| Literature DB >> 31641691 |
James A Griffin1, Tracy N Casanova2, Elizabeth D Eldridge-Smith2, Lara M Stepleman2.
Abstract
Purpose: Transgender individuals continue to face wide-ranging health disparities, which may be due in part to unique and chronic gender identity-related stressors. The present study assessed the relationships between barriers to health care, proximal minority stress related to perceived community safety, and overall health perceptions of transgender individuals living in a small metropolitan region of the Southern United States.Entities:
Keywords: barriers to care; gender minority stress; health disparities; transgender health
Year: 2019 PMID: 31641691 PMCID: PMC6802727 DOI: 10.1089/trgh.2019.0028
Source DB: PubMed Journal: Transgend Health ISSN: 2380-193X
Sample Demographics (N=66)
| Variables | Range | ||
|---|---|---|---|
| Age (years) | 18–75 | 30.33 (11.68) | |
| Race | |||
| White | 47 (71.2) | ||
| Black | 5 (7.6) | ||
| Hispanic | 5 (7.6) | ||
| Other | 9 (13.6) | ||
| Gender identity | |||
| Transgender men | 22 (33.3) | ||
| Transgender women | 20 (30.3) | ||
| Gender nonbinary | 24 (36.4) | ||
| Education level | |||
| <High school | 1 (1.6) | ||
| Diploma/GED | 13 (20.3) | ||
| Some college | 30 (46.9) | ||
| Associate's degree | 7 (10.9) | ||
| Bachelor's degree | 7 (10.9) | ||
| Graduate degree | 5 (7.8) | ||
| Doctoral/professional degree | 1 (1.6) | ||
| Household income (USD) | |||
| <10,000 | 12 (23.5) | ||
| 10,000–14,999 | 10 (19.6) | ||
| 15,000–19,999 | 4 (7.8) | ||
| 20,000–29,999 | 2 (3.9) | ||
| 30,000–30,999 | 3 (5.9) | ||
| 40,000–49,999 | 6 (11.8) | ||
| 50,000–74,999 | 7 (13.7) | ||
| 75,000–99,999 | 4 (7.8) | ||
| 100,000+ | 3 (5.9) | ||
Valid percentages reported due to missing data for some variables.
GED, general education development; SD, standard deviation; USD, US dollars.
Correlations Between Health Perceptions, Demographics, and Gender Minority Stressors (N=66)
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |
|---|---|---|---|---|---|---|---|---|
| 1. Health perception | — | |||||||
| 2. Age | −0.062 | — | ||||||
| 3. White | 0.172 | 0.014 | — | |||||
| 4. Education level | −0.125 | 0.282[ | 0.225 | — | ||||
| 5. Medical access barriers | 0.243 | 0.102 | 0.096 | 0.066 | — | |||
| 6. Psychosocial needs barriers | 0.405[ | 0.029 | 0.173 | −0.062 | 0.504[ | — | ||
| 7. Personal resource barriers | 0.432[ | −0.087 | 0.015 | −0.301[ | 0.443[ | 0.267[ | — | |
| 8. Perceived lack of safety | 0.342[ | −0.112 | 0.368[ | 0.083 | 0.393[ | 0.355[ | 0.128 | — |
p<0.05; **p<0.01.
Point biserial correlations reported where one variable is dichotomous. Pearson correlations reported where both variables are continuous.
Multiple Linear Regression Model of Gender Minority Stress Variables Predicting Health Perceptions (N=62)
| Variables | Step 1 | Step 2 | ||
|---|---|---|---|---|
| 95% CI | 95% CI | |||
| 1. Psychosocial needs barriers | 0.339[ | 0.208 to 1.907 | 0.249[ | 0.004 to 0.534 |
| 2. Personal resource barriers | 0.233 | −0.004 to 0.427 | 0.224 | −0.007 to 0.412 |
| 3. Perceived lack of safety | 0.259[ | 0.024 to 0.575 | ||
p<0.05, **p<0.01.
Model Summary: Step 1 R2=0.212, F(2,60)=8.050, p<0.05; Step 2 R2=0.270, F(3,59)=7.283, p<0.05.
CI, confidence interval.