Table 4.
Multinominal logistic regression to estimate the association between non-redundant built environment variables and telomere length.
| Variables | 1st quartile | 2nd quartile | 3rd quartile | 4th quartile |
|---|---|---|---|---|
| ORs (95% CI)a | ORs (95% CI)a | ORs (95% CI)a | ORs (95% CI)a | |
| Population density | 1.00 | 1.00 (0.90, 1.11) | 1.01 (0.91, 1.13) | 1.04 (0.93, 1.16) |
| Intersection density | 1.00 | 0.96 (0.88, 1.05) | 1.00 (0.91, 1.09) | 0.97 (0.89, 1.07) |
| Distance to highway | 1.00 | 1.03 (0.94, 1.13) | 0.99 (0.90, 1.08) | 1.02 (0.92, 1.12) |
| Networked distance to the nearest park | 1.00 | 1.01 (0.91, 1.13) | 1.07 (0.96, 1.19) | 0.96 (0.85, 1.07) |
| Rundle's LUM | 1.00 | 1.27 (1.06, 1.52) | 1.23 (1.03, 1.48) | 1.23 (1.02, 1.48) |
| Frank's LUM | 1.00 | 1.29 (0.95, 3.41) | 1.24 (0.96, 3.12) | 1.35 (0.92, 3.30) |
| CDC mREFI | 1.00 | 1.00 (0.98, 1.02) | 0.99 (0.97, 1.01) | 1.01 (0.99, 1.02) |
aAdjusted by age, sex, BMI, physical activity, health insurance, born place, acculturation, and census income.