Asthma is a common, heterogeneous chronic lung disease caused by a combination of genetic and environmental influences. It is well recognized that exposure to outdoor air pollution adversely affects respiratory health, even in non-asthmatics 1. Numerous epidemiologic studies have documented that outdoor air pollution is associated with decreased lung function 23, and an increased number of hospital admissions for asthma 45678. A series of studies have also reported associations between outdoor air pollution levels and emergency department visits for asthma 91011, a surrogate measure for asthma attacks.

While children and the elderly have been identified as population subgroups particularly sensitive to the harmful effects of air pollution 1213, risk estimates for asthma obtained from hospital-based studies have not been consistent. These differences may be attributed, in part, to variations in the pollution mix between the urban centers that were examined, or other uncontrolled factors (e.g., pollen) that vary seasonally. In addition, studies that have investigated associations in children have, for the most part, used broadly defined age-groups. Differences between infants and adolescents with respect to activity patterns, lung development, and immune systems suggest that associations between outdoor air pollution and respiratory health could vary in important ways 12.

In this study, we use a time-stratified case-crossover study design to examine the effects of outdoor air pollution on the daily number of ED visits in the census metropolitan area of Edmonton, Alberta. This area, that has a population of nearly one million persons, has ambient pollution levels that are influenced by several factors. These factors include emissions from coal fired power plants that are approximately 65 kilometers to the west, urban vehicular traffic, and petrochemical refineries and a variety of other industries to the east. The primary objective of this investigation was to examine variations in asthma risk by finely defined age-groups. In so doing, we extend similar Canadian work conducted in Toronto 14, Vancouver 15, and Saint John 16. To date, associations between air pollution and hospital visits for asthma have not been examined in the Canadian province of Alberta. Moreover, only a few studies 17181920 have examined the extent through which exposure to aeroallergens may confound associations between outdoor air pollution and asthma ED visits.

Asthma visits accounted for approximately 2% of all ED visits in these 5 hospitals. A total of 57,912 emergency department visits were identified during the study interval and formed the basis of the case-crossover analyses (Table 1). Almost 13% of these visits occurred in young children (2 – 4 years of age), while 8.1% occurred among those aged 65 years of age and older. There were slightly more visits among females (51.8%) than their male counterparts. A total of 30,576 visits occurred between the months of April to September. Trends in the frequency of asthma ED visits over the course of the year, by age group, are presented in Figure 1. A peak was observed in late September; this excess was most pronounced among children.

Daily levels of ambient air pollution over the study period are presented in Table 2. Gaseous pollutant data were available for the entire study period (1992 to 2002), while daily particulate matter data were only available from 1998 onwards. For the most part, pollution levels were higher during the winter season, the notable exception being ozone. Aeroallergen levels for the period 1996 to 2002 are also described. For the most part, no sampling for aeroallergens was completed during the winter season since pollen, during the majority of that period, would be absent or at a very low level and would not be significant for patient reactions. Regarding the fungal spores, it is expected that levels would be insignificant during the months from December to beginning of collections and although levels during late fall may be significant, the data remains unavailable. Pearson correlation coefficients were generated to better understand the associations between pollutants and aeroallergens [data not shown]. NO₂ and CO were strongly correlated with each other (r = 0.74), as were PM_2.5 and PM₁₀ (r = 0.79). Ozone was strongly correlated with temperature and relative humidity (r = 0.54). The strongest associations between pollutant and aeroallergen levels were observed with Ascomycetes and NO₂ (r = -0.26), pollens from trees and O₃ (daily max) (r = 0.24), Ascomycetes and O₃ (daily max) (r = -0.16).

Adjusted odds ratios for ED visits for asthma according to levels of ambient air pollution, by season, are displayed in Table 3. For the most part, there were no statistically significant associations between air pollution levels and ED visits for asthma in the period between October and March (fall/winter). In contrast, statistically significant associations were observed in the period between April and September with NO₂, CO, PM_2.5, PM₁₀ and O₃. These associations were stronger when the 5-day average was used, relative to the other shorter term exposures indices that we used. No association was evident for SO₂.

In Tables 4, 5, 6, 7, 8, 9, analyses are replicated for different age groups. Associations between air pollution and ED visits for asthma were consistently found in the summer/spring season and absent in the fall/winter. Therefore, the discussion of results in this paragraph is limited to our findings for the April to September period. The most marked associations with ED visits and air pollution levels occurred among very young children (2 – 4 years of age) (Table 4). In this age group, an increase in the interquartile range of the 5-day average for NO₂ or CO was associated with 50% and 48% increases, respectively, in the risk of an asthma ED visit (p < 0.05). No association was observed with SO₂, however, increased levels of O₃, PM_2.5 and PM₁₀ were positively associated with the number of ED visits for asthma (p < 0.05).

NO₂ and PM₁₀ were the pollutants for which the strongest associations were observed among children 5–14 years of age (Table 5). In general, associations were strongest for the air pollution metric constructed using the 5-day average. Among those aged 15–44, associations were less pronounced than those found in children, however, NO₂ and CO signals were evident (Table 6). Relative to the findings for other adults, associations were stronger among those 75 years of age and older (Table 9). Specifically, an increase in the interquartile range of the 5-day average for O₃ was associated with a 54% increase in the number of asthma visits in this age group; the corresponding estimate for NO₂ was 37%. Two pollutant modeling revealed stronger associations for NO₂, relative to CO, for all age groups except those aged 15 – 44 years of age (Figure 2).

The addition of aeroallergens to the age-specific model did not produce a material change in the air pollution risk estimates shown in Table 4 to 9. Like air pollution levels, the magnitude of the aeroallergen derived odds ratios was strongest for the 5-day average exposure index. However, the effects were much smaller in magnitude than those found for changes in air pollution levels. The strongest association was found for Deuteromycetes where an IQR change in the 5-day average resulted in an odds ratio of 1.03 (95% CI = 1.00–1.06) for an ED visit for asthma.

The economic burden of asthma is considerable, and therefore, it is valuable to identify exposures that can be modified on a population-level basis to reduce the health care costs to treat it. In 1994, the economic costs of asthma for the US were estimated to be in excess of $10 billion dollars 27. The corresponding estimate for Canada, in 1990, was estimated to fall in the range between $504 and $648 million 28. A review of published studies found that hospital costs typically account for 20–25% of the overall direct costs of asthma 29. Given that there are approximately 150,000 ED visits for asthma in Canada annually, a modest reduction in these numbers alone would provide considerable costs saving. We found positive associations between outdoor levels of air pollution and asthma ED visits, between April and September, in each age-group examined. Associations were generally stronger for NO₂ and CO, however, they were also evident for O₃ and particulate matter. These findings provide compelling evidence that reductions in emissions from the sources that give rise to these pollutant levels may decrease the associated direct health care costs of asthma in this region. Elsewhere, interventions to reduce outdoor air pollution levels have proven to be successful as they were accompanied with a concomitant decrease in the number of hospital visits and admissions for asthma, particularly in young children 3031.

This study was undertaken, in part, because there have been few Canadian studies that have evaluated how associations between ambient levels of air pollution and hospitals visits for asthma vary by age. In addition, the composition mix of pollution in Edmonton differs from other Canadian cities due to the close proximity of coal and petrochemical industries. The findings of our study are similar to those reported for a case-crossover study in Toronto where positive associations with CO and NO₂ and hospital admissions for asthma in both males and females aged 6 to 12 were observed, however no effect was found for O₃ 14. Further support for the relevance of vehicular traffic on asthma comes from the work by Oyana who reported an increased prevalence of asthma among children and adults who lived in close proximity to ambient sources of pollution at a US-Canada border crossing 3233. In contrast, associations with ozone have been noted in the Canadian cities of Saint John, New Brunswick 34, but not with NO₂ 16. Positive associations with ozone have been also noted in a study of ED visits in the province of Ontario and Toronto 3536; for the province wide study, effects were more pronounced among children under the age of one, however, asthma remains an unclear diagnosis in children under the age of two.

Positive associations were observed with both particulate and gaseous phase pollution and as previously mentioned, they were most evident with NO₂ and CO, both typically regarded as markers of vehicular traffic. In the province of Alberta, transportation accounts for a much smaller percentage of overall nitrogen oxides (NO_X) emissions (26%), than it does in Canada as a whole (50%) 37. Therefore, it is possible that industrial sources of NO₂ in the Edmonton area contribute to the increased risk of asthma visits. The nature of the hospital or pollution data does not allow us to evaluate the respective contributions of industrial versus transportation sources of pollution to the increased risk of asthma visits.

To better understand the interrelationship between CO, NO₂ which were highly correlated with each other (r = 0.70), two-pollutant models were fit. These analyses revealed stronger associations with ED asthma visits among children and the elderly for NO₂, relative to CO, in all age ranges except among those aged 15 to 45. There exist several biological mechanisms whereby NO₂ can affect respiratory health. It has been shown to make people more susceptible to respiratory viral infections that exacerbate asthma 38, and enhance allergic responses after subsequent challenge 39. NO₂ has also been shown to increase bronchitis symptoms among asthmatics 40, and reduced lung function among children who spend more time outside 41. More recently, research from the California Children's Health Study found that prolonged exposure to traffic pollution, including NO₂, increases the incidence of childhood asthma 4243. Taken together, there is growing support for the relevance of traffic related pollution in the exacerbation and development of asthma.

The ambient pollutant that has been most frequently associated with asthma hospitalizations has been ozone. In our study, an association between ozone and asthma ED visits was observed in patients of all ages; this association was strongest among those 5 – 14 years of age, while not statistically significant in other age ranges. Ozone (O₃) is formed from photochemical reactions between NO_X and volatile organic compounds in the presence of sunlight. Ozone levels are highest on warm sunny and calm days, with exposures peaking in mid-afternoon. Controlled laboratory studies have shown that O₃ can invoke acute lower inflammatory responses in both healthy and asthmatic subjects, however, asthmatics appear to experience more severe responses 44. Given that the oxidant capacity of NO₂ is smaller than that for O₃ 45, our finding of a stronger association with NO₂ and asthma visits is somewhat surprising. However, similar patterns have been observed in several recent asthma studies that have evaluated both pollutants 1446. Recently, an eight city panel study of 990 children found that NO₂ and CO were strongly related to asthma exacerbations while no such association was noted for O₃ 47. Differences in meteorology, the complex mixture of pollution between regions, and the possibility of a threshold effect for ozone 48 may contribute to equivocal findings reported in different regions.

Emergency department studies of asthma have also evaluated the role of ambient particulate matter. Particulate air pollution is a mixture of solid particles and liquid droplets that can differ considerably in origin, size, and composition. Particulate matter includes aerosols, smoke, fumes, dust, ash and pollen. Fine particulate matter, which comprises those particles with an average aerodynamic diameter of 2.5 microns or less, has been studied more of late because it can better penetrate the respiratory system than particles of larger size. Positive associations between particulate matter and hospital visits for asthma have been reported in many international studies 20464950515253545556, but not all 91934475758. Future short-term health effect studies of ambient pollution need to better isolate the biologically important constituents, and physical properties of particles that invoke responses in persons with asthma.

The validity of our findings relies on the accuracy of diagnosing asthma within the ED, and this accuracy is known to vary by the patient's age. As mentioned before, we excluded asthma ED visits among children less than two years of age as it is often confused with bronchiolitis 59. In older patients, while clinicians in theory are able to distinguish between asthma and chronic obstructive pulmonary disease (COPD), some diagnostic misclassification does occur 5960. To evaluate the extent that such misclassification affects our presented risk estimates, we evaluated the association between air pollution and COPD visits in the elderly. We found that outdoor levels of air pollution were unrelated to ED visits for COPD in our patient population. This indicates that two different disease entities are being captured through the diagnostic patterns in place in the Edmonton area hospitals. However, the misdiagnosis of COPD as asthma would serve to underestimate the strength of our associations.

We found that the associations were strongest between outdoor air pollution and ED visits for asthma among children between 2 – 4 years of age, and among the elderly (= 75). Children are widely regarded to be a susceptible population for air pollution health effects for several reasons. They have higher minute ventilation and higher levels of physical activity, spend more time outside than adults, and their peripheral airways more susceptible to inflammatory narrowing 61. In addition, they retain a disproportionately higher amount of air pollution per unit body weight than adults 62. Factors that may increase the susceptibility of the elderly to air pollution include: higher airways deposition rate of particulate matter, deficits of dietary factors such as antioxidants, and compromised immune systems due to comorbidities and increased medication use 13. While further work is needed to evaluate how air pollution differentially affects the exacerbation of acute asthma by age, diverse findings from previously conducted Canadian studies highlights the continued need to look at both gaseous and particulate phase component of the air pollution mix.

The risk estimates presented here have been adjusted for meteorological effects of temperature, and relative humidity. They have also been adjusted for daily ED counts for influenza in order to control for viral respiratory seasonal epidemics. The case-crossover study design is also effective in controlling for the influence of individual-level risk factors that are unlikely to vary over short time intervals. For asthma, such factors are numerous and include: age, sex, cigarette smoking, household pets, and genetic predisposition to asthma. While cigarette smoke has been identified as an important risk factor for asthma, it is unlikely that it would confound our results as these exposures, as suggested by recent analyses of Canadian national survey data, are not related to with outdoor air pollution levels from fixed sited monitoring station 63. Similarly, indoor sources of NO₂ from cooking and heating are unlikely to be correlated with outdoor sources over the short time interval of the study. Perhaps most importantly, the time-stratified case-crossover approach has also been demonstrated as a suitable method to control for time trends in both air pollution exposures and outcomes 26.

The case-crossover approach relies on the assumption that the event of interest, here ED visits for asthma, define the case intervals while no such visit can occur during the matched control intervals. This assumption can be violated under the scenario of recurrent events. For example, individuals may present themselves to the ED for asthma multiple times, and therefore, the control periods associated with some individuals could be misclassified. With the time-stratified design, this would occur if an individual had an ED visit for asthma on the same day of the week more than once in a given month. Unlike many other hospital-based case-crossover studies of recurrent outcomes, patient identification data were available for most visits; this allowed us to evaluate the extent of this possible bias. In our dataset for which patient identification data were available, approximately 33% of these patients visited the ED more than once over the study period. However, there were very few instances (n = 411) where an individual who visited the ED for asthma had a subsequent visit for asthma on the same day of the week, within the same month in a given year. Neither the exclusion of these matched sets, nor the re-coding of the control intervals to properly reflect the fact that these were case intervals changed the risk estimates in any appreciable way.

Our risk estimates are reliant on the use of air pollution levels derived from fixed-site monitoring stations. Measurement error from fixed site monitoring stations can occur from the devices themselves, or from an inability to account for heterogeneous pollution levels that exist spatially within the region. The magnitude of these measurement errors vary between pollutants. For example, pollutants such as NO₂ exhibit tremendous spatial variability and have been shown to be correlated to traffic measures 64. In contrast, meteorological conditions strongly influence the efficiency of photochemical processes that lead to ozone formation 6566, and for this reason ground-level ozone air pollution is largely characterized on a regional-scale basis, rather than on an intra urban scale. While individual-level exposure estimates are generally recognized to be superior for evaluating risk of environmental exposures, as pointed out by Schwartz the use of a daily mean exposure for an entire city is relevant 67. Namely, the mean of personal exposures among residents in that city is likely more highly correlated with central monitoring station than individual exposures. Recent work into the measurement error associated with the use of fixed site monitoring stations suggest that most of the difference between personal and fixed site monitoring measurements of exposure are Berkson error, and therefore, do not bias the risk estimates. The work by Zeger suggests that the remaining measurement error follows the classical error model, and therefore, the overall net effect would be risk estimates that are biased towards the null 68. As a result, the measurement error associated with the use of fixed site monitoring stations is not the source of the positive associations found in our study population.

Along the same lines, aeroallergen levels likely varied within the Edmonton census area. One sampling device was used to infer daily aeroallergen levels. We expect that the mixing of spores in air, and transport by wind provides a more uniform mixture of aeroallergens throughout the study region. Because of this, and the fact that people are not stationary, we feel that the use of one sampling device is a valid means to represent daily aeroallergen levels in the study region. Further support for this comes from a sampling study that found high correlations in pollen counts between two sampling sites located 5.6 km apart 69.

Exacerbations of asthma are often caused by viral illnesses, exposure to irritants or allergens. In this study, we partitioned ED visits into two seasons, April to September and October to March. Daily monitoring of aeroallergen indicate that their relevance pertains strictly to the period between April and September. In contrast, as evidenced by seasonal patterns in the number of daily visits for influenza, a viral etiology predominates the winter period. Like others, we modeled the daily number of visits for influenza to control for seasonal viral respiratory epidemics 207071. While the frequency of daily influenza visits were correlated with the number of asthma visits during the winter, the addition of this term produced no appreciable change in the air pollution risk estimates. Similarly, aeroallergen levels did not confound the air pollution risk estimates between April and September.

Air pollution levels were generally higher in the period between October to March, than April to September where associations with asthma ED visits were evident. Differences in the air pollution risk estimates between the two seasons themselves may possibly be explained in part by differential exposure misclassification. As Edmonton-area residents spend a greater proportion of their time outside during the spring and summer seasons, fixed-site monitoring data likely more accurately reflects the average exposure to ambient pollution in the summer. Therefore, if the association between air pollution and asthma is real, there would be greater attenuation in risk estimates for winter time exposures.

Finally, it is important to note that this study undertook a large number of comparisons as we explored associations between multiple ambient measures of air pollution pollutants using several types of metrics, across different age groups and seasons. Due to the large number of statistical tests performed, the chances of detecting a spurious finding are increased. We did not change our p-values to take into account the multiple testing performed in this study as such an approach has criticized for introducing more problems than they are intended to solve 72. Despite the large number of tests performed, it is also important to recognize that our findings of stronger association in the young and elderly are consistent with the hypotheses we had a priori .3031.

In conclusion, this study implicates ambient pollution, particularly NO₂, as an important contributor to asthma morbidity between April and November, particularly in young children and elderly. This finding persisted after adjustment for meteorological variables, control for seasonal viral epidemics, as well as outdoor levels of aeroallergens. Efforts to mitigate these exposures should be considered, particularly in light of past initiatives that have produced tangible health benefits 3031.

CH: Capital Health;

CI: Confidence interval;

CO: Carbon monoxide;

COPD: Chronic obstructive pulmonary disease;

ED: Emergency Department;

ICD-9: International Classification of Diseases, 9^th Revision;

IQR: Interquartile range;

NAPS: National Air Pollution Surveillance;

NO₂: Nitrogen dioxide;

NOx: Nitrogen oxides;

OR: Odds ratio;

PM₁₀ Fine particulate matter with an aerodynamic diameter of less than 10 μm;

PM_2.5: Fine particulate matter with an aerodynamic diameter of less than 2.5 μm;

SO_2: Sulfur dioxide;

WHO: World Health Organization.

The author(s) declare that they have no competing interests.

All authors have made substantive contributions to this study. PV conceived of the design, guided the analysis of the data, coordinated access of the data with the collaborators, and played the lead role in the writing and revising this manuscript. LC was the biostatistician who performed the analysis, and contributed in the writing of the manuscript. BR arranged for the acquisition of hospital data for the purpose of these analyses, and contributed to the drafting and revising of the manuscript. FC coordinated the collection and provision of the aeroallergen data used in these analyses and contributed in the writing of this manuscript. All authors have read and approved this version of the manuscript.