Table 3.
Cause | Exposure | Percent change (95% CI) |
---|---|---|
Respiratory | PM2.5 short term | 0.41% (0.16%; 0.65%)** |
PM2.5, long term | 4.09% (3.31%; 4.87%)** | |
Temperature, short term | 8.63% (7.88%; 9.39%)** | |
Temperature, long term (10th p) | 6.24% (6.54%; 5.93%)** | |
Temperature, long term (90th p) | 1.37% (1.28%;1.47%)** | |
Cardiac | PM2.5, short term | 0.02% (−0.18%; 0.23%) |
PM2.5, long term | 6.58% (5.90%; 7.26%)** | |
Temperature, short term | 3.63% (3.01%; 4.25%)** | |
Temperature, long term (10th p) | −2.15% (−2.36%; −1.93%)** | |
Temperature, long term (90th p) | −1.69% (−1.77%; −1.60%)** | |
Ischemic stroke | PM2.5 short term | 1.20% (0.71%; 1.69%)** |
PM2.5, long term | 0.82% (−0.68%; 2.35%) | |
Temperature, short term | −0.08% (−1.49%; 1.34%) | |
Temperature, long term (10th p) | 7.32% (6.68%; 7.96%)** | |
Temperature, long term (90th p) | 0.15% (−0.04%; 0.34%) |
Results are presented as percent change and 95% Confidence Intervals (CI) for an IQR increase in short term PM2.5 (5.4 μg/m3), long term PM 3, 2.5 (2.3 μg/m) short term temperature (9.2 °C) and long term temperature (2.2 °C). The effect of the long-term exposure to temperature was modeled using penalized splines, results are therefore presented as percent change and 95% Confidence Intervals (CI) for IQR increases in the 10th (8 °C) and 90th (10.2 °C) percentile of temperature. We used the moving average of PM2.5 at lag days 0-1 for the calculation of the short-term exposure to PM2.5, temperature ta lag day 0 for the calculation of short-term temperature and annual averages for the long-term exposures of PM2.5 and temperature.
p<0.05