Abstract
Background:
Adults with poor access to care are known to have worse quality of life (QoL). The purpose of this study was to determine cancer survivors’ differences in access to care by sexual orientation and to examine the association between access to care and QoL.
Methods:
This secondary data analysis utilized 4 years of Behavior Risk Factor Surveillance Survey data on adult men and women who self-reported a history of cancer. Among the 70,524 cancer survivors, 1,931 self-identified as sexual minorities, defined as lesbian, gay, bisexual, or other non-heterosexual.
Results:
Sexual minority women had significantly more access deficits compared to heterosexual women (42.7% vs. 28.0%; p<.0001), while men of different sexual orientations had similar access to care. Access deficits among sexual minority women had higher odds of poor physical QoL compared to heterosexual women (odds ratio (OR), 2.0; 95% confidence interval (CI), 1.2–3.4 vs. OR, 1.3; 95% CI, 1.2–1.5), poor mental QoL (OR, 1.8; 95% CI, 1.1–3.1vs. OR, 1.5; 95% CI, 1.3–1.7), and difficulties concentrating (OR, 2.0; 95% CI, 1.2–3.5 vs. OR, 1.7; 95% CI, 1.4–1.9). Access deficits had greater odds of difficulty concentrating among sexual minority men than heterosexual men (OR, 4.3; 95% CI, 2.0–9.3 vs. OR, 1.5; 95% CI, 1.2–1.9). Among men, sexual minority status increased the odds of poor mental QoL (OR, 1.49; 95% CI, 1.11– 2.01).
Conclusions:
Sexual minority cancer survivors’ access to care needs improvement, sexual minority women being a focus, in that their poor access to care more strongly relates to worse QoL.
Keywords: Cancer Survivorship, Sexual minorities, Access to Care, Quality of Life, Disparities
Precis
Access to care is linked to cancer survivors’ quality of life. This study identified inequities in cancer survivors’ access to care by sexual orientation and showed that the association between access to care and quality of life is stronger for sexual minority cancer survivors than heterosexual cancer survivors.
Achieving health equity for all US Americans through improving access to comprehensive quality health care services is a key goal of Healthy People 2020 and of paramount importance across the cancer continuum.1, 2 Access to care encompasses multiple dimensions and has been defined as “the timely use of personal health services to achieve the best health outcomes.”3 The multiple dimensions of access to care are interwoven, with health insurance being a major determinant in access: individuals with health insurance are more likely to have a primary care provider and thus receive care in a more timely manner.4 Evidence from general (non-cancer) studies shows that sexual minorities, here defined as lesbian, gay, bisexual, or other non-heterosexual identified individuals, have worse access to care and have been declared a health disparate population.5–7 Although disparities identified in the general population also occur among cancer survivors,8–10 studies of sexual minority cancer survivors’ access to care are lacking.11
Cancer is widely recognized as having long-term and late physical and psychological effects on cancer survivors;12, 13 one reason regular follow up is recommended.14 Cancer survivors without health insurance may not follow recommendations to monitor their cancer or comply with other preventive medical care.15 Studies point to multiple access barriers that interfere with health care utilization, even among insured cancer survivors.8 For example, insured survivors may find co-payments an obstacle, leading to a delay in needed care.8, 16, 17 Poor access to care has been linked to adverse outcomes among cancer survivors, namely recurrence, poorer disease-free and overall survival, and poorer QoL.14–16, 18–20
While sexual minorities in the general population are known to have poorer access to care compared to their heterosexual counterparts,7, 21 sexual minority cancer survivors’ access to care is unknown and its association to QoL has never been examined. This study examined the link between access to care and QoL, using four years of the Behavioral Risk Factor Surveillance System (BRFSS) data on cancer survivors, comparing sexual minority and heterosexual survivors in separate analyses of men and women. Consistent with the current understanding of sexual minority health inequities, rooted in sexual minorities’ personal and structural barriers to access to care,7 we hypothesized that sexual minority cancer survivors will have poorer access to care compared to heterosexual cancer survivors. Second, we hypothesized that the association between access to care and QoL will be stronger among sexual minority than heterosexual survivors. This is consistent with Meyer’s minority stress model, which posits sexual minorities’ disadvantaged status in society subjects them to discrimination, victimization, and social prejudice, and contributes to worse mental health.22
Methods
Annually, the Centers for Disease Control and Prevention administers via telephone the BRFSS Survey to the noninstitutionalized adult population ≥ 18 years residing in the US. The BRFSS core data captures information from all 50 states, the District of Columbia, Puerto Rico, and Guam. Since 2014, states may elect to augment their annual survey with a sexual orientation and gender identity (SOGI) module. More specific information about BRFSS can be obtained at (https://www.cdc.gov/brfss/index.html).
Study population
We combined 2014, 2015, 2016, and 2017 BRFSS data, utilizing data from the 35 states and Guam that collected SOGI data. This resulted in 712,119 respondents who reported their sexual orientation as straight, lesbian or gay, bisexual, or other. We restricted the analytic sample to individuals who responded yes to the question, “Have you ever been told you have cancer (other than skin cancer)”, which resulted in 70,797 respondents. We then removed 263 transgender individuals because of their small sample size and 10 individuals who had missing information on sex, resulting in a final analytic sample of 70,524 cancer survivors.
Measures
For sexual orientation comparisons, we created a dichotomous variable by defining as sexual minority individuals those who self-reported as lesbian, gay, bisexual, or other versus individuals who self-reported as heterosexual. Other sociodemographic characteristics included binary gender (male/female), measures of age, race/ethnicity, education level, marital status, employment status, and annual household income, retaining BRFSS response categories or combining categories to avoid small cell sizes.
The BRFSS assesses four dimensions of access to care: (1) not having health insurance, (2) delaying care, (3) avoiding care because of costs, and (4) lacking a trusted physician, which we coded into dichotomous (yes/no) responses. Consistent with prior research, we derived a dichotomous summary measure of poor access to care or access deficit.20 Survivors are defined as having poor access to care if they are lacking any one of the four access to care conditions.
From the available health-related QoL measures in the BRFSS, we selected three measures to capture different dimensions of cancer survivors’ QoL. We chose two healthy day measures to capture cancer survivors’ mental and physical QoL: the number of days an individual reported poor mental health and a separate question about poor physical health, in the past 30 days. We followed the BRFSS and prior research’s categorization of poor mental health days into 0 days to describe absence of mental distress, 1–13 days to capture infrequent mental distress and 14 or more days, which is a proxy for clinical depression and anxiety disorders.23–25 Poor physical health days were categorized analogously.23–25 The third measure captured yes/no responses to cognitive deficits: difficulty concentrating, remembering, or making decisions because of a physical, mental, or emotional condition. We chose this measure of psychological QoL because difficulty concentrating is prevalent among cancer patients.26, 27
Statistical Analysis
Consistent with the complex sampling design of the BRFSS, we performed weighted analyses, utilizing the raking weights provided with the BRFSS data set. Because our data set entailed four years of data, we adjusted the weights for states that collected multiple years of SOGI data. We calculated weighted frequencies and standard errors for categorical variables, and means and standard deviations for continuous variables, performing non-directional statistical tests (Tables 1–2). We examined each dimension of access to care and performed sensitivity analyses to determine access deficits among insured survivors and separate analyses among survivors aged 18 to 64, prior to Medicare eligibility. To test associations between access to care and each QoL outcome, we used the summary measure of poor access to care. We computed odds ratios and 95% confidence intervals (CI) using cumulative logit models (proportional odds ratios) for poor physical and poor mental health days, and logistic regressions for difficulty concentrating. All final models (Table 3, 4, and 5) considered relevant confounders. Consistent with recent concerns that adjusting for social factors may conceal salient differences in cancer survivorship,28 we calculated separate final models for each sexual orientation to reveal potential differences in the strength of the relationship between poor access to care and each QoL measure. All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC) software.
Table 1.
Characteristics of Analytic Sample of Cancer Survivors, Behavioral Risk Factor Surveillance Survey (BRFSS) 2014–2017 (N=70,524)
| Sexual Minority Men % (SE) |
Heterosexual Men % (SE) |
p | Sexual Minority Women % (SE) |
Heterosexual Women % (SE) |
p | |
|---|---|---|---|---|---|---|
| Unweighted Sample Size, N | 782 | 24,422 | 1,149 | 44,171 | ||
| Weighted Frequency, % (SE) | 3.23 (0.25) | 96.77 (0.25) | 3.28 (0.26) | 96.72 (0.26) | ||
| Demographics | ||||||
| Age†, mean (SE) | 58.17 (1.37) | 66.18 (0.23) | <.0001 | 51.74 (1.38) | 61.85 (0.18) | <.0001 |
| Age Categories 18–44 years 45–64 years 65 years or older |
21.27 (3.45) 40.96 (3.75) 37.76 (3.79) |
6.89 (0.53) 30.55 (0.71) 62.56 (0.77) |
<.0001 |
37.09 (3.72) 34.42 (3.31) 28.49 (4.75) |
12.95 (0.45) 38.79 (0.64) 48.26 (0.63) |
<.0001 |
| Race/Ethnicity Non-Hispanic White Non-Hispanic Black Non-Hispanic Other Hispanic |
72.26 (3.62) 10.90 (2.90) 7.68 (2.00) 9.16 (2.05) |
79.43 (0.76) 9.75 (0.46) 4.15 (0.38) 6.66 (0.62) |
0.1576 |
65.66 (4.78) 9.97 (2.03) 15.44 (5.28) 8.93 (2.10) |
77.66 (0.68) 8.51 (0.41) 6.04 (0.42) 7.79 (0.54) |
0.1543 |
| Education High School or less Some College/Technical School College Grad/Graduate School |
34.73 (4.05) 24.05 (3.17) 41.23 (3.67) |
39.07 (0.76) 30.07 (0.71) 30.86 (0.66) |
0.0108 |
38.39 (3.81) 37.14 (4.51) 24.47 (2.52) |
40.93 (0.64) 33.63 (0.62) 25.43 (0.52) |
0.7555 |
| Marital Status Married/Unmarried Couple Single/Never Married Widowed/Separated/Divorced |
38.75 (3.94) 34.56 (3.52) 26.68 (3.48) |
67.23 (0.76) 7.46 (0.42) 25.31 (0.72) |
<.0001 |
36.85 (3.50) 25.44 (3.29) 37.71 (4.47) |
52.66 (0.64) 8.01 (0.36) 39.33 (0.61) |
<.0001 |
| Employment Status Employed for Wages Other |
36.48 (3.77) 63.52 (3.77) |
31.18 (0.73) 68.82 (0.73) |
0.1709 |
42.46 (3.83) 57.54 (3.83) |
31.36 (0.60) 68.64 (0.60) |
0.0025 |
| Annual Household Income < $35,000 $35,000-$74,999 $75,000 or greater MissingΩ |
37.45 (3.62) 24.14 (3.00) 26.65 (3.45) 11.76 (3.58) |
29.35 (0.70) 28.46 (0.68) 29.54 (0.70) 12.66 (0.50) |
0.1347 |
43.41 (3.84) 20.45 (2.94) 23.65 (4.82) 12.49 (2.04) |
37.82 (0.61) 22.71 (0.50) 22.47 (0.58) 17.00 (0.49) |
0.0848 |
| Quality of Life Outcomes | ||||||
| Poor physical health days 0 1–13 14 or more |
43.51 (3.85) 28.26 (3.39) 28.23 (3.77) |
54.73 (0.77) 22.31 (0.65) 22.97 (0.63) |
0.0202 |
36.57 (4.69) 29.55 (3.17) 33.88 (3.42) |
48.83 (0.65) 25.75 (0.59) 25.41 (0.53) |
0.0108 |
| Poor mental health days 0 1–13 14 or more |
54.78 (3.91) 25.72 (3.56) 19.50 (2.93) |
73.23 (0.75) 16.17 (0.64) 10.59 (0.52) |
<.0001 |
47.67 (4.22) 22.65 (2.97) 29.68 (3.27) |
61.14 (0.63) 22.29 (0.50) 16.57 (0.51) |
0.0001 |
| Difficulty concentrating or making decisions because of physical, mental, or emotional condition |
23.91 (3.20) |
11.53 (0.50) |
0.0002 |
27.58 (2.91) |
17.13 (0.46) |
<.0001 |
Age is truncated at 80, coding all individuals who are 80 or older as 80 years of age.
Missing income was considered in the analysis.
Table 2.
Male and Female Cancer Survivors’ Access to Care by Sexual Orientation
| Sexual Minority Men % (SE) |
Heterosexual Men % (SE) |
p | Sexual Minority Women % (SE) |
Heterosexual Women % (SE) |
p | |
|---|---|---|---|---|---|---|
| Without health care coverage | 5.61 (1.43) | 3.58 (0.36) | 0.1664 | 10.02 (1.95) | 4.51 (0.29) | 0.0046 |
| Without a personal doctor | 10.49 (2.46) | 7.38 (0.56) | 0.2204 | 14.61 (2.56) | 5.71 (0.29) | 0.0006 |
| Could not see MD because of cost | 12.52 (2.01) | 6.96 (0.41) | 0.0054 | 27.35 (3.31) | 12.50 (0.44) | <.0001 |
| Without routine checkup within past year | 15.18 (2.57) | 14.16 (0.59) | 0.6988 | 20.71 (2.64) | 15.41 (0.43) | 0.0386 |
| Poor access to care | 26.41 (3.09) | 23.83 (0.71) | 0.4103 | 42.66 (3.87) | 27.98 (0.58) | <.0001 |
Table 3.
Male and Female Cancer Survivors’ Likelihood of Poor Physical Quality of Life ¥
| Model 1 | Model 2 | Model for Heterosexuals | Model for Sexual Minorities | |
|---|---|---|---|---|
| Men | ||||
| Sexual Minority status | 1.31 (0.95, 1.81) |
1.32 (0.95, 1.84) |
__ | __ |
| Poor access to care | __ |
1.20 (1.04, 1.38) |
1.20 (1.04, 1.38) |
1.48 (0.82, 2.69) |
| Women | ||||
| Sexual Minority status | 1.39 (0.96, 2.01) |
1.38 (0.96, 1.98) |
__ | __ |
| Poor access to care | __ |
1.32 (1.18, 1.48) |
1.30 (1.16, 1.46) |
2.02 (1.20, 3.39) |
All models adjusted for age, race, education, marital status, income, and employment status.
Model 1 consists of all adjusters and sexual minority status only, whereas Model 2 adds poor access to care to Model 1.
Table 4.
Male and Female Cancer Survivors’ Likelihood of Poor Mental Quality of Life ¥
| Model 1 | Model 2 | Model for Heterosexuals | Model for Sexual Minorities | |
|---|---|---|---|---|
| Men | ||||
| Sexual Minority status |
1.49 (1.11, 2.01) |
1.54 (1.14, 2.08) |
__ | __ |
| Poor access to care | __ |
1.38 (1.16, 1.63) |
1.39 (1.17, 1.65) |
1.08 (0.57, 2.03) |
| Women | ||||
| Sexual Minority status | 1.24 (0.90, 1.69) |
1.22 (0.89, 1.65) |
__ | __ |
| Poor access to care | __ |
1.51 (1.34, 1.72) |
1.51 (1.32, 1.72) |
1.82 (1.07, 3.08) |
All models adjusted for age, race, education, marital status, income, and employment status.
Model 1 consists of all adjusters and sexual minority status only, whereas Model 2 adds poor access to care to Model 1.
Table 5.
Male and Female Cancer Survivors’ Likelihood of Difficulties Concentrating ¥
| Model 1 | Model 2 | Among Heterosexuals | Among Sexual Minorities | |
|---|---|---|---|---|
| Men | ||||
| Sexual Minority status |
1.85 (1.26, 2.74) |
1.93 (1.31, 2.85) |
__ | __ |
| Poor access to care | __ |
1.60 (1.28, 1.99) |
1.54 (1.22, 1.93) |
4.34 (2.03, 9.30) |
| Women | ||||
| Sexual Minority status | 1.22 (0.84, 1.78) |
1.19 (0.82, 1.71) |
__ | __ |
| Poor access to care | __ |
1.67 (1.43, 1.95) |
1.65 (1.41, 1.94) |
2.02 (1.15, 3.53) |
All models adjusted for age, race, education, marital status, income, and employment status.
Model 1 consists of all adjusters and sexual minority status only, whereas Model 2 adds poor access to care to Model 1.
Results
Cancer survivors’ demographic characteristics significantly differed by sexual orientation (Table 1). Compared to heterosexual men and women, sexual minority men and women were significantly younger, by an average of 10 years. Only about a third of the sexual minority cancer survivors were married, while the majority of heterosexual survivors were married. Sexual minority men were significantly more educated than heterosexual men, whereas employment was similar among male survivors. Compared to heterosexual women, more sexual minority women reported being employed for wages, whereas education levels were similar among women. All cancer survivors reported similar race/ethnicity and income; between 65% and 80% of cancer survivors self-reported Non-Hispanic White race, and about one quarter reported an income of $75,000 or more.
Sexual minority survivors of either gender significantly differed from heterosexual men and women on each of the three QoL measures, reporting worse physical and mental QoL and greater difficulty concentrating.
Significantly more sexual minority men reported avoiding medical care due to costs compared to heterosexual men (Table 2). However, men of either sexual orientation had similar access to care conditions with respect to insurance status, having a personal physician, and an annual visit. Overall, about one quarter of men had poor access to care. Women differed significantly on all dimensions of access to care; sexual minority women were more likely to report having no health insurance, being without a personal physician, avoiding medical care due to costs, being without an annual visit. Overall, sexual minority women were more likely to have poor access to care compared to heterosexual women.
Because some might argue cancer survivors’ access deficits are caused by not having health insurance, we also examined access to care conditions among the 68,467 cancer survivors who were insured (results not shown). Among insured cancer survivors, access to care conditions remained largely unchanged, in that 9.3% of sexual minority men reported avoiding care because of costs compared to 5.8% of heterosexual men (p<.05). Among the insured, 10.1% of sexual minority women reported being without a provider compared to 4.2% of their heterosexual counterparts (p<.05). Twenty-two percent of insured sexual minority women avoided care because of costs compared to 10.4% of heterosexual women (p<.001), and 36.2% of sexual minority women had poor access to care compared to 24.5% of heterosexual women (p<.01). Among insured women survivors, having an annual visit no longer differed by sexual orientation.
Table 3 summarizes survivors’ physical QoL. After controlling for confounders, sexual minority and heterosexual men’s physical QoL was similar (Model 1). When considering both sexual minority status and poor access to care, only poor access to care was significantly associated with men’s physical QoL. After performing separate analyses for each sexual orientation group, poor access to care was significantly associated with heterosexual men’s physical QoL, but not with sexual minority men’s.
Among women, physical QoL did not significantly differ by sexual orientation. In Model 2, when both poor access to care and sexual minority status were considered, only poor access to care was significantly associated with women’s physical QoL. In separate analyses, poor access to care increased the likelihood of poor physical QoL by 1.3 among heterosexual women, whereas poor access to care increased the likelihood by 2.0 among sexual minority women.
Sexual minority men had significantly greater odds of poor mental QoL than heterosexual men, while controlling for confounders (Table 4). Both sexual minority status and poor access to care significantly increased men’s likelihood of poor mental QoL. In separate models, poor access to care significantly increased the likelihood of poor mental QoL among heterosexual men, but not among sexual minority men.
Women cancer survivors’ mental QoL did not significantly differ by sexual orientation. When both sexual minority status and access to care were considered, only poor access to care significantly increased the likelihood of poor mental QoL among women. Poor access to care increased the likelihood of poor mental QoL by 1.5 among heterosexual women, whereas the odds were 1.8 among sexual minority women.
Sexual minority men had 1.9 the odds of difficulty concentrating (Table 5). When adding poor access to care to the model, both significantly increased men’s likelihood of difficulty concentrating. Poor access to care increased the likelihood of difficulty concentrating by 1.5 among heterosexual men, whereas the odds were 4.3 among sexual minority men.
Women cancer survivors had similar odds of difficulty concentrating, irrespective of sexual orientation. When sexual minority status and access to care were considered together, only poor access to care significantly increased women’s odds of difficulty concentrating. In separate models, poor access to care increased the odds of difficulty concentrating by 1.7 among heterosexual women, whereas the odds were 2.0 among sexual minority women.
Discussion
Although cancer survivors’ long term outcomes, including recurrence, overall survival, and QoL, are closely linked to access to care,14–16, 18–20 disparities between sexual minority and heterosexual cancer survivors’ access to care have not been well established.11 This study addresses this gap in knowledge and is the first study to have examined the link between sexual minority cancer survivors’ access to care and QoL.
Our hypothesis that sexual minority survivors have poorer access to care was strongly confirmed for sexual minority women who were disadvantaged compared to heterosexual women with respect to each access condition. Men, on the other hand, had similar overall access to care but sexual minority men avoided medical care due to costs more than did heterosexual men. These findings are consistent with earlier studies of sexual minority and heterosexual individuals in the general population, which likewise reported gender differences in access to care.7, 29
Gender differences are highlighted in this study and serve as a caution against combining sexual minority men and women in analyses. Sexual minority women survivors’ access had a stronger association with the three QoL measures compared to heterosexual women survivors. For men, the association of access to care differed for each of the different QoL measures between heterosexual and sexual minority men. Notably, sexual minority men’s access to care was linked to worse difficulty concentrating compared to heterosexual men. Also, men’s sexual minority status was independently linked to their mental QoL and difficulty concentrating. Beyond a general call for equity in access to care for all,1 the findings speak specifically to a need to focus on sexual minority women with cancer. Given QoL’s predictive validity of mortality, these findings may further explain studies that report sexual minority women have a higher cancer mortality compared to heterosexual women survivors.30–33 They also speak for the need to focus on sexual minority men’s mental health since their sexual minority status is independently linked with mental QoL.
While this study’s findings on sexual minority cancer survivors’ QoL contributes to an equivocal body of literature, we are unable to resolve inconsistencies due to the fact that population-based representative samples were used for both this study and others.34–36 However, this study contributes novel information by showing that sexual minority women’s QoL outcomes are more strongly dependent on their access to care than heterosexual women’s QoL. Further, this study is consistent with prior survivor studies,34, 35, 37 showing sexual minority cancer survivors are significantly younger compared to heterosexual survivors.
Limitations
This study has a number of limitations. We recognize that our sample of cancer survivors may not be reflective of all regions of the US because the available data were from 35 US states and Guam. Additional characteristics, including the time and stage of diagnosis, cancer type, and whether follow up visits and the personal health care provider referred to oncology or primary care, are not collected by the BRFSS. While we relied on a large population-based sample of cancer survivors, which included 782 sexual minority men and 1,149 sexual minority women, further disaggregation of sexual minorities into lesbian/gay, bisexual, or other groups was not possible due to limited cell sizes. Studies of health insurance coverage often restrict their samples to individuals who are between 18 and 64 years of age, while we did not. In this sample, only 25,907 survivors were between age 18 and 64. However, when we performed analyses on this sample, we found the availability of health insurance showed the same pattern as in the larger sample of survivors that included Medicare eligible survivors. We therefore felt comfortable retaining Medicare eligible cancer survivors in all analyses.
Conclusions
This study informs about an under-researched aspect of cancer research. Despite a likely overrepresentation of sexual minorities among cancer survivors, which is expected to increase in the future,38 few suitable data sources that include sexual orientation are available. Future studies are needed to confirm this study’s patterns of the relationship between access to care and QoL among sexual minority cancer survivors. In the short-term, sexual minority cancer survivors’ QoL and its associations with access to care point to an important area of inequity that needs to be addressed at the policy level to ensure equitable and high-quality cancer care delivery. This is especially important, as this study captured roughly a time frame after the implementation of the Affordable Care Act and after the legalization of same-sex marriage took place, which implies that sexual minority cancer survivors in this sample may have already benefitted from greater health care access that resulted from both of these legal changes.39 Further, supplemental analyses of insured survivors demonstrated that differences in access to care by sexual orientation remained unchanged. Policies must therefore move beyond health insurance alone and offer services tailored to sexual minority survivors. Clinicians must also be aware of the multiple dimensions of access problems and take the opportunity to address them during visits; for example, address medical costs with sexual minority cancer survivors.
Funding
This work was supported by the National Cancer Institute at the National Institutes of Health (1R01CA181392–01A1).
Footnotes
None of the authors report a conflict of interest.
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