Short-term effects of particulate air pollution on cardiovascular diseases in eight European cities.

STUDY OBJECTIVE: As part of the APHEA project this study examined the association between airborne particles and hospital admissions for cardiac causes (ICD9 390-429) in eight European cities (Barcelona, Birmingham, London, Milan, the Netherlands, Paris, Rome, and Stockholm). All admissions were studied, as well as admissions stratified by age. The association for ischaemic heart disease (ICD9 410-413) and stroke (ICD9 430-438) was also studied, also stratified by age. DESIGN: Autoregressive Poisson models were used that controlled for long term trend, season, influenza epidemics, and meteorology to assess the short-term effects of particles in each city. The study also examined confounding by other pollutants. City specific results were pooled in a second stage regression to obtain more stable estimates and examine the sources of heterogeneity. MAIN RESULTS: The pooled percentage increases associated with a 10 micro g/m(3) increase in PM(10) and black smoke were respectively 0.5% (95% CI: 0.2 to 0.8) and 1.1% (95% CI: 0.4 to 1.8) for cardiac admissions of all ages, 0.7% (95% CI: 0.4 to 1.0) and 1.3% (95% CI: 0.4 to 2.2) for cardiac admissions over 65 years, and, 0.8% (95% CI: 0.3 to 1.2) and 1.1% (95% CI: 0.7 to 1.5) for ischaemic heart disease over 65 years. The effect of PM(10) was little changed by control for ozone or SO(2), but was substantially reduced (CO) or eliminated (NO(2)) by control for other traffic related pollutants. The effect of black smoke remained practically unchanged controlling for CO and only somewhat reduced controlling for NO(2). CONCLUSIONS: These effects of particulate air pollution on cardiac admissions suggest the primary effect is likely to be mainly attributable to diesel exhaust. Results for ischaemic heart disease below 65 years and for stroke over 65 years were inconclusive.

Acute effects of particulate air pollution on respiratory admissions: results from APHEA 2 project. Air Pollution and Health: a European Approach.

The APHEA 2 project investigated short-term health effects of particles in eight European cities. In each city associations between particles with an aerodynamic diameter of less than 10 microm (PM(10)) and black smoke and daily counts of emergency hospital admissions for asthma (0-14 and 15-64 yr), chronic obstructive pulmonary disease (COPD), and all-respiratory disease (65+ yr) controlling for environmental factors and temporal patterns were investigated. Summary PM(10) effect estimates (percentage change in mean number of daily admissions per 10 microg/m(3) increase) were asthma (0-14 yr) 1.2% (95% CI: 0.2, 2.3), asthma (15-64 yr) 1.1% (0.3, 1.8), and COPD plus asthma and all-respiratory (65+ yr) 1.0% (0.4, 1.5) and 0.9% (0.6, 1.3). The combined estimates for Black Smoke tended to be smaller and less precisely estimated than for PM(10). Variability in the sizes of the PM(10) effect estimates between cities was also investigated. In the 65+ groups PM(10) estimates were positively associated with annual mean concentrations of ozone in the cities. For asthma admissions (0-14 yr) a number of city-specific factors, including smoking prevalence, explained some of their variability. This study confirms that particle concentrations in European cities are positively associated with increased numbers of admissions for respiratory diseases and that some of the variation in PM(10) effect estimates between cities can be explained by city characteristics.

Confounding and effect modification in the short-term effects of ambient particles on total mortality: results from 29 European cities within the APHEA2 project.

We present the results of the Air Pollution and Health: A European Approach 2 (APHEA2) project on short-term effects of ambient particles on mortality with emphasis on effect modification. We used daily measurements for particulate matter less than 10 microm in aerodynamic diameter (PM10) and/or black smoke from 29 European cities. We considered confounding from other pollutants as well as meteorologic and chronologic variables. We investigated several variables describing the cities' pollution, climate, population, and geography as potential effect modifiers. For the individual city analysis, generalized additive models extending Poisson regression, using a smoother to control for seasonal patterns, were applied. To provide quantitative summaries of the results and explain remaining heterogeneity, we applied second-stage regression models. The estimated increase in the daily number of deaths for all ages for a 10 microg/m3 increase in daily PM10 or black smoke concentrations was 0.6% [95% confidence interval (CI) = 0.4-0.8%], whereas for the elderly it was slightly higher. We found important effect modification for several of the variables studied. Thus, in a city with low average NO2, the estimated increase in daily mortality for an increase of 10 microg/m3 in PM10 was 0.19 (95% CI = 0.00-0.41), whereas in a city with high average NO2 it was 0.80% (95% CI = 0.67-0.93%); in a relatively cold climate the corresponding effect was 0.29% (95% CI = 0.16-0.42), whereas in a warm climate it was 0.82% (95% CI = 0.69-0.96); in a city with low standardized mortality rate it was 0.80% (95% CI = 0.65-0.95%), and in one with a high rate it was 0.43% (95% CI = 0.24-0.62). Our results confirm those previously reported on the effects of ambient particles on mortality. Furthermore, they show that the heterogeneity found in the effect parameters among cities reflects real effect modification, which is explained by specific city characteristics.

[Surveillance of short-term effects of urban air pollution on mortality. Results of a feasibility study in 9 French cities]. / Surveillance des effets à court terme de la pollution atmosphérique sur la mortalité en milieu urbain. Résultats d'une étude de faisabilité dans 9 villes françaises.

BACKGROUND: This study aims at quantifying air pollution effects on mortality and at evaluating the feasibility of a standardized epidemiological surveillance system of air pollution in 9 French cities. METHODS: Data collection and analysis followed a standardized protocol. Data pollution depended on the development of local air quality surveillance networks (number of indicators, number of stations.). The Generalised Additive Models (GAM) were used to quantify the association between air pollution and mortality. RESULTS: In the 9 studied areas, associations between all causes, cardiovascular and respiratory mortality, and air pollution indicators were observed. These associations were linear without threshold. Depending on the pollutants, excess in mortality related to an interquartile increase in acid-particulate pollution varied between 0.3 and 3.5% for total mortality, 0.5 and 6.3% for cardiovascular mortality, and between 0.1 and 12% for respiratory mortality. Photochemical air pollution varied between 0.4 and 7.3% for total mortality, 1.4 and 6.7% for cardiovascular mortality, and between 1.7 and 30.4% for respiratory mortality. CONCLUSION: In spite of a standardized common protocol, some disparities, inherent to the local characteristics, were noted (length of time series, numbers of ambient urban stations selected and pollutants available.). Nevertheless, this pilot study showed that multicentric epidemiological monitoring of air pollution effects on health was feasible. Yet, this requires to validate the results obtained through a re-analysis of the mortality data on a longer period of study. It also requires to study the feasibility and the relevance of the use of other health indicators, such as hospital admissions.

Structural and conjunctural compensation method for hospital budgetary allocation on the basis of DRGs.

We propose here a structural and conjunctural compensation method to improve budgetary allocation which could be based on Diagnosis Related Groups. This method consists in the determination of sub-group costs within DRGs. The specification of these sub-groups is possible by introducing clinical and social parameters in the statistical model. Hospitals could then compare their sub-group proportions and analyze their differences in relation to conjunctural factors (recruitment, medical practices) and structural factors (technical team, local medical structure). This method also allows an identification of specialty hospitals (outliers) and a compensation allocation for budgeting for these hospitals.