Ambient air pollution and adult asthma incidence in six European cohorts (ESCAPE).

BACKGROUND: Short-term exposure to air pollution has adverse effects among patients with asthma, but whether long-term exposure to air pollution is a cause of adult-onset asthma is unclear. OBJECTIVE: We aimed to investigate the association between air pollution and adult onset asthma. METHODS: Asthma incidence was prospectively assessed in six European cohorts. Exposures studied were annual average concentrations at home addresses for nitrogen oxides assessed for 23,704 participants (including 1,257 incident cases) and particulate matter (PM) assessed for 17,909 participants through ESCAPE land-use regression models and traffic exposure indicators. Meta-analyses of cohort-specific logistic regression on asthma incidence were performed. Models were adjusted for age, sex, overweight, education, and smoking and included city/area within each cohort as a random effect. RESULTS: In this longitudinal analysis, asthma incidence was positively, but not significantly, associated with all exposure metrics, except for PMcoarse. Positive associations of borderline significance were observed for nitrogen dioxide [adjusted odds ratio (OR) = 1.10; 95% CI: 0.99, 1.21 per 10 µg/m3; p = 0.10] and nitrogen oxides (adjusted OR = 1.04; 95% CI: 0.99, 1.08 per 20 µg/m3; p = 0.08). Nonsignificant positive associations were estimated for PM10 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 10 µg/m3), PM2.5 (adjusted OR = 1.04; 95% CI: 0.88, 1.23 per 5 µg/m3), PM2.5absorbance (adjusted OR = 1.06; 95% CI: 0.95, 1.19 per 10-5/m), traffic load (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 4 million vehicles × meters/day on major roads in a 100-m buffer), and traffic intensity (adjusted OR = 1.10; 95% CI: 0.93, 1.30 per 5,000 vehicles/day on the nearest road). A nonsignificant negative association was estimated for PMcoarse (adjusted OR = 0.98; 95% CI: 0.87, 1.14 per 5 µg/m3). CONCLUSIONS: Results suggest a deleterious effect of ambient air pollution on asthma incidence in adults. Further research with improved personal-level exposure assessment (vs. residential exposure assessment only) and phenotypic characterization is needed.

Development of land use regression models for elemental, organic carbon, PAH, and hopanes/steranes in 10 ESCAPE/TRANSPHORM European study areas.

Land use regression (LUR) models have been used to model concentrations of mainly traffic-related air pollutants (nitrogen oxides (NOx), particulate matter (PM) mass or absorbance). Few LUR models are published of PM composition, whereas the interest in health effects related to particle composition is increasing. The aim of our study was to evaluate LUR models of polycyclic aromatic hydrocarbons (PAH), hopanes/steranes, and elemental and organic carbon (EC/OC) content of PM2.5. In 10 European study areas, PAH, hopanes/steranes, and EC/OC concentrations were measured at 16-40 sites per study area. LUR models for each study area were developed on the basis of annual average concentrations and predictor variables including traffic, population, industry, natural land obtained from geographic information systems. The highest median model explained variance (R(2)) was found for EC - 84%. The median R(2) was 51% for OC, 67% for benzo[a]pyrene, and 38% for sum of hopanes/steranes, with large variability between study areas. Traffic predictors were included in most models. Population and natural land were included frequently as additional predictors. The moderate to high explained variance of LUR models and the overall moderate correlation with PM2.5 model predictions support the application of especially the OC and PAH models in epidemiological studies.

Cross-sectional associations between air pollution and chronic bronchitis: an ESCAPE meta-analysis across five cohorts.

BACKGROUND: This study aimed to assess associations of outdoor air pollution on prevalence of chronic bronchitis symptoms in adults in five cohort studies (Asthma-E3N, ECRHS, NSHD, SALIA, SAPALDIA) participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE) project. METHODS: Annual average particulate matter (PM(10), PM(2.5), PM(absorbance), PM(coarse)), NO(2), nitrogen oxides (NO(x)) and road traffic measures modelled from ESCAPE measurement campaigns 2008-2011 were assigned to home address at most recent assessments (1998-2011). Symptoms examined were chronic bronchitis (cough and phlegm for ≥3 months of the year for ≥2 years), chronic cough (with/without phlegm) and chronic phlegm (with/without cough). Cohort-specific cross-sectional multivariable logistic regression analyses were conducted using common confounder sets (age, sex, smoking, interview season, education), followed by meta-analysis. RESULTS: 15 279 and 10 537 participants respectively were included in the main NO(2) and PM analyses at assessments in 1998-2011. Overall, there were no statistically significant associations with any air pollutant or traffic exposure. Sensitivity analyses including in asthmatics only, females only or using back-extrapolated NO(2) and PM10 for assessments in 1985-2002 (ECRHS, NSHD, SALIA, SAPALDIA) did not alter conclusions. In never-smokers, all associations were positive, but reached statistical significance only for chronic phlegm with PM(coarse) OR 1.31 (1.05 to 1.64) per 5 µg/m(3) increase and PM(10) with similar effect size. Sensitivity analyses of older cohorts showed increased risk of chronic cough with PM(2.5abs) (black carbon) exposures. CONCLUSIONS: Results do not show consistent associations between chronic bronchitis symptoms and current traffic-related air pollution in adult European populations.

Performance of multi-city land use regression models for nitrogen dioxide and fine particles.

BACKGROUND: Land use regression (LUR) models have been developed mostly to explain intraurban variations in air pollution based on often small local monitoring campaigns. Transferability of LUR models from city to city has been investigated, but little is known about the performance of models based on large numbers of monitoring sites covering a large area. OBJECTIVES: We aimed to develop European and regional LUR models and to examine their transferability to areas not used for model development. METHODS: We evaluated LUR models for nitrogen dioxide (NO2) and particulate matter (PM; PM2.5, PM2.5 absorbance) by combining standardized measurement data from 17 (PM) and 23 (NO2) ESCAPE (European Study of Cohorts for Air Pollution Effects) study areas across 14 European countries for PM and NO2. Models were evaluated with cross-validation (CV) and hold-out validation (HV). We investigated the transferability of the models by successively excluding each study area from model building. RESULTS: The European model explained 56% of the concentration variability across all sites for NO2, 86% for PM2.5, and 70% for PM2.5 absorbance. The HV R2s were only slightly lower than the model R2 (NO2, 54%; PM2.5, 80%; PM2.5 absorbance, 70%). The European NO2, PM2.5, and PM2.5 absorbance models explained a median of 59%, 48%, and 70% of within-area variability in individual areas. The transferred models predicted a modest-to-large fraction of variability in areas that were excluded from model building (median R2: NO2, 59%; PM2.5, 42%; PM2.5 absorbance, 67%). CONCLUSIONS: Using a large data set from 23 European study areas, we were able to develop LUR models for NO2 and PM metrics that predicted measurements made at independent sites and areas reasonably well. This finding is useful for assessing exposure in health studies conducted in areas where no measurements were conducted.

Association of ambient air pollution with the prevalence and incidence of COPD.

The role of air pollution in chronic obstructive pulmonary disease (COPD) remains uncertain. The aim was to assess the impact of chronic exposure to air pollution on COPD in four cohorts using the standardised ESCAPE exposure estimates. Annual average particulate matter (PM), nitrogen oxides (NOx) and road traffic exposure were assigned to home addresses using land-use regression models. COPD was defined by NHANES reference equation (forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) less than the lower limit of normal) and the Global Initiative for Chronic Obstructive Lung Disease criterion (FEV1/FVC <0.70) and categorised by severity in non-asthmatics. We included 6550 subjects with assigned NOx and 3692 with PM measures. COPD was not associated with NO2 or PM10 in any individual cohort. In meta-analyses only NO2, NOx, PM10 and the traffic indicators were positively, although not significantly, associated with COPD. The only statistically significant associations were seen in females (COPD prevalence using GOLD: OR 1.57, 95% CI 1.11-2.23; and incidence: OR 1.79, 95% CI 1.21-2.68). None of the principal results were statistically significant, the weak positive associations of exposure with COPD and the significant subgroup findings need to be evaluated in further well standardised cohorts followed up for longer time, and with time-matched exposure assignments.

Ecological study on hospitalizations for cancer, cardiovascular, and respiratory diseases in the industrial area of Etang-de-Berre in the South of France.

The Etang-de-Berre area is a large industrialized area in the South of France, exposing 300,000 inhabitants to the plumes of its industries. The possible associated health risks are of the highest concern to the population, who asked for studies investigating their health status. A geographical ecological study based on standardized hospitalizations ratios for cancer, cardiovascular, and respiratory diseases was carried out over the 2004-2007 period. Exposure to air pollution was assessed using dispersion models coupled with a geographic information system to estimate an annual mean concentration of sulfur dioxide (SO2) for each district. Results showed an excess risk of hospitalization for myocardial infarction in women living in districts with medium or high SO2 exposure, respectively, 38% [CI 95% 4 : 83] and 54% [14 : 110] greater than women living in districts at the reference level exposure. A 26% [2 : 57] excess risk of hospitalization for myocardial infarction was also observed in men living in districts with high SO2 levels. No excess risk of hospitalization for respiratory diseases or for cancer was observed, except for acute leukemia in men only. Results illustrate the impact of industrial air pollution on the cardiovascular system and call for an improvement of the air quality in the area.

Associations between fine and coarse particles and mortality in Mediterranean cities: results from the MED-PARTICLES project.

BACKGROUND: Few studies have investigated the independent health effects of different size fractions of particulate matter (PM) in multiple locations, especially in Europe. OBJECTIVES: We estimated the short-term effects of PM with aerodynamic diameter ≤ 10 µm (PM10), ≤ 2.5 µm (PM2.5), and between 2.5 and 10 µm (PM2.5-10) on all-cause, cardiovascular, and respiratory mortality in 10 European Mediterranean metropolitan areas within the MED-PARTICLES project. METHODS: We analyzed data from each city using Poisson regression models, and combined city-specific estimates to derive overall effect estimates. We evaluated the sensitivity of our estimates to co-pollutant exposures and city-specific model choice, and investigated effect modification by age, sex, and season. We applied distributed lag and threshold models to investigate temporal patterns of associations. RESULTS: A 10-µg/m3 increase in PM2.5 was associated with a 0.55% (95% CI: 0.27, 0.84%) increase in all-cause mortality (0-1 day cumulative lag), and a 1.91% increase (95% CI: 0.71, 3.12%) in respiratory mortality (0-5 day lag). In general, associations were stronger for cardiovascular and respiratory mortality than all-cause mortality, during warm versus cold months, and among those ≥ 75 versus < 75 years of age. Associations with PM2.5-10 were positive but not statistically significant in most analyses, whereas associations with PM10 seemed to be driven by PM2.5. CONCLUSIONS: We found evidence of adverse effects of PM2.5 on mortality outcomes in the European Mediterranean region. Associations with PM2.5-10 were positive but smaller in magnitude. Associations were stronger for respiratory mortality when cumulative exposures were lagged over 0-5 days, and were modified by season and age.

Development of land use regression models for particle composition in twenty study areas in Europe.

Land Use Regression (LUR) models have been used to describe and model spatial variability of annual mean concentrations of traffic related pollutants such as nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM). No models have yet been published of elemental composition. As part of the ESCAPE project, we measured the elemental composition in both the PM10 and PM2.5 fraction sizes at 20 sites in each of 20 study areas across Europe. LUR models for eight a priori selected elements (copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)) were developed. Good models were developed for Cu, Fe, and Zn in both fractions (PM10 and PM2.5) explaining on average between 67 and 79% of the concentration variance (R(2)) with a large variability between areas. Traffic variables were the dominant predictors, reflecting nontailpipe emissions. Models for V and S in the PM10 and PM2.5 fractions and Si, Ni, and K in the PM10 fraction performed moderately with R(2) ranging from 50 to 61%. Si, NI, and K models for PM2.5 performed poorest with R(2) under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE.

Chronic burden of near-roadway traffic pollution in 10 European cities (APHEKOM network).

Recent epidemiological research suggests that near road traffic-related pollution may cause chronic disease, as well as exacerbation of related pathologies, implying that the entire "chronic disease progression" should be attributed to air pollution, no matter what the proximate cause was. We estimated the burden of childhood asthma attributable to air pollution in 10 European cities by calculating the number of cases of 1) asthma caused by near road traffic-related pollution, and 2) acute asthma events related to urban air pollution levels. We then expanded our approach to include coronary heart diseases in adults. Derivation of attributable cases required combining concentration-response function between exposures and the respective health outcome of interest (obtained from published literature), an estimate of the distribution of selected exposures in the target population, and information about the frequency of the assessed morbidities. Exposure to roads with high vehicle traffic, a proxy for near road traffic-related pollution, accounted for 14% of all asthma cases. When a causal relationship between near road traffic-related pollution and asthma is assumed, 15% of all episodes of asthma symptoms were attributable to air pollution. Without this assumption, only 2% of asthma symptoms were attributable to air pollution. Similar patterns were found for coronary heart diseases in older adults. Pollutants along busy roads are responsible for a large and preventable share of chronic disease and related acute exacerbations in European urban areas.

Evaluation of land use regression models for NO2 and particulate matter in 20 European study areas: the ESCAPE project.

Land use regression models (LUR) frequently use leave-one-out-cross-validation (LOOCV) to assess model fit, but recent studies suggested that this may overestimate predictive ability in independent data sets. Our aim was to evaluate LUR models for nitrogen dioxide (NO2) and particulate matter (PM) components exploiting the high correlation between concentrations of PM metrics and NO2. LUR models have been developed for NO2, PM2.5 absorbance, and copper (Cu) in PM10 based on 20 sites in each of the 20 study areas of the ESCAPE project. Models were evaluated with LOOCV and "hold-out evaluation (HEV)" using the correlation of predicted NO2 or PM concentrations with measured NO2 concentrations at the 20 additional NO2 sites in each area. For NO2, PM2.5 absorbance and PM10 Cu, the median LOOCV R(2)s were 0.83, 0.81, and 0.76 whereas the median HEV R(2) were 0.52, 0.44, and 0.40. There was a positive association between the LOOCV R(2) and HEV R(2) for PM2.5 absorbance and PM10 Cu. Our results confirm that the predictive ability of LUR models based on relatively small training sets is overestimated by the LOOCV R(2)s. Nevertheless, in most areas LUR models still explained a substantial fraction of the variation of concentrations measured at independent sites.

A simple indicator to rapidly assess the short-term impact of heat waves on mortality within the French heat warning system.

We propose a simple method to provide a rapid and robust estimate of the short-term impacts of heat waves on mortality, to be used for communication within a heat warning system. The excess mortality during a heat wave is defined as the difference between the observed mortality over the period and the observed mortality over the same period during the N preceding years. This method was tested on 19 French cities between 1973 and 2007. In six cities, we compared the excess mortality to that obtained using a modelling of the temperature-mortality relationship. There was a good agreement between the excess mortalities estimated by the simple indicator and by the models. Major differences were observed during the most extreme heat waves, in 1983 and 2003, and after the implementation of the heat prevention plan in 2006. Excluding these events, the mean difference between the estimates obtained by the two methods was of 13 deaths [1:45]. A comparison of mortality with the previous years provides a simple estimate of the mortality impact of heat waves. It can be used to provide early and reliable information to stakeholders of the heat prevention plan, and to select heat waves that should be further investigated.

Development of Land Use Regression models for PM(2.5), PM(2.5) absorbance, PM(10) and PM(coarse) in 20 European study areas; results of the ESCAPE project.

Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coarse) were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R(2)) was 71% for PM(2.5) (range across study areas 35-94%). Model R(2) was higher for PM(2.5) absorbance (median 89%, range 56-97%) and lower for PM(coarse) (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R(2) was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R(2) results were on average 8-11% lower than model R(2). Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.

Mapping of inflammatory bowel disease in northern France: spatial variations and relation to affluence.

BACKGROUND: Geographic variations in the incidence of inflammatory bowel disease (IBD) may reflect variations in the distribution of environmental etiologic factors. We assessed spatial variation in the incidence of IBD in northern France and analyzed its association with a deprivation index. METHODS: All cases of IBD included in the EPIMAD registry between 1990 and 2003 were extracted. The standardized incidence ratio (SIR) was calculated for each canton in the region. The association between incidence and deprivation was assessed using the Townsend deprivation index. RESULTS: The mean annual incidence rates of Crohn's disease (CD) and ulcerative colitis (UC) were 6.2 x 10(-5) and 3.8 x 10(-5), respectively. The mean cumulative numbers of cases by canton were 18.4 (1-183) for CD and 11.3 (0-148) for UC. For both CD and UC, mapping depicted spatial heterogeneity in the SIR with spatial autocorrelation. A high relative risk (RR) of CD was observed in mainly rural and periurban cantons of the region. For UC, a high RR was found in cantons of the south and the center of Pas-de-Calais. No significant correlation was observed between spatial variations in IBD and deprivation. CONCLUSIONS: The incidence of IBD is associated with spatial heterogeneity in northern France. The noteworthy predominance of CD in agricultural areas warrants further investigations.

Short term effects of air pollution on hospitalizations for cardiovascular diseases in eight French cities: the PSAS program.

INTRODUCTION: Short term associations between air pollution indicators and hospitalizations for cardiovascular diseases have been suggested by epidemiological and clinical studies. The present study aims at estimating the association between particles with diameter <10 microm (PM(10)), nitrogen dioxide (NO(2)) and ozone and hospitalizations for cardiovascular diseases in eight French cities during the 1998-2003 period. METHODS: The daily number of hospitalizations in each city was extracted from the French hospital information system (PMSI) for cardiovascular diseases, cardiac diseases, ischemic heart diseases and stroke. Excess relative risks (ERRs) of hospitalization associated with a 10 microg/m(3) increase in pollutant levels were estimated in each city by fitting a Poisson regression model, controlling for well-known confounding factors and temporal trends. City-specific results were then combined by inverse variance weighting. RESULTS: Daily number of hospitalizations for cardiovascular diseases was associated with PM(10) levels (for a 10 microg/m(3) increase, ERR=0.8%, 95% CI: [0.2, 1.5]), with NO(2) (1.1%, [0.6, 1.6]) but not with ozone (0.1% [-0.2%, 0.5%]). Associations were stronger in people aged 65 years and over, and when only hospitalizations for ischemic heart diseases were considered. No association was found between strokes and air pollution levels. DISCUSSION: Our study suggests that the ambient levels of air pollutants currently experienced in the eight French cities, which are close to European air quality guidelines, are yet linked to a short term increase of hospitalizations for cardiovascular diseases. These results are consistent with epidemiological and toxicological data on the cardiovascular effects of air pollution.

Performance of several decision support tools for determining the need for systematic screening of childhood lead poisoning around industrial sites.

BACKGROUND: Living around industrial sites may expose young children to lead and cause elevated blood lead levels (BLLs). Systematic screening for childhood lead poisoning is necessarily invasive but may be appropriate, depending on children's exposure levels. Our objective was to assess the performance of several decision support tools for determining the need for systematic BLL screening in children around industrial sites. METHOD: We used several exposure models to predict BLLs: the pharmacokinetic model IEUBK, the InVS dose model, and an empirical relation (Lewin, 1999) between soil concentrations and BLLs. We tested the BLLs (percentage of children with a BLL >100 micro g/l) that they predicted as well as threshold levels of soil pollution (200, 400, 500 ppm) for 71 situations for which the literature reports both environmental soil concentrations and BLLs in children aged 0-6 years. The tools' performance (sensitivity and specificity) was assessed by the rate of 'correct' (mass screening or not) decisions, judged retrospectively on the basis of measured BLLs, for different tolerated percentages of children with elevated BLLs. RESULTS: Decision support systems based on soil pollution levels were not adequately protective. The IEUBK and (updated) InVS mechanistic exposure models were the most effective in this setting. CONCLUSION: Exposure models may provide decision support if sufficient data about environmental contamination and dietary intake are available. Absolute performance measurement nonetheless remains difficult, in view of the limitations of the input data.

The relation between temperature, ozone, and mortality in nine French cities during the heat wave of 2003.

BACKGROUND: During August 2003, record high temperatures were observed across Europe, and France was the country most affected. During this period, elevated ozone concentrations were measured all over the country. Questions were raised concerning the contribution of O3 to the health impact of the summer 2003 heat wave. METHODS: We used a time-series design to analyze short-term effects of temperature and O3 pollution on mortality. Counts of deaths were regressed on temperatures and O3 levels, controlling for possible confounders: long-term trends, season, influenza outbreaks, day of the week, and bank holiday effects. For comparison with previous results of the nine cities, we calculated pooled excess risk using a random effect approach and an empirical Bayes approach. FINDINGS: For the nine cities, the excess risk of death is significant (1.01% ; 95% confidence interval, 0.58-1.44) for an increase of 10 microg/m3 in O3 level. For the 3-17 August 2003 period, the excess risk of deaths linked to O3 and temperatures together ranged from 10.6% in Le Havre to 174.7% in Paris. When we compared the relative contributions of O3 and temperature to this joint excess risk, the contribution of O3 varied according to the city, ranging from 2.5% in Bordeaux to 85.3% in Toulouse. INTERPRETATION: We observed heterogeneity among the nine cities not only for the joint effect of O3 and temperatures, but also for the relative contribution of each factor. These results confirmed that in urban areas O3 levels have a non-negligible impact in terms of public health.

Influence of set-up conditions of exposure indicators on the estimate of short-term associations between urban pollution and mortality.

In the past few years many studies on air pollution and health based on time series have been carried out. Yet, this approach does not assess exposure to air pollution at an individual level but it is based on ambient concentrations measured by air quality monitoring networks. Questions on the estimates of exposure to pollutants have been raised, in particular the fact that background measuring stations only have been considered in the set up of pollution indicators. To assess the impact of exposure indicator characteristics on the results of time series analysis, two series (black smoke and sulfur dioxide, respectively) of exposure indicators to urban air pollution were set up taking into account a growing part of proximity measures (industrial sources) available in the studied urban area (Le Havre, France). For each pollutant, indicators distributions were almost similar, especially for black smoke. Whatever the pollutant, the most obvious heterogeneity could be observed between the 100% background indicator and the indicator including the arithmetic mean for all the stations (50% background stations and 50% proximity stations). Then the sensitivity of the associations between mortality and air pollution to these indicators was studied. These indicators did not show statistically significant differences in the estimated excess risk. Yet, confidence intervals were more statistically significant as the contribution of proximity stations was more substantial, in particular for SO2. To conclude, the use of proximity measurements did not influence dramatically on the mean estimates of the association between air pollution and mortality indicators in Le Havre. Therefore it does not seem relevant to include the data provided by the proximity stations in the urban exposure indicators within the context of the epidemiology monitoring system.

Impact of the 2003 heatwave on all-cause mortality in 9 French cities.

BACKGROUND: A heatwave occurred in France in August 2003, with an accompanying excess of all-cause mortality. This study quantifies this excess mortality and investigates a possible harvesting effect in the few weeks after the heatwave. METHODS: A time-series study using a Poisson regression model with regression splines to control for nonlinear confounders was used to analyze the correlation between heatwave variable and mortality in 9 French cities. RESULTS: After controlling for long-term and seasonal time trends and the usual effects of temperature and air pollution, we estimated that 3,096 extra deaths resulted from the heatwave. The maximum daily relative risk of mortality during the heatwave (compared with expected deaths at that time of year) ranged from 1.16 in Le Havre to 5.00 in Paris. There was little evidence of mortality displacement in the few weeks after the heatwave, with an estimated deficit of 253 deaths at the end of the period. CONCLUSIONS: The heatwave in France during August 2003 was associated with a large increase in the number of deaths. The impact estimated using a time-series design was consistent with crude previous estimates of the impact of the heatwave. This finding suggests that neither air pollution nor long-term and seasonal trends confounded previous estimates. There was no evidence to suggest that the extras deaths associated with the heatwave were simply brought forward in time.