Association between Air Pollution and Daily Consultations with General Practitioners for Allergic Rhinitis in London, United Kingdom

S. Hajat1,4, A. Haines1,5, R. W. Atkinson2, S. A. Bremner2, H. R. Anderson2 and J. Emberlin3

1 Department of Primary Care and Population Sciences, Royal Free and University College Medical School, London, United Kingdom.
2 Department of Public Health Sciences, St. George's Hospital Medical School, London, United Kingdom.
3 National Pollen Research Unit, University College Worcester, Worcester, United Kingdom.
4 Present address: Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
5 Present address: London School of Hygiene and Tropical Medicine, London, United Kingdom.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Few published studies have looked at the health effects of air pollution in the primary care setting, and most have concentrated on lower rather than upper respiratory diseases. The authors investigated the association of daily consultations with general practitioners for allergic rhinitis with air pollution in London, United Kingdom. Generalized additive models were used to regress time series of daily numbers of patients consulting for allergic rhinitis against 1992–1994 measures of air pollution, after control for possible confounders and adjustment for overdispersion and serial correlation. In children, a 10th–90th percentile increase in sulfur dioxide (SO2) levels 4 days prior to consultation (13–31 µg/m3) was associated with a 24.5% increase in consultations (95% confidence interval: 14.6, 35.2; p < 0.00001); a 10th–90th percentile increase in averaged ozone (O3) concentrations on the day of consultation and the preceding 3 days (6–29 parts per billion) was associated with a 37.6% rise (95% confidence interval: 23.3, 53.5; p < 0.00001). For adults, smaller effect sizes were observed for SO2 and O3. The association with SO2 remained highly significant in the presence of other pollutants. This study suggests that air pollution worsens allergic rhinitis symptoms, leading to substantial increases in consultations. SO2 and O3 seem particularly responsible, and both seem to contribute independently.

air pollutants; air pollution; family practice; ozone; primary health care; rhinitis; sulfur dioxide

Abbreviations: CI, confidence interval; PM10, particulate matter less than 10 µm in diameter; SD, standard deviation


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Most research on the health effects of air pollution has focused on lower respiratory diseases such as asthma, but the effects on upper respiratory diseases have not been studied extensively. The incidence of allergic disease is thought to be on the increase (1Go, 2Go) and has been attributed in part to increased exposure to air pollution, possibly because of particulates (3Go). It has been suggested that differences in the incidence of allergic rhinitis in children from Leipzig and Munich, Germany, may be due to higher levels of nitrogen dioxide from car exhaust fumes in Munich, although particulate concentrations were higher in Leipzig (4Go). Another study found that the incidence of red cedar pollen rhinitis in Japan was directly related to the level of pollution from automobile exhaust (5Go). Finn suggested that hay fever is an industrial disease, mainly because there were few reports of hay fever before the industrial revolution (6Go). However, an examination of the incidence of allergic rhinitis in general practice throughout England and Wales showed no important differences between urban and rural locations, and the investigators concluded that local pollutants were unlikely to have a role in the incidence of hay fever (7Go).

Most time-series studies have focused on mortality and hospital admissions; very few have considered the primary care setting, where most patient contacts occur. We carried out a time-series analysis of daily general practitioner consultations for allergic rhinitis in London, United Kingdom, over the period 1992–1994. We chose to study London because it is a large city with adequate numbers of general practitioner consultations, and extensive air pollution data are available. With the exception of sulfur dioxide, London's air pollution is predominantly due to traffic (8Go), and our results should be applicable to other cities with similar emission sources.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
General practitioner consultation data
Daily numbers of persons consulting general practitioners for allergic rhinitis between January 1992 and December 1994 were obtained from the General Practice Research database. The database consists of anonymous, computerized patient records and is currently available from the Medicines Control Agency, which manages the database on behalf of the Department of Health (both located in London). Participating practices are required to record all significant morbidity and drugs prescribed, with dates, as well as an indication (diagnosis) for each prescription and the initial indication for any repeat prescription. Persons consulting more than once a day are recorded only once in the database; however, for brevity, in this paper we have adopted the term "consultations" rather than "persons consulting." The combined daily number of consultations for either an emergency or an elective complaint is recorded and includes home visits. General practitioners are not required to record all consultations, but a validation study of 13 General Practice Research database practices found that, on average, 95 percent of all known prescriptions were recorded on a computer system (9Go).

For the 3-year period analyzed, 44,406–49,596 registered patients aged <1–14 years and 185,267–204,039 patients aged 15–64 years from 45–47 general practices in the greater London area contributed information to the database. This paper focuses on the diagnostic grouping allergic rhinitis (International Classification of Diseases, Ninth Revision code 477) and presents the results of our analysis of children (aged <1–14 years) and adults (aged 15–64 years). The numbers of cases of allergic rhinitis in elderly people (aged >=65 years) were too small to be analyzed (the mean number of daily consultations was 1.0).

Air pollution, meteorologic, and aeroallergen data
Pollution measures were obtained from monitoring stations distributed throughout London (10Go). Measures from 1992–1994 were used because of the availability of data when the study started and the completeness of the measures (as determined by a protocol devised by the collaborative European project APHEA (11Go)). Sulfur dioxide and black smoke data were obtained from five sites dispersed across London; nitrogen dioxide and carbon monoxide data came from three sites in central London, two of which also provided ozone measures; and one central site provided data on particulate matter less than 10 µm in diameter (PM10). Missing values were estimated by using a regression technique in which estimates are based on levels obtained from other sites for the same time period (12Go). Further, detailed information on the sites and measurement methods used is provided in a comprehensive review of air quality in the United Kingdom (10Go).

Daily maximum and minimum temperatures and the 6 a.m. and 3 p.m. relative humidity at Holborn in central London were obtained from the Meteorological Office. Daily average temperature and relative humidity measures were computed as the mean of their two respective values.

Pollen data from the London site of the National Pollen Network were obtained from the National Pollen Research Unit at Worcester. The data were collected with a Burkard volumetric spore trap, which was situated on the exposed rooftop of a seven-story building in Holloway, north London. The standard techniques adopted by the British Aerobiology Federation were used. Data on the daily maximum 2-hour and 24-hour average concentrations of pollen grains per cubic meter were available. The pollen types considered were hazel, birch, alder, oak, nettle, grasses, plantain, lime, dock, chestnut, and willow.

Statistical methods
The time-series analyses were conducted by using generalized additive models with nonparametric smoothers to control for seasonal patterns. A smoother is a tool for summarizing the trend in one variable, in this case the number of visits to the general practitioner, as a function of another variable, in this instance time. This method allows for very flexible control of unusual seasonal patterns such as those observed in the allergic rhinitis series. The span of the smoother was varied to control the amount of smoothing carried out on the time series. The aim was to select the span that removed long-term seasonality but left short-term patterns, since they may be caused by fluctuations in air pollution levels. The amount of smoothing required varied between series; therefore, to determine the amount of smoothing needed, a relatively large span was used initially and the model diagnostics examined. Successive reductions in the smoothing window were then made, and individual smoothers were created for more problematic periods of the series. Model diagnostics were reassessed at each step. Goodness of fit of the statistical model was assessed from the model residuals, the magnitude of the dispersion parameter, the partial autocorrelation function, and the model deviance.

Dummy variables were used to allow for day-of-the-week effects. Temperature and humidity were included in the model after various diagnostic plots of the seasonally adjusted model residuals were considered against different lags, both single and cumulative, of the meteorologic variables. Depending on which were more appropriate, either parametric functions or broad smoothers of the meteorologic variables were used to model the associations. Variation in the practice population over the 3-year period, counts for lagged allergic pollen measures, and the daily number of consultations for influenza were all adjusted for in the "core" model if necessary. Once all of these potential confounding variables had been included, the air pollution indicator was added to complete the statistical model. After we allowed for overdispersion and autocorrelation if necessary (13Go), Poisson generalized additive models (quasi-likelihood) regression (or robust regression if deemed more appropriate) was used to determine the relative risk of consultation associated with an increase in the pollution measure. All statistical analyses were carried out by using S-PLUS software (14Go).

The results obtained were expressed as a percentage change in the mean number of consultations for 10th–90th percentile increases in pollutant levels. A predetermined set of daily pollution measures was tested, in turn, in the statistical model. For sulfur dioxide, black smoke, carbon monoxide, and PM10, the 24-hour average measure was tested. For nitrogen dioxide and ozone, two daily measures were used; for nitrogen dioxide, we used the 24-hour average and maximum 1-hour measures; and for ozone, the maximum 8-hour running average and maximum 1-hour measures were used. For completeness, all pollutants were tested, even though we did not expect a causal relation between allergic rhinitis consultations and some pollutants such as carbon monoxide. Pollutant levels on the current day; the previous day; and 2, 3, 4, 5, and 6 days prior to the day of consultation (described as lag 0, lag 1, lag 2, etc.), as well as cumulative measures calculated as the mean value of lags 0 and 1, lags 0–2, lags 0–3, etc., were each tested in the model. When appropriate, models with two pollutant measures were also run to determine whether one pollutant was more important than another. When a strong single-pollutant association was found, exposure-response plots of the relative risk of consulting a general practitioner for allergic rhinitis against the level of pollutant were investigated to identify the nature of the relation. Because of the large number of pollutants and lags tested, this paper emphasizes the consistency of associations across lags and measures and discusses only the more highly significant findings (i.e., p < 0.01).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Descriptive data
Figure 1 shows the daily numbers of consultations for allergic rhinitis in children between January 1, 1992, and December 31, 1994. The adult series (not shown) included more consultations but followed a very similar pattern. As expected, visits were restricted mainly to the spring and summer months. The numbers included two peaks each year, one in late April and a larger one in June. In this figure, the line indicates the amount of smoothing used in the "core" regression model. No significant autocorrelation was present. In the adult series, a similar degree of smoothing was used, and the partial autocorrelation function of this series suggested significant serial correlation remaining on a lag of 1 day, which was adjusted for by including the appropriate autoregressive term in the model.



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FIGURE 1. Daily numbers of consultations with general practitioners for allergic rhinitis in children in participating London, United Kingdom, practices between January 1, 1992, and December 31, 1994. The line indicates the amount of smoothing used in the "core" regression model.

 
Table 1 shows the mean (standard deviation) and the 10th and 90th percentiles of the air pollution and meteorologic variables and the daily number of consultations for allergic rhinitis in children and adults. The mean number of daily consultations was 4.8 (standard deviation (SD), 11.5) for the children and 15.3 (SD, 33.2) for the adults. Pearson correlation coefficients between air pollution and meteorologic variables were presented in a previous paper, which looked at the effects of air pollution on general practitioner consultations for asthma and other lower respiratory diseases (15Go). Generally, the correlation coefficients between nitrogen dioxide, sulfur dioxide, black smoke, carbon monoxide, and PM10 were high and positive. Ozone was negatively correlated with most other pollutants. Correlations between sites for nitrogen dioxide, ozone, and carbon monoxide were all positive and high at 0.7–0.96 but were smaller for the five sites providing sulfur dioxide and black smoke data.


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TABLE 1. Summary statistics for daily numbers of consultations with general practitioners for allergic rhinitis and for air pollution and meteorologic variables, London, United Kingdom, 1992–1994

 
Regression analysis
Figures 2GoGo5 show the results of the single-pollutant analysis of both lagged single-day measures and cumulative measures for children and adults. Included is the percentage change (and 95 percent confidence interval) in the number of consultations associated with a 10th–90th percentile increase in pollutant. Results of the nitrogen dioxide and ozone 1-hour measures did not differ greatly from the other nitrogen dioxide and ozone measures and are not shown.



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FIGURE 2. Graphic representation of the percentage change (and 95% confidence interval (CI)) in the number of consultations with general practitioners for allergic rhinitis in children associated with a 10th–90th percentile increase in pollutant for single-day measures on the day of consultation and 1–6 days prior to consultation, London, United Kingdom, 1992–1994. NO2, nitrogen dioxide; O3, ozone; SO2, sulfur dioxide; BS, black smoke; CO, carbon monoxide; PM10, particulate matter less than 10 µm in diameter.

 


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FIGURE 3. Graphic representation of the percentage change (and 95% confidence interval (CI)) in the number of consultations with general practitioners for allergic rhinitis in children associated with a 10th–90th percentile increase in pollutant for cumulative mean measures from day 0 and day 1 to day 6, London, United Kingdom, 1992–1994. For each pollutant, the cumulative measure is mean (lags 0 and 1), mean (lags 0–2), mean (lags 0–3), mean (lags 0–4), mean (lags 0–5), and mean (lags 0–6), respectively. NO2, nitrogen dioxide; O3, ozone; SO2, sulfur dioxide; BS, black smoke; CO, carbon monoxide; PM10, particulate matter less than 10 µm in diameter.

 


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FIGURE 4. Graphic representation of the percentage change (and 95% confidence interval (CI)) in the number of consultations with general practitioners for allergic rhinitis in adults associated with a 10th–90th percentile increase in pollutant for single-day measures on the day of consultation and 1–6 days prior to consultation, London, United Kingdom, 1992–1994. NO2, nitrogen dioxide; O3, ozone; SO2, sulfur dioxide; BS, black smoke; CO, carbon monoxide; PM10, particulate matter less than 10 µm in diameter.

 


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FIGURE 5. Graphic representation of the percentage change (and 95% confidence interval (CI)) in the number of consultations with general practitioners for allergic rhinitis in adults associated with a 10th–90th percentile increase in pollutant for cumulative mean measures from day 0 and day 1 to day 6, London, United Kingdom, 1992–1994. For each pollutant, the cumulative measure is mean (lags 0 and 1), mean (lags 0–2), mean (lags 0–3), mean (lags 0–4), mean (lags 0–5), and mean (lags 0–6), respectively. NO2, nitrogen dioxide; O3, ozone; SO2, sulfur dioxide; BS, black smoke; CO, carbon monoxide; PM10, particulate matter less than 10 µm in diameter.

 
As shown in figures 2 and 3, ozone, sulfur dioxide, and, to a lesser extent, nitrogen dioxide and PM10 all were associated with significant increases in the number of consultations for allergic rhinitis in children. For example, there was a 24.5 percent (95 percent confidence interval (CI): 14.6, 35.2) rise in the number of consultations associated with a 10th–90th percentile increase in sulfur dioxide levels (13–31 µg/m3) on 4 days prior to consultation and a 37.6 percent increase in consultations (95 percent CI: 23.3, 53.5) associated with a 10th–90th percentile increase in averaged ozone concentrations on the day of consultation and the preceding 3 days (6–29 parts per billion). In general, the estimates were largest for a lag of 3 or 4 days prior to consultation; beyond this time, the effect of the pollutants seemed to diminish.

In the adults series (figures 4 and 5), significant associations were again observed between sulfur dioxide, ozone, PM10, and nitrogen dioxide and the number of consultations for allergic rhinitis; however, the percentage increases generally were not as large as those found for children. The strongest associations were observed with cumulative measures of pollutants rather than single-day lags, and a pattern of increase in effect size with increase in cumulative measure was observed up to lag 6. Lags of more than 6 days were also considered, but very few associations were found.

Table 2 summarizes the findings of the single-pollutant analysis. For each age group, the most significant lag up to 6 days, irrespective of whether the association was negative or positive, was selected for inclusion in the tables. Results for both single-day and cumulative measures of each pollutant are reported.


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TABLE 2. Summary of results of the single-pollutant analysis* of consultations with general practitioners for allergic rhinitis, London, United Kingdom, 1992–1994

 
Two-pollutant analysis
Table 3 shows selected results of the two-pollutant analysis. The diagonal underlined elements give the single-pollutant model results and the off-diagonal (not underlined) elements the results for the "row pollutant" in the presence of the "column pollutant." To choose one single-day lag when all selected pollutants were strongly associated with consultations, a lag of 4 days was used for each pollutant in the series for children and a lag of 3 days for adults.


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TABLE 3. Selected results of two-pollutant analysis,* London, United Kingdom, 1992–1994

 
The analysis shows that, for children, associations with nitrogen dioxide or PM10 were no longer significant at the 1 percent level once any of the other pollutants was incorporated into the model. With ozone, the association remained although was reduced particularly in the presence of sulfur dioxide. Sulfur dioxide remained highly significant in the presence of other pollutants. For adults, a sizable association with sulfur dioxide remained in the presence of any other pollutant. Possible interactions between pollutants were considered, but none was found.

Exposure-response associations
Figures 6GoGo9 show the exposure-response relation between the relative risk of consulting general practitioners for allergic rhinitis against sulfur dioxide and ozone levels for children and adults. The risks are based on models adjusted for all factors, including the other of the two pollutants. Pointwise one standard error limits are given, with a "rug" along the bottom to indicate where prediction was based on relatively few points.



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FIGURE 6. Dose-response plots of the relative risk of consulting with general practitioners for allergic rhinitis in children against sulfur dioxide (SO2) levels 4 days prior to consultation, London, United Kingdom, 1992–1994. Pointwise one standard error limits are given, with a "rug" along the bottom to indicate where estimation was based on relatively few points. Vertical dotted line, median pollution level; horizontal dotted line, null relative risk.

 


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FIGURE 7. Dose-response plots of the relative risk of consulting with general practitioners for allergic rhinitis in children against average ozone (O3) levels over lags 0–3, London, United Kingdom, 1992–1994. Pointwise one standard error limits are given, with a "rug" along the bottom to indicate where estimation was based on relatively few points. Vertical dotted line, median pollution level; horizontal dotted line, null relative risk.

 


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FIGURE 8. Dose-response plots of the relative risk of consulting with general practitioners for allergic rhinitis in adults against sulfur dioxide (SO2) levels 3 days prior to consultation, London, United Kingdom, 1992–1994. Pointwise one standard error limits are given, with a "rug" along the bottom to indicate where estimation was based on relatively few points. Vertical dotted line, median pollution level; horizontal dotted line, null relative risk.

 


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FIGURE 9. Dose-response plots of the relative risk of consulting with general practitioners for allergic rhinitis in adults against average ozone (O3) levels over lags 0–3, London, United Kingdom, 1992–1994. Pointwise one standard error limits are given, with a "rug" along the bottom to indicate where estimation was based on relatively few points. Vertical dotted line, median pollution level; horizontal dotted line, null relative risk.

 
For children, figures 6 and 7 suggest that risk leveled off at higher pollution levels. An F test of nonlinearity of the sulfur dioxide term was not significant at the 5 percent level, however, although it was for the ozone measure (p = 0.002), suggesting strongly that the relation between the risk of consultation and ozone levels is nonlinear.

For adults (figures 8 and 9Go), the sulfur dioxide effect again leveled off, although the plateau occurred at about 20 µg/m3, a much lower concentration than that for children. For adults, the relation between the risk of consulting a general practitioner and ozone levels suggested a dip in risk at moderate levels of ozone followed by an increase, with no suggestion of a leveling off.


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
In studies of this type, a key issue is appropriate control for confounding variables. Our statistical models were constructed by following an accepted methodology and were checked to ensure that the model fit was satisfactory. Furthermore, as a form of sensitivity analysis, the data were reanalyzed by using an alternative, parametric methodology (11Go). The results obtained by this method were remarkably similar for the group aged <1–14 years; for example, for the same increase in 4-day lagged sulfur dioxide levels that led to a 24.5 percent rise in the number of consultations (95 percent CI: 14.6, 35.2) using generalized additive models, a 25.9 percent (95 percent CI: 15.4, 37.3) change was observed when the parametric method was used (full results available from the authors on request).

For adults, the core model obtained by using the parametric method was poor in that it had unaccountably large residuals and a less-than-adequate dispersion parameter. This finding suggests that parametrically adjusting for seasonality by using trigonometric terms may not be appropriate for series such as allergic rhinitis consultations, where numbers are negligible throughout the year except in the summer months, when numbers peak (figure 1). Generalized additive models methodology handles these peaks better by creating individual "smoothers" for each of these periods. The series for children was not as "noisy" as that for adults and so could be modeled more adequately. For children, the consistency of results between the two methods suggests that the associations of air pollution with consultations for allergic rhinitis presented in this paper are robust to the modeling strategy used. The lack of any association observed when another diagnostic category, cardiovascular disease, was considered for adults (results available on request) and the difference in associations found for asthma and other lower respiratory diseases (15Go) suggest that our results are specific to allergic rhinitis consultations.

The core model to which the pollutant measures were added included pollen. The numbers of consultations for allergic rhinitis peaked twice, once in late April and again in June. We found that the larger yearly peak coincided with high levels of grass pollen in June; this observation has been reported previously (16Go). The earlier peak may have been due to several factors, including exposure to birch and oak pollen; levels of both rise in late April.

The strongest associations of pollutants with allergic rhinitis consultations were found for children. In adults, use of over-the-counter medication may reduce consultations with a general practitioner. For children, strong associations were observed between the number of consultations and most pollutants on a lag of 4 days; for adults, the greatest effect sizes were observed by using cumulative measures up to 6 days previously. This finding suggests that for allergic rhinitis consultations, lagged measures of pollution with more than 3 days of exposure are required to show true effect sizes, which could be due to the nonemergency nature of allergic rhinitis consultations or reflect the effect of prolonged exposure to pollution. The latter suggestion could explain the much higher estimates of ozone obtained with cumulative measures rather than single-day lags for both age groups. Compared with adults, the group aged <1–14 years may have taken less time to present to general practitioners, perhaps reflecting parents' more immediate reaction to illness in their children.

The two-pollutant analysis of the children's model showed that the PM10 and nitrogen dioxide associations observed in the single-pollutant analysis disappeared once either sulfur dioxide or ozone was incorporated into the model. This finding is not surprising since there is a strong intercorrelation between most air pollutants (with the exception of ozone); furthermore, in the summer months, when most allergic rhinitis consultations occur, even ozone was weakly positively correlated with the other pollutants. Unsurprisingly, then, the association of consultations for allergic rhinitis with ozone was only slightly reduced in the presence of other pollutants. In patients suffering from allergic rhinitis, exposure to ozone can induce an influx of neutrophils and eosinophils in the nasal mucosa (17Go). The association with sulfur dioxide, although weakened once other pollutants were included in the model, remained highly significant. It was found that sulfur dioxide levels were not particularly high during hay fever periods; in our data set, the mean sulfur dioxide level on April 1 and July 31 was 20.8 (SD, 6.3) µg/m3 compared with 21.5 (SD, 8.5) µg/m3 at all other times.

For ozone, effect sizes may have been underestimated because of the possible nonlinear relation between the risk of consulting with general practitioners and ozone levels, as indicated by the exposure-response plots. The plots also suggest that there exist levels of sulfur dioxide and ozone at which point the risk of consulting for allergic rhinitis in children begins to level off; therefore, perhaps a more realistic linear estimate could be obtained by considering just those pollutant ranges below the threshold value. For adults, a leveling off was observed with sulfur dioxide but not ozone. The apparent increase in risk observed at lower levels of ozone compared with moderate levels could be due to the high negative correlation of ozone with most other pollutants. The steepest increases in risk for both children and adults were observed at ozone levels well below the current World Health Organization exceedable level of 50 parts per billion.

In conclusion, our work has demonstrated that strong associations exist between sulfur dioxide and ozone and the number of consultations for allergic rhinitis, with both pollutants seemingly making an independent contribution. These results were not found in the study by Ross and Fleming (7Go); however, their distinction of urban and rural locations as an indicator of pollution levels may have been too crude. Whereas concentrations of most pollutants are likely to be higher in cities than in rural areas, ozone is broken down by oxides of nitrogen around roads; therefore, concentrations are lower in urban areas (10Go). Although our data did not distinguish between first and subsequent consultations, the increases likely indicate an exacerbation of symptoms by pollutants rather than an initiation of allergies (18Go). Experimental data have shown that, compared with nonrhinitic subjects, the nasal congestive response of subjects with seasonal allergic rhinitis is significantly augmented when they are exposed to a controlled, low-level chemical irritant (19Go). Our findings are consistent with an acute effect of air pollution, particularly sulfur dioxide and ozone, and show that primary care is a feasible source of data for demonstrating the health effects of air pollution.


    ACKNOWLEDGMENTS
 
This report forms one part of a Department of Health–funded project, which studied the effects of air pollution on daily mortality, hospital admissions, accident and emergency visits, and general practitioner consultations in London.

The steering group for this project consisted of H. R. Anderson, M. Bland, J. Bower, J. Emberlin, A. Haines, A. J. McMichael, and D. Strachan.


    NOTES
 
Reprint requests to S. Hajat, Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, United Kingdom (e-mail: Shakoor.Hajat{at}lshtm.ac.uk).


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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Received for publication March 14, 2000. Accepted for publication July 18, 2000.