Using seasonal variations in asthma hospitalizations in children to predict hospitalization frequency.

Abstract

Asthma hospitalization rates have increased in the United States since 1980. The exposure risk of many environmental factors, which contribute to respiratory disease, vary throughout the year. The objective of this study was to investigate the seasonal variation of pediatric asthma hospitalizations and predict hospitalization frequency. This was a longitudinal analysis of all pediatric asthma hospitalizations in the state of Maryland by age, gender, race, and residence using non-confidential discharge data sets from 1986 to 1999. Of the 631,422 pediatric hospitalizations in the state of Maryland during the years 1986-1999, 45,924 (7%) had a primary admission diagnosis of asthma. Frequency of hospitalization for asthma was lowest in the summer in all age groups, and highest in the fall. Seasonal variation in severe asthma episodes was least striking in children aged 15-18. This was in contrast to non-asthma admissions, which were highest in winter in preschool children, but relatively flat in school- and teenaged children. Using neural network modeling, weekly asthma hospitalizations could be predicted with an R2 between 0.71 and 0.8. Temporal trends in asthma hospitalizations were seen in each age group, gender, race, and location. The seasonal variability in asthma hospitalizations suggests that acute asthma is influenced by variables beyond socioeconomic factors and adherence to medical regimens. Strategies to combat exacerbations of asthma should take into consideration seasonal effects on a population. In addition, temporal trends examined over many years can be used to predict frequency of severe asthma episodes in a population.