Exposure to ambient air pollutants and the onset of dementia in Québec, Canada.

BACKGROUND: Effects of air pollutants are related to oxidative stress which is also linked to the pathogenesis of dementia including Alzheimer's and related diseases. OBJECTIVE: We assessed associations between exposure to air pollutants and the onset of dementia; the association with the distance between residence and major roads was also assessed for the island of Montreal. METHODS: We created an open cohort of adults aged 65 years and older starting in 2000 and ending in 2012 in the province of Québec, Canada using linked medico-administrative databases. New cases of dementia were defined based on a validated algorithm. Annual residential levels of nitrogen dioxide (NO2) and fine particles (PM2.5) at residential levels were estimated for each year of follow up using estimates based on satellite images and ground air monitoring data. Hazard ratios (HRs) were assessed with Extended (time dependent exposure) Cox models with age as the time axis and stratified for sex, for the annual exposure level at each residential address. Models were adjusted for the calendar year, area-wide social and material deprivation indexes and for NO2 or PM2.5; they were also indirectly adjusted for smoking. RESULTS: 1,807,133 persons (13,242,270 person-years) were followed and 199,826 developed dementia. From models (adjusted for calendar year, social and material deprivation indexes), HRs for an interquartile range (IQR) increase in time-varying exposure to NO2 (IQR 13.26 ppb), PM2.5 (IQR 3.90 µg/m³), and distance to major roads (IQR 150 m, in Montreal only), were 1.005 (CI 95% 0.994-1.017), 1.016 (CI 95% 1.003-1.028) and 0.969 (CI 95% 0.958-0.980), respectively. CONCLUSIONS: Results suggest that the onset of dementia may be related to residential exposure to PM2.5, NO2, and distance to major roads.

Associations of outdoor fine particulate air pollution and cardiovascular disease in 157 436 individuals from 21 high-income, middle-income, and low-income countries (PURE): a prospective cohort study.

BACKGROUND: Most studies of long-term exposure to outdoor fine particulate matter (PM2·5) and cardiovascular disease are from high-income countries with relatively low PM2·5 concentrations. It is unclear whether risks are similar in low-income and middle-income countries (LMICs) and how outdoor PM2·5 contributes to the global burden of cardiovascular disease. In our analysis of the Prospective Urban and Rural Epidemiology (PURE) study, we aimed to investigate the association between long-term exposure to PM2·5 concentrations and cardiovascular disease in a large cohort of adults from 21 high-income, middle-income, and low-income countries. METHODS: In this multinational, prospective cohort study, we studied 157 436 adults aged 35-70 years who were enrolled in the PURE study in countries with ambient PM2·5 estimates, for whom follow-up data were available. Cox proportional hazard frailty models were used to estimate the associations between long-term mean community outdoor PM2·5 concentrations and cardiovascular disease events (fatal and non-fatal), cardiovascular disease mortality, and other non-accidental mortality. FINDINGS: Between Jan 1, 2003, and July 14, 2018, 157 436 adults from 747 communities in 21 high-income, middle-income, and low-income countries were enrolled and followed up, of whom 140 020 participants resided in LMICs. During a median follow-up period of 9·3 years (IQR 7·8-10·8; corresponding to 1·4 million person-years), we documented 9996 non-accidental deaths, of which 3219 were attributed to cardiovascular disease. 9152 (5·8%) of 157 436 participants had cardiovascular disease events (fatal and non-fatal incident cardiovascular disease), including 4083 myocardial infarctions and 4139 strokes. Mean 3-year PM2·5 at cohort baseline was 47·5 µg/m3 (range 6-140). In models adjusted for individual, household, and geographical factors, a 10 µg/m3 increase in PM2·5 was associated with increased risk for cardiovascular disease events (hazard ratio 1·05 [95% CI 1·03-1·07]), myocardial infarction (1·03 [1·00-1·05]), stroke (1·07 [1·04-1·10]), and cardiovascular disease mortality (1·03 [1·00-1·05]). Results were similar for LMICs and communities with high PM2·5 concentrations (>35 µg/m3). The population attributable fraction for PM2·5 in the PURE cohort was 13·9% (95% CI 8·8-18·6) for cardiovascular disease events, 8·4% (0·0-15·4) for myocardial infarction, 19·6% (13·0-25·8) for stroke, and 8·3% (0·0-15·2) for cardiovascular disease mortality. We identified no consistent associations between PM2·5 and risk for non-cardiovascular disease deaths. INTERPRETATION: Long-term outdoor PM2·5 concentrations were associated with increased risks of cardiovascular disease in adults aged 35-70 years. Air pollution is an important global risk factor for cardiovascular disease and a need exists to reduce air pollution concentrations, especially in LMICs, where air pollution levels are highest. FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).

Within-city Spatial Variations in Ambient Ultrafine Particle Concentrations and Incident Brain Tumors in Adults.

BACKGROUND: Ambient ultrafine particles (UFPs, <0.1 µm) can reach the human brain, but to our knowledge, epidemiologic studies have yet to evaluate the relation between UFPs and incident brain tumors. METHODS: We conducted a cohort study of within-city spatial variations in ambient UFPs across Montreal and Toronto, Canada, among 1.9 million adults included in multiple cycles of the Canadian Census Health and Environment Cohorts (1991, 1996, 2001, and 2006). UFP exposures (3-year moving averages) were assigned to residential locations using land-use regression models with exposures updated to account for residential mobility within and between cities. We followed cohort members for malignant brain tumors (ICD-10 codes C71.0-C71.9) between 2001 and 2016; Cox proportional hazards models (stratified by age, sex, immigration status, and census cycle) were used to estimate hazard ratios (HRs) adjusting for fine particle mass concentrations (PM2.5), nitrogen dioxide (NO2), and various sociodemographic factors. RESULTS: In total, we identified 1,400 incident brain tumors during the follow-up period. Each 10,000/cm increase in UFPs was positively associated with brain tumor incidence (HR = 1.112, 95% CI = 1.042, 1.188) after adjusting for PM2.5, NO2, and sociodemographic factors. Applying an indirect adjustment for cigarette smoking and body mass index strengthened this relation (HR = 1.133, 95% CI = 1.032, 1.245). PM2.5 and NO2 were not associated with an increased incidence of brain tumors. CONCLUSIONS: Ambient UFPs may represent a previously unrecognized risk factor for incident brain tumors in adults. Future studies should aim to replicate these results given the high prevalence of UFP exposures in urban areas.

Evaluating the Sensitivity of PM2.5-Mortality Associations to the Spatial and Temporal Scale of Exposure Assessment.

BACKGROUND: The temporal and spatial scales of exposure assessment may influence observed associations between fine particulate air pollution (PM2.5) and mortality, but few studies have systematically examined this question. METHODS: We followed 2.4 million adults in the 2001 Canadian Census Health and Environment Cohort for nonaccidental and cause-specific mortality between 2001 and 2011. We assigned PM2.5 exposures to residential locations using satellite-based estimates and compared three different temporal moving averages (1, 3, and 8 years) and three spatial scales (1, 5, and 10 km) of exposure assignment. In addition, we examined different spatial scales based on age, employment status, and urban/rural location, and adjustment for O3, NO2, or their combined oxidant capacity (Ox). RESULTS: In general, longer moving averages resulted in stronger associations between PM2.5 and mortality. For nonaccidental mortality, we observed a hazard ratio of 1.11 (95% CI = 1.08, 1.13) for the 1-year moving average compared with 1.23 (95% CI = 1.20, 1.27) for the 8-year moving average. Respiratory and lung cancer mortality were most sensitive to the spatial scale of exposure assessment with stronger associations observed at smaller spatial scales. Adjustment for oxidant gases attenuated associations between PM2.5 and cardiovascular mortality and strengthened associations with lung cancer. Despite these variations, PM2.5 was associated with increased mortality in nearly all of the models examined. CONCLUSIONS: These findings support a relationship between outdoor PM2.5 and mortality at low concentrations and highlight the importance of longer-exposure windows, more spatially resolved exposure metrics, and adjustment for oxidant gases in characterizing this relationship.

Ambient Air Pollution and Mortality After Cardiac Transplantation.

BACKGROUND: Heart transplant recipients are at high risk for mortality, with traditional risk scores performing modestly in predicting post-transplant survival, underscoring the importance of as yet unidentified factors in determining prognosis. In this analysis, the association between PM2.5 exposure levels and survival after heart transplantation were investigated. OBJECTIVES: This study sought to study the association between PM2.5 exposure and mortality following heart transplantation. METHODS: On the basis of the zip code of residence, mortality data in patients who underwent heart transplantation (2004 to 2015) in the United Network for Organ Sharing (UNOS) database were linked with validated estimates of fine particulate matter concentrations (particles with diameter <2.5 µm [PM2.5]; 1 × 1-km grids) for each calendar year during which a UNOS cardiac transplant recipient was at risk for death. Cox proportional hazard models were used to estimate the relationship between exposure and overall mortality adjusting for recipient, donor, and neighborhood variables. RESULTS: A total of 21,800 patients with 86,713 patient-years of follow-up was included. Mean age at transplantation was 52.6 ± 12.6 years, 75% were male, 69% were white, and 39% had ischemic etiology of heart failure. Mean annual exposure to PM2.5 was 10.6 ± 2.3 µg/m3. At a median follow-up of 4.8 (95% confidence interval: 2.0 to 7.8) years, 5,208 patients (23.9%) had died. The estimated mortality hazard ratio, per 10 µg/m3 increment increase in annual PM2.5 exposure was 1.43 (95% confidence interval: 1.21 to 1.49). After adjusting for 30 recipient, donor, and neighborhood variables, the estimated mortality hazard ratio per 10 µg/m3 increment in annual exposure to PM2.5 was 1.26 (95% confidence interval: 1.11 to 1.43) relative increase in hazard of mortality. This association was consistent across subgroups. CONCLUSIONS: This study provides evidence linking air pollution with mortality after heart transplantation. These results suggest an important influence of a key environmental factor in outcomes following heart transplantation, and supports the need for further studies in this population.

Born to be Wise: a population registry data linkage protocol to assess the impact of modifiable early-life environmental exposures on the health and development of children.

INTRODUCTION: Deficiencies in childhood development is a major global issue and inequalities are large. The influence of environmental exposures on childhood development is currently insufficiently explored. This project will analyse the impact of various modifiable early life environmental exposures on different dimensions of childhood development. METHODS: Born to be Wise will study a Canadian cohort of approximately 34 000 children who have completed an early development test at the age of 5. Land use regression models of air pollution and spatially defined noise models will be linked to geocoded data on early development to analyse any harmful effects of these exposures. The potentially beneficial effect on early development of early life exposure to natural environments, as measured by fine-grained remote sensing data and various land use indexes, will also be explored. The project will use data linkages and analyse overall and age-specific impact, including variability depending on cumulative exposure by assigning time-weighted exposure estimates and by studying subsamples who have changed residence and exposure. Potentially moderating effects of natural environments on air pollution or noise exposures will be studied by mediation analyses. A matched case-control design will be applied to study moderating effects of natural environments on the association between low socioeconomic status and early development. The main statistical approach will be mixed effects models, applying a specific software to deal with multilevel random effects of nested data. Extensive confounding control will be achieved by including data on a range of detailed health and sociodemographic variables. ETHICS AND DISSEMINATION: The study protocol has been ethically approved by the Behavioural Research Ethics Board at the University of British Columbia. The findings will be published in peer-reviewed journals and presented at scholarly conferences. Through stakeholder engagement, the results will also reach policy and a broader audience.

Biomass Burning as a Source of Ambient Fine Particulate Air Pollution and Acute Myocardial Infarction.

BACKGROUND: Biomass burning is an important source of ambient fine particulate air pollution (PM2.5) in many regions of the world. METHODS: We conducted a time-stratified case-crossover study of ambient PM2.5 and hospital admissions for myocardial infarction (MI) in three regions of British Columbia, Canada. Daily hospital admission data were collected between 2008 and 2015 and PM2.5 data were collected from fixed site monitors. We used conditional logistic regression models to estimate odds ratios (ORs) describing the association between PM2.5 and the risk of hospital admission for MI. We used stratified analyses to evaluate effect modification by biomass burning as a source of ambient PM2.5 using the ratio of levoglucosan/PM2.5 mass concentrations. RESULTS: Each 5 µg/m increase in 3-day mean PM2.5 was associated with an increased risk of MI among elderly subjects (≥65 years; OR = 1.06, 95% CI: 1.03, 1.08); risk was not increased among younger subjects. Among the elderly, the strongest association occurred during colder periods (<6.44°C); when we stratified analyses by tertiles of monthly mean biomass contributions to PM2.5 during cold periods, ORs of 1.19 (95% CI: 1.04, 1.36), 1.08 (95% CI: 1.06, 1.09), and 1.04 (95% CI: 1.03, 1.06) were observed in the upper, middle, and lower tertiles (Ptrend = 0.003), respectively. CONCLUSION: Short-term changes in ambient PM2.5 were associated with an increased risk of MI among elderly subjects. During cold periods, increased biomass burning contributions to PM2.5 may modify its association with MI.

Linking the Canadian Community Health Survey and the Canadian Mortality Database: An enhanced data source for the study of mortality.

BACKGROUND: This study summarizes the linkage of the Canadian Community Health Survey (CCHS) and the Canadian Mortality Database (CMDB), which was performed to examine relationships between social determinants, health behaviours and mortality in the household population. DATA AND METHODS: The 2000/2001-to-2011 Canadian Community Health Surveys were linked to the 2000-to-2011 CMDB using probabilistic methods based on common identifiers (names, date of birth, postal code and sex) for eligible respondents (85%; n = 614,774). Mortality records from January 1, 2000 through December 31, 2011 for people aged 12 or older were eligible for linkage (n = 2.774 million). The linkage was enhanced with information from the Historical Tax Summary File. Quality assessment consisted of internal and external validation. Cox survival analysis (age-adjusted) was conducted to estimate hazard ratios (HRs) associated with selected health behaviours. RESULTS: Overall, 5.3% of eligible CCHS respondents linked to a mortality record; false positive and false negative rates were 0.04% and 2.43%, respectively. Linkage rates were higher among males (5.8%) and people aged 75 or older (20.2%), reflecting known mortality risks. Survival analyses confirmed elevated mortality risk associated with heavy (HR 2.36, CI 1.84, 2.89) and light smoking (HR 1.91, CI 1.52, 2.33), compared with not smoking; underweight and obesity, compared with normal and overweight; low fruit and vegetable consumption; and lack of physical activity. INTERPRETATION: Linking health behaviour information from the CCHS to mortality data from the CMDB allows for a greater understanding of modifiable determinants of mortality.

Ozone exposure and cardiovascular-related mortality in the Canadian Census Health and Environment Cohort (CANCHEC) by spatial synoptic classification zone.

Our objective is to analyse the association between long term ozone exposure and cardiovascular related mortality while accounting for climate, location, and socioeconomic factors. We assigned subjects with 16 years of follow-up in the Canadian Census Health and Environment Cohort (CanCHEC) to one of seven regions based on spatial synoptic classification (SSC) weather types and examined the interaction of exposure to both fine particulate matter (PM2.5) and ground level ozone and cause of death using survival analysis, while adjusting for socioeconomic characteristics and individual confounders. Correlations between ozone and PM2.5 varied across SSC zones from -0.02 to 0.7. Comparing zones using the most populated SSC zone as a reference, a 10 ppb increase in ozone exposure was associated with increases in hazard ratios (HRs) that ranged from 1.007 (95% CI 0.99, 1.015) to 1.03 (95% CI 1.02, 1.041) for cardiovascular disease, 1.013 (95% CI 0.996, 1.03) to 1.058 (95% CI 1.034, 1.082) for cerebrovascular disease, and 1.02 (95% CI 1.006, 1.034) for ischemic heart disease. HRs remained significant after adjustment for PM2.5. Long term exposure to ozone is related to an increased risk of mortality from cardiovascular and cerebrovascular diseases; the risk varies by location across Canada and is not attenuated by adjustment for PM2.5. This research shows that the SSC can be used to define geographic regions and it demonstrates the importance of accounting for that spatial variability when studying the long term health effects of air pollution.

Ambient PM2.5 and risk of emergency room visits for myocardial infarction: impact of regional PM2.5 oxidative potential: a case-crossover study.

BACKGROUND: Regional differences in the oxidative potential of fine particulate air pollution (PM2.5) may modify its impact on the risk of myocardial infarction. METHODS: A case-crossover study was conducted in 16 cities in Ontario, Canada to evaluate the impact of regional PM2.5 oxidative potential on the relationship between PM2.5 and emergency room visits for myocardial infarction. Daily air pollution and meteorological data were collected between 2004 and 2011 from provincial monitoring sites and regional estimates of glutathione (OP(GSH)) and ascorbate-related (OP(AA)) oxidative potential were determined using an acellular assay based on a synthetic respiratory tract lining fluid. Exposure variables for the combined oxidant capacity of NO2 and O3 were also examined using their sum (Ox) and a weighted average (Ox (wt)) based on their redox potentials. RESULTS: In total, 30,101 cases of myocardial infarction were included in the analysis. For regions above the 90(th) percentile of OP(GSH) each 5 µg/m(3) increase in same-day PM2.5 was associated with a 7.9 % (95 % CI: 4.1, 12) increased risk of myocardial infarction whereas a 4.1 % (95 % CI: 0.26, 8.0) increase was observed in regions above the 75(th) percentile and no association was observed below the 50(th) percentile (p-interaction = 0.026). A significant 3-way interaction was detected with the strongest associations between PM2.5 and myocardial infarction occurring in areas with high regional OP(GSH) and high Ox (wt) (p-interaction < 0.001). CONCLUSIONS: Regional PM2.5 oxidative potential may modify the impact of PM2.5 on the risk of myocardial infarction. The combined oxidant capacity of NO2 and O3 may magnify this effect.

Oxidative burden of fine particulate air pollution and risk of cause-specific mortality in the Canadian Census Health and Environment Cohort (CanCHEC).

BACKROUND: Fine particulate air pollution (PM2.5) is known to contribute to cardiorespiratory mortality but it is not clear how PM2.5 oxidative burden (i.e. the ability of PM2.5 to cause oxidative stress) may influence long-term mortality risk. METHODS: We examined the relationship between PM2.5 oxidative burden and cause-specific mortality in Ontario, Canada. Integrated PM2.5 samples were collected from 30 provincial monitoring sites between 2012 and 2013. The oxidative potential (% depletion/µg) of regional PM2.5 was measured as the ability of filter extracts to deplete antioxidants (glutathione and ascorbate) in a synthetic respiratory tract lining fluid. PM2.5oxidative burden was calculated as the product of PM2.5 mass concentrations and regional estimates of oxidative potential. In total, this study included 193,300 people who completed the Canadian long-form census in 1991 and who lived within 5km of a site where oxidative potential was measured. Deaths occurring between 1991 and 2009 were identified through record linkages and Cox proportional hazard models were used to estimate hazard ratios (and 95% confidence intervals) for interquartile changes in exposure adjusting for individual-level covariates and indirect-adjustment for smoking and obesity. RESULTS: Glutathione-related oxidative burden was associated with cause-specific mortality. For lung cancer specifically, this metric was associated with a 12% (95% CI: 5.0-19) increased risk of mortality whereas a 5.0% (95% CI: 0.1, 10) increase was observed for PM2.5. Indirect adjustment for smoking and obesity decreased the lung cancer hazard ratio for glutathione-related oxidative burden but it remained significantly elevated (HR=1.07, 95% CI: 1.005, 1.146). Ascorbate-related oxidative burden was not associated with mortality. CONCLUSIONS: Our findings suggest that glutathione-related oxidative burden may be more strongly associated with lung cancer mortality than PM2.5 mass concentrations.

Modelling risk factor information for linked census data: The case of smoking.

BACKGROUND: Statistics Canada has initiated a series of data linkages of Census of Population long form and health outcome data. These linked data lack risk factor information. This study assesses the feasibility of using statistical modelling techniques to assign smoking status to census respondents. DATA AND METHODS: The 2000/2001 Canadian Community Health Survey (CCHS) was used to develop age-/sex-specific predictive models to model smoking status based on variables available on the 1991 Census. The 2002/2003 CCHS was used to validate the modelled variable. Data from the 2002/2003 CCHS linked to data from the Hospital Morbidity Database (2001/2002 to 2004/2005) were used to evaluate the use of modelled versus self-reported smoking status on smoking-related hospitalizations. RESULTS: For the current daily smoker models, income, education, marital status, dwelling ownership and region of birth were significant predictors. For the never smoker models, marital status, dwelling ownership, Aboriginal identity and region of birth were significant predictors. Modelled current daily smoker status was associated with increased odds of smoking-related hospitalization, compared with being a never smoker, even when adjusting for covariates. INTERPRETATION: This study demonstrates the feasibility of using statistical modelling techniques to assign smoking status to census data, provided socio-economic and identity information is available.

Ambient particulate air pollution and acute lower respiratory infections: a systematic review and implications for estimating the global burden of disease.

Acute lower respiratory infections (ALRI) account for nearly one fifth of mortality in young children worldwide and have been associated with exposures to indoor and outdoor sources of combustion-derived air pollution. A systematic review was conducted to identify relevant articles on air pollution and ALRI in children. Using a Bayesian approach to meta-analysis, a summary estimate of 1.12 (1.03, 1.30) increased risk in ALRI occurrence per 10 µg/m3 increase in annual average PM2.5 concentration was derived from the longer-term (subchronic and chronic) effects studies. This analysis strengthens the evidence for a causal relationship between exposure to PM2.5 and the occurrence of ALRI and provides a basis for estimating the global attributable burden of mortality due to ALRI that is not influenced by the wide variation in regional case fatality rates. Most studies, however, have been conducted in settings with relatively low levels of PM2.5. Extrapolating their results to other, more polluted, regions will require a model that is informed by evidence from studies of the effects on ALRI of exposure to PM2.5 from other combustion sources, such as secondhand smoke and household solid fuel use.

Tracking national and regional spatial-temporal mortality risk associated with NO2 concentrations in Canada: a Bayesian hierarchical two-level model.

The association between daily variations in urban air quality and mortality has been well documented using time series statistical methods. This approach assumes a constant association over time. We develop a space-time dynamic model that relaxes this assumption, thus more directly examining the hypothesis that improvements in air quality translate into improvements in public health. We postulate a Bayesian hierarchical two-level model to estimate annual mortality risks at regional and national levels and to track both risk and heterogeneity of risk within and between regions over time. We illustrate our methods using daily nitrogen dioxide concentrations (NO2) and nonaccidental mortality data collected for 1984-2004 in 24 Canadian cities. Estimates of risk and heterogeneity are compared by cause of mortality (cardio-pulmonary [CP] versus non-CP) and season, respectively. Over the entire period, the NO2 risk for CP mortality was slightly lower but with a narrower credible interval than that for non-CP mortality, mainly due to an unusually low risk for a single year (1998). Warm season NO2 risk was higher than cold season risk for both CP and non-CP mortality. For 21 years overall there were no significant differences detected among the four regional NO2 risks. We found overall that there was no strong evidence for time trends in NO2 risk at national or regional levels. However, an increasing linear time trend in the annual between-region heterogeneities was detected, which suggests the differences in risk among the four regions are getting larger, and further studies are necessary to understand the increasing heterogeneity.

Exposure assessment for estimation of the global burden of disease attributable to outdoor air pollution.

Ambient air pollution is associated with numerous adverse health impacts. Previous assessments of global attributable disease burden have been limited to urban areas or by coarse spatial resolution of concentration estimates. Recent developments in remote sensing, global chemical-transport models, and improvements in coverage of surface measurements facilitate virtually complete spatially resolved global air pollutant concentration estimates. We combined these data to generate global estimates of long-term average ambient concentrations of fine particles (PM(2.5)) and ozone at 0.1° × 0.1° spatial resolution for 1990 and 2005. In 2005, 89% of the world's population lived in areas where the World Health Organization Air Quality Guideline of 10 µg/m(3) PM(2.5) (annual average) was exceeded. Globally, 32% of the population lived in areas exceeding the WHO Level 1 Interim Target of 35 µg/m(3), driven by high proportions in East (76%) and South (26%) Asia. The highest seasonal ozone levels were found in North and Latin America, Europe, South and East Asia, and parts of Africa. Between 1990 and 2005 a 6% increase in global population-weighted PM(2.5) and a 1% decrease in global population-weighted ozone concentrations was apparent, highlighted by increased concentrations in East, South, and Southeast Asia and decreases in North America and Europe. Combined with spatially resolved population distributions, these estimates expand the evaluation of the global health burden associated with outdoor air pollution.

Spatial analysis of air pollution and childhood asthma in Hamilton, Canada: comparing exposure methods in sensitive subgroups.

BACKGROUND: Variations in air pollution exposure within a community may be associated with asthma prevalence. However, studies conducted to date have produced inconsistent results, possibly due to errors in measurement of the exposures. METHODS: A standardized asthma survey was administered to children in grades one and eight in Hamilton, Canada, in 1994-95 (N approximately 1467). Exposure to air pollution was estimated in four ways: (1) distance from roadways; (2) interpolated surfaces for ozone, sulfur dioxide, particulate matter and nitrous oxides from seven to nine governmental monitoring stations; (3) a kriged nitrogen dioxide (NO2) surface based on a network of 100 passive NO2 monitors; and (4) a land use regression (LUR) model derived from the same monitoring network. Logistic regressions were used to test associations between asthma and air pollution, controlling for variables including neighbourhood income, dwelling value, state of housing, a deprivation index and smoking. RESULTS: There were no significant associations between any of the exposure estimates and asthma in the whole population, but large effects were detected the subgroup of children without hayfever (predominately in girls). The most robust effects were observed for the association of asthma without hayfever and NO2LUR OR = 1.86 (95%CI, 1.59-2.16) in all girls and OR = 2.98 (95%CI, 0.98-9.06) for older girls, over an interquartile range increase and controlling for confounders. CONCLUSION: Our findings indicate that traffic-related pollutants, such as NO2, are associated with asthma without overt evidence of other atopic disorders among female children living in a medium-sized Canadian city. The effects were sensitive to the method of exposure estimation. More refined exposure models produced the most robust associations.

Acute effects of ambient particulate matter on mortality in Europe and North America: results from the APHENA study.

BACKGROUND: THE APHENA (AIR POLLUTION AND HEALTH: A Combined European and North American Approach) study is a collaborative analysis of multicity time-series data on the effect of air pollution on population health, bringing together data from the European APHEA (Air Pollution and Health: A European Approach) and U.S. NMMAPS (National Morbidity, Mortality and Air Pollution Study) projects, along with Canadian data. OBJECTIVES: The main objective of APHENA was to assess the coherence of the findings of the multicity studies carried out in Europe and North America, when analyzed with a common protocol, and to explore sources of possible heterogeneity. We present APHENA results on the effects of particulate matter (PM) < or = 10 microm in aerodynamic diameter (PM(10)) on the daily number of deaths for all ages and for those < 75 and > or = 75 years of age. We explored the impact of potential environmental and socioeconomic factors that may modify this association. METHODS: In the first stage of a two-stage analysis, we used Poisson regression models, with natural and penalized splines, to adjust for seasonality, with various degrees of freedom. In the second stage, we used meta-regression approaches to combine time-series results across cites and to assess effect modification by selected ecologic covariates. RESULTS: Air pollution risk estimates were relatively robust to different modeling approaches. Risk estimates from Europe and United States were similar, but those from Canada were substantially higher. The combined effect of PM(10) on all-cause mortality across all ages for cities with daily air pollution data ranged from 0.2% to 0.6% for a 10-microg/m(3) increase in ambient PM(10) concentration. Effect modification by other pollutants and climatic variables differed in Europe and the United States. In both of these regions, a higher proportion of older people and higher unemployment were associated with increased air pollution risk. CONCLUSIONS: Estimates of the increased mortality associated with PM air pollution based on the APHENA study were generally comparable with results of previous reports. Overall, risk estimates were similar in Europe and in the United States but higher in Canada. However, PM(10) effect modification patterns were somewhat different in Europe and the United States.

Testing the harvesting hypothesis by time-domain regression analysis. I: baseline analysis.

Although the association between air pollution and daily mortality is well established, the mechanisms by which air pollution results in excess mortality are not yet well understood. In particular, there exists debate over whether air pollution has a direct effect on mortality in the general population or simply shortens the life span of frail individuals, a hypothesis referred to as "harvesting." The goal of this investigation is to test the harvesting hypothesis using the time-domain regression method of Dominici et al. (2003a). We conducted simulations based on a two-compartment model that divides the population into a larger group of healthy individuals and a frail subpopulation. Death from air pollution is assumed to take place in two steps, by first moving from healthy population to the frail pool, then death with probability related to the level of air pollution. Using time-domain analysis, we seek to identify data patterns that would be characteristic of harvesting under different scenarios. For a pure harvesting model, time-domain analysis indicates that mortality is associated with a short-term air pollution episode of less than 2 d if the mean residency time in the frail pool is short. If both entrants and deaths depend on the level of air pollution and the rates of entry to and exit from the frail pool are about the same, the log relative risk estimates are essentially unchanged at all time scales. If pollution affects mortality in the frail pool more than entrants, larger effects will occur at shorter time scales.

Testing the harvesting hypothesis by time-domain regression analysis. II: covariate effects.

This article extends the previous work of Fung et al. (2004) investigating the ability of the time-scale log-linear regression model, proposed by Dominici et al. (2003), to detect mortality displacement (sometimes known as harvesting) in time-series data relating air pollution to excess mortality. We conducted a simulation study based on two different compartment models of the death process: pure frailty model and mixed frailty model. We assume that nonaccidental death only affects frail population in a pure frailty model and affects both frail people and other individuals in the mixed frailty model. With a pure frailty model and a moderate-size pollution effect, we identified a characteristic mortality displacement pattern in the different time-scale coefficients of log relative risk. However, once a covariate like temperature was introduced into the model, such a mortality displacement pattern disappeared. Furthermore, a false mortality displacement effect was present in the incorrectly specified model, when temperature was not taken into account. We believe that time-scale regression has limited value for detecting mortality displacement in time-series data.

Comparison of time series and case-crossover analyses of air pollution and hospital admission data.

BACKGROUND: Time series analysis is the most commonly used technique for assessing the association between counts of health events over time and exposure to ambient air pollution. Recently, case-crossover analysis has been proposed as an alternative analytical approach. While each technique has its own advantages and disadvantages, there remains considerable uncertainty as to which statistical methodology is preferable for evaluating data of this type. METHODS: The objective of this paper is to evaluate the performance of different variations of these two procedures using computer simulation. Hospital admission data were generated under realistic models with known parameters permitting estimates based on time series and case-crossover analyses to be compared with these known values. RESULTS: While accurate estimates can be achieved with both methods, both methods require some decisions to be made by the researcher during the course of the analysis. With time series analysis, it is necessary to choose the time span in the LOESS smoothing process, or degrees of freedom when using natural cubic splines. For case-crossover studies using either uni- or bi-directional control selection strategies, the choice of time intervals needs to be made. CONCLUSIONS: We prefer the times series approach because the best estimates of risk that can be obtained with time series analysis are more precise than the best estimates based on case-crossover analysis.