Table 1 Descriptive statistics of transgender participants, by gender identity among transgender and non-binary participants
Non-binary n = 620 (67.0%) | Transfeminine n = 231 (25.0%) | Transmasculine n = 75 (8.1%) | P value | |
|---|---|---|---|---|
Tobacco | 0.38 | |||
No | 273 (44.0%) | 89 (38.5%) | 30 (40.0%) | |
Yes | 327 (52.7%) | 133 (57.6%) | 38 (50.7%) | |
Missing | 20 (3.2%) | 9 (3.9%) | 7 (9.3%) | |
Alcohol | 0.04 | |||
No | 192 (31.0%) | 81 (35.1%) | 15 (20.0%) | |
Yes | 411 (66.3%) | 144 (62.3%) | 59 (78.7%) | |
Missing | 17 (2.7%) | 6 (2.6%) | 1 (1.3%) | |
Cannabis | 0.36 | |||
No | 470 (75.8%) | 185 (80.1%) | 56 (74.7%) | |
Yes | 97 (15.6%) | 28 (12.1%) | 9 (12.0%) | |
Missing | 53 (8.5%) | 18 (7.8%) | 10 (13.3%) | |
Socioeconomic status | 0.03 | |||
Lower | 78 (12.6%) | 31 (13.4%) | 14 (18.7%) | |
Lower middle | 252 (40.7%) | 75 (32.5%) | 19 (25.3%) | |
Upper middle | 171 (27.6%) | 64 (27.7%) | 25 (33.3%) | |
Upper | 32 (5.2%) | 22 (9.5%) | 4 (5.3%) | |
Missing | 87 (14.0%) | 39 (16.9%) | 13 (17.3%) | |
Education | 0.11 | |||
Did not complete secondary school | 30 (4.8%) | 11 (4.8%) | 8 (10.7%) | |
Completed secondary or trade school | 154 (24.8%) | 65 (28.1%) | 21 (28.0%) | |
Attended or completed higher education | 355 (57.3%) | 120 (52.0%) | 34 (45.3%) | |
Missing | 81 (13.1%) | 35 (15.2%) | 12 (16.0%) | |
Age category | 0.003 | |||
≤ 25 | 173 (27.9%) | 68 (29.4%) | 20 (26.7%) | |
25–40 | 310 (50.0%) | 123 (53.3%) | 25 (33.3%) | |
> 40 | 137 (22.1%) | 40 (17.3%) | 30 (40.0%) | |
Missing | 0 | 0 | 0 | |
Refused health services | 0.03 | |||
No | 263 (42.4%) | 84 (36.4%) | 28 (37.3%) | |
Yes | 95 (15.3%) | 49 (21.2%) | 6 (8.0%) | |
Missing | 262 (42.3%) | 98 (42.4%) | 41 (54.7%) | |
Refused police services | 0.16 | |||
No | 220 (35.5%) | 72 (31.2%) | 23 (30.7%) | |
Yes | 110 (17.7%) | 54 (23.4%) | 12 (16.0%) | |
Missing | 290 (46.8%) | 105 (45.5%) | 40 (53.3%) | |
Disability status | 0.82 | |||
No | 427 (68.9%) | 156 (67.5%) | 48 (64.0%) | |
Yes | 58 (9.4%) | 24 (10.4%) | 8 (10.7%) | |
Missing | 135 (21.8%) | 51 (22.1%) | 19 (25.3%) | |
Lost job due to COVID-19 | 0.67 | |||
No | 424 (68.4%) | 156 (67.5%) | 45 (60.0%) | |
Yes | 46 (7.4%) | 16 (6.9%) | 7 (9.3%) | |
Missing | 150 (24.2%) | 59 (25.5%) | 23 (30.7%) | |
Rurality/urbanicity | 0.02 | |||
Rural | 45 (6.9%) | 11 (4.8%) | 3 (4.0%) | |
Small city | 140 (22.6%) | 39 (16.9%) | 7 (9.3%) | |
Large city | 353 (56.9%) | 145 (62.8%) | 53 (70.7%) | |
Missing | 84 (13.6%) | 36 (15.6%) | 12 (16.0%) | |
Region | < 0.001 | |||
European | 312 (50.3%) | 142 (61.5%) | 40 (53.3%) | |
American | 67 (10.8%) | 22 (9.5%) | 12 (16.0%) | |
South East Asian | 159 (25.7%) | 14 (6.1%) | 9 (12.0%) | |
Eastern Mediterranean | 30 (4.8%) | 28 (12.1%) | 4 (5.3%) | |
Western Pacific | 17 (2.7%) | 6 (2.6%) | 4 (5.3%) | |
African | 3 (0.5%) | 5 (2.2%) | 1 (1.3%) | |
Missing | 32 (5.2%) | 14 (6.1%) | 5 (5.7%) | |