Table 3 Characteristics of study respondents by the willingness and uptake of COVID-19 vaccination
Characteristics | Uptake of COVID-19 vaccination | Willingness of COVID-19 vaccination among those not vaccinated | ||
|---|---|---|---|---|
Vaccinated /scheduled (%) | Not vaccinated/scheduled (%) | Willing (%) | Unwilling (%) | |
Total | 530 (23.62) | 1714 (76.38) | 888 (51.90) | 823 (48.10) |
City | P = 0.040 |  | P = 0.022 |  |
 Nanjing | 237 (21.72) | 854 (78.28) | 419 (49.12) | 434 (50.88) |
 Chizhou | 293 (25.41) | 860 (74.59) | 469 (54.66) | 389 (45.34) |
Gender | P = 0.252 |  | P = 0.082 |  |
 Male | 176 (25.14) | 524 (74.86) | 288 (55.07) | 235 (44.93) |
 Female | 354 (22.93) | 1190 (77.07) | 600 (50.51) | 588 (49.49) |
Age (years) | P < 0.001 |  | P = 0.799 |  |
 18–25 | 46 (21.10) | 172 (78.90) | 90 (52.33) | 82 (47.67) |
 26–35 | 183 (17.55) | 860 (82.45) | 454 (52.98) | 403 (47.02) |
 36–45 | 186 (32.80) | 381 (67.20) | 193 (50.66) | 188 (49.34) |
  >  = 46 | 115 (27.64) | 301 (72.36) | 151 (50.17) | 150 (49.83) |
Residency | P = 0.499 |  | P = 0.822 |  |
 Local residents | 464 (23.86) | 1481 (76.14) | 766 (51.79) | 713 (48.21) |
 Migrants | 66 (22.07) | 233 (77.93) | 122 (52.59) | 110 (47.41) |
Marital status | P = 0.667 |  | P = 0.277 |  |
 Single | 70 (24.73) | 213 (75.27) | 113 (53.05) | 100 (46.95) |
 Married | 446 (23.34) | 1465 (76.66) | 761 (52.05) | 701 (47.95) |
 Divorced/widow | 14 (28) | 36 (72) | 14 (38.89) | 22 (61.11) |
Educational attainment | P < 0.001 |  | P = 0.784 |  |
 Middle school or lower | 33 (9.68) | 308 (90.32) | 155 (50.49) | 152 (49.51) |
 High school or technical secondary school | 53 (13.18) | 349 (86.82) | 188 (54.18) | 159 (45.82) |
 Junior college | 149 (26.70) | 409 (73.30) | 209 (51.10) | 200 (48.90) |
 Bachelor's degree or higher | 295 (31.28) | 648 (68.72) | 336 (51.85) | 312 (48.15) |
Occupation | P < 0.001 |  | P = 0.321 |  |
 Government agency | 363 (46.90) | 411 (53.10) | 221 (53.77) | 190 (46.23) |
 Service industry | 101 (17.41) | 479 (82.59) | 251 (52.51) | 227 (47.49) |
 Manufacturing industry or agriculture | 22 (7.28) | 280 (92.72) | 152 (54.29) | 128 (45.71) |
 Others | 44 (7.48) | 544 (92.52) | 264 (48.71) | 278 (51.29) |
Annual individual income | P = 0.007 |  | P = 0.973 |  |
  < 20 k | 37 (15.16) | 207 (84.84) | 107 (52.20) | 98 (47.80) |
 20-50 k | 81 (21.72) | 292 (78.28) | 151 (51.71) | 141 (48.29) |
 50-100 k | 173 (24.68) | 528 (75.32) | 270 (51.14) | 258 (48.86) |
 100-200 k | 151 (24.92) | 455 (75.08) | 235 (51.76) | 219 (48.24) |
  > 200 k | 88 (27.50) | 232 (72.50) | 125 (53.88) | 107 (46.12) |
Self-reported health status | P = 0.072 |  | P = 0.050 |  |
 Good | 489 (24.15) | 1536 (75.85) | 808 (52.71) | 725 (47.29) |
 Poor | 41 (18.72) | 178 (81.28) | 80 (44.94) | 98 (55.06) |
Awareness of COVID-19 | P < 0.001 |  | P < 0.001 |  |
 High | 510 (24.50) | 1572 (75.50) | 851 (54.20) | 719 (45.80) |
 Low | 20 (12.35) | 142 (87.65) | 37 (26.24) | 104 (73.76) |
Perceived susceptibility of COVID-19 | P < 0.001 |  | P = 0.025 |  |
 High | 81 (55.48) | 65 (44.52) | 42 (65.63) | 22 (34.38) |
 Low | 449 (21.40) | 1649 (78.60) | 846 (51.37) | 801 (48.63) |
Perceived severity of COVID-19 | P = 0.103 |  | P = 0.163 |  |
 Severe or moderate | 113 (26.65) | 311 (73.35) | 172 (55.48) | 138 (44.52) |
 Mild | 417 (22.91) | 1403 (77.09) | 716 (51.11) | 685 (48.89) |