Table 1 Sample demographics and socio-economic loss impact characteristics by HIV status in a global sample of transgender and nonbinary people (n = 902)
| Â | Total n (%) | HIV-negative n (%) | HIV-positive n (%) | HIV-unknown n (%) | p-value |
|---|---|---|---|---|---|
Total | 902 (100.00) | 590 (64.41) | 120 (13.30) | 192 (21.29) | Â |
Demographics | |||||
 Gender identity | |||||
  Nonbinary | 604 (66.96) | 391 (66.27) | 87 (72.50) | 126 (65.62) | 0.642 f |
  Trans masculine | 35 (3.80) | 22 (3.73) | 5 (4.17) | 8 (4.17) |  |
  Trans feminine | 263 (29.16) | 177 (30.00) | 28 (23.33) | 58 (30.21) |  |
 Age | |||||
  18–29 years old | 463 (51.33) | 308 (52.20) | 57 (47.50) | 98 (51.04) | 0.558 |
  30–39 years old | 267 (29.60) | 170 (28.81) | 39 (32.50) | 58 (30.21) |  |
  40–29 years old | 119 (13.19) | 78 (13.22) | 13 (10.83) | 28 (14.58) |  |
  50 or more years old | 53 (5.88) | 34 (5.76) | 11 (9.17) | 8 (4.17) |  |
 Education | |||||
  Less than college | 213 (23.83) | 137 (23.30) | 28 (23.73) | 48 (25.53) | 0.822 |
  College/Some college | 681 (76.17) | 451 (76.70) | 90 (76.27) | 140 (74.47) |  |
 Level of socioeconomic status | |||||
  Lower | 141 (15.68) | 87 (14.77) | 19 (15.97) | 35 (18.35) | 0.010f |
  Lower-middle | 445 (49.50) | 277 (47.03) | 69 (57.98) | 99 (51.83) |  |
  Upper-middle | 272 (30.26) | 195 (33.11) | 23 (19.33) | 54 (28.27) |  |
  Upper | 41 (4.56) | 30 (5.09) | 8 (6.72) | 3 (1.57) |  |
 Migrant status | |||||
  No/Unsure | 754 (84.81) | 482 (83.10) | 104 (86.67) | 168 (88.89) | 0.130 |
  Yes | 135 (15.19) | 98 (16.90) | 16 (13.33) | 21 (11.11) |  |
 WHO continent region | |||||
  South-East Asia | 217 (24.72) | 124 (21.60) | 36 (30.51) | 57 (30.65) | < 0.001 |
  Americas | 83 (9.45) | 61 (10.63) | 14 (11.86) | 8 (4.30) |  |
  Eastern Mediterranean | 80 (9.11) | 64 (11.15) | 9 (7.63) | 7 (3.76) |  |
  Africa | 34 (3.87) | 22 (3.83) | 9 (7.63) | 3 (1.61) |  |
  Europe | 424 (48.29) | 277 (48.26) | 48 (40.68) | 99 (53.23) |  |
  Western Pacific | 40 (4.56) | 26 (4.53) | 2 (1.69) | 12 (6.45) |  |
 Setting | |||||
  Urban | 658 (71.11) | 449 (76.36) | 85 (70.83) | 124 (64.58) | 0.005 |
  Rural | 242 (26.89) | 139 (23.64) | 35 (29.17) | 68 (35.42) |  |
 Racial/Ethnic Minority | |||||
  No/Not Sure | 662 (73.64) | 425 (72.16) | 82 (68.91) | 155 (81.15) | 0.022 |
  Yes | 237 (26.36) | 164 (27.84) | 37 (31.09) | 36 (18.85) |  |
Socio-economic Loss due to COVID-19 Indicators | |||||
 Income reduction (anticipated) | |||||
  No | 239 (27.10) | 167 (28.99) | 21 (17.65) | 51 (27.27) | 0.040 |
  Yes | 643 (72.90) | 409 (71.01) | 98 (82.35) | 136 (72.73) |  |
 Insurance loss (anticipated) | |||||
  No | 382 (61.51) | 265 (64.79) | 43 (49.43) | 74 (59.20) | 0.023 |
  Yes | 239 (38.49) | 144 (35.21) | 44 (50.57) | 51 (40.80) |  |
 Job loss/unemployment (anticipated) | |||||
  No | 753 (84.23) | 502 (86.11) | 97 (80.83) | 154 (80.63) | 0.104 |
  Yes | 141 (15.77) | 81 (13.89) | 23 (19.17) | 37 (19.37) |  |
 Cutting Meals | |||||
  No | 510 (60.36) | 345 (61.61) | 61 (54.46) | 104 (60.12) | 0.369 |
  Yes | 335 (39.64) | 215 (38.39) | 51 (45.54) | 69 (39.88) |  |