title: Effects of meteorological factors on daily hospital admissions for asthma in adults: a time-series analysis.
abstract: BACKGROUND
  There is limited evidence for the impacts of meteorological changes on asthma hospital admissions in adults in Shanghai, China.
  
  
  OBJECTIVE
  To quantitatively evaluate the short-term effects of daily mean temperature on asthma hospital admissions.
  
  
  METHODS
  Daily hospital admissions for asthma and daily mean temperatures between January 2005 and December 2012 were analyzed. After controlling for secular and seasonal trends, weather, air pollution and other confounding factors, a Poisson generalized additive model (GAM) combined with a distributed lag non-linear model were used to explore the associations between temperature and hospital admissions for asthma.
  
  
  RESULTS
  During the study periods, there were 15,678 hospital admissions for asthma by residents of Shanghai, an average 5.6 per day. Pearson correlation analysis found a significant negative correlation (r = -0.174, P<0.001) between asthma hospitalizations and daily mean temperature (DMT). The DMT effect on asthma increased below the median DMT, with lower temperatures associated with a higher risk of hospital admission for asthma. Generally, the cold effect appeared to be relatively acute, with duration lasting several weeks, while the hot effect was short-term. The relative risk of asthma hospital admissions associated with cold temperature (the 25th percentile of temperature relative to the median temperature) was 1.20 (95% confidence interval [CI], 1.01∼1.41) at lag0-14. However, warmer temperatures were not associated with asthma hospital admissions.
  
  
  CONCLUSIONS
  Cold temperatures may trigger asthmatic attacks. Effective strategies are needed to protect populations at risk from the effects of cold.
authors.affiliation: Department of Epidemiology, School of Public Health, and Key Laboratory of Public Health Safety (Ministry of Education), Fudan University, Shanghai, China.
authors.forename: Yue
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Shanghai Center for Urban Environmental Meteorology, Shanghai, China; Shanghai Key Laboratory of Meteorology and Health, Shanghai, China.
authors.forename: Li
authors.initials: L
authors.lastname: Peng
authors.affiliation: Department of Epidemiology, School of Public Health, and Key Laboratory of Public Health Safety (Ministry of Education), Fudan University, Shanghai, China; Fudan Tyndall Centre, Fudan University, Shanghai, China.
authors.forename: Haidong
authors.initials: H
authors.lastname: Kan
authors.affiliation: Shanghai Center for Urban Environmental Meteorology, Shanghai, China; Shanghai Key Laboratory of Meteorology and Health, Shanghai, China.
authors.forename: Jianming
authors.initials: J
authors.lastname: Xu
authors.affiliation: Department of Epidemiology, School of Public Health, and Key Laboratory of Public Health Safety (Ministry of Education), Fudan University, Shanghai, China.
authors.forename: Renjie
authors.initials: R
authors.lastname: Chen
authors.affiliation: Department of Epidemiology, School of Public Health, and Key Laboratory of Public Health Safety (Ministry of Education), Fudan University, Shanghai, China.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Department of Epidemiology, School of Public Health, and Key Laboratory of Public Health Safety (Ministry of Education), Fudan University, Shanghai, China; Fudan Tyndall Centre, Fudan University, Shanghai, China.
authors.forename: Weibing
authors.initials: W
authors.lastname: Wang
mesh_terms: D000328:Adult; D000397:Air Pollution / Q000032:analysis; D001249:Asthma / Q000453:epidemiology*; D002681:China / Q000453:epidemiology; D006801:Humans; D008685:Meteorological Concepts; D008962:Models, Theoretical; D017711:Nonlinear Dynamics; D010343:Patient Admission / Q000706:statistics & numerical data*; D016012:Poisson Distribution; D013696:Temperature; D013997:Time Factors