Table 3 Association between minimum percentage green space thresholds and neighbourhood socioeconomic circumstances, adjusting for city and population density: binary logit regression with robust standard errors
Model 1 | Model 2 | Model 3 | |
|---|---|---|---|
Odds Ratio (95% Confidence Interval) | |||
% green space cut-point for the outcome variable | ≥10% | ≥20% | ≥40% |
City (ref: Sydney) | |||
Melbourne | 0.48 (0.39, 0.59)*** | 0.49 (0.39, 0.62)*** | 0.45 (0.30, 0.67)*** |
Brisbane | 0.75 (0.60, 0.94)* | 0.68 (0.53, 0.87)** | 0.47 (0.29, 0.74)*** |
Perth | 0.96 (0.75, 1.24) | 0.95 (0.74, 1.22) | 0.72 (0.47, 1.09) |
Adelaide | 0.53 (0.40, 0.72)*** | 0.61 (0.44, 0.84)** | 0.58 (0.32, 1.06) |
Population density (logged) | 0.82 (0.77, 0.87)*** | 0.74 (0.70, 0.78)*** | 0.61 (0.57, 0.65)*** |
Percentage low income householdsa (ref: 0%) | |||
1 – 4% | 1.04 (0.92, 1.17) | 1.00 (0.88, 1.13) | 0.85 (0.69, 1.06) |
5 – 9% | 0.85 (0.74, 0.97)* | 0.76 (0.66, 0.88)*** | 0.64 (0.50, 0.81)*** |
10 – 19% | 0.73 (0.62, 0.85)*** | 0.61 (0.51, 0.73)*** | 0.35 (0.26, 0.47)*** |
20%+ | 0.77 (0.63, 0.93)** | 0.63 (0.51, 0.79)*** | 0.30 (0.20, 0.44)*** |