Prediction of asthma exacerbations among children through integrating air pollution, upper atmosphere, and school health surveillances

Allergy Asthma Proc. 2013 Jan-Feb;34(1):e1-8. doi: 10.2500/aap.2013.34.3629.

Abstract

Climatic factors and air pollution are important in predicting asthma exacerbations among children. This study was designed to determine if a relationship exists between asthma exacerbations among elementary school children and the combined effect of daily upper atmosphere observations (temperature, relative humidity, dew point, and mixing ratio) and daily air pollution (particulate matter, sulfur dioxide, nitrogen dioxide, carbon monoxide, and ozone) and, if so, to predict asthma exacerbations among children using a mathematical model. Using an ecological study design, school health records of 168,825 students in elementary schools enrolled in "Health eTools for Schools" within 49 Pennsylvania counties were analyzed. Data representing asthma exacerbations were originally recorded by school nurses as the type of treatment given to a student during a clinic visit on a particular day. Daily upper atmosphere measurements from ground level to the 850-mb pressure level and air pollution measurements were obtained. A generalized estimating equation model was used to predict the occurrence of >48 asthma exacerbations, the daily mean for 2008-2010. The greatest occurrence of asthma among school children was in the fall, followed by summer, spring, and winter. Upper atmosphere temperature, dew point, mixing ratio, and six air pollutants as well as their interactions predicted the probability of asthma exacerbations occurring among children. Monitoring of upper atmosphere observation data and air pollutants over time can be a reliable means for predicting increases of asthma exacerbations among elementary school children. Such predictions could help parents and school officials implement effective precautionary measures.

MeSH terms

  • Air Pollution / adverse effects
  • Air Pollution / statistics & numerical data*
  • Asthma / diagnosis*
  • Asthma / epidemiology*
  • Atmosphere
  • Atmospheric Pressure
  • Child
  • Disease Progression
  • Female
  • Health Surveys
  • Humans
  • Male
  • Models, Theoretical
  • Pennsylvania / epidemiology
  • Prevalence
  • Prognosis
  • Public Health Surveillance
  • Schools / statistics & numerical data*
  • Seasons
  • Software