Table 1.
Demographic characteristics of participants and knowledge level of COVID-19 by demographic variables.
| Characteristics | Participants, n (%) | Perception above average level, n (%) | Misled rates, n (%) | |
| Age (years) | P<.001 | P<.001 | ||
|
|
≤20 | 599 (12.5) | 563 (94.0) | 65 (10.9) |
|
|
21-40 | 1774 (37.1) | 1704 (96.1) | 222 (12.5) |
|
|
41-60 | 1601 (33.4) | 1521 (95.0) | 329 (20.5) |
|
|
>60 | 814 (17.0) | 733 (90.0) | 193 (23.7) |
| Gender | P=.06 | P=.25 | ||
|
|
Male | 2248 (47.0) | 2108 (93.8) | 365 (16.2) |
|
|
Female | 2540 (53.0) | 2413 (95.0) | 444 (17.5) |
| Marital status | P<.001 | P<.001 | ||
|
|
Unmarried | 1725 (36.0) | 1654 (95.9) | 189 (11.0) |
|
|
Married or remarried | 2851 (59.5) | 2682 (94.1) | 566 (19.9) |
|
|
Divorced or widowed, not remarried | 212 (4.4) | 185 (87.3) | 54 (25.5) |
| Occupation | P<.001 | P<.001 | ||
|
|
Seeking employment | 300 (6.3) | 274 (91.3) | 62 (20.7) |
|
|
Not working (not able to work) | 273 (5.7) | 239 (87.5) | 65 (23.8) |
|
|
Self-employed shop owner or entrepreneur | 569 (11.9) | 533 (93.7) | 118 (20.7) |
|
|
Staff member in a government or public institution | 615 (12.8) | 599 (97.4) | 110 (19.7) |
|
|
Farmer, fisherman, or herdsman | 321 (6.7) | 287 (89.4) | 83 (25.9) |
|
|
Retired | 499 (10.4) | 469 (94.0) | 112 (22.4) |
|
|
Student | 1155 (24.1) | 1109 (96.0) | 102 (8.8) |
|
|
Staff member in a big company | 276 (5.8) | 264 (95.7) | 45 (16.3) |
|
|
Staff member in a small or medium company | 426 (8.9) | 410 (96.2) | 58 (13.6) |
|
|
Other | 354 (7.4) | 337 (95.2) | 54 (15.3) |
| Education (years) | P<.001 | P<.001 | ||
|
|
≤6 | 698 (14.6) | 621 (89.0) | 160 (22.9) |
|
|
7-9 | 809 (16.9) | 758 (93.7) | 166 (20.5) |
|
|
10-12 | 865 (18.1) | 811 (93.8) | 178 (20.6) |
|
|
13-16 | 2145 (44.8) | 2064 (96.2) | 286 (13.3) |
|
|
>16 | 271 (5.7) | 267 (98.5) | 19 (7.0) |
| Areas | P=.09 | P=.88 | ||
|
|
Eastern China | 1317 (27.5) | 1259 (95.6) | 227 (17.2) |
|
|
Central China | 2191 (45.8) | 2058 (93.9) | 371 (16.9) |
|
|
Western China | 1280 (26.7) | 1204 (94.1) | 211 (16.5) |
| Type of area | P<.001 | P=.93 | ||
|
|
Urban | 3065 (64.0) | 2928 (95.5) | 519 (16.9) |
|
|
Rural | 1723 (36.0) | 1593 (92.5) | 290 (16.8) |
| Household composition | P=.005 | P=.36 | ||
|
|
Living with others | 4370 (91.3) | 4139 (94.7) | 745 (17.0) |
|
|
Living alone | 418 (8.7) | 382 (91.4) | 64 (15.3) |
| Relative self-reported individual income | P<.001 | P=.03 | ||
|
|
Low (0%-20%) | 1505 (31.4) | 1393 (92.6) | 266 (17.7) |
|
|
Low and middle (20%-40%) | 1141 (23.8) | 1069 (93.7) | 214 (18.8) |
|
|
Average (40%-60%) | 1816 (37.9) | 1743 (96.0) | 269 (14.8) |
|
|
Upper middle (60%-80%) | 285 (6.0) | 277 (97.2) | 55 (19.3) |
|
|
High (80%-100%) | 41 (0.9) | 39 (95.1) | 5 (12.2) |
| Household income in 2019, RMB (US $) | P<.001 | P=.008 | ||
|
|
<100,000 (<14,954) | 2074 (43.3) | 1920 (92.6) | 395 (19.0) |
|
|
100,000-200,000 (14,954-29,909) | 1735 (36.2) | 1667 (96.1) | 270 (15.6) |
|
|
200,000-300,000 (29,909-44,864) | 579 (12.1) | 556 (96.0) | 89 (15.4) |
|
|
300,000-400,000 (44,864-59,819) | 193 (4.0) | 182 (94.3) | 23 (11.9) |
|
|
>400,000 (59,819) | 207 (4.3) | 196 (94.7) | 32 (15.5) |