Table 2.

Association Between Insurance Status and Gender-Affirming Hormone Use Among Respondents to the 2015 US Transgender Survey

CharacteristicUse of Nonprescription Hormones, Among Those Using Hormonesa (n = 12,037)Use of Hormones, Among Those Interested (n = 21,237)
aOR (95% CI)P ValueaOR (95% CI)P Value
Uninsured (compared with insured)2.64 (1.88-3.71)<.0010.37 (0.24-0.56)<.001
Age (for each additional year)0.986 (0.975-0.996).0080.969 (0.96-0.98)<.001
Gender identity (compared with trans man)
   Trans woman3.71 (2.30-5.00)<.0010.56 (0.40-0.77)<.001
   Assigned female at birth, genderqueer/nonbinary2.41 (1.25-4.65).0090.16 (0.10-0.23)<.001
   Assigned male at birth, genderqueer/nonbinary6.02 (2.82-12.82)<.0010.19 (0.10-0.39)<.001
Race (compared with White)
   Alaska Native/American Indian0.49 (0.22-1.09).080.93 (0.35-2.44).88
   Asian/Native Hawaiian/Pacific Islander2.72 (0.94-7.89).061.30 (0.65-2.62).45
   Biracial/multiracial/not listed3.28 (1.92-5.61)<.0011.23 (0.76-1.98).39
   Black/African American0.92 (0.55-1.56).770.75 (0.40-1.38).35
   Latinx/Hispanic1.07 (0.60-1.89).821.01 (0.51-1.97).98
   Middle Eastern/North African3.68 (0.66-20.45).142.06 (0.50-8.39).31
Education (compared with less than high school)
   High school1.38 (0.62-3.08).430.47 (0.19-1.17).10
   Some college1.32 (0.63-2.78).460.56 (0.24-1.27).16
   Bachelor’s degree or higher1.13 (0.51-2.50).760.50 (0.22-1.15).10
At or near poverty level0.80 (0.57-1.13).200.76 (0.51-1.14).19
  • aOR = adjusted odds ratio.

  • Note: Data analyzed using weighted multivariable logistic regression. For all analyses, crossdressers were excluded from the overall sample because of their unique characteristics.

  • a Analysis excluded respondents currently in active military service, given their unique pathways to accessing gender-affirming hormones.