Skip to main content
NCBI home page
Canadian Respiratory Journal logoLink to Canadian Respiratory Journal
. 2012 Mar-Apr;19(2):97–102. doi: 10.1155/2012/218957

Active and uncontrolled asthma among children exposed to air stack emissions of sulphur dioxide from petroleum refineries in Montreal, Quebec: A cross-sectional study

Leylâ Deger 1, Céline Plante 1, Louis Jacques 1,2,3,4, Sophie Goudreau 1, Stéphane Perron 1, John Hicks 5, Tom Kosatsky 6, Audrey Smargiassi 2,7,✉
PMCID: PMC3373279  PMID: 22536578

Abstract

BACKGROUND:

Little attention has been devoted to the effects on children’s respiratory health of exposure to sulphur dioxide (SO2) in ambient air from local industrial emissions. Most studies on the effects of SO2 have assessed its impact as part of the regional ambient air pollutant mix.

OBJECTIVE:

To examine the association between exposure to stack emissions of SO2 from petroleum refineries located in Montreal’s (Quebec) east-end industrial complex and the prevalence of active asthma and poor asthma control among children living nearby.

METHODS:

The present cross-sectional study used data from a respiratory health survey of Montreal children six months to 12 years of age conducted in 2006. Of 7964 eligible households that completed the survey, 842 children between six months and 12 years of age lived in an area impacted by refinery emissions. Ambient SO2 exposure levels were estimated using dispersion modelling. Log-binomial regression models were used to estimate crude and adjusted prevalence ratios (PRs) and 95% CIs for the association between yearly school and residential SO2 exposure estimates and asthma outcomes. Adjustments were made for child’s age, sex, parental history of atopy and tobacco smoke exposure at home.

RESULTS:

The adjusted PR for the association between active asthma and SO2 levels was 1.14 (95% CI 0.94 to 1.39) per interquartile range increase in modelled annual SO2. The effect on poor asthma control was greater (PR=1.39 per interquartile range increase in modelled SO2 [95% CI 1.00 to 1.94]).

CONCLUSIONS:

Results of the present study suggest a relationship between exposure to refinery stack emissions of SO2 and the prevalence of active and poor asthma control in children who live and attend school in proximity to refineries.

Keywords: Asthma, Children, Cross-sectional study, Dispersion modelling, Point source emissions, Sulphur dioxide

Epidemiological studies suggest that exposure to air pollution is associated with adverse consequences on children’s respiratory health (1). Sulphur dioxide (SO2), a gaseous respiratory irritant, is among the air pollutants of public health concern in urban and industrialized environments.

Most epidemiological investigations on the effects of SO2 have assessed its acute and chronic effects as a component of the regional ambient air pollutant mix. Panel studies involving children and time series analyses have documented associations between short-term (daily) exposure to regional SO2 levels and respiratory effects (eg, lung function changes, increased respiratory symptoms, emergency department visits and hospital admissions for asthma and other respiratory causes) in healthy and asthmatic children (2–10). An association between long-term (years) exposure to regional SO2 levels and respiratory effects (increased prevalence of symptoms and respiratory diseases in children) has also been reported in cross-sectional and semi-ecological cohort studies in which urban regional SO2 levels were compared (11–18). In other studies, little or no evidence supporting a relationship between regional ambient SO2 levels and adverse acute or chronic respiratory effects was found (13,19–22). Many factors may explain this discrepancy, including the varying mixes of air pollutants and misclassification of exposure.

Few studies have assessed the respiratory health effects of an individual’s exposure within a community to industrial emissions of SO2. Refineries and power plants are among the well-known industrial facilities that contribute locally and regionally to ambient SO2 levels. The present study aimed to examine the effects of stack emissions of SO2 from petroleum refineries located in Montreal’s (Quebec) east-end industrial complex on the prevalence of active asthma and poor asthma control among children six months to 12 years of age living in the vicinity of these industrial facilities. Data from a cross-sectional survey performed across the Island of Montreal on the prevalence of asthma was linked to dispersion model data from another study on acute effects performed in the same region (23). Dispersion modelling provides an approximation of ground-level concentrations of air pollutants around point sources and near housing, and can be used to quantify an individual’s exposure, particularly over the long term, using averaged meteorological data (24).

METHODS

Study design and population

Between April and July 2006, a cross-sectional, population-based survey on the determinants of respiratory health in children was conducted on the Island of Montreal by the Montreal Public Health Department (25). Study participants were recruited from a random list of names and addresses of 17,697 Montreal households with at least one child between six months and 12 years of age, which was provided by the Quebec Health Insurance Board (RAMQ). To be eligible for the survey, the child had to reside in the Montreal area and live with the responding mother, father or legal guardian at least 50% of the time, and the child’s parent or legal guardian had to be a French- or English-speaking adult (≥18 years of age). These households received a letter inviting them to participate in the study. Furthermore, 12,680 households were matched with a telephone number, of which 3012 were nonvalid (eg, wrong numbers). The remaining 9668 households were contacted by telephone and 6813 (70%) completed the survey, either by telephone or on the Internet. An additional 1167 households unpaired with a telephone number completed the web questionnaire (using the personal identification number for the Internet provided in the letter), yielding a total of 7980 completed questionnaires. The response rate for the households unpaired with a telephone number was estimated to be approximately 30%. This response rate was estimated assuming, as for those contacted by telephone, that 76% (9668 of 12,680) of those unpaired with a telephone number (ie, 17,697i12,680) received the letter. The resulting overall response rate was, therefore, estimated to be approximately 60% (7980 of 13,481). Overall, 52.3% answered the questionnaire on the Internet and 47.7% by telephone. In families that had more than one eligible child, the questionnaire was completed for the child whose birthday was nearest to the survey date.

In the present study, survey subjects who resided in the east end of the Island of Montreal, where an industrial sector comprising two petroleum refineries is located, were selected. This area is comprised of primarily working-class residents. The defined geographical area of the study corresponds to the Forward Sortation Areas (FSAs) H1A, H1B, H1K, H1L, H1C, H1E, and H1J (Figure 1). Residences in the study area defined by the seven FSAs are located as close as 0.4 km and up to 12.8 km from the refinery stacks (median 3.6 km). Schools in the area are 1.0 km to 8.8 km from the stacks (median 4.2 km). To limit exposure misclassification due to moving, children who resided within any of the seven FSAs since birth or who had lived at the same address in the study area for ≥1 year before the 2006 survey were selected.

Figure 1).

Figure 1)

Open in a new tab

Study area, location of refineries and the industrial area, three-character postal areas (Forward Sortation Areas) and, residential six-character postal codes. A six-character postal code represents a segment of road (block side) on which approximately 50 individuals reside

From the 7980 completed questionnaires, 842 met the residency inclusion criteria (in the east end of the Island of Montreal since birth or for ≥1 year). The response rate among the east-end Montreal population was similar to that for the entire sample (see above), and was estimated to be 65%. In the east end of the Island of Montreal, 50.4% answered the questionnaire on the Internet and 49.6% by telephone.

The questionnaire was based on the International Study of Asthma and Allergies in Childhood (ISAAC) and the European Community Respiratory Health Survey (ECHRS) standardized written questionnaires, as well as the Quebec Child and Adolescent Health and Social Survey, to ensure comparability between Canadian and International results. Survey and asthma experts were asked to review the questionnaire, and a small-scale pretest was performed for content validation. Questions focused on the child’s respiratory and allergy symptoms and illnesses, use of health care services, personal and family medical history, home environmental exposures, lifestyle factors and sociodemographic characteristics. Home postal codes (six characters) were requested from the respondents. Within the study area, a six-digit postal code often corresponds to a single segment of road on which fewer than 50 individuals reside. A question about the location of the school the child attended (when applicable) was also included. Written informed consent was obtained from the child’s parent or legal guardian. The study protocol was approved by the Montreal Public Health Research Ethics Board.

Study variables

Health outcomes:

The definition of active asthma in Health Canada’s 1995–1996 Student Lung Health Survey was used (26). ‘Active asthma’ was defined as ever having being diagnosed with asthma by a physician and having reported one or more of the following features during the 12 months preceding the survey: wheezing or whistling in the chest, a dry cough at night, an asthma attack or use of bronchodilators.

‘Asthma control’ was established in subjects with ‘active asthma’ and was assessed on the basis of five specific symptom-based criteria that are similar to those in the Canadian Pediatric Asthma Consensus guidelines (27). Asthma was considered poorly controlled if one or more of the following features was reported: daytime symptoms (eg, wheezing or whistling in the chest ≥3 times a week); night-time symptoms (eg, awakened by dry cough or wheezing ≥1 night a week); the need for ≥3 doses a week of short-acting beta-2-agonist rescue medication; physical activity limitations during the previous three months; or absence from school or daycare due to asthma during the previous three months. The survey questions related to these outcomes are listed in Appendix 1.

Individual characteristics:

The individual characteristics of children were age as linear spline basis functions with one knot at six years of age chosen on the basis of the relationship between asthma prevalence and age; sex; parental history of atopy defined as a reported history of asthma, allergic rhinitis or eczema in the child’s biological mother or father; household income (<$75,000/year or ≥$75,000/year, based on the second tercile); maternal educational level (secondary or less, or postsecondary); and environmental tobacco smoke (ETS) exposure defined as any current (eg, at the time of survey) exposure to smoking in the home.

Residential and school exposure to SO2:

The geographical location of a child’s home and school within the seven FSAs was estimated using the centroid coordinates of the six-digit postal codes.

Yearly ambient SO2 levels from refinery stack emissions were estimated at the locations of the centroid coordinates of these six-digit postal codes. They were computed from hourly SO2 levels using the AERMOD air dispersion model as described in an earlier study that assessed their acute respiratory effects (23). This model is recommended by the United States Environmental Protection Agency for estimating the concentration of pollutants at specific ground-level receptors surrounding an emission source (28). Refinery emissions of SO2 and meteorological data for 2004 were used because 2005 emission data were not available.

Briefly, data for several point-source emissions of the two refineries were used to model hourly SO2 levels at receptor locations corresponding to the residential six-digit postal code centroids in the east end of Montreal (in the FSAs H1A, H1B, H1K, H1L, H1C, H1E and H1J). The point-source emissions included those from main vents and stacks that emit continuously throughout the year (seven point-source emission sources for one refinery and five for the other). Data regarding the longitude/latitude, emission temperature, height and exit velocity for each vent and stack were available. The emissions from the main vents and stacks represented approximately 90% of the total SO2 emissions from the two refineries. From 1994 to 2005, emissions from the two refineries represented more than 80% of the industrial SO2 emissions in the area (>7500 tons/year according to the Canadian National Pollutant Release Inventory) (29).

The inputs to the dispersion model also included hourly meteorological records from the Pierre Elliott Trudeau Montreal International Airport, approximately 25 km from the study area, and upper air data from a rural monitoring site descriptive of the greater Montreal region. All meteorological data were acquired from Environment Canada (30). The topographical characteristics across the area of interest were considered to be constant. Allowances in the model were made for the nature of the local terrain, including both vegetated (grass) and paved surfaces.

Attempts were made to account for the time-activity patterns of all selected study children. For children younger than than five years of age on September 30, 2005 (compulsory school attendance age cut-off date each year), who were assumed to spend most of their time at home, hourly SO2 exposure estimates included only home exposure values. For school-age children (between five and 12 years of age), the time spent at home and at school was considered: it was assumed that 8 h a day (08:00 to 16:00) was spent at school on weekdays (Monday to Friday) from September to June and that the remaining time was spent at home. A missing SO2 value for school exposure was assigned to children attending schools outside the area of east-end Montreal (11.7%). Background ambient SO2 levels were not considered because only one average value at the monitoring station was available for the Island of Montreal (a constant for all the children in the present study). For the analyses, intra-urban geographical variations in pollutant levels emitted by industrial stacks were available only for SO2.

Data analysis

Two different sets of analyses were performed according to the prevalence of the two defined outcomes: children with active asthma and children with poor asthma control. Cases with missing data (“do not know” or “refusal”) for any of the variables included in the analyses were excluded.

Descriptive analyses estimated the frequency distribution of the study population characteristics (child’s age and sex, parental history of atopy, household income, maternal education level, maternal immigration status, ETS exposure and yearly SO2 exposure), comparing children with the disease with those without the disease as outlined above. χ2 tests were used for categorical variables and t tests for continuous variables.

Log-binomial regression models were used to estimate crude and adjusted prevalence ratios (PRs) with corresponding 95% CIs for the association between yearly SO2 exposure levels (AERMOD estimates) and asthma outcomes. Potential confounders included child’s age and sex, parental history of atopy and ETS exposure at home. The PRs are expressed per interquartile range of yearly SO2 levels (SO2 interquartile range 4.7 μg/m3). All statistical analyses were performed using STATA version 9.2 (STATA Corporation, USA).

RESULTS

Study population characteristics

Of the 842 eligible respondents who completed the survey, a total of 821 (97.5%) provided complete questionnaire data to establish the child’s asthma status and potential confounder variables.

A total of 652 (79.4% of 821) children had not been previously diagnosed with asthma. Among those ever diagnosed with asthma by a physician (n=169), 142 (17.3% of 821) experienced active asthma in the previous year. Of these, 35.9% met at least one of the five criteria of poor asthma control and five could not be evaluated because of missing data (6.2% [51 of 816]). For comparison, the prevalence of active and uncontrolled asthma was 12.8% and 4.5%, respectively, for the entire population of children in Montreal.

The characteristics of the study population are summarized in Table 1. No significant differences were found with respect to age according to asthma status. The proportion of boys was higher among children with poor asthma control (60.8%) compared with the rest of the children (ie, no asthma or controlled asthma [49.9%]). Parental history of atopy was lowest (33.0%) among children who were not asthmatic. Asthmatic subjects were also more likely to be in lower socioeconomic groups (ie, low household income and maternal education).

TABLE 1.

Characteristics of children from east-end Montreal (Quebec), 2006

Variable Active asthma (n=142) No active asthma (n=679) Poor asthma control* (n=51) Active asthma with acceptable control* (n=86) No asthma or controlled asthma(n=765)
Age, years, mean ± SD 7.6±2.7 7.5±3.3 7.2±2.7 7.6±2.7 7.5±3.3
Sex, n (%)
  Male 72 (50.7) 345 (50.8) 31 (60.8)† 37 (43.0) 382 (49.9)
  Female 70 (49.3) 334 (49.2) 20 (39.2) 49 (57.0) 383 (50.1)
Parental history of atopy, n (%) 90 (63.4)‡ 224 (33.0) 34 (66.7)§ 51 (59.3) 275 (36.0)
Household income/year, n (%)
  <$75,000 96 (73.8)† 393 (64.5) 36 (75.0) 57 (73.1) 450 (65.5)
  ≥$75,000 34 (26.2) 216 (35.5) 12 (25.0) 21 (26.9) 237 (34.5)
Maternal educational level, n (%)**
  Secondary and lower 54 (39.1) 212 (32.0) 19 (37.3) 33 (40.2) 245 (32.9)
  Postsecondary 84 (60.9) 451 (68.0) 32 (62.7) 49 (59.8) 500 (67.1)
Passive smoke exposure, n (%) 28 (19.7) 125 (18.4) 10 (19.6) 16 (18.6) 141 (18.4)
Yearly SO2exposure, μg/m3, mean ± SD 4.75 (3.24) 4.37 (3.17) 5.37 (3.50)†† 4.55 (3.09) 4.39 (3.2)
Open in a new tab
*

Assessment of asthma control was not possible for five active asthmatic subjects, thus, the number of controlled and uncontrolled asthmatics does not sum to 142;

†

Significant difference from the group of children without active asthma (χ2 P<0.05);

‡

Significant difference from the group of children without active asthma (χ2 P<0.001);

§

Significant difference from the group of children with no asthma or controlled asthma (χ2 P<0.001);

Eighty-two individuals had missing values (n=739);

**

Twenty individuals had missing values (n=801);

††

Significant difference from the group of children with no asthma or controlled asthma (t Sulphur test P<0.05). SO2 dioxide

Associations between AERMOD SO2 exposure levels and asthma outcomes

The crude and adjusted PRs of association for asthma outcomes with yearly total AERMOD SO2 estimates are presented in Table 2. The estimated crude and multivariate-adjusted PRs demonstrate a tendency toward an association between active asthma in children from east-end Montreal, and residential and school SO2 concentrations. A significant and more marked association was found between poor asthma control and SO2 concentrations (crude PR 1.45 [95% CI 1.03 to 2.03] and adjusted PR 1.39 [95% CI 1.00 to 1.94] per interquartile range). Adjusting for child’s age and sex, parental atopy and ETS exposure slightly decreased the PRs. Stratification according to age (<6 years of age and ≥6 years of age) showed that associations with SO2 were mainly observed in the older age group (data not shown). Adjusting for socioeconomic status (ie, household income and maternal educational level) had limited influence on the results of the analyses (<5%, data not shown).

TABLE 2.

Prevalence ratios (PR) for the association between yearly ambient sulphur dioxide exposure levels (AERMOD estimates) and prevalence of active asthma and poor asthma control

Health outcomes Yes No PR (95% CI) PR (95% CI)*
Active asthma 142 679 1.15 (0.94–1.41) 1.14 (0.94–1.39)
Poor asthma control† 51 765 1.45 (1.03–2.03) 1.39 (1.00–1.94)
Open in a new tab
*

Expressed as an interquartile range (IQR) increase and adjusted for child’s age, sex, parental atopy and environmental tobacco smoke exposure at home;

†

There were missing data for the questions used for the assessment of asthma control in five children

DISCUSSION

The present study demonstrated an association between the prevalence of active and poor asthma control among children living in east-end Montreal, and ambient school and residential exposure to refinery stack emissions of SO2. In the present study, SO2 exposure was estimated using a dispersion model, which provided the intra-urban geographical variation of ambient SO2 levels. In earlier studies, the association between industrial SO2 emissions and respiratory health effects among children was assessed by comparing large geographical areas with different SO2 levels or areas in varying proximity to industrial facilities that burn coal or oil, such as power plants, refineries, incinerators, petrochemical complexes and other industrial sources of SO2 (31).

Our results concur with those of Charpin et al (32), Dales et al (33) and Yang et al (34) who reported an increased prevalence of respiratory symptoms in industrial-polluted communities with higher levels of SO2 compared with low-pollution areas. Our results are also in agreement with studies reporting an increased prevalence of asthma (35–37) or asthma-related symptoms (37–39) among children living in proximity to industrial areas, including refineries and petrochemical plants, where SO2 emissions occur.

The prevalence of parental atopy was quite high in our study (more than 60% in children with active asthma and poor control of their disease, and 33% in children without asthma). Some previous studies that measured parental atopy using questionnaires reported widely varying prevalences of positive parental history of atopy in asthmatic children, for example, ranging from 15% (family history of asthma) to 28% (mother has asthma) among Canadian children with asthma (40,41). In these studies, different approaches were used to define the presence of atopy (42). The differences observed between our study and previous work could partly result from the fact that we used a more inclusive definition (ie, a reported history of asthma, allergic rhinitis and/or eczema in the child’s biological mother or father) to capture a variety of parental atopy profiles associated with asthma. The higher prevalence of parental atopy in this population could also be due to a much lower proportion of immigrants living in the area (the lowest on the Island of Montreal). In fact, the prevalence of declared parental atopy among immigrants was approximately one-half of that among the domestic population (North American origin) (25).

Furthermore, other studies did not find an association between proximity to areas with SO2-emitting industrial facilities and asthma-related outcomes (43,44). These inconsistencies may be due to the fact that most studies failed to properly classify exposure. Exposure may be better estimated with the use of dispersion modelling than by proximity to industrial facilities.

While a dispersion model was used to estimate exposure, our study was still subject to several limitations. First, definitive information regarding the residency of the children was not available. Our school-residence weighted time may not have been an adequate representation of exposure. We assumed that children who were younger than five years of age were at home; however, some were likely attending daycare, but the location of the daycare centres was not available. Nevertheless, school and daycare hours are small compared with home hours, and would have limited influence on annual exposure estimates. In support of this, when we used home exposure data only (ie, without school exposure), similar results were observed.

Second, the exposure estimates did not include other sources of SO2. We focused on the contribution of SO2 emissions from the refineries because it was the main source of this pollutant in the study area. Background SO2 emissions from other local industrial sources or from diverse urban sources were considered to be neglible.

Third, we do not know whether the effects observed in our study were due to SO2, to other pollutants or to a combination of both. Stack emissions of other pollutants such as fine particles, which have been associated with asthma, occur concurrently with SO2. Fugitive volatile organic compound (VOC) and stack emissions are dispersed to residential areas by winds and expose the population. Unfortunately, we could not address the effects of VOC and fine particulate emissions in our analyses because the levels of these pollutants were not modelled. Furthermore, we do not know whether the effects were due to cumulative or recent exposure. Pollutant levels and refinery emissions were higher in the past and, for older children, exposure might have been higher in the early years of life. However, asthma control is probably more influenced by recent exposure.

Given the multifactorial etiology of asthma, it is also possible that pollutants derived from indoor sources contribute to the aggravation of the disease. Yet, we controlled for ETS exposure in the home – the most probable confounder or effect modifier among environmental and lifestyle risk factors for asthma. Analyses controlling for the presence of reported mold or humidity in the house, as well as road traffic density on the street of the residence were also performed, with no confounders to the associations with SO2 levels observed (data not shown).

It is also worth noting that in the current study, asthma diagnosis and asthma status (active asthma and disease control) were not validated with objective measurements such as lung function tests. Nevertheless, the methods we used were similar to those of other national and international epidemiological studies that used validated and standardized questionnaires. We also assessed asthma symptoms and control using criteria and questions that are widely used in clinical practices involving children. We should also point out that asthma cannot be definitely confirmed in children younger than six years of age, and that the diagnosis of asthma is not based on physiological criteria for that age group (27,45).

Finally, the high level of public concern about the health impacts of refinery pollution might have led subjects to move away from the industrial sector, which might have influenced our prevalence results. To limit the effect of moving, we studied only children who resided at the same address in the study area for at least one year before the 2006 survey or since birth. Furthermore, public concern might have led subjects living near the refineries to over-report respiratory health symptoms. While differential reporting bias was not ruled out, the initial study was presented as a respiratory health survey of Montreal children rather than an assessment of the respiratory health effects from exposure to refinery emissions, thereby reducing such bias. Furthermore, the use of a dispersion model to estimate exposure, rather than only proximity to the industrial complex, renders differential reporting of asthma symptoms according to exposure category less likely.

CONCLUSION

Results of the present study suggest an association between exposure to SO2 from refinery stack emissions and the prevalence of active and poor asthma control. Additional studies are needed to understand whether the observed associations were due to repeat acute or chronic exposure or to both, and if industrial emissions are associated with the development of asthma.

Acknowledgments

The authors thank F Tessier, G Morneau, Y Bourassa, and Y Otis for technical support, Environment Canada and the City of Montreal for air pollution and meteorological data, and the Montreal refineries that provided emission data. This study was funded by the Quebec Ministry of Health and Social Services and by Direction de santé publique de l’Agence de la santé et des services sociaux de Montréal.

APPENDIX 1.

Health outcomes: Asthma assessment questions

Active asthma
Has a doctor ever said your child had asthma?
And, in the past 12 months, did your child have one or more of the following:

  • – … wheezing or whistling in the chest?

  • – … a dry cough at night?

  • – … an attack of asthma?

  • – … did your child use any medication against asthma (pumps, nebulizers, syrup or injection)?

Asthma control (applied to subjects with active asthma only)
Active asthma not under control if one or more of these features were reported:

  • – Currently, does your child wheeze or have a whistling sound in the chest three times or more a week?

  • – Currently, is your child awakened at night by a dry cough or by wheezing one time or more a week?

  • – During the past 3 months, has your child limited or avoided physical activities because of his/her asthma?

  • – During the past 3 months, has your child missed school or daycare, because of his/her asthma?

  • –At the time of the survey, the child used frequently (ie, ≥3 times per week) a bronchodilator for asthma.

The following questions were used to assess frequent bronchodilator use (a positive answer to the first question below was mandatory and one of the two other features was necessary to identify children using a bronchodilatator ≥3 times per week:

  1. Does your child use a bronchodilatator, such as Ventolin*? (Yes)

  2. How often does your child use the bronchodilatator ? (everyday, a few times per week)

  3. If the answer to the previous questions was ‘a few times per week, the respondent was asked: Does your child use the bronchodilatator three times or more a week? (Yes)

Open in a new tab
*

GlaxoSmithKline, USA

Footnotes

COMPETING INTERESTS: The authors have no competing interests to declare.

AUTHORS’ CONTRIBUTIONS: LJ was responsible for the design and the implementation of the ‘parent study’ (ie, Respiratory health survey in Montreal children). AS conceived the present study design. LD and AS performed the literature review and drafted the manuscript. JH developed the dispersion model. SG and CP performed the analysis and assisted in manuscript preparation, particularly the Methods and Results sections. TK provided guidance for the ‘parent’ and the present studies. All authors contributed to data interpretation and manuscript preparation.

REFERENCES

  • 1.Bates DV. The effects of air pollution on children. Environ Health Perspect. 1995;103:49–53. doi: 10.1289/ehp.95103s649. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Boezen HM, van der Zee SC, Postma DS, et al. Effects of ambient air pollution on upper and lower respiratory symptoms and peak expiratory flow in children. The Lancet. 1999;353:874–8. doi: 10.1016/S0140-6736(98)06311-9. [DOI] [PubMed] [Google Scholar]
  • 3.Neas LM, Dockery DW, Koutrakis P, Tollerud DJ, Speizer FE. The association of ambient air pollution with twice daily peak expiratory flow rate measurements in children. Am J Epidemiol. 1995;141:111–22. doi: 10.1093/oxfordjournals.aje.a117399. [DOI] [PubMed] [Google Scholar]
  • 4.Peters A, Goldstein IF, Beyer U, et al. Acute health effects of exposure to high levels of air pollution in eastern Europe. Am J Epidemiol. 1996;144:570–81. doi: 10.1093/oxfordjournals.aje.a008967. [DOI] [PubMed] [Google Scholar]
  • 5.Roemer W, Hoek G, Brunekreef B. Effect of ambient winter air pollution on respiratory health of children with chronic respiratory symptoms. Am Rev Respir Dis. 1993;147:118–24. doi: 10.1164/ajrccm/147.1.118. [DOI] [PubMed] [Google Scholar]
  • 6.Schwartz J, Dockery DW, Neas LM, et al. Acute effects of summer air pollution on respiratory symptom reporting in children. Am J Respir Crit Care Med. 1994;150:1234–42. doi: 10.1164/ajrccm.150.5.7952546. [DOI] [PubMed] [Google Scholar]
  • 7.Segala C, Fauroux B, Just J, Pascual L, Grimfeld A, Neukirch F. Short-term effect of winter air pollution on respiratory health of asthmatic children in Paris. Eur Respir J. 1998;11:677–85. [PubMed] [Google Scholar]
  • 8.Timonen KL, Pekkanen J. Air pollution and respiratory health among children with asthmatic or cough symptoms. Am J Respir Crit Care Med. 1997;156:546–52. doi: 10.1164/ajrccm.156.2.9608044. [DOI] [PubMed] [Google Scholar]
  • 9.Buchdahl R, Parker A, Stebbings T, Babiker A. Association between air pollution and acute childhood wheezy episodes: Prospective observational study. BMJ. 1996;312:661–5. doi: 10.1136/bmj.312.7032.661. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Barnett AG, Williams GM, Schwartz J, et al. Air pollution and child respiratory health: A case-crossover study in Australia and New Zealand. Am J Respir Crit Care Med. 2005;171:1272–8. doi: 10.1164/rccm.200411-1586OC. [DOI] [PubMed] [Google Scholar]
  • 11.Braun-Fahrlander C, Vuille JC, Sennhauser FH, et al. Respiratory health and long-term exposure to air pollutants in Swiss schoolchildren. SCARPOL Team. Swiss Study on Childhood Allergy and Respiratory Symptoms with Respect to Air Pollution, Climate and Pollen. Am J Respir Crit Care Med. 1997;155:1042–9. doi: 10.1164/ajrccm.155.3.9116984. [DOI] [PubMed] [Google Scholar]
  • 12.Chapman RS, Calafiore DC, Hasselblad V. Prevalence of persistent cough and phlegm in young adults in relation to long-term ambient sulfur oxide exposure. Am Rev Respir Dis. 1985;132:261–7. doi: 10.1164/arrd.1985.132.2.261. [DOI] [PubMed] [Google Scholar]
  • 13.Dockery DW, Cunningham J, Damokosh AI, et al. Health effects of acid aerosols on North American children: Respiratory symptoms. Environ Health Perspect. 1996;104:500–5. doi: 10.1289/ehp.96104500. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Herbarth O, Fritz G, Krumbiegel P, Diez U, Franck U, Richter M. Effect of sulfur dioxide and particulate pollutants on bronchitis in children – a risk analysis. Environmental Toxicology. 2001;16:269–76. doi: 10.1002/tox.1033. [DOI] [PubMed] [Google Scholar]
  • 15.Hirsch T, Weiland SK, von Mutius E, et al. Inner city air pollution and respiratory health and atopy in children. Eur Respir J. 1999;14:669–77. doi: 10.1034/j.1399-3003.1999.14c29.x. [DOI] [PubMed] [Google Scholar]
  • 16.Penard-Morand C, Charpin D, Raherison C, et al. Long-term exposure to background air pollution related to respiratory and allergic health in schoolchildren. Clin Exp Allergy. 2005;35:1279–87. doi: 10.1111/j.1365-2222.2005.02336.x. [DOI] [PubMed] [Google Scholar]
  • 17.Pikhart H, Bobak M, Gorynski P, et al. Outdoor sulphur dioxide and respiratory symptoms in Czech and Polish school children: A small-area study (SAVIAH). Small-Area Variation in Air Pollution and Health. Int Arch Occup Environ Health. 2001;74:574–8. doi: 10.1007/s004200100266. [DOI] [PubMed] [Google Scholar]
  • 18.Ware JH, Ferris BG, Jr, Dockery DW, Spengler JD, Stram DO, Speizer FE. Effects of ambient sulfur oxides and suspended particles on respiratory health of preadolescent children. Am Rev Respir Dis. 1986;133:834–42. [PubMed] [Google Scholar]
  • 19.Hoek G, Brunekreef B. Acute effects of a winter air pollution episode on pulmonary function and respiratory symptoms of children. Arch Environ Health. 1993;48:328–35. doi: 10.1080/00039896.1993.9936721. [DOI] [PubMed] [Google Scholar]
  • 20.Roemer W, Hoek G, Brunekreef B, Haluszka J, Kalandidi A, Pekkanen J. Daily variations in air pollution and respiratory health in a multicentre study: The PEACE project. Pollution Effects on Asthmatic Children in Europe. Eur Respir J. 1998;12:1354–61. doi: 10.1183/09031936.98.12061354. [DOI] [PubMed] [Google Scholar]
  • 21.Schildcrout JS, Sheppard L, Lumley T, Slaughter JC, Koenig JQ, Shapiro GG. Ambient air pollution and asthma exacerbations in children: An eight-city analysis. Am J Epidemiol. 2006;164:505–17. doi: 10.1093/aje/kwj225. [DOI] [PubMed] [Google Scholar]
  • 22.Dockery DW, Speizer FE, Stram DO, Ware JH, Spengler JD, Ferris BG., Jr Effects of inhalable particles on respiratory health of children. Am Rev Respir Dis. 1989;139:587–94. doi: 10.1164/ajrccm/139.3.587. [DOI] [PubMed] [Google Scholar]
  • 23.Smargiassi A, Kosatsky T, Hicks J, et al. Risk of asthmatic episodes in children exposed to sulfur dioxide stack emissions from a refinery point source in Montreal, Canada. Environ Health Perspect. 2009;117:653–9. doi: 10.1289/ehp.0800010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Kibble A, Harrison R. Point sources of air pollution. Occup Med (Lond) 2005;55:425–31. doi: 10.1093/occmed/kqi138. [DOI] [PubMed] [Google Scholar]
  • 25.Jacques L, Plante C, Goudreau S, et al. Rapport synthèse régional de l’étude sur la santé respiratoire des jeunes Montréalais de 6 mois à 12 ans. Montréal: Direction de santé publique de l’Agence de la santé et des services sociaux de Montréal; 2011. ISBN 978-2-89673-045-2 (printed version), ISBN 978-2-89673-046-9 (PDF document). [Google Scholar]
  • 26.Santé Canada . L’asthme infantile dans les secteurs desservis par les unités de santé sentinelles. Rapport des résultats de l’Enquête sur la santé pulmonaire des jeunes 1995–1996. Système de surveillance par unité de santé sentinelle - volet asthme. Ottawa: Division des maladies respiratoires; Bureau des maladies cardio-respiratoires et du diabète; Laboratoire de lutte contre la maladie, 1998 0-662-83351-1 Contract No.: 9 novembre 2007. [Google Scholar]
  • 27.Becker A, Berube D, Chad Z, et al. Canadian Pediatric Asthma Consensus guidelines, 2003 (updated to December 2004): Introduction. CMAJ. 2005;173:S12–4. doi: 10.1503/cmaj.045064. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.U.S. Environmental Protection Agency . Support Center for Regulatory Atmospheric Modeling. < www.epa.gov/scram001/dispersion_prefrec.htm> (Accessed July 7, 2008). [Google Scholar]
  • 29.National Pollutant Release Inventory Online Data Search < www.ec.gc.ca/pdb/websol/querysite/query_e.cfm/> (Accessed July 7, 2008).
  • 30.Environnement Canada National Climate Data and Information Archive. < www.climat.meteo.ec.gc.ca/climateData/canada_e.html> (Accessed on July 7, 2008).
  • 31.U.S. Environmental Protection Agency . Integrated Science Assessment (ISA) for Sulfur Oxides – Health Criteria (Final Report). Report EPA/600/R-08/047F. Washington DC: U.S Environmental Protection Agency; 2008. [Google Scholar]
  • 32.Charpin D, Kleisbauer JP, Fondarai J, Graland B, Viala A, Gouezo F. Respiratory symptoms and air pollution changes in children: The Gardanne Coal-Basin Study. Arch Environ Health. 1988;43:22–7. doi: 10.1080/00039896.1988.9934369. [DOI] [PubMed] [Google Scholar]
  • 33.Dales RE, Spitzer WO, Suissa S, Schechter MT, Tousignant P, Steinmetz N. Respiratory health of a population living downwind from natural gas refineries. Am Rev Respir Dis. 1989;139:595–600. doi: 10.1164/ajrccm/139.3.595. [DOI] [PubMed] [Google Scholar]
  • 34.Yang CY, Wang JD, Chan CC, Hwang JS, Chen PC. Respiratory symptoms of primary school children living in a petrochemical polluted area in Taiwan. Pediatr Pulmonol. 1998;25:299–303. doi: 10.1002/(sici)1099-0496(199805)25:5<299::aid-ppul2>3.0.co;2-e. [DOI] [PubMed] [Google Scholar]
  • 35.Forastiere F, Corbo GM, Pistelli R, et al. Bronchial responsiveness in children living in areas with different air pollution levels. Arch Environ Health. 1994;49:111–8. doi: 10.1080/00039896.1994.9937463. [DOI] [PubMed] [Google Scholar]
  • 36.Henry RL, Abramson R, Adler JA, Wlodarcyzk J, Hensley MJ. Asthma in the vicinity of power stations: I. A prevalence study. Pediatric Pulmonol. 1991;11:127–33. doi: 10.1002/ppul.1950110209. [DOI] [PubMed] [Google Scholar]
  • 37.White N, teWaterNaude J, van der Walt A, Ravenscroft G, Roberts W, Ehrlich R. Meteorologically estimated exposure but not distance predicts asthma symptoms in schoolchildren in the environs of a petrochemical refinery: A cross-sectional study. Environ Health. 2009;8:45. doi: 10.1186/1476-069X-8-45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Wichmann FA, Muller A, Busi LE, et al. Increased asthma and respiratory symptoms in children exposed to petrochemical pollution. J Allergy Clin Immunol. 2009;123:632–8. doi: 10.1016/j.jaci.2008.09.052. [DOI] [PubMed] [Google Scholar]
  • 39.Halliday JA, Henry RL, Hankin RG, Hensley MJ. Increased wheeze but not bronchial hyperreactivity near power stations. J Epidemiol Community Health. 1993;47:282–6. doi: 10.1136/jech.47.4.282. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Millar WJ, Hill GB. Childhood asthma. Health Reports (Statistics Canada, Catalogue 82-003) 1998;10:9–21. [PubMed] [Google Scholar]
  • 41.Lévesque B, Rhainds M, Ernst P, et al. Asthma and allergic rhinitis in Quebec children. Can Respir J. 2004;11:343–8. doi: 10.1155/2004/731463. [DOI] [PubMed] [Google Scholar]
  • 42.Burke W, Fesinmeyer M, Reed K, Hampson L, Carlsten C. Family history as predictor of asthma risk. Am J Prev Med. 2003;24:160–9. doi: 10.1016/s0749-3797(02)00589-5. [DOI] [PubMed] [Google Scholar]
  • 43.Bhopal RS, Phillimore P, Moffatt S, Foy C. Is living near a coking works harmful to health? A study of industrial air pollution. J Epidemiol Comm Health. 1994;48:237–47. doi: 10.1136/jech.48.3.237. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Ramadour M, Burel C, Lanteaume A, et al. Prevalence of asthma and rhinitis in relation to long-term exposure to gaseous air pollutants. Allergy. 2000;55:1163–9. doi: 10.1034/j.1398-9995.2000.00637.x. [DOI] [PubMed] [Google Scholar]
  • 45.Global Initiative For Asthma Global Strategy for the Diagnosis and Management of Asthma in Children 5 Years and Younger. < www.ginasthma.org> (Accessed October 1, 2008). [DOI] [PubMed]

Articles from Canadian Respiratory Journal : Journal of the Canadian Thoracic Society are provided here courtesy of Wiley

RESOURCES