TY - JOUR
T1 - The Complexities of Categorizing Gender
T2 - A Hierarchical Clustering Analysis of Data from the First Australian Trans and Gender Diverse Sexual Health Survey
AU - Callander, Denton
AU - Newman, Christy E.
AU - Holt, Martin
AU - Rosenberg, Shoshana
AU - Duncan, Dustin T.
AU - Pony, Mish
AU - Timmins, Liadh
AU - Cornelisse, Vincent
AU - Duck-Chong, Liz
AU - Wang, Binhuan
AU - Cook, Teddy
N1 - Funding Information:
The Australian Trans and Gender Diverse Sexual Health Survey received funding from the Australian Health and Medical Research Council.
Publisher Copyright:
© Copyright 2021, Mary Ann Liebert, Inc.
PY - 2021/4
Y1 - 2021/4
N2 - Purpose: This study used self-reported gender among trans and gender diverse people in Australia to identify and describe broad, overarching gender categories that encompass the expansive ways in which gender can be defined and expressed. Methods: Data were collected as part of the Australian Trans and Gender Diverse Sexual Health Survey hosted in October 2018. Participant self-identification with nonexclusive gender categories were analyzed using algorithm-based hierarchical clustering; factors associated with gender clusters were identified using logistic regression analyses. Results: Usable data were collected from 1613 trans and gender diverse people in Australia, of whom 71.0% used two or more labels to describe their gender. Three nonexclusive clusters were identified: (i) women/trans women, (ii) men/trans men, and (iii) nonbinary. In total, 33.8% of participants defined their gender in exclusively binary terms (i.e., men/women, trans men/trans women), 40.1% in nonbinary terms, and 26.0% in both binary and nonbinary terms. The following factors were associated with selecting nonbinary versus binary gender labels: presumed female gender at birth (adjusted odds ratio [aOR]=2.02, 95% confidence interval [CI]=1.60-2.54, p<0.001), having a majority of sexual and/or gender minority friends (aOR=2.46, 95% CI=1.49-3.10, p<0.001), and having spent more than half of one's life identifying as trans and/or gender diverse (aOR=1.75, 95% CI=1.37-2.23, p<0.001). Conclusion: Trans and gender diverse people take up diverse and often multiple gender labels, which can be broadly categorized as binary and nonbinary. Systems of health care and research must be adapted to include nonbinary people while remaining amenable to further adaptation.
AB - Purpose: This study used self-reported gender among trans and gender diverse people in Australia to identify and describe broad, overarching gender categories that encompass the expansive ways in which gender can be defined and expressed. Methods: Data were collected as part of the Australian Trans and Gender Diverse Sexual Health Survey hosted in October 2018. Participant self-identification with nonexclusive gender categories were analyzed using algorithm-based hierarchical clustering; factors associated with gender clusters were identified using logistic regression analyses. Results: Usable data were collected from 1613 trans and gender diverse people in Australia, of whom 71.0% used two or more labels to describe their gender. Three nonexclusive clusters were identified: (i) women/trans women, (ii) men/trans men, and (iii) nonbinary. In total, 33.8% of participants defined their gender in exclusively binary terms (i.e., men/women, trans men/trans women), 40.1% in nonbinary terms, and 26.0% in both binary and nonbinary terms. The following factors were associated with selecting nonbinary versus binary gender labels: presumed female gender at birth (adjusted odds ratio [aOR]=2.02, 95% confidence interval [CI]=1.60-2.54, p<0.001), having a majority of sexual and/or gender minority friends (aOR=2.46, 95% CI=1.49-3.10, p<0.001), and having spent more than half of one's life identifying as trans and/or gender diverse (aOR=1.75, 95% CI=1.37-2.23, p<0.001). Conclusion: Trans and gender diverse people take up diverse and often multiple gender labels, which can be broadly categorized as binary and nonbinary. Systems of health care and research must be adapted to include nonbinary people while remaining amenable to further adaptation.
KW - cluster analysis
KW - gender identity
KW - health informatics
KW - nonbinary
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U2 - 10.1089/trgh.2020.0050
DO - 10.1089/trgh.2020.0050
M3 - Article
AN - SCOPUS:85097497628
SN - 2380-193X
VL - 6
SP - 74
EP - 81
JO - Transgender Health
JF - Transgender Health
IS - 2
ER -