Table 2.
Logistic Regression Model for Association Between Variables of Interest and Delays in Care
| Full Sample | ||
|---|---|---|
| (N = 7 615) | ||
| Factors associated with Delays in Care+ | OR* | (95% CI) |
| Race/ethnicity (Ref. = Non-Hispanic Blacks) | ||
| Non-Hispanic Whites | 1.37 | (1.19, 1.58) |
| Hispanics | 1.09 | (0.91, 1.30) |
| Other racial/ethnic backgrounds | 1.31 | (1.02, 1.67) |
| Age (Ref. = 71–104) | ||
| 53–70 | 1.67 | (1.46, 1.92) |
| U.S. geographical region (Ref. = South) | ||
| Northeast | 1.06 | (0.91, 1.23) |
| Midwest | 1.19 | (1.04, 1.37) |
| West | 1.22 | (1.06, 1.40) |
| Prior/current COVID-19 diagnosis | 1.00 | (0.76, 1.31) |
| Knowledge of anyone in the household with a COVID-19 diagnosis | 0.85 | (0.63, 1.14) |
| Knowledge of anyone elsewhere with a COVID-19 diagnosis | 1.34 | (1.20 1.50) |
| Knowledge of anyone who had died of COVID-19 | 1.16 | (1.03, 1.32) |
| High concerns about COVID-19 pandemic | 1.26 | (1.13, 1.41) |
Statistically significant odd ratios at the 5% are bolded.
Notes: *CI = confidence interval; OR = odds ratio; ref. = reference.
†Only variables of interest are shown in the table (ie, race/ethnicity, age, and COVID-19-related factors). The logistic regression model was adjusted for covariates, including marital status, sex, education, employment status, medical and dental insurance status, history of chronic health conditions, current use of medications or medical treatment, poor/fair perceived health, and past health service utilization.