[Meta-analysis of the Italian studies on short-term effects of air pollution--MISA 1996-2002].
BACKGROUND
the Italian Meta-analysis of short-term effects of air pollution for the period 1996-2002 (MISA-2) is a planned study on 15 Italian cities, among the larger country towns summing up 9 millions and one hundred thousand inhabitants at 2001 census. HEALTH OUTCOMES DATA: mortality for all natural causes (362254 deaths), for respiratory causes (22317) and cardiovascular causes (146830), and hospital admissions for acute conditions, respiratory (278028 admissions), cardiac (455540) and cerebrovascular (60960), have been considered. Mortality data came from Regional or Local Health Unit Registries, while hospital admissions data have been selected from Regional or Hospital Archives (exclusion percentages range for all admissions between 45% and 82%). For each participating city daily series averaged about 4.3 years, with a minimum of three consecutive years. AIR POLLUTANTS DATA: daily pollutants concentration series (SO2, NO2, CO, PM10, O3) came from air quality monitoring networks of Regional Environmental Protection Agencies, of Environmental Offices of Provinces or Municipalities. Monitors' selection has been done by a working group composed by representatives of monitoring network Agencies. The selection criteria are the representativeness of general population exposure for each specific pollutant, avoiding as possible monitors close to high traffic roads; and the number, quality and location of monitors, selecting around 3-4 monitors with continuous data flow in the period (at least 75% of valid hourly data). The final series has been created averaging over monitors and imputing missing values under proportionality assumptions. Median of Pearson correlation coefficients between pairs of monitors of the each city was 0.62, interquartile range 0.42-0.77.


METHODS
A generalized linear model on daily counts of health events has been fitted for each city. Linear pollutant effect has been specified and bi-pollutant models have been fitted for PM10+NO2 and PMO+O3. Temperature has been modelled parametrically using a change point at 21 degrees C and lagged effects. Humidity, day of the week, national holidays and influenza epidemics (using data from the National Surveillance Programs from 1999) are the other considered confounders. An age-specific natural cubic spline on season has been specified with 5 degree of freedom (on average) per year for mortality and 7 degree of freedom per year for hospital admission data. The base model is age-stratified (0-64, 65-74, 75+ years). Gender, age, season specific models have been fitted, too. Five sensitivity analyses have been done, varying the degree of freedom for the seasonality spline and specifying non parametric functions on temperature. Constrained distributed lag models have been fitted on mortality data to study potential harvesting effects. City-specific results have been meta-analyzed by random effects hierarchical Bayesian model. Four different models have been fitted in the sensitivity analyses, assuming different priors on heterogeneity variance and outlier-resistant prior on city-specific effects. Bayesian meta-regressions have been fitted on base model, bi-pollutant and season-specific city-specific results. Attributable deaths have been estimated by Monte Carlo methods using effect, pollutant, baseline rate distributions. Fourteen different scenarios have been considered for PM10 and ten for NO2 and CO, using meta-analitic and posterior city-specific effect estimates


RESULTS
Pollutants effects are reported as percent increase on mortality or hospital admissions for an increase of 10 microg/m3 of SO2, NO2 and PM10, and 1 mg/m3 of CO. We found an increase on mortality for all natural causes associated to increase of air pollutants concentration (for NO2 0.6% 95%CrI 0.3,0.9; CO 1.2% 0.6,1.7; PM10 0.31% -0.2,0.7). Similar findings were found for cardiorespiratory mortality and hospital admissions for respiratory and cardiac diseases. We found no difference by gender. There was a weak evidence of greater effect size in extreme age groups (0-24 months and over 85 years where we found a percent increase in mortality for all natural causes for PM10 of 0.39% CrI95% 0.0,0.8). There was a strong evidence for each pollutant of greater effects in the warm season (1st May-30th September) on mortality and hospital admissions (we found a percent increase in mortality for all natural causes for PM10 in the warm season of 1.95% CrI95% 0.6,3.3). The associations between pollutants concentration and health events were present at different time lags, depending on outcome and exposure. For mortality, the excess risk peaked within few days from the exposure increase (two days for PM10, up to four days for NO2 and CO). Mortality displacement was minor and ended within two weeks. Cumulative effects at fifteen days showed higher risks for respiratory diseases (PM10 1.65% CI95% 0.3,3.0). The results of meta-regressions showed associations between PM10 effects on mortality and hospital admissions, and mortality for all causes (SMR) and PM10/NO2 ratio. The effect modification of temperature was very consistent, and also using bi-pollutant models. Such effect modification was greater during the cold season. We found and overall impact on mortality for all natural causes in the period 1996-2002 between 1.4% and 4.1% of all deaths for gaseous pollutants (NO2 and CO). The estimates were more imprecise for PM10, due to the variability among cities of the effect estimates (0.1%; 3.3%). The limits stated in the European Union directives for 2010 would have been saved about 900 deaths (1.4%) for PM10 or 1400 deaths for NO2 (1.7%) among all the MISA cities, applying posterior city-specific effect estimates.
Biggeri
Annibale
A
Bellini
Pierantonio
P
Terracini
Benedetto
B
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000397:Air Pollution / Q000009:adverse effects* / Q000032:analysis / Q000706:statistics & numerical data*; D002423:Cause of Death; D002648:Child; D002675:Child, Preschool; D004781:Environmental Exposure / Q000009:adverse effects / Q000032:analysis; D005260:Female; D006801:Humans; D007223:Infant; D007558:Italy; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009026:Mortality / Q000639:trends; D012044:Regression Analysis; D012680:Sensitivity and Specificity; D013997:Time Factors