Table 4:
Results of multivariate regression of exposure factors as a predictor of heterogeneity in the association between a 10 μg/m3 increase in PM2.5 and percent change in mortality, per IQR change in exposure factor. Kitchen sink method was used to drop one covariate at a time based on highest p-value, until all covariates included were significant.
| Exposure factors | Beta (5th; 95th %tile) | p-value |
|---|---|---|
| 1Model 1 | ||
| Median home age | −0.288 (−0.516; −0.059) | 0.014 |
| Duplex homes | 0.135 (0.021; 0.249) | 0.021 |
| Median number of rooms, renter occupied | −0.123 (−0.243; −0.002) | 0.047 |
| Utility gas | −0.471 (−0.684; −0.257) | <0.001 |
| Heating degree days | 0.448 (0.162; 0.733) | 0.002 |
| Cooling degree days | −0.228 (−0.432; −0.023) | 0.030 |
| 2Model 2 | ||
| Duplex homes | 0.128 (0.059; 0.198) | <0.001 |
| Median number of rooms, renter occupied | 0.215 (0.081; 0.348) | 0.002 |
| Utility gas | −0.427 (−0.627; −0.227) | <0.001 |
1
Adjusted R-squared: 0.126; F-statistic: 8.47
2
Adjusted R-squared: 0.1144; F-statistic: 14.35