TABLE 4—
Multivariate Logistic Regression Models of Nonoccupational Injuries and Occupational Injuries in Past 3 Months Among US Workers: National Health Interview Survey, United States, 2006–2010
| Nonoccupational Injuries, AOR (95% CI) | Occupational Injuries, AOR (95% CI) | |
| Disability status | ||
| Workers without disabilities (Ref) | 1.00 | 1.00 |
| Workers with disabilities | 2.35 (2.04, 2.71) | 2.39 (1.89, 3.01) |
| Gender | ||
| Female (Ref) | 1.00 | 1.00 |
| Male | 1.09 (1.00, 1.19) | 1.60 (1.37, 1.86) |
| Age, y | ||
| 35–54 (Ref) | 1.00 | 1.00 |
| 18–34 | 1.26 (1.12, 1.41) | 1.19 (1.00, 1.42) |
| ≥ 55 | 0.98 (0.86, 1.12) | 0.88 (0.72, 1.07) |
| Marriage status | ||
| Married (Ref) | 1.00 | 1.00 |
| Single or never married | 1.33 (1.17, 1.52) | 1.14 (0.94, 1.38) |
| Separated, divorced, or widowed | 1.48 (1.30, 1.68) | 1.39 (1.13, 1.70) |
| Race/ethnicity | ||
| Non-Hispanic White (Ref) | 1.00 | 1.00 |
| Non-Hispanic Black | 0.77 (0.66, 0.88) | 0.99 (0.82, 1.20) |
| Hispanic | 0.66 (0.54, 0.80) | 0.96 (0.76, 1.22) |
| Others | 0.76 (0.59, 0.96) | 0.81 (0.47, 1.39) |
| Education | ||
| ≥ bachelor’s degree (Ref) | 1.00 | 1.00 |
| High school graduate or GED | 0.83 (0.75, 0.91) | 1.93 (1.57, 2.37) |
| < 12 y (no high school diploma) | 0.75 (0.62, 0.91) | 1.67 (1.25, 2.24) |
| Occupation | ||
| Not labor-related (Ref) | 1.00 | 1.00 |
| Labor-related | 0.84 (0.70, 1.00) | 1.89 (1.52, 2.36) |
| Unknown | 0.79 (0.73, 0.87) | 1.11 (0.94, 1.31) |
| Hours worked last wk | ||
| Full-time (≥ 32; Ref) | 1.00 | 1.00 |
| Part-time (1–31) | 1.16 (1.04, 1.30) | 0.78 (0.61, 0.98) |
| Self-employment income | ||
| No (Ref) | 1.00 | 1.00 |
| Yes | 1.18 (1.05, 1.34) | 0.91 (0.71, 1.17) |
| Health insurance coverage | ||
| Covered (Ref) | 1.00 | 1.00 |
| Not covered | 0.76 (0.66, 0.87) | 1.00 (0.82, 1.22) |
| Born in US | ||
| Yes (Ref) | 1.00 | 1.00 |
| No | 0.65 (0.54, 0.78) | 0.74 (0.57, 0.96) |
Note. AOR = adjusted odds ratio; CI = confidence interval; GED = General Equivalency Diploma. AORs were obtained from logistic regression analyses with all the variables in the table included in the models.