Table 2.
Poisson regression exponentiated coefficients of the relationship between concentration of air contaminants and monthly number of embolizations.
| Relationship between number of embolizations in a given month and … | … concentration of the contaminant in the same month (x t) | … concentration of the contaminant in the previous month (x t−1) | … increase (from the previous month) in the concentration of the contaminant (x t − x t−1) |
|---|---|---|---|
| Contaminants | |||
| SO2 (per 1 μg/m3) | 1.010 (p = 0.918) | 1.070 (p = 0.521) | 0.961 (p = 0.636) |
| NO (per 15 μg/m3) | 1.169 (p = 0.132) | 0.958 (p = 0.679) | 1.445 (p = 0.006)∗∗ |
| NO2 (per 10 μg/m3) | 1.135 (p = 0.177) | 0.945 (p = 0.521) | 1.292 (p = 0.014)∗ |
| O3 (per 20 μg/m3) | 0.868 (p = 0.154) | 0.900 (p = 0.301) | 0.839 (p = 0.302) |
| CO (per 0.1 μg/m3) | 1.073 (p = 0.490) | 0.923 (p = 0.511) | 1.253 (p = 0.094) |
| PM10 (per 10 μg/m3) | 1.029 (p = 0.770) | 0.991 (p = 0.926) | 1.097 (p = 0.432) |
| Potential confounds | |||
| Temperature (per 10°C) | 0.987 (0.933) | 1.118 (0.511) | 0.596 (0.101) |
| Influenza (per 500 searches) | 0.808 (0.182) | 0.857 (0.339) | 0.993 (0.959) |
Each cell shows the Poisson regression exponentiated coefficient and the p value of the relationship. The exponentiated coefficient shows the amount by which the expected number of embolizations is multiplied per each unit increase in the contaminant (e.g., for the right-most NO cell, 1.169, the expected number of embolizations in a given month is 16.9% higher if the concentration of NO is 15 μg/m3 higher). The measurement units were semiconventionally chosen (round numbers with similar standard deviations ~ 0.5–1), but statistics were conducted considering the variables as continuous for which p values do not depend on these measure units.
∗∗Statistically significant after correction for multiple comparisons.
∗Only statistically significant before correction for multiple comparisons.