorol, 2012; 56, 205-7.
  • 10Basu R, Ostro BD. A multicounty analysis identifying the populations vulnerable to mortality associated with high ambient temperature in California. Am J Epidemiol, 2008; 168, 632-7.

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