Table 2.
Logistic Regression Model for Longitudinal Data
| Variable (referent) | Exp(B) | 95% CI | Wald | df | p Value |
|---|---|---|---|---|---|
| Time (per 1-year increment) | 0.96 | 0.95–0.97 | 44.15 | 1 | <.001 |
| Baseline age (per 1-year increment) | 0.95 | 0.94–0.96 | 85.73 | 1 | <.001 |
| Man gender (woman) | 1.15 | 1.03–1.27 | 6.28 | 1 | .012 |
| Relationship status (married/common-law) | — | — | 6.18 | 3 | .103 |
| Never married | 0.8 | 0.63–1.00 | 3.83 | 1 | .050 |
| Separated/divorced | 1.1 | 0.94–1.28 | 1.43 | 1 | .231 |
| Widowed | 1.02 | 0.92–1.13 | 0.11 | 1 | .735 |
| Living arrangement (house) | — | — | 4.83 | 4 | .306 |
| Apartment | 0.88 | 0.77–1.01 | 3.29 | 1 | .070 |
| Retirement home | 0.99 | 0.77–1.27 | 0.01 | 1 | .928 |
| Condominium | 1 | 0.91–1.10 | 0.00 | 1 | .965 |
| Other | 0.88 | 0.73–1.07 | 1.61 | 1 | .204 |
| Setting (rural) | — | — | 2.03 | 2 | .362 |
| Urban | 0.94 | 0.82–1.07 | 0.88 | 1 | .348 |
| Other | 1.07 | 0.84–1.38 | 0.31 | 1 | .580 |
| Community size (<10,000) | — | — | 20.18 | 5 | .001 |
| 10,000–49,999 | 0.92 | 0.78–1.09 | 0.95 | 1 | .331 |
| 50,000–99,999 | 0.99 | 0.79–1.25 | 0.01 | 1 | .926 |
| 100,000–500,000 | 1.11 | 0.94–1.31 | 1.46 | 1 | .226 |
| >500,000 | 1.21 | 1.04–1.41 | 5.90 | 1 | .015 |
| Unsure | 0.94 | 0.74–1.20 | 0.25 | 1 | .616 |
| Education (post/graduate degree) | — | — | 5.46 | 5 | .362 |
| Degree | 0.97 | 0.87–1.08 | 0.37 | 1 | .544 |
| Diploma | 0.9 | 0.78–1.04 | 1.99 | 1 | .159 |
| Trade/technical school | 0.98 | 0.85–1.14 | 0.05 | 1 | .830 |
| High school | 0.98 | 0.87–1.10 | 0.13 | 1 | .717 |
| Grade school | 0.86 | 0.74–1.00 | 3.87 | 1 | .049 |
| Exposure (per 10,000 km) | 1.13 | 1.08–1.19 | 27.89 | 1 | <.001 |
| MoCA | 1.01 | 0.99–1.02 | 1.05 | 1 | .305 |
| Constant | 0.57 | 0.40–0.83 | 8.81 | 1 | .003 |
| Variance of random intercepts | 0.19 | 0.16–0.22 | — | — | — |
Notes: CI = confidence interval; MoCA = Montreal Cognitive Assessment. Wald tests with df = 1 are the squares of z-tests reported by Stata’s -melogit- command. Wald tests with df > 1 were obtained by using postestimation -contrast- commands.