Caregiving and Sexual/Gender Minorities: Evidence from a National Sample

Background: Informal caregiving is extremely common: 1-in-8 U.S. adults provide unpaid caregiving to another adult, often a family or friend and typically someone in later life. Despite a considerable body of caregiving research, still very little is known about sexual and gender minority caregivers. Berkman and Glass (2000) theorized that social networks influence health via psychosocial pathways, including social support and caregiving. Moreover, it is well established that sexual and gender minority (SGM) adults (e.g., lesbian, bisexual, gay, transgender or gender non-conforming individuals) have different social networks, particularly a greater salience of chosen family and fewer children, than cis-gender heterosexuals. However, few population-representative studies to date have explored differences in prevalence or the dynamics of caregiving between SGM and non-SGM adults.

Methods: This study used Behavioral Risk Factor Surveillance Survey (BRFSS) data, an annual, cross-sectional telephone survey, from the 18 states that included optional modules on caregiving and SGM status, respectively, in either 2015 or 2016 (n=124,689). Respondents self-reported sexual and gender orientation, respectively; we dichotomized these responses to any SGM (i.e., any lesbian, gay, bisexual, transgender, or gender non-conforming individuals) and non-SGM (e.g. cis-gender, heterosexual). Respondents also reported their caregiving behavior in the last year from which we created 5 binary dependent variables: caregiving prevalence (any/none), duration (>6 months vs. 0-6 months), frequency (>8 vs. 0-8 hours per week), type of caregiving (HIV vs. non-HIV caregiving), relationship (non-family vs. a family member). We tested differences in the odds of caregiving by SGM status with logistic regression models, adjusted for age and race.

Results: The total sample of 124,689 included 3,594 (2.88%) SGM respondents. In the year prior to the survey, the prevalence of caregiving was slightly, and statistically significantly higher in SGM (22.9%) than in non-SGM (20.5%; chi-square(1df): 12.864, p<0.001). In age and race adjusted models, SGM had 17% higher odds of caregiving (Odds Ratio (OR): 1.17, 95% Confidence Interval (CI): 1.08, 1.27, p<0.001) than non-SGM. Among caregivers, SGM had slightly higher, but not statistically significant, odds of spending more hours caregiving (OR: 1.13, 95% CI: 0.97, 1.31) or caregiving for longer duration (OR: 1.05, 95% CI: 0.92, 1.20), than non-SGM. However, SGM caregivers had significantly higher odds of caring for a non-family member (OR:1.54, 95% CI: 1.30, 1.81), after adjusting for age and race, than non-SGM.

Conclusions: SGM were more likely to be caregivers, provided a similar amount of care and over a similar period of time, and were more likely to provide caregiving to non-family than non-SGM adults. These findings suggest SGM caregivers may be at similar, if not higher risk for caregiving consequences like stress and caregiving burden, than non-SGM, which could exacerbate existing, minority stress (Meyer 2003) sexual and gender minority adults face. Moreover, we speculate that SGM caregivers may be less “seen” as caregivers and offered caregiving services (e.g., supportive interventions, health information) because they are more likely to be caring for non-family. Future social work research on caregiving should address these dynamics of stress and isolation/integration among SGM caregivers.