Table 2. Bayesian conditional autoregressive Poisson model for counts of alcohol-related road crashes within 9214 Statistical Area level 1 units in Melbourne, Australia.
| Variable | IRR | (95% CI) |
|---|---|---|
| Land Use | ||
| Bar density a | 0.997 | (0.923, 1.074) |
| Bar density – adjacent a | 1.387 | (1.098, 1.755) |
| Restaurant density a | 0.973 | (0.917, 1.026) |
| Restaurants density – adjacent a | 0.866 | (0.731, 1.018) |
| Off-premise outlet density a | 0.843 | (0.704, 0.999) |
| Off-premise outlet density – adjacent a | 0.608 | (0.343, 1.071) |
| Proportion land area zoned retail b | 0.997 | (0.941, 1.055) |
| Proportion land area zoned retail – adjacent b | 1.000 | (0.999, 1.000) |
| Population Demographics | ||
| Population density c | 0.992 | (0.956, 1.025) |
| Population density – adjacent c | 1.027 | (0.973, 1.084) |
| Proportion male b | 0.974 | (0.894, 1.058) |
| Proportion English speakers b | 1.004 | (0.999, 1.008) |
| Age (years) d | 1.019 | (0.952, 1.088) |
| SES index (decile) | 0.950 | (0.921, 0.981) |
| Roadway Network | ||
| Total length (kms) | 1.011 | (0.992, 1.029) |
| Proportion highway/freeway b | 0.959 | (0.910, 1.010) |
| Proportion arterials b | 0.981 | (0.946, 1.017) |
| Intersections (count) d | 0.938 | (0.871, 1.013) |
| Proportion “T” intersections b | 1.793 | (1.123, 2.892) |
|
| ||
| CAR random effect | ||
| Proportion of variance explained by CAR | 0.054 | (0.014, 0.167) |
| Global Moran's I | 0.894 | |
Bolded parameter estimates do not include values of 1.000, indicating associations are well-supported
a
per 10 outlets/km2 increase
b
per 10% increase
c
per 1,000 people/km2 increase
d
per 10 unit increase