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|Title:||Statistical Analysis of Asthma Hospitalization Incidences in Canadian Children|
|Keywords:||statistical analysis;asthma;hospitalization;children;Canada;Canadian children;hospitalization incidences;asthma hospitalization;statistics|
|Abstract:||Asthma is the leading chronic disease of children in industrialized countries. In Canada, it is the most common cause of hospital admissions in children. Data were assembled for all asthma hospitalizations in Canada from 1990 to 2000 by the Canadian Institute for Health Information (CIHI). The annual cycles of asthma hospitalization among Canadian children from 1990 to 2000 were compared. For every year, region and latitude, asthma hospitalizations were lowest in July and August followed by a major peak in September then a rapid decline. Contingency table analyses were done to examine the homogeneity of the distributions of asthma hospitalization counts for the factors age, gender, region and latitude groups. Age, region and latitude groups were found to be significantly different with respect to their distribution of asthma counts. However, the distributions of asthma hospitalization counts did not differ significantly for gender. A nonlinear least squares model was fitted to the asthma hospitalization data for weeks 30 to 42. The primary objective was to obtain estimates of the parameter that describes the timing of the September peak. Next, a likelihood ratio test was done to assess the homogeneity of the September peaks for the factors age, gender, latitude and region. We found that, apart from gender, the September peaks were significantly different. Furthermore, the annual cycle of asthma hospitalization for children aged 2 to 4 was identical to that of children aged 5 to 15 except the peak in hospitalization for 2 to 4 year olds occurred on average 2 days after the older children. We suspect that the increase prevalence of and exposure to viral infections, exposure of school-aged children to allergens at school and the transmission of these factors to younger siblings are responsible for the September asthma epidemic. A Quasi-Poisson log-linear model was also fitted to the data to assess jointly the effects of age, gender, latitude, year and risk group size. The data were overdispersed, after accounting for overdispersion, we found that age, gender, latitude, year and the interactions between age and gender, age and latitude and gender and latitude were significant in explaining the data. Surprisingly, time had a negative effect suggesting a tendency to decline in the number of asthma incidences requiring hospitalization over the years.|
|Appears in Collections:||Digitized Open Access Dissertations and Theses|
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