<p>Respiratory diseases have been and still are one of the major challenges in health research. While many studies have demonstrated that respiratory health varies by socio-economic status and environmental exposure, consensus among the scientific community is still lacking regarding the sufficiency of evidence to infer a causal relationship therefore highlighting the need for improved assessment of both exposure and outcome. This thesis addresses these issues through a reanalysis of the Hamilton Children's Cohort (HCC) study, undertaken in the 1980's in Hamilton, Ontario, Canada. The HCC study was the first one that provided important evidence linking adverse respiratory health with smoking, hospitalization in infancy and air pollution. However, given the limited development of spatial analysis and GIS at the time of study, the spatial dimensions of respiratory diseases and air pollution were not fully explored. The objective of this thesis is to re-analyse the HCC data in order to investigate the spatial variation of air pollution and children's adverse respiratory health as well as the relative importance of other characteristics that may determine the burden of respiratory incidences. Children's exposure to air pollution is first re-estimated using kriging and land-use regression. Based on exposure assessment analysis, compared to kriging, the land-use regression model performs better in capturing local variation of particulate pollution (TSP). The results of the land-use regression model are then used in multivariate linear and logistic regression analysis for the assessment of children's respiratory health. Findings of the multivariate analysis verify and strengthen the results of the HCC study indicating that in addition to their findings, children's respiratory health is associated with chest illness in</p> <p>siblings, use of gas for cooking, low income and household crowding. In conclusion, this thesis demonstrates the usefulness of spatial analysis and GIS in assessing children's exposure to air pollution and also strengthens the HCC study findings revealing statistically stronger associations between children's respiratory health and a number of covariates. In general, the results hold promise and in combination with space-time analysis may lead to the development of advanced exposure assessment models in order to improve our understanding of the potential determinants of respiratory health.</p> / Master of Science (MSc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/10397 |
| Date | 08 1900 |
| Creators | Pouliou, Theodora |
| Contributors | Elliott, Susan J., Kanaroglou, Pavlos S., Geography and Earth Sciences |
| Source Sets | McMaster University |
| Detected Language | English |
| Type | thesis |
Page generated in 0.0019 seconds