To investigate the acute impact of various air pollutants on various disease groups in the urban area of the city of Toronto, Canada. Statistical models were developed to estimate the relative risk of an emergency department visit associated with ambient air pollution concentration levels. These models were generated for 8 air pollutants (lagged from 0 to 14 days) and for 18 strata (based on sex, age group, and season). Twelve disease groups extracted from the International Classification of Diseases 10th Revision (ICD-10) were used as health classifications in the models. The qualitative results were collected in matrices composed of 18 rows (strata) and 15 columns (lags) for each air pollutant and the 12 health classifications. The matrix cells were assigned a value of 1 if the association was positively statistically significant; otherwise, they were assigned to a value of 0. The constructed matrices were totalized separately for each air pollutant. The resulting matrices show qualitative associations for grouped diseases, air pollutants, and their corresponding lagged concentrations and indicate the frequency of statistically significant positive associations. The results are presented in colour-gradient matrices with the number of associations for every combination of patient strata, pollutant, and lag in corresponding cells. The highest number of the associations was 8 (of 12 possible) obtained for the same day exposure to carbon monoxide, nitrogen dioxide, and days with elevated air quality health index (AQHI) values. For carbon monoxide, the number of the associations decreases with the increasing lags. For this air pollutant, there were almost no associations after 8 days of lag. In the case of nitrogen dioxide, the associations persist even for longer lags. The numerical values obtained from the models are provided for every pollutant. The constructed matrices are a useful tool to analyze the impact of ambient air pollution concentrations on public health.

The aim of this study is to determine associations between ambient air pollution and the number of emergency department (ED) visits for diseases of the genitourinary tract in Toronto, Canada. We used the National Ambulatory Care Reporting System (NACRS) database to obtain the related ED visits and developed statistical models using daily data on ED visits, temperature, relative humidity, and outdoor air pollution concentration levels. The NACRS database contains data on hospital-based and community-based ambulatory care. The environmental data were retrieved from the National Air Pollution Surveillance (NAPS) program. The NAPS is the main source of ambient air quality data in Canada. We considered 2 air quality health indexes and 6 air pollutants: daily means of fine particulate matter PM2.5, O3, CO, NO2, SO2, and also maximum 8-hour average ozone. For every air pollutant, we fit 270 models (15 lags × 18 strata). We found that same-day air pollution concentrations have the highest number of statistically significantly positive associations with ED visits for genitourinary health outcomes. A total of 133 positive associations were identified over the 14 days lag. In subgroup (strata) analysis, females older than 60 years of age were found to have the most positive associations. In particular, nitrogen dioxide was found to be highly associated with ED visits for females over 60; an increase in NO2 was associated with an increased relative risk (RR) of ED visits when lagged over 0, 1, and 2 days (RR = 1.040 [95% confidence interval: 1.028, 1.052], 1.020 [1.009, 1.032], and 1.025 [1.013, 1.036], respectively). The values of risks are reported for a 1 interquartile range increase in concentration (8.8 ppb). Our results suggest that urban ambient air pollution affect the number of ED visits due to genitourinary system conditions.

Air pollution affects various aspects of human health. Here, the associations between the number of emergency department visits for circulatory and respiratory problems and ambient air pollution in Toronto, Canada, in the period between April 2004 and December 2015 were studied. The health data were linked with urban air pollution data and weather factors. The conditional Poisson regression models were built for 18 strata (sex, age group, season), 8 exposure factors (air pollutants, indexes), and their 15 lags (0-14 days). Circulatory problems: the associations were intensified in the cold period (October - March) and were associated with the air quality health index (AQHI). The estimated relative risks for all patients in the cold period, for an increase of the AQHI by 1, at lags 0, 1, and 2 were 1.017 and 95% confidence interval (1.010, 1.024), 1.014 (1.007, 1.021), and 1.009 (1.002, 1.016). Respiratory problems: the analogous results for ozone and its increase by 12.8 ppb at lags 3, 4, and 5 were 1.052 (1.033, 1.161), 1.039 (1.020, 1.121), and 1.027 (1.008, 1.082). It was observed that exposure to certain air pollutants (nitrogen dioxide, ozone, and the AQHI index) are associated with increased emergency department visits in both cardiac and respiratory health problems.

Introduction. There is a large body of research which suggests that air pollutants might affect infectious diseases, their transmission, severity, and a length of recovery. Aim. The aim of this study is to examine the relationships between ambient air pollution and emergency department (ED) visits for influenza and viral pneumonia in Toronto, Canada. Material and Methods. The National Ambulatory Care Reporting System database was used to drawn ED visits (4 282 days). Five ambient air pollutants: carbon monoxide, nitrogen dioxide, sulphur dioxide, ozone (CO, NO2, SO2, O3, O3H8 – ozone as a maximum eight hour average, respectively), and fine particulate matter (PM2.5) were examined. In addition, the Air Quality Health Index (AQHI; combines NO2, O3, and PM2.5) was tested. Conditional Poisson models were constructed using daily counts of ED visits. Temperature and relative humidity in the models were represented by natural splines. Air pollutants and weather factors were lagged by 0 to 14 days. The analysis was done by strata of age group, sex, and two seasons. Results. In the period of the study, 26,200 ED visits were identified; 13,963 for females and 12,237 for males. For each air pollutant, 270 models were generated (18 strata × 15 lags). Ambient air pollution concentrations lagged by 10 and 11 days have the highest impact on ED visits, with 48 and 47 positive associations, respectively. Ozone has 181, sulphur dioxide has 104, and PM2.5 has 76 among the 417 total positive statistically significant (P-Value<0.05) associations. For all persons an increase (12.8 ppb) in ambient ozone lagged by 0, 1, and 2 days gives the following relative risks and their 95% confidence intervals 1.214 (1.135, 1.299), 1.200 (1.121, 1.284), and 1.179 (1.102, 1.263), respectively. Conclusion. The results suggest that exposures to urban ambient air pollution affect the number of ED visits for viral respiratory illness.

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This study examines the relation between ambient air pollution and emergency department (ED) visits due to certain infectious diseases in Toronto, Canada. The National Ambulatory Care Reporting System database was used to draw the corresponding health cases. Daily data on ED visits, ambient air pollution concentration levels, and weather conditions during the period from April 2004 to December 2015 (4,292 days in total) were linked together and used in statistical models. Six air pollutants (fine particulate matter PM2.5, CO, NO2, SO2, ozone O3 as a daily average, and ozone O3-8 hour ozone, as a maximum eight hour average) were investigated. In addition, the Air Quality Health Index (combining NO2, O3, and PM2.5) was also considered. The time-stratified case-crossover technique was applied in the study design. Conditional Poisson models were created using the daily counts of ED visit data. The considered factors, air pollutants and weather, were lagged by the same number of days, from 0 to 14. In the period of the study 339,644 ED visits were identified; 177,619 for females and 162,025 for males. For each air pollutant 270 models were realized (15 lags x 18 strata). Ambient air pollution concentrations lagged by 2, 3, and 5 days have the highest impact on ED visits, with 34, 32, and 35 positive associations, respectively. For all patients and an increase in a one interquartile range (IQR=1.2 ppb) of sulphur dioxide, the following values of the relative risks (RR) were estimated: RR=1.005 (95% confidence interval: 0.998, 1.013), 1.008 (1.001, 1.016), 1.009 (1.001, 1.016), 1.011 (1.004, 1.019), 1.007 (0.987, 1.028), and 1.009 (1.002, 1.016) for lags from 0 to 5, respectively. The results suggest that exposures for certain air pollutants (mainly CO, O3, and SO2) in urban environment affect the number of ED visits related to infectious diseases.

Cam impingement occurs in 15% of the population and is strongly associated with the development of osteoarthritis. Clinical measurements do not predict the risk for asymptomatic hips and their risk of developing osteoarthritis adequately. Thus, developing FE analyses of cam-deformed hips that combine accurate material models, patient-specific morphology and kinematics to emphasize the dynamic quality of impingement is the objective of this study. Such models were developed for control, asymptomatic and symptomatic hips through CT segmentation and generation of 3D models of cartilage and the labrum.Forces and rotations during walking and sitting down were applied, where the Asymptomatic hip experienced the highest first principal stresses (0.32 MPa and 0.61 MPa, respectively). The contrast between the camaffected hips highlighted the importance of morphology and kinematics when examining impingement. These findings emphasized the shortcomings of current measurements of cam deformities and the need to consider impingement as a dynamic problem.i Contents Contents iiList of Tables iv List of Figures v Nomenclature xiList of Figures 1 Cross-section of hip joint with visible cartilage, labrum, and surrounding connective tissue . . . .

Introduction. This study investigates associations between air pollution and emergency department (ED) visits for urticaria in Toronto, Canada. Aim. To verify the hypothesis that urticaria are related to air pollution. Material and methods. The National Ambulatory Care Reporting System database is used to draw the daily ED visits. The L50 section of the International Classification of Disease 10th Revision is applied to extract ED visits whose primary causes was urticaria-related skin condition. Statistical models (condition Poisson regression) using daily counts of ED visits are constructed for urticaria (health response) with ambient air pollution concentrations and weather factors as independent variable. Two air quality health indexes and six ambient air pollutants: fine particulate matter PM2.5, O3, CO, NO2, SO2, and maximum 8-hour average ozone are considered as an exposure. Results. A total of 176 statistically significant (P-Value <0.05) positive correlations were identified over the 15 day lag period (0-14 days). For daily average of ambient ozone, 74 positive correlations were observed with the following relative risks (RR) for a one interquartile range (IQR=12.8 ppb) increase: RR=1.361 (95% confidence interval: 1.302, 1.404), 1.359 (1.299, 1.401), 1.351 (1.281, 1.404) in the warm season (April-September), lag 0, and RR=1.019 (1.013, 1.025), 1.023 (1.016, 1.030), 1.014 (1.007, 1.021), lag 1, in the cold period (October-March), for all, females, and males, respectively. 10, 45 and 45 positive correlations were also obtained for sulfur dioxide, fine particulate matter, and daily maximum 8-hour average ozone concentrations, respectively. Conclusions. The results indicate that urban ambient air pollution could influence the numbers of ED visits for urticaria. Ambient ozone was determined as the main environmental factor contributing to these associations.