Monitoring the health of transgender and other gender minority populations: Validity of natal sex and gender identity survey items in a U.S. national cohort of young adults

Background: A barrier to monitoring the health of gender minority (transgender) populations is the lack of brief, validated tools with which to identify participants in surveillance systems. Methods: We used the Growing Up Today Study (GUTS), a prospective cohort study of U.S. young adults (mean age = 20.7 years in 2005), to assess the validity of self-report measures and implement a two-step method to measure gender minority status (step 1: assigned sex at birth, step 2: current gender identity). A mixed-methods study was conducted in 2013. Construct validity was evaluated in secondary data analysis of the 2010 wave (n = 7,831). Cognitive testing interviews of close-ended measures were conducted with a subsample of participants (n = 39). Results: Compared to cisgender (non-transgender) participants, transgender participants had higher levels of recalled childhood gender nonconformity age < 11 years and current socially assigned gender nonconformity and were more likely to have ever identified as not completely heterosexual (p < 0.001). No problems with item comprehension were found for cisgender or gender minority participants. Assigned sex at birth was interpreted as sex designated on a birth certificate; transgender was understood to be a difference between a person’s natal sex and gender identity. Participants were correctly classified as male, female, or transgender. Conclusions: The survey items performed well in this sample and are recommended for further evaluation in languages other than English and with diverse samples in terms of age, race/ethnicity, and socioeconomic status

Sexual Orientation/Gender Identity, Socioeconomic Status, and Health across the Life Course (SOGI-SES) Survey with Specifications

SOGI-SES used an online survey; there was no paper survey option. The programmed survey uses extensive skip patterns to simplify content flow and decrease burden for respondents. All survey questions, skip logic, and programmer notes are included below. For data analysis purposes, we recommend using this document in combination with the study’s Codebooks, Index (located at the end of the Restricted-Use Codebook) and associated User Guide available at Add Health’s website - https://addhealth.cpc.unc.edu/