The Complexities of Categorizing Gender: A Hierarchical Clustering Analysis of Data from the First Australian Trans and Gender Diverse Sexual Health Survey

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