Time series of daily administrative cardio-respiratory health and environmental information have been extensively used to assess the potential public health impact of ambient air pollution. Both series are subject to strong but unrelated temporal cycles. These cycles must be removed from the time series prior to examining the role air pollution plays in exacerbating cardio-respiratory disease. In this paper, we examine a number of methods of temporal filtering that have been proposed to eliminate such temporal effects. The techniques are illustrated by linking the number of daily admissions to hospital for respiratory diseases in Toronto, Canada for the 11 year period 1981 to 1991 with daily concentrations of ambient ozone. The ozone-hospitalization relationship was found to be highly sensitive to the length of temporal cycle removed from the admission time series, and to day of the week effects, ranging from a relative risk of 0.874 if long wave cycles were not removed at all to 1.020 for models which removed at least cycles greater than or equal to one month based on the interquartile pollutant range. The specific statistical method of adjustment was not a critical factor. The association was not as sensitive to removal of cycles less than one month, except that negative autocorrelation increased for series in which cycles of one week or less were removed. We recommend three criteria in selecting the degree of smoothing in the outcome: removal of temporal cycles, minimizing autocorrelation and optimizing goodness of fit. The association between ambient ozone levels and hospital admissions for respiratory diseases was also sensitive to the season of examination, with weaker associations observed outside the summer months.
The role of ambient levels of carbon monoxide (CO) in the exacerbation of heart problems in individuals with both cardiac and other diseases was examined by comparing daily variations in CO levels and daily fluctuations in nonaccidental mortality in metropolitan Toronto for the 15-year period 1980-1994. After adjusting the mortality time series for day-of-the-week effects, nonparametic smoothed functions of day of study and weather variables, statistically significant positive associations were observed between daily fluctuations in mortality and ambient levels of carbon monoxide, nitrogen dioxide, sulfur dioxide, coefficient of haze, total suspended particulate matter, sulfates, and estimated PM2.5 and PM10. However, the effects of this complex mixture of air pollutants could be almost completely explained by the levels of CO and total suspended particulates (TSP). Of the 40 daily nonaccidental deaths in metropolitan Toronto, 4.7% (95% confidence interval of 3.4%-6.1%) could be attributable to CO while TSP contributed an additional 1.0% (95% confidence interval of 0.2-1.9%), based on changes in CO and TSP equivalent to their average concentrations. Statistically significant positive associations were observed between CO and mortality in all seasons, age, and disease groupings examined. Carbon monoxide should be considered as a potential public health risk to urban populations at current ambient exposure levels.
To clarify the health effects of ozone exposure in young children, the authors studied the association between air pollution and hospital admissions for acute respiratory problems in children less than 2 years of age during the 15-year period from 1980 to 1994 in Toronto, Canada. The daily time series of admissions was adjusted for the influences of day of the week, season, and weather. A 35% (95% confidence interval: 19%, 52%) increase in the daily hospitalization rate for respiratory problems was associated with a 5-day moving average of the daily 1-hour maximum ozone concentration of 45 parts per billion, the May-August average value. The ozone effect persisted after adjustment for other ambient air pollutants or weather variables. Ozone was not associated with hospital admissions during the September-April period. Ambient ozone levels in the summertime should be considered a risk factor for respiratory problems in children less than 2 years of age.
Although some consensus has emerged among the scientific and regulatory communities that the urban ambient atmospheric mix of combustion related pollutants is a determinant of population health, the relative toxicity of the chemical and physical components of this complex mixture remains unclear. Daily mortality rates and concurrent data on size-fractionated particulate mass and gaseous pollutants were obtained in eight of Canada's largest cities from 1986 to 1996 inclusive in order to examine the relative toxicity of the components of the mixture of ambient air pollutants to which Canadians are exposed. Positive and statistically significant associations were observed between daily variations in both gas- and particulate-phase pollution and daily fluctuations in mortality rates. The association between air pollution and mortality could not be explained by temporal variation in either mortality rates or weather factors. Fine particulate mass (less than 2.5 microns in average aerometric diameter) was a stronger predictor of mortality than coarse mass (between 2.5 and 10 microns). Size-fractionated particulate mass explained 28% of the total health effect of the mixture, with the remaining effects accounted for by the gases. Forty-seven elemental concentrations were obtained for the fine and coarse fraction using nondestructive x-ray fluorescence techniques. Sulfate concentrations were obtained by ion chromatography. Sulfate ion, iron, nickel, and zinc from the fine fraction were most strongly associated with mortality. The total effect of these four components was greater than that for fine mass alone, suggesting that the characteristics of the complex chemical mixture in the fine fraction may be a better predictor of mortality than mass alone. However, the variation in the effects of the constituents of the fine fraction between cities was greater than the variation in the mass effect, implying that there are additional toxic components of fine particulate matter not examined in this study whose concentrations and effects vary between locations. One of these components, carbon, represents half the mass of fine particulate matter. We recommend that measurements of elemental and organic carbon be undertaken in Canadian urban environments to examine their potential effects on human health.
Determine the risk of premature mortality due to the urban ambient air pollution mix in Canada.
The number of daily deaths for non-accidental causes were obtained in 11 cities from 1980 to 1991 and linked to concentrations of ambient gaseous air pollutants using relative risk regression models for longitudinal count data.
Nitrogen dioxide had the largest effect on mortality with a 4.1% increased risk (p
Comment In: Can J Public Health. 1998 Jul-Aug;89(4):228, 238, 240 passim9735513
We obtained data on daily numbers of admissions to hospital in Toronto, Canada, from 1980 to 1994 for respiratory, cardiac, cerebral vascular, and peripheral vascular diseases. We then linked the data to daily measures of particulate mass less than 10 microns in aerodynamic diameter (PM10), particulate mass less than 2.5 microns in aerodynamic diameter (PM2.5), and particulate mass between 2.5 and 10 microns in aerodynamic diameter (PM10-2.5), ozone, carbon monoxide, nitrogen dioxide, and sulfur dioxide. Air pollution was only associated weakly with hospitalization for cerebral vascular and peripheral vascular diseases. We controlled for temporal trends and climatic factors, and we found that increases of 10 microg/m3 in PM10, PM2.5, and PM10-2.5 were associated with 1.9%, 3.3%, and 2.9% respective increase in respiratory and cardiac hospital admissions. We further controlled for gaseous pollutants, and the percentages were reduced to 0.50%, 0.75%, and 0.77%, respectively. Of the 7.72 excess daily hospital admissions in Toronto attributable to the atmospheric pollution mix, 11.8% resulted from PM2.5, 8.2% to PM10-2.5, 17% to carbon monoxide, 40.4% to nitrogen dioxide, 2.8% to sulfur dioxide, and 19.8% to ozone.
The impact of ambient aeroallergens on morbidity from childhood asthma is largely unknown. To address this issue, we studied the association between daily emergency department visits for asthma to a children's hospital, and daily concentrations of both pollen grains and fungal spores during a 5-yr period between 1993 and 1997. Air pollution and meteorological data accounted for in the analyses included ozone, nitrogen dioxide, sulfur dioxide, sulfates, temperature, barometric pressure, and relative humidity. The daily number of asthma visits ranged from 0 to 36 per day with an average of 7.5. Fungal spores, but not pollen grains, were associated with visits (p
The association between daily fluctuations in ambient particulate matter and daily variations in nonaccidental mortality have been extensively investigated. Although it is now widely recognized that such an association exists, the form of the concentration-response model is still in question. Linear, no threshold and linear threshold models have been most commonly examined. In this paper we considered methods to detect and estimate threshold concentrations using time series data of daily mortality rates and air pollution concentrations. Because exposure is measured with error, we also considered the influence of measurement error in distinguishing between these two completing model specifications. The methods were illustrated on a 15-year daily time series of nonaccidental mortality and particulate air pollution data in Toronto, Canada. Nonparametric smoothed representations of the association between mortality and air pollution were adequate to graphically distinguish between these two forms. Weighted nonlinear regression methods for relative risk models were adequate to give nearly unbiased estimates of threshold concentrations even under conditions of extreme exposure measurement error. The uncertainty in the threshold estimates increased with the degree of exposure error. Regression models incorporating threshold concentrations could be clearly distinguished from linear relative risk models in the presence of exposure measurement error. The assumption of a linear model given that a threshold model was the correct form usually resulted in overestimates in the number of averted premature deaths, except for low threshold concentrations and large measurement error.