Table 3.
Bivariate analysesa of the reasons for experiencing health care delays resulting from the COVID-19 pandemic (N=2570).
| Independent variables | Yes | No | P value | |
| Age (years), mean (SD) | 38.9 (13.1) | 36.0 (12.1) | <.001 | |
| Gender identity, %b | ||||
|
|
Cisgender women | 87.2 | 83.8 | <.001 |
|
|
Cisgender men | 8.3 | 13.4 | —c |
|
|
Transgender or nonbinary individuals | 4.6 | 3.8 | — |
| Race, %b | ||||
|
|
White | 87.8 | 83.9 | .005 |
|
|
People of color | 12.2 | 16.1 | — |
| Sexual identity, %b | ||||
|
|
Heterosexual | 60 | 57.6 | .22 |
|
|
Sexual minority | 40 | 42.4 | — |
| Education, %b | ||||
|
|
Less than a Bachelor’s degree | 17 | 14.6 | .007 |
|
|
Bachelor’s degree or some graduate school | 38.9 | 35.3 | — |
|
|
Graduate or doctorate degree | 44.1 | 50.2 | — |
| Distance to nearest hospital (miles), mean (SD) | 2.3 (1.0) | 2.3 (0.9) | .15 | |
| Worry about general health (scale of 0-100), mean (SD) | 54.5 (27.0) | 50.1 (26.2) | <.001 | |
| Worry about COVID-19 (scale of 0-100), mean (SD) | 76.3 (20.4) | 73.6 (20.6) | <.001 | |
aBivariate tests are used to determine whether each independent variable is related to each dependent variable. Continuous independent variables are used in an independent samples t test to identify a significant association, while categorical independent variables are used in a chi-square test of association.
bPercentages are based on column totals.
cNot available.