Table 3.
Logistic regression analysis to estimate the association between built environment variable and mtDNA copy number.
| Variables | ORs (95% CI)a | P value |
|---|---|---|
| Age | 0.96 (0.94, 0.98) | < 0.001 |
| Gender (female vs male) | 0.61 (0.40, 0.96) | 0.032 |
| Age × gender | 1.02 (1.01, 1.03) | < 0.001 |
| BMI | 0.98 (0.97, 0.99) | < 0.001 |
| Physical activity | ||
| Medium vs low | 0.98 (0.86, 1.14) | 0.775 |
| High vs low | 0.74 (0.55, 0.99) | 0.040 |
| Insurance | 0.90 (0.80, 0.99) | 0.048 |
| Household density | ||
| 1st quartile | 1 | |
| 2nd quartile | 1.09 (0.93, 1.28) | 0.277 |
| 3rd quartile | 1.23 (1.05, 1.44) | 0.009 |
| 4th quartile | 1.31 (1.10, 1.54) | 0.007 |
| P for trend = 0.012 | ||
| Road/intersection ratio | ||
| 1st quartile | 1 | |
| 2nd quartile | 1.07 (0.92, 1.25) | 0.375 |
| 3rd quartile | 1.12 (0.96, 1.31) | 0.143 |
| 4th quartile | 1.21 (1.03, 1.42) | 0.018 |
| P for trend = 0.025 | ||
aAdjusted by age, sex, age × sex, BMI, physical activity, and insurance.