Abstract
Purpose:
This cross-sectional study of young adult lesbians explores their healthcare experiences including having a primary care provider, forgone care, knowledge of where to obtain Pap testing, and sexually transmitted infection testing.
Methods:
Quantitative surveys were conducted at lesbian, gay, bisexual, and transgender venues and events with a sample of 100 young adult lesbians in New York City between June and October 2016. Using the Andersen model of healthcare access, this study examined associations between sociodemographic characteristics and healthcare experiences using multivariable logistic regression models.
Results:
Having a primary care provider was associated with having health insurance (adjusted odds ratio (AOR) = 4.9, p < 0.05). Both insurance (AOR = 0.2, p < 0.05) and employment (AOR = 0.2, p < 0.05) status were protective against foregone care among young adult lesbians. Disclosure of sexual orientation to a provider improved knowledge of where to access Pap testing (AOR = 7.5, p < 0.05). Disclosure of sexual orientation to friends and family improved knowledge of where to access sexually transmitted infection testing (AOR = 3.6, p < 0.05).
Conclusion:
Socioeconomic factors are significantly associated with healthcare access among young adult lesbians in New York City. Maintaining non-discrimination protections for both healthcare services and insurance coverage are important for this population. In addition, financial subsidies that lower the cost of health insurance coverage may also help improve healthcare access among young adult lesbians.
Keywords: access, healthcare, lesbians, satisfaction, screening
Introduction
Lesbian, gay, bisexual, transgender, and queer (LGBTQ) populations face myriad health disparities compared to non-LGBTQ people.1,2 Lack of access to and low utilization of healthcare services as well as discrimination and stigma in healthcare contribute to these disparities and likely reinforce and perpetuate inequalities.3 Young LGBTQ adults in particular are more likely to have unmet healthcare needs and forego necessary care than non-LGBTQ young adults.4–6 The extant LGBTQ health research focuses on gay and bisexual men, with less focus on lesbians.7 The majority of lesbian health data focuses on adult women or adolescents, while little has addressed the health needs of emerging adult lesbians. Young adults generally have lower rates of healthcare utilization than other age groups,8 and this may be compounded for young adult lesbians (YALs) due to the unique aspects of transitioning into adulthood9 and the stress of sexual orientation disclosure to healthcare providers.10
Previous research has found that lesbians were less likely to have seen a healthcare provider in the previous 12 months and less likely to have a usual source of healthcare than heterosexual women.11 Overall, lesbians were more likely to have unmet healthcare needs due to financial issues.11 Another study found that 34% of the lesbian participants reported decreased healthcare utilization after experiencing a negative healthcare event, such as experiencing discrimination from a healthcare provider. Participants who were younger, did not have health insurance, were employed part time, and did not have a regular healthcare provider were more likely to experience a negative healthcare event.12 Overall, quality of healthcare, negative experiences related to discrimination, and patient passive coping response were associated with lower healthcare utilization.
YALs face two distinct barriers to healthcare access: those faced by lesbians as previously discussed and those faced by young adults. The healthcare needs of young adults are often not fully addressed due to discomfort discussing sexual health needs with providers,13–15 lack of provider knowledge about healthcare needs,16,17 concerns about privacy,18–20 and accidental disclosure of sexual orientation.13,14 These barriers, along with the barriers faced by lesbians, act syndemically to create a unique set of challenges faced by YALs. Furthermore, the need for contraceptive and reproductive health services are often the entry point into the healthcare system for many young adult women21 and help young adult women establish access to healthcare as a healthy behavior at a critical point in their development.22 Healthcare providers may not offer reproductive health services to lesbians based on a perceived lack of need that may not reflect acutal needs as many lesbian women have had sexual intercourse with a male partner.23 In addition, heteronormative assumptions of healthcare providers create tensions in the provider–patient relationship were related to decreased healthcare utilization12 which contributes to the increased reports of unmet medical needs among YALs.6
These barriers result in lower rates of preventive healthcare screenings including Pap and sexually transmitted infection (STI) testing among lesbians.15–18 Similarly, routine Pap testing is critical for the early detection of human papillomavirus (HPV) and cervical cancer; however, the rate of Pap testing among lesbians ranges from 44% to 57%, compared with a range of 75%–84% among American women in general.24 A recent national study found that among women who have sex with women, 53% tested positive for HPV and 37% having a high risk for HPV.25 Lesbians are generally considered to have low risk for STIs, and as a result, STI testing is often neglected,26 which may further complicate the accessibility of testing. STI testing is an important healthcare service for lesbians as transmission of herpes virus, trichomonas, Candida albicans, HPV, and bacterial vaginosis is possible through sexual activity between women.26
These findings suggest that YALs face several disparities that are largely unmet by the healthcare system. Thus, the study presented here seeks to (1) provide critical data about how YALs access healthcare and (2) make recommendations for improving access to care among this population.
Methods
Study design
Participants were recruited between June and October 2016. A list of 23 local LGBTQ venues and events was compiled via searches of lesbian events posted on various social media sites, known lesbian bars, and Pride month events. This list of venues was used to select recruitment sessions using a modified time-space sampling protocol. Venues included LGBTQ community–based health and social service organizations, bars and clubs, LGBTQ community events, college campuses, and public spaces. For each venue, days and times of operation were collected. Initial recruitment was conducted in four of the five boroughs of New York City (NYC). Recruitment did not occur in the Bronx as this borough did not have any LGBTQ-friendly venues. After the initial recruitment events were completed, the research staff identified recruitment events resulted in enrolling at least one participant and these venues were revisited for additional recruitment events.
This study was funded by the Center for Health, Identity, Behavior and Prevention Studies. The (information blinded for peer-review purposes) approved the study protocol (IRB Number IRB-FY2016-854).
Sample
Participants were eligible to participate if they were (1) between the ages of 18–29, (2) identify as female, (3) identify as lesbian, (4) live in the NYC metro area, and (5) reside in the US only during the last five years.
Procedures
Research staff approached women in these public venues, regardless of perceived age or sexual orientation. During the recruitment conversation, research staff identified themselves as research staff, provided information about the study, and informed participants they would receive US$5 for completing the 5- to 10-min survey. Interested individuals were then screened using an iPad. Once eligibility was determined, participants provided tacit consent to enroll in the study. Consent was collected via a yes-or-no option as part of the survey instrument. Surveys were self-administered by participants using iPads using QuickTap (QuickTap, Toronto, Canada) survey software. In total, research staff screened 223 women for eligibility at 38 recruitment events. The final sample comprised 100 women who met the eligibility criteria and completed the survey.
Measures
The Andersen Model of Healthcare Access provides a framework for understanding the relationship between policy, the healthcare system, and the populations at risk (Aday and Andersen, 1974). Using this theory, sociodemographic characteristics were assessed as predisposing factors (age, race/ethnicity, and history of regular healthcare provider), enabling factors (income, school enrollment, employment status, insurance status, and disclosure of sexual orientation to friends and family), and need factors (lifetime history of a sexual healthcare need and general health status and disclosure of sexual orientation to their primary care provider (PCP)).
Sociodemographic characteristics
Data are based on self-reported information.
Predisposing factors
Participants were asked to self-report their age and racial and ethnic background. Age was collected using whole integers for values between 18 and 29 and was dichotomized into two groups: 18–24 and 25–29. Race and ethnicity data were collapsed into a dichotomous variable of White participants and participants of color. Participants were also asked if they had regular access to healthcare during childhood (yes/no).
Enabling factors
Annual income was dichotomized into less than US$14,999 and over US$15,000. This cut-point was based on the 2016 NY State Federal Poverty Level (US$11,880) and Medicaid income level (US$16,394).27 Current school enrollment data were collected via a yes/no question. For current employment status, participants could select employed full-time, employed part-time, or not employed; full-time and part-time employment was collapsed. To assess insurance coverage, participants were asked if they had private health insurance, public health insurance, or not insured. These data were collapsed into insured and uninsured. Finally, participants were asked about how many of their friends/family knew they were lesbians based on a five-point Likert-type scale that was then dichotomized into all, most or some, few, or none.
Need factors
Participants were asked about diagnoses of 10 different STIs (bacterial vaginosis, chlamydia, gonorrhea, hepatitis B, hepatitis C, herpes, HPV, syphilis, trichomoniasis, and human immunodeficiency virus (HIV)) made by a medical provider. For the purpose of this analysis, a composite variable called lifetime sexual healthcare need was created. Data on lifetime history of birth control use, emergency contraception use, STI diagnosis, HIV diagnosis, pregnancy, and abortion were collected via a dichotomous answer choice (yes/no). Any affirmative response to one of the sexual history questions was coded as a “yes.” Participants were also asked to rate their general health status using a five-point Likert-type scale. The responses were dichotomized as excellent/very good or good/fair/poor. Finally, participants were asked if their PCP knew they had sex with women (yes/no).
Healthcare access outcomes
Participants were asked if they currently had a PCP (yes/no). Finally, participants were asked about foregone healthcare. Foregone care was operationalized as a time in the past twelve months when they needed healthcare but did not access services (yes/no). Participants were asked if they knew where to access Pap testing and STI testing via a yes/no question.
Analytic plan
Descriptive statistics were computed for all sociodemographic characteristics (age, race, and ethnicity; access to a pediatrician; income; school enrollment; employment status; insurance status; being out to family/friends; lifetime sexual healthcare need and general physical health; and disclosure of sexual orientation to their PCP) as well as healthcare access outcomes and preventive care access outcomes. All variables were dichotomized prior to the bivariate analysis due to the small study sample. Pearson chi-square tests were used to test associations between dependent and independent variables. Logistic regression was used to test the associations between the covariates and each of the outcome variables. All covariates that were significant at the p < .05 level were included in the constrained model. Analyses were conducted with SPSS version 23.
Results
Univariate analysis
Table 1 describes the sociodemographic characteristics of the sample. The mean age is 24.3 years (standard deviation, 8.2), and 58% (n = 58) of the sample is between the ages of 18 and 24. Approximately half of the sample identified as white (48%, n = 48). Slightly less than one third of the sample self-identified as Hispanic (31.0%, n = 31). The remaining participants identified as black (14.0%, n = 14), Asian or Pacific Islander (2.0%, n = 2), more than one race (4.0%, n = 4), and other (1.0%, n = 1). Slightly more than half (54%, n = 54) of the participants had a sexual healthcare need during their lifetime. Fifty-six percent (n = 56) of the sample reported a very good or excellent self-rated health status, and 51% (n = 51) had disclosed their sexual orientation to their PCP.
Table 1.
Sociodemographic characteristics of participants enrolled in a study of healthcare access, n = 100, 2016, NYC.
| Sociodemographic characteristics | % | N = 100 |
|---|---|---|
| Age (M = 24.27, SD = 8.16) | ||
| Range 18–29 | ||
| 18–24 | 58.0 | 58 |
| 25–29 | 41.0 | 41 |
| Missing | 1.0 | 1 |
| Race/ethnicity | ||
| Hispanic | 31.0 | 31 |
| Black non-Hispanic | 14.0 | 14 |
| White non-Hispanic | 48.0 | 48 |
| Asian/Pacific Islander | 2.0 | 2 |
| More than one race | 4.0 | 4 |
| Other | 1.0 | 1 |
| Regular access to pediatrician | ||
| Yes | 96.0 | 96 |
| No | 4.0 | 4 |
| Income | ||
| US$0–US$9,999 | 33.0 | 33 |
| US$10,000 and over | 63.0 | 63 |
| Missing | 4.0 | 4 |
| School enrollment | ||
| Yes | 54.0 | 54 |
| No | 46.0 | 46 |
| Employment status | ||
| Employed | 84.0 | 84 |
| Not employed | 14.0 | 14 |
| Missing | 2.0 | 2 |
| Insurance status | ||
| Insured | 86.0 | 86 |
| Uninsured | 10.0 | 10 |
| Missing | 4.0 | 4 |
| Disclosure to friends/family | ||
| All/most | 71.0 | 71 |
| Some/few/none | 28.0 | 28 |
| Missing | 1.0 | 1 |
| Lifetime sexual healthcare need | ||
| Yes | 54.0 | 54 |
| No | 46.0 | 46 |
| General health status | ||
| Excellent/very good | 56.0 | 56 |
| Good/fair/poor | 44.0 | 44 |
| Disclosure to PCP | ||
| Yes | 51.0 | 51 |
| No | 21.0 | 21 |
| Missing | 28.0 | 28 |
SD: standard deviation; PCP: primary care provider; NYC: New York City.
Healthcare access outcomes
Table 2 describes the healthcare access outcomes of the sample. Nearly three-fourths of participants have a current PCP (73%, n = 73). Slightly more than a quarter of the of the women in this study reported a time in the past 12 months when they needed care but did not get care (27%, n = 27). The majority of the sample knew where to access services: 89.0% (n = 89) knew where to access Pap tests and 87% (n = 87) knew where to access STI testing.
Table 2.
Healthcare access outcomes of participants enrolled in a study of healthcare access, n = 100, 2016, NYC.
| Healthcare access outcomes | % | N = 100 |
|---|---|---|
| Have primary care provider | ||
| No | 27.0 | 27 |
| Yes | 73.0 | 73 |
| Foregone healthcare | ||
| Yes | 27.0 | 27 |
| No | 73.0 | 73 |
| Where to access Pap testing | ||
| Yes | 89.0 | 89 |
| No | 11.0 | 11 |
| Where to access STI testing | ||
| Yes | 87.0 | 87 |
| No | 13.0 | 13 |
STI: sexually transmitted infection; NYC: New York City.
Multivariate analysis
The final multivariable logistic regression models are presented in Table 3. The model for having a PCP achieved significance (χ2(2) = 7.8, p = 0.02) with Nagelkerke R2 = 11.4%. The odds of reporting having a PCP were higher among those who were enrolled in school (odds ratio (OR) = 2.6, 95% confidence interval (CI) 1.0–6.6, p < 0.05). Similarly, the odds of reporting having a PCP were also higher among those who had health insurance (either public or private) (OR = 5.3, 95% CI 1.4–20.7, p < 0.05). In the adjusted model, only insurance was significantly associated with higher odds of having a PCP (adjusted odds ratio (AOR) = 4.9, 95% CI 1.2–19.4, p < 0.05).
Table 3.
Multivariable logistic regression model examining associations between sociodemographic and health-related factors of participants enrolled in a study of healthcare access, n = 100, 2016, NYC.
| Unadjusted model |
Adjusted model |
|||||
|---|---|---|---|---|---|---|
| OR | 95% CI | p-value | OR | 95% CI | p-value | |
| Have primary care provider | ||||||
| Age | 0.6 | 0.28–1.4 | 0.199 | – | – | – |
| Race/ethnicity | 0.7 | 0.3–1.6 | 0.359 | – | – | – |
| Regular access to pediatrician | 2.8 | 0.4–21.2 | 0.309 | – | – | – |
| Income | 0.6 | 0.2–1.5 | 0.264 | – | – | – |
| Enrolled in school | 2.6 | 1.1–6.6 | 0.049* | 2.0 | 0.7–5.4 | 0.167 |
| Employment status | 1.6 | 0.5–5.2 | 0.463 | – | – | – |
| Insurance status | 5.3 | 1.4–20.7 | 0.017* | 4.9 | 1.2–19.4 | 0.025* |
| Disclosure to friends/family | 0.9 | 0.3–2.3 | 0.750 | – | – | – |
| Lifetime sexual healthcare need | 0.7 | 0.3–1.8 | 0.522 | – | – | – |
| General health status | 1.0 | 0.4–2.5 | 0.957 | – | – | – |
| Disclosure to PCP | a | a | a | – | – | – |
| Foregone care | ||||||
| Age | 0.8 | 0.3–1.9 | 0.589 | – | – | – |
| Race/ethnicity | 0.8 | 0.4–2.0 | 0.665 | – | – | – |
| Regular access to pediatrician | 0.4 | 0.1–2.6 | 0.309 | – | – | – |
| Income | 0.5 | 0.2–1.2 | 0.111 | – | – | – |
| Enrolled in school | 1.4 | 0.6–3.3 | 0.476 | – | – | – |
| Employment status | 0.3 | 0.1–0.9 | 0.039* | 0.2 | 0.1–0.8 | 0.022* |
| Insurance status | 0.2 | 0.1–0.8 | 0.021* | 0.2 | 0.1–0.7 | 0.011* |
| Disclosure to friends/family | 0.5 | 0.2–1.4 | 0.183 | – | – | – |
| Lifetime sexual healthcare need | 2.1 | 0.8–5.2 | 0.126 | – | – | – |
| General health status | 0.6 | 0.3–1.6 | 0.338 | – | – | – |
| Disclosure to PCP | 1.3 | 0.4–4.6 | 0.678 | – | – | – |
| Where to access Pap testing | ||||||
| Age | 3.6 | 0.7–1.7 | 0.116 | – | – | – |
| Race/ethnicity | 2.7 | 0.7–11.1 | 0.157 | – | – | – |
| Regular access to pediatrician | 2.9 | 0.3–30.2 | 0.381 | – | – | – |
| Income | 9.2 | 1.9–45.3 | 0.007** | 4.8 | 0.4–55.5 | 0.206 |
| Enrolled in school | 0.4 | 0.1–1.6 | 0.222 | – | – | – |
| Employment status | 5.2 | 1.2–21.6 | 0.023* | 8.6 | 0.9–75.5 | 0.052 |
| Insurance status | 1.3 | 0.3–11.4 | 0.841 | – | – | – |
| Disclosure to friends/family | 3.6 | 1.0–13.0 | 0.500 | – | – | – |
| Lifetime sexual healthcare need | 0.9 | 0.2–3.4 | 0.969 | – | – | – |
| General health status | 1.1 | 0.3–3.8 | 0.918 | – | – | – |
| Disclosure to PCP | 9.8 | 1.8–53.7 | 0.009** | 7.5 | 1.1–54.9 | 0.048* |
| Where to access STI testing | ||||||
| Age | 1.7 | 0.5–5.9 | 0.407 | – | – | – |
| Race/ethnicity | 2.3 | 0.7–8.0 | 0.191 | – | – | – |
| Regular access to pediatrician | 2.3 | 0.2–24.3 | 0.478 | – | – | – |
| Income | 1.4 | 0.4–4.7 | 0.546 | – | – | – |
| Enrolled in school | 1.4 | 0.4–4.7 | 0.560 | – | – | – |
| Employment status | 0.5 | 0.1–3.9 | 0.476 | – | – | – |
| Insurance status | 3.7 | 0.8–16.7 | 0.094 | – | – | – |
| Disclosure to friends/family | 3.6 | 1.1–11.9 | 0.035* | 3.6 | 1.1–11.9 | 0.035* |
| Lifetime sexual healthcare need | 3.0 | 0.9–10.6 | 0.082 | – | – | – |
| General health status | 1.1 | 0.3–3.6 | 0.867 | – | – | – |
| Disclosure to PCP | 3.7 | 0.9–15.4 | 0.075 | – | – | – |
OR: odds ratio; CI: confidence interval; PCP: primary care provider; STI: sexually transmitted infection; NYC: New York City.
statistics not computed based on skip logic.
p < 0.05, **p < 0.01.
The model for foregone care achieved significance (χ2(2) = 10.8, p = 0.004) with Nagelkerke R2 = 15.8%. Participants who were employed had lower odds of reporting an instance of foregone care in the past 12 months (OR = 0.3, 95% CI 0.1–0.9, p < 0.05). Those with health insurance were less likely to reporting having foregone care at least once in the past 12 months (OR = 0.20, 95% CI 0.1–0.8, p < 0.05). In the adjusted model, both employment and insurance status retained significance. Participants who were employed were less likely to report forgoing care (AOR = 0.2, 95% CI 0.1–0.8, p < 0.05). Insurance status also had a protective effect against foregone care. Those with insurance were less likely to report an instance of foregone care in the past 12 months (AOR = 0.16, 95% CI 0.1–0.7, p < 0.05).
Similarly, the model for knowledge of where to access Pap testing achieved significance (χ2(3) = 16.6, p = 0.001) with Nagelkerke R2 = 45.0%. The model for knowledge of where to access STI testing achieved significance (χ2(1) = 4.4, p = 0.036) with Nagelkerke R2 = 8.0%. Participants who had disclosed their sexual orientation to their friends and family were more likely to report knowing where to access STI testing (OR = 3.6, 95% CI 1.1–11.9, p < 0.05).
Discussion
Under the Trump Administration, there is an increasing uncertainty of healthcare access as proposed changes to the Affordable Care Act continue to be considered. This study contributes to our understanding of how YALs experience healthcare access, with a particular focus on how enabling factors—specifically, employment status and health insurance—shape this population’s ability to access care. Our study found that having insurance was positively associated with having a PCP and negatively associated with choosing to forego care. This aligns with previous research that has found that lesbians cite inadequate insurance coverage as a barrier to accessing healthcare.28 The connection between insurance coverage and access to healthcare services is well documented,7,11 but even when lesbians had health insurance, this population is still more likely to delay healthcare due to financial concerns.29 In our study, most participants knew where to obtain the medical/preventive services analyzed, but income level and insurance seem to play a major role in accessing these services, particularly in the areas of Pap testing.
For YALs, the decision to delay healthcare is likely also related to the difficulty in finding healthcare providers that are trained in their healthcare needs.28 Implicit provider bias against LGBTQ patients further complicates the patient–provider relationship.30–32 Moreover, discrimination of LGBTQ populations has a detrimental effect on healthcare utilization. For example, lesbians in states with anti-discrimination legislation were more likely to disclose their sexual orientation to their providers.33 Taken together, these findings suggest that institutional changes are critical.
Pap testing and STI testing are important parts of preventive healthcare for lesbians, and these findings can be used to inform the development of policies, programming, and interventions that aim to increase healthcare engagement among YALs. These efforts should focus on improving access and decreasing stigma. In particular, clinicians of all types should be trained to serve and communicate effectively with this population, and public health should increase its messaging toward YALs.
Limitations
There are several limitations to this study, first being the modest sample size. Research staff found that it was difficult to recruit women that identified as lesbians. Sexual orientation research indicates that women’s sexuality and self-identification fall along a spectrum instead of a binary construct.34 Screener data analysis revealed that a reported sexual orientation other than lesbian was the most common reason for ineligibility to participate in the study. Second, these data were self-reported and therefore subject to social desirability and recall bias; however, data were collected via iPads to provide some level of privacy in an attempt to mitigate these biases. Next, the PCP measure does not explicitly state a specialty (e.g. internal medicine), so we do not know what type of provider participants consider as their PCP. Research indicates that young women tend to engage with reproductive healthcare at higher rates that other types of care,35–37 and the lack of definition for PCP may conflate access to reproductive care with access to primary care. Last, this study is conducted in NYC where there are numerous organizations that provide LGBTQ-friendly and/or low-cost healthcare. These facilities act as facilitators to healthcare access and thus reduce the generalizability of this study to other non-urban locales.
Conclusion
This study contributes to the literature on lesbians’ healthcare access by specifically examining the period of young adulthood and may help explain how these habits affect the healthcare of lesbians across their life course. In addition, this study underscores the need for provider training on health issues facing lesbian patients. An important first step would be to develop inclusive intake forms that provide options for sexual orientation and gender identity for both the index patient and their partner or partners. These forms act as an important cue for patients that they should discuss these topics with their providers. Furthermore, provider trainings should be incorporated into medical school curriculums and continuing education courses should be developed to help address the disparity in access to sexual and reproductive healthcare and screening services for lesbian patients.
Acknowledgments
CHIBPS staff members contributed to the development of the survey instrument.
Footnotes
Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.
ORCID iD: Marybec Griffin 
https://orcid.org/0000-0002-4840-3293
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