title: Forecasting models for sugi (Cryptomeria japonica D. Don) pollen count showing an alternate dispersal rhythm.
abstract: BACKGROUND
  Pollen information is indispensable for allergic individuals and clinicians. This study aimed to develop forecasting models for the total annual count of airborne pollen grains based on data monitored over the last 20 years at the Mie Chuo Medical Center, Tsu, Mie, Japan.
  
  
  METHODS
  Airborne pollen grains were collected using a Durham sampler. Total annual pollen count and pollen count from October to December (OD pollen count) of the previous year were transformed to logarithms. Regression analysis of the total pollen count was performed using variables such as the OD pollen count and the maximum temperature for mid-July of the previous year.
  
  
  RESULTS
  Time series analysis revealed an alternate rhythm of the series of total pollen count. The alternate rhythm consisted of a cyclic alternation of an "on" year (high pollen count) and an "off" year (low pollen count). This rhythm was used as a dummy variable in regression equations. Of the three models involving the OD pollen count, a multiple regression equation that included the alternate rhythm variable and the interaction of this rhythm with OD pollen count showed a high coefficient of determination (0.844). Of the three models involving the maximum temperature for mid-July, those including the alternate rhythm variable and the interaction of this rhythm with maximum temperature had the highest coefficient of determination (0.925).
  
  
  CONCLUSIONS
  An alternate pollen dispersal rhythm represented by a dummy variable in the multiple regression analysis plays a key role in improving forecasting models for the total annual sugi pollen count.
authors.affiliation: Department of Otorhinolaryngology, National Hospital Organization, Mie Chuo Medical Center, Mie, Japan. fujiyuki@iris.ocn.ne.jp
authors.forename: Yukiko
authors.initials: Y
authors.lastname: Ito
authors.forename: Reiko
authors.initials: R
authors.lastname: Hattori
authors.forename: Hiroki
authors.initials: H
authors.lastname: Mase
authors.forename: Masako
authors.initials: M
authors.lastname: Watanabe
authors.forename: Itaru
authors.initials: I
authors.lastname: Shiotani
mesh_terms: D000485:Allergens / Q000032:analysis* / Q000096:biosynthesis; D032485:Cryptomeria; D006801:Humans; D008954:Models, Biological; D010507:Periodicity; D011058:Pollen / Q000276:immunology; D054817:Pollination / Q000276:immunology; D011379:Prognosis; D012044:Regression Analysis; D006255:Rhinitis, Allergic, Seasonal / Q000175:diagnosis / Q000276:immunology / Q000503:physiopathology*; D013696:Temperature
chemical_list: D000485:Allergens