Thesis (Ph.D.)--University of Western Australia, 2007.

[Truncated abstract] Background: Genetic epidemiology draws on the mechanisms of heredity and the reproductive characteristics of populations to formulate methods to investigate the role of genetic factors and their interaction with the environment in disease aetiology. Asthma and atopy are complex genetic disorders and are among the most common diseases to affect the developed world. Twin studies provide an elegant means of disentangling genetic and environmental contributions to the aetiology of conditions that have a significant impact on the health of the general population in ways that cannot be achieved by any other study design, by comparing disease frequency in monozygotic (MZ) or identical twins, who share 100% of their genes with that in dizygotic (DZ) or non-identical twins who share, on average, 50% of their genes. Twin-family studies allow the complete partitioning of phenotypic variation into components representing additive genetic, dominance, shared environment and non-shared environment. ... For twin family data, the best fitting model was the one which included additive genetic effects and either genetic dominance or shared sibling environment, and that shared family environment was not important. With respect to asthma in WA twin families, there are no reasons to conclude that the EEA is not valid. Conclusions: The WA Twin Register is the first population-based register of childhood multiples to be established in Australia, and the WATCH study is one of only a few population-based twin-family studies in the world. Families who participated in the WATCH study were no different from non-participants with respect to social class and there was no difference in the prevalence of DDA in WATCH study twins and either their singleton siblings or the general population of WA children. Results from the GEE models replicate those found in numerous studies from many different countries. The BUGS models developed have been shown to produce consistent results with both simulated and real data sets and offer alternative methods of analyzing twin and twin-family data. By including an extra term in the partitioning of the variance to account for the environment effect of being a MZ twin, a numerical value is calculated for the difference in MZ and DZ correlation with respect to the phenotype examined, which allows the validity of the EEA to be directly assessed.