Regressive logistic modeling of familial aggregation for asthma in 7,394 population-based nuclear families

Genet Epidemiol. 1997;14(3):317-32. doi: 10.1002/(SICI)1098-2272(1997)14:3<317::AID-GEPI9>3.0.CO;2-1.


The aim of this population-based study was to determine whether asthma aggregates in families, and if so, whether aggregation was consistent with environmental and/or genetic etiologies. Data were from 7,394 nuclear families (41,506 individuals) from the 1968 Tasmanian Asthma Survey, in which all Tasmanian schoolchildren born in 1961 were surveyed by respiratory questionnaire completed by their parents. Similar data were obtained for parents and siblings of probands. For a child, having ever had asthma was predicted by a parent or sibling having ever had asthma; odds ratio (OR) = 3.13 (95% confidence interval [CI] 2.82-3.48) for mother, 2.99 (2.69-3.32) for father, and 3.47 (3.23-3.72) for a sibling. Regressive logistic modeling showed that, in addition to parent-offspring effects, the data were consistent with the existence of an unmeasured factor shared by siblings, evident in 15% (SE 2%) of families and associated with a conditional OR of 9.68 (8.27-11.32). Familial aggregation was best described by a general oligogenic model with non-Mendelian transmission probabilities. Of the Mendelian models, a codominant model with an allele frequency of 16% (SE 0.3%) was preferred. Under a dominant model there was evidence for additional parent-offspring and sibling effects of similar magnitude. It is unlikely that there is one major loci influencing asthma susceptibility; the overall effects of asthma genes in the population are more likely to be inherited codominantly, at least for the majority of loci of major etiological importance. The role of environmental factors in explaining part of familial aggregation for asthma cannot be ruled out, as major triggers of asthma attacks are familial.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Asthma / epidemiology
  • Asthma / genetics*
  • Female
  • Humans
  • Likelihood Functions
  • Logistic Models*
  • Male
  • Nuclear Family
  • Population Surveillance
  • Tasmania / epidemiology