Introduction: Asthma has a significant impact on the Manitoba healthcare system. Asthma related health expenditures in Canada are around $2 billion annually and are the leading causes of emergency treatment for the younger demographic. Asthma is, however, challenging to diagnose at an earlier age and routine checks are not possible within the younger age groups. Wheezing however is one of the symptoms of asthma but is not exclusive to asthma. Ideally a predictive model for asthma development to have the most clinical impact is needed before children reach the age of two, which current models fail to provide.

Objectives: The objectives were to: (1) determine at what extent does location affect the severity of wheezing in Manitoba, and (2) determine how wheezing severity changes throughout childhood.

Methods: This project used data from the Canadian Healthy Infant Longitudinal Development (CHILD) which is a prospective longitudinal pregnancy cohort. The study population comprised of 1,055 participants from Manitoba for which recruitment of pregnant mothers was conducted from 2009-2012 within a radius of Winnipeg and Morden-Winkler. A logistic longitudinal model was developed which used wheezing severity as a response and incorporated area and individual effects into the model. The study used the 96 regional health authority districts (RHADs) as small areas in Manitoba. A zero-inflated Poisson (ZIP) model with random effects was also developed to model the number of wheezing episodes for children within the CHILD study. The two types of models were used to determine how wheezing frequency and severity changed throughout thus covering two definitions of wheezing severity. Area-level logistic and ZIP models were used to answer the first objective of this project by mapping the predicted proportions and rates for each small area in Manitoba. The second objective was also assessed by using the longitudinal logistic and ZIP models.

Results: The unit-level binary logistic model showed an increased odds of wheezing in the case of previous maternal asthma (OR: 3.31, 95% CI: (1.87, 5.81)) and smoking (OR: 2.85, 95% CI: 0.98, 7.46)). Living near a farm (OR: 0.70, 95% CI: (0.23, 1.82)) decreased the odds of wheezing while the ZIP model showed that among those already experiencing wheezing, living near a farm (RR: 2.45, 95% CI: (1.11, 5.93)) increased the average rate of wheezing. The areas with the highest predicted proportions (and average rates) of wheezing were Gimli, Hanover, Spruce Woods, and St Pierre.

Conclusion: Our study demonstrated that wheezing is heavily affected by maternal health history. Gimli, Spruce Woods, and St Pierre were found to have the highest proportions of wheezing and persistent wheezing episodes, but further recruitment in Manitoba is needed to verify these results.