Table 2a.
OLS regression modela explaining years of potential life lost per 100,000.
| Variable | B | SE | B | t | Sig. | |||
|---|---|---|---|---|---|---|---|---|
| Adult smoking | 89.380 | 5.779 | 0.240 | 15.468 | 0.000 | |||
| Adult obesity | 81.462 | 9.986 | 0.157 | 8.158 | 0.000 | |||
| Glucose testing | −41.458 | 5.715 | −0.108 | −7.254 | 0.000 | |||
| Uninsured | 7.789 | 12.288 | 0.017 | 0.634 | 0.526 | |||
| Poverty index | 968.348 | 72.872 | 0.324 | 13.288 | 0.000 | |||
| Rural county | 472.201 | 65.068 | 0.102 | 7.257 | 0.000 | |||
| Public health spending (logged) | −23.003 | 24.806 | −0.014 | −0.927 | 0.354 | |||
| Predicted incarceration rate |
0.823 |
0.211 |
0.088 |
3.895 |
0.000 |
|||
| aCoefficients for state dummy variables are not presented herein; CT, DE, HI and RI are excluded because of missing data. | ||||||||
| R2 = .685 | ||||||||
| F (53, 2,176) = 89.471 (p < .001) | ||||||||
| N = 2229 | ||||||||