Neonatal characteristics and risk of atopic asthma in schoolchildren: results from a large prospective birth-cohort study

Acta Paediatr. 2007 Nov;96(11):1606-10. doi: 10.1111/j.1651-2227.2007.00449.x. Epub 2007 Sep 19.

Abstract

Aim: Asthma is among the most common chronic diseases in childhood and steadily increasing in prevalence. Identification of risk predictors for a hospitalization for atopic asthma in childhood may help design prevention programmes and improve our understanding of disease pathobiology.

Methods: An ongoing birth-cohort study prospectively enrolled all liveborn infants in Tyrol. Between 1994 and 1999 baseline data were collected for 33,808 infants. From 2000 to 2005, all children hospitalized for atopic asthma at an age of 6 years or over (n = 305) were identified in a careful search of hospital databases. Disease status was ascertained from the typical medical history, a thorough examination and proof of atopy.

Results: Male sex (relative risk 2.11, 95% CI 1.65-2.70), urban living environment (vs. rural) (1.93, 1.47-2.54), neonatal admission to hospital (1.70, 1.20-2.40), lack of breastfeeding (1.32, 1.02-1.70), postnatal smoking (1.31, 1.00-1.72) and low birth weight (1.45, 0.94-2.23) all emerged as adverse risk predictors for hospitalization for atopic asthma whereas a low risk was found among children living on a farm (0.22, 0.05-0.87) and children with two to three siblings (vs. no or one sibling) (0.71, 0.51-0.97).

Conclusion: In this study a number of neonatal characteristics and environmental exposures were associated with hospitalization for atopic asthma in childhood, suggesting that early life is crucial for disease determination and lending further indirect support to the hygiene hypothesis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Asthma / epidemiology*
  • Asthma / prevention & control
  • Austria / epidemiology
  • Breast Feeding
  • Child
  • Disease Susceptibility
  • Family Characteristics
  • Female
  • Health Surveys*
  • Hospitalization / statistics & numerical data*
  • Humans
  • Infant, Newborn
  • Logistic Models
  • Male
  • Medical Records / statistics & numerical data
  • Prospective Studies
  • Risk Assessment*
  • Risk Factors
  • Sex Factors
  • Surveys and Questionnaires