Table 5 Firth’s logistic regression model for health/demographic variables (D.V. is “Presence of significant crime reduction”—CR = 1)
From: Disentangling community-level changes in crime trends during the COVID-19 pandemic in Chicago
|
(1) Burglary sig. Reduction OR (SE) |
(2) Assault sig. Reduction OR (SE) |
(3) Narcotics sig. Reduction OR (SE) |
(4) Robbery sig. Reduction OR (SE) | |
|---|---|---|---|---|
| % Population aged >65 |
0.781** (0.087) |
1.008 (0.074) |
0.863** (0.067) |
0.782** (0.091) |
| % Population aged <18 |
0.932 (0.063) |
0.862** (0.052) |
0.973 (0.049) |
0.957 (0.061) |
| Overall health status |
1.015 (0.052) |
1.026 (0.045) |
0.919** (0.035) |
1.178** (0.092) |
| ln (Covid cases rate) (per 10k in) |
1.130 (0.631) |
0.568 (0.238) |
0.477* (0.206) |
0.633 (0.335) |
| Burglary rate 2019 (per 10k in.) |
1.019 (0.018) | |||
| Assault rate 2019 (per 10k in.) |
1.010* (0.005) | |||
| Narcotics rate 2019 (per 10k in.) |
1.030*** (0.011) | |||
| Robbery rate 2019 (per 10k in.) |
1.053**** (0.016) | |||
| Intercept |
1.111 (6.529) |
12.307 (67.700) |
3.04e+5 (1.54e+6) |
0.000 (0.000) |
| N | 77 | 77 | 77 | 77 |
| Chi2 | 5.657 | 11.877 | 12.837 | 13.096 |
| p | 0.341 | 0.037 | 0.025 | 0.022 |
