Predicting future asthma morbidity in preschool inner-city children

J Asthma. 2011 Oct;48(8):797-803. doi: 10.3109/02770903.2011.604887. Epub 2011 Aug 23.

Abstract

Background and aims: Children living in the inner city are particularly vulnerable to asthma. While we know much about factors that affect near-term outcomes in inner-city children, there is little evidence to guide clinicians on what to expect in the coming years, especially in preschool children. The purpose of our study was to determine which clinical and environmental factors are predictive of poor long-term asthma control in preschool inner-city children.

Materials and methods: Baseline characteristics determined to be potential predictors of asthma severity were examined: demographics, asthma symptoms, medication use, healthcare utilization, early life medical history, family history, allergen exposure and allergic disease, and pollutant exposure. Bivariate and multivariate analyses were performed using logistic regression to examine the association of predictors of asthma severity with healthcare utilization at 2 years.

Results: Of the 150 children at baseline, the follow-up rate was 83% at 2 years; therefore, 124 children were included in final analyses. At baseline, the mean age was 4.4 years and participants were predominantly African-American (90%). Most of the children were atopic and 32.5% reported using inhaled corticosteroids. Nighttime awakening from asthma and a history of pneumonia were predictive of future poor control.

Conclusion: Preschool children with nighttime awakening from asthma and a history of pneumonia may deserve closer monitoring to prevent future asthma morbidity.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Asthma / epidemiology*
  • Asthma / etiology
  • Asthma / immunology
  • Baltimore / epidemiology
  • Child
  • Child, Preschool
  • Follow-Up Studies
  • Humans
  • Interviews as Topic
  • Logistic Models
  • Male
  • Morbidity
  • Multivariate Analysis
  • Risk Factors