(PS1-C64) Deriving Subgroups of Transgender Peoples' Exposure to Adverse Childhood Experiences

Adverse childhood experiences (ACEs), defined as potentially traumatic and negative life events experienced before the age of 18, have previously been found to be associated with a wide variety of negative psychosocial outcomes in adulthood (e.g., depression, reduced quality of life, substance abuse). Exposure to ACEs has been shown to display dose response curves with regard to many of these outcomes, such that the higher the number of ACE domains that an individual experiences (e.g., parental substance use, child abuse/neglect), the more likely they are to experience negative outcomes across domains. Much of the previous research on this topic has focused solely on the number of types of ACEs experienced, rather than other potentially relevant factors, such as specific combinations of these experiences. This may ignore crucial information, as is possible some ACE domains are more detrimental than others; additionally, some specific combinations of ACEs might be much more predictive of negative outcomes later in life than others.

Members of gender minorities (e.g., transgender people) face a variety of unique stressors (e.g., transphobia, transmisogyny) and have been found to have worse mental and physical health when compared to the overall population (Meyer et al., 2017). Additionally, previous research has found that transgender people in the United States report experiencing more domains of ACEs than cisgender members of sexual minorities. The intersection between exposure to ACEs and other stressors experienced by transgender individuals is an important area to further investigate, in order to better identify individuals who may be at extreme risk of negative outcomes. Mixture modeling, such as latent class analysis, provides one avenue for better understanding common patterns of exposure to ACEs that transgender individuals might exhibit. Although this approach has been used in multiple studies of the general population, no study to date has assessed latent subgroups of transgender peoples’ exposure to ACEs.

This study used latent class analysis to determine patterns of ACEs in a sample of individuals who responded to the Centers for Disease Control and Prevention’s 2010 Behavioral Risk Factor Surveillance System, a random-digit dialed national phone survey. 310 individuals were grouped into classes based on their pattern of experiencing nine domains of ACEs (household mental illness, household alcoholism, household substance use, incarceration, parental divorce, domestic violence, physical abuse, emotional abuse, and sexual abuse). Based on a variety of fit indices (e.g., Bayesian Information Criterion), as well as the interpretability of the derived model, a four-class structure was found to best explain the data. These classes were characterized by 1) Moderate Household Dysfunction (32.3% of sample), 2) High ACEs (11.0%), 3) Abuse and Conflict (10.3%), and 4) Low ACEs (46.5%). These derived classes will be compared to those previously found in largely cisgender samples. Additional findings and implications for studying patterns of ACE exposure will be discussed.