title: The use of mixed generalized additive modeling to assess the effect of temperature on the usage of emergency electrocardiography examination among the elderly in Shanghai.
abstract: BACKGROUND
  Acute coronary artery diseases have been observed to be associated with some meteorological variables. But few of the previous studies considered autocorrelated outcomes. Electrocardiography is a widely used tool in the initial diagnosis of acute cardiovascular events, and emergency electrocardiography counts were shown to be highly correlated with acute myocardial infarction in our pilot study, hence a good index of prediction for acute cardiovascular events morbidity among the elderly. To indirectly assess the impact of temperature on the number of acute cardiovascular events, we studied the association between temperature and emergency electrocardiography counts while considering autocorrelated nature of the response variables.
  
  
  METHODS
  We collected daily emergency electrocardiography counts for elderly females and males in Shanghai from 2007 to middle 2012, and studied temperature and other effects on these data using Mixed Generalized Additive Modelling methods. Delayed temperature effect distribution was described as the weighted average of the temperatures within 3 days before the counts was recorded. Autoregressive random effects were used in the model to describe the autocorrelation of the response variables.
  
  
  RESULTS
  Temperature effect was observed to be piecewise linearly associated with the logarithm of emergency electrocardiography counts. The optimal weights of the delayed temperature effect distribution were obtained from the model estimation. The weights of lag-1 were the maximums, significantly greater than the weights of lag-2 and lag-3 for both females and males. The model showed good fit with R2 values of 0.860 for females and 0.856 for males.
  
  
  CONCLUSIONS
  From the mixed generalized additive model, we infer that during cold and mild days, the number of emergency electrocardiography counts increase as temperature effect decreases, while during hot days, counts increase as temperature effect increases. Similar properties could be inferred for the occurrence of cardiovascular events.
authors.affiliation: Department of Biostatistics and Social Medicine, School of Public Health, Fudan University, Shanghai, China.
authors.forename: Wei-ping
authors.initials: WP
authors.lastname: Ma
authors.affiliation: Shanghai Children's Medical Center, Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China.
authors.forename: Shuo
authors.initials: S
authors.lastname: Gu
authors.affiliation: Children's Hospital of Fudan University, Shanghai, China.
authors.forename: Yi
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Shang Hai Medical Insurance Administration, Shanghai, China.
authors.forename: Xian-jing
authors.initials: XJ
authors.lastname: Zhang
authors.affiliation: Shang Hai Medical Insurance Administration, Shanghai, China.
authors.forename: Ai-rong
authors.initials: AR
authors.lastname: Wang
authors.affiliation: Department of Biostatistics and Social Medicine, School of Public Health, Fudan University, Shanghai, China.
authors.forename: Nai-qing
authors.initials: NQ
authors.lastname: Zhao
authors.affiliation: Department of Biostatistics, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
authors.forename: Yan-yan
authors.initials: YY
authors.lastname: Song
mesh_terms: D002318:Cardiovascular Diseases / Q000175:diagnosis* / Q000453:epidemiology*; D002681:China / Q000453:epidemiology; D004562:Electrocardiography / Q000706:statistics & numerical data*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D010865:Pilot Projects; D011379:Prognosis; D013696:Temperature; D013997:Time Factors