Abstract
Background
Gender minorities and cisgender women face barriers to healthcare access. Prior work suggests cost may represent a particular barrier to accessing care for transgender and gender diverse (TGD) individuals.
Objective
To examine odds of delaying care for any reason and, secondarily, for 7 specific reasons among TGD individuals and cisgender women compared with cisgender men in the All of Us Research Program.
Design
We calculated the odds of delayed care by gender identity relative to cisgender men using multivariable-adjusted logistic regression, with adjustment for age, race, income, education, and Charlson comorbidity index.
Participants
We examined 117,806 All of Us participants who completed the healthcare access and utilization survey.
Main Measures
The primary outcome was self-reported delayed care in the past 12 months for any of 7 potential reasons: cost (out-of-pocket cost, co-payment costs, and/or high deductible), lack of childcare, lack of eldercare, nervousness associated with visiting the healthcare provider, rurality, inability to take time off work, and lack of transportation.
Key Results
Compared with cisgender men, the multivariable-adjusted odds ratio (OR) for delaying care for any reason was 1.48 (95% CI, 1.44–1.53; P < 0.001) among cisgender women, 1.65 (95% CI, 1.24–2.21; P < 0.001) among TGD individuals assigned male at birth, and 2.76 (95% CI, 2.26–3.39; P < 0.001) among TGD individuals assigned female at birth. Results were consistent across multiple sensitivity analyses. TGD individuals were substantially more likely to cite nervousness with visiting a healthcare provider as a barrier, whereas cisgender women were more likely to delay care due to lack of childcare coverage.
Conclusions
Cisgender women and TGD individuals were more likely to delay seeking heath care compared with cisgender men, and for partially different reasons. These findings highlight the need to address common and distinct barriers to care access among marginalized groups.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
INTRODUCTION
Reducing inequities in healthcare access represents a key priority in the USA.1 Marginalized populations, including sexual, gender, and racial/ethnic minorities, face barriers to access.2, 3 An analysis of the 2016–2019 Behavioral Risk Factor Surveillance System (BRFSS) found that 14% of US adults, and 27% of those with economic disadvantage, had difficulty accessing medical care.4 Data from the 2016–2019 BRFSS suggested that women, despite lower uninsurance rates, are more likely than men to delay and forego care due to cost,5 but prior BRFSS data from 2014 to 2015 suggest men may be more likely to delay care.6 Transgender and gender diverse (TGD) individuals encompass those who identify as transgender, nonbinary, genderfluid, genderqueer, or two spirit.7 TGD individuals face discrimination at the individual level, structural level,8 and in healthcare settings.9 While research on TGD individuals has increased significantly in recent years, this population remains understudied.2 In the 2014–2015 BRFSS, compared with cisgender women, TGD individuals were more likely to have forgone care due to cost and to not have had a routine checkup in the past year.6 More recent data from the 2019–2020 BRFSS study found that both rural and urban TGD individuals were more likely to delay care due to cost.10
The All of Us Research Program healthcare access and utilization survey provides complementary and additional information to the BFRSS in ascertaining a more comprehensive set of potential reasons for delayed care and by incorporating electronic health record (EHR) data, in addition to self-reported comorbidities. The All of Us Research Program also uses a validated 2-step approach to ascertaining gender identity,11 whereas the BRFSS uses a one-step approach in a transgender specific survey (adopted by 32 states by 2020)6, 10 that has been criticized for inaccurately gathering sex assigned at birth and generating higher levels of missing data than the two-step approach.10, 12 Using contemporary data from the All of Us Research Program, we examined differences in rates of delayed care across different gender identities and self-reported reasons for delaying care. We hypothesized that cisgender women and TGD individuals would be more likely than cisgender men to delay seeking care.
METHODS
The All of Us Program is an ongoing national initiative to collect survey, electronic health record, and other data from 1 million Americans. As there is intentional oversampling of previously underrepresented groups, All of Us is not a representative sample of the US population. Enrollment is open to anyone aged 18 years and older who resides in the USA. All of Us primarily recruits patients out of health centers, including the Veterans Health Administration, regional health centers, and federally qualified health centers with additional recruitment at community centers. Participants may also enroll through the All of Us website and then visit their nearest designated clinic or laboratory to complete biometric measurements.13,14,15 Researchers may request data access at https://www.researchallofus.org/. The All of Us Program was approved by a dedicated All of Us Institutional Review Board.
We included participants from All of Us version 5 (data collected May 6, 2018–April 1, 2021; last accessed November 13, 2023) with available medical history data who completed the healthcare access and utilization survey. The study exposure was gender identity, categorized as (1) TGD assigned female sex at birth, (2) TGD assigned male sex at birth, (3) cisgender women, or (4) cisgender men. As noted earlier, gender identity was determined via a two-step approach in which participants were asked to report their sex assigned at birth (male, female, intersex), and their gender identity (man, woman, nonbinary, transgender, or none of the above). If participants selected nonbinary, transgender, or none of the above, they were asked to select one or multiple additional identifiers: trans man/transgender man/female-to-male, trans woman/transgender woman/male-to-female, genderqueer, genderfluid, gender variant, or two-spirit.16 Participants who were assigned female at birth and selected man, transgender, nonbinary, or “none of these describe me” were categorized TGD assigned female at birth. Participants who were assigned male at birth and selected woman, transgender, nonbinary, or “none of these describe me” were categorized TGD assigned male at birth. Individuals (n = 2076) who did not indicate sex assigned at birth, did not indicate gender identity, or indicated intersex were excluded from analyses16 (Fig. 1). Intersex individuals were excluded due to privacy concerns for small sample size (<20) of these individuals among those who answered the healthcare access and utilization survey.
The primary outcome was self-reported delayed care in the past 12 months for any of the following potential reasons: out-of-pocket cost for a service or procedure, co-payment costs, high deductible, lack of childcare, lack of eldercare, nervousness associated with visiting the healthcare provider, rurality, inability to take time off work, and lack of transportation. We separately examined 7 potential reasons for delayed care as secondary outcomes, with out-of-pocket cost for a service or procedure, co-payment costs, and high deductible combined into one category due to substantial overlap. We calculated the odds of delayed care by gender identity using multivariable-adjusted logistic regression relative to cisgender men, adjusted for covariates that may strongly influence whether and how participants seek healthcare and may differ by TGD status: age, race, income, education, and Charlson comorbidity index, a measure of health status based on several comorbidities.17 Components of the Charlson comorbidity index include prior myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, rheumatologic disease, ulcer disease, mild liver disease, diabetes mellitus (weighted 1), hemiplegia, moderate or severe renal disease, diabetes with end organ damage, any tumor, leukemia, lymphoma (weighted 2), moderate or severe liver disease (weighted 3), metastatic solid tumor, and HIV/AIDS (weighted 6). The components of the Charlson comorbidity index were retrieved from either self-reported history (in the personal and family health history survey) or from record of these comorbidities in the EHR. Missing race, income, and education were included as a separate category within each respective variable. Those who skipped and therefore had missing data for all 12 delay of care questions were excluded (Fig. 1). Those with missing data for some specific reasons for delayed care were excluded from the respective models (range 1.0–10.4% of individuals excluded across models of specific reasons for delayed care).
Sensitivity analyses were performed (1) without covariate adjustment; (2) with race/ethnicity binned as White vs. person of color to probe for sparse data bias;18 (3) with adjustment for cardiovascular risk factors (hypertension, hypercholesterolemia, and type 2 diabetes) and clinical ASCVD in lieu of the Charlson index; (4) with adjustment for self-reported health status (excellent, very good, good, fair, or poor) in lieu of Charlson index; (5) with adjustment for depression or anxiety (per EHR or survey data); (6) restricting the cohort to individuals who enrolled and completed the healthcare access and utilization survey prior to the start of the COVID-19 pandemic (i.e., before March 1, 2020); and (7) further adjusted for insurance status. Furthermore, we conducted secondary analyses comparing TGD individuals as a group to all cisgender individuals.
Two-sided P < 0.05 indicated statistical significance. Analyses were performed in R 4.2.1.
RESULTS
Of 123,664 participants who completed the healthcare access and utilization survey and answered at least one delay of care question, 2076 were excluded for not answering the sex at birth or gender identity questions, and 3782 were excluded for lack of EHR or health history survey data, leaving 117,806 (95.3%) participants in the final dataset (Fig. 1). Of those included, 217 (0.2%) were TGD assigned male at birth, 522 (0.3%) were TGD assigned female at birth, 77,024 (65.4%) were cisgender women, and 40,043 (34.0%) were cisgender men (Table 1). The average age of TGD participants was lower than cisgender individuals (40 vs. 54 years, P < 0.001), and 19.3% of TGD assigned female at birth individuals and 15.2% of TGD assigned male at birth had 1 or more persons under 18 in their household, compared with 18.8% of cisgender men and 26.6% of cisgender women (Table 1).
Overall, 42,754 (36.3%) reported delays in seeking care within the past 12 months, including 113/217 (52.1%) of TGD individuals assigned male at birth, 370/522 (70.9%) of TGD individuals assigned female at birth, 31,402/77,024 (40.8%) of cisgender women, and 10,869/40,043 (27.1%) of cisgender men. The most frequently cited reasons for delaying care across all groups were cost and nervousness (Table 2).
Compared with cisgender men, the unadjusted odds ratio (OR) for delaying care for any reason was 1.85 (95% CI, 1.79–1.86) for cisgender women, 2.92 (95% CI, 2.23–3.81) for TGD individuals assigned male at birth, and 6.53 (95% CI, 5.41–7.92) for TGD individuals assigned female at birth. After multivariable adjustment, the corresponding ORs were 1.48 (95% CI, 1.44–1.53) for cisgender women, 1.65 (95% CI, 1.24–2.21) for TGD individuals assigned male at birth, and 2.76 (95% CI, 2.26–3.39) for TGD individuals assigned female at birth vs. cisgender men. Increased odds of delayed care in TGD groups were consistently observed across most specific reasons cited, including cost, lack of eldercare, nervousness associated with visiting a healthcare provider, lack of transportation, and lack of time off work (Fig. 2). TGD individuals more commonly reported nervousness associated with visiting a healthcare provider (TGD assigned female at birth: OR, 3.94; 95% CI, 3.27–4.75; TGD assigned male at birth: OR, 2.71; 95% CI, 1.95–3.71. However, when adjusting for mental health diagnoses (anxiety/depression), these ORs were only modestly attenuated (TGD assigned female at birth: OR, 3.15; 95% CI, 2.60–3.81); TGD assigned male at birth: OR, 2.27; 95% CI, 1.62–3.12) (Table 3). Additionally, cisgender women had a significantly higher odds ratio of delaying care due to lack of childcare coverage (OR, 2.62; 95% CI, 2.35–2.91) relative to cisgender men. By contrast, compared with cisgender men, TGD individuals were not more likely to report childcare as a significant barrier.
Sensitivity analyses adjusted for cardiovascular risk factors and clinical ASCVD in lieu of the Charlson comorbidity index, those adjusted for self-reported health status, and those restricted to individuals surveyed prior to March 2020 each yielded highly consistent results vs. the primary analysis for associations of gender with delayed care (Table 3). Additionally, when adjusting for health insurance status, ORs were materially unchanged compared with the primary model.
In models comparing delayed care between all TGD and cisgender individuals, the OR for delaying care for any reason for TGD individuals compared with cisgender individuals was 1.77 (95% CI, 1.50–2.08). TGD individuals consistently had significantly higher odds of delaying care for all specific reasons except for delay due to lack of childcare or eldercare (Table 4).
DISCUSSION
Among approximately 118,000 US adults, we found that cisgender women and TGD individuals were significantly more likely to delay seeking care compared with cisgender men. Our analyses align with prior studies which report that TGD individuals experience greater delays in seeking healthcare than cisgender individuals.6 We found that cisgender women were more likely to delay care than cisgender men, which is consistent with 2016–2019 BRFSS data5 and stands in contrast with the 2014–2015 BRFSS data which showed cisgender men were more likely to delay care.6 The authors of this analysis posit that masculine beliefs may influence unwillingness to receive healthcare,6 and these attitudes may have changed since 2015. Nervousness and cost-related barriers were the most commonly cited reasons for delay across gender groups. Notably, we found that TGD individuals were more likely than cisgender men to cite nervousness associated with visiting a healthcare provider, lack of transportation, time off work, and lack of dependent care as factors underlying delays in care.
Our analysis aligns with and extends prior research regarding delays in care stemming from cost, insurance status, and lack of a regular provider5, 6, 10 and suggests additional socioeconomic and social factors that may differentially impact care delay among cisgender women and TGD individuals. We found nervousness associated with visiting medical providers to be a significant determinant in delaying care for TGD individuals. Prior work suggests this may be related to discrimination faced in healthcare settings.19, 20 For example, a survey-based study of US adults found 22% of TGD adults avoided healthcare due to fear of discrimination.9 TGD individuals also have higher rates of depression and anxiety,21 which appeared to explain only a modest portion of the reported nervousness with seeking care among TGD individuals when we included mental health diagnoses in our modeling. Approaches to mitigating this disparity should focus on both increased access to mental health services and strategies to reduce discrimination of TGD individuals in healthcare settings. Of note, cost-related barriers and nervousness were top reasons for delaying care across all genders, so addressing these barriers is likely to improve care access for many adults. Lack of transportation and time off work were also significant factors for TGD individuals. Others have shown that those without paid medical leave are more likely to forego specific preventive care services.22 Stronger medical leave policies in the USA, which are not currently mandated, and while important for all US adults, may particularly impact TGD individuals, who were more likely than cisgender individuals to report lack of time off work as a barrier to healthcare.23 Additionally, increasing access to telehealth may address concerns of lack of transportation or distance to a healthcare provider for rural individuals.
The USA ranks low in childcare and early childhood education investment,24 and in a Kaiser survey conducted in 2017, 14% of women cited lack of childcare as a reason for delaying medical care.25 A study of low-income families in California found lack childcare was a significant reason for parental delays in seeking care.26 We also found that, compared with cisgender men, lack of childcare was a more commonly cited reason for delaying care among cisgender women in our study. Furthermore, in our analysis, both cisgender women and TGD individuals were significantly more likely than cisgender men to cite needing to care for a dependent adult as a reason for delaying their own medical care, although the absolute number of TGD individuals citing this reason was small (< 20 in each TGD group).27
Strengths of our study include ascertainment of gender identity using a validated two-step method and examination of wider array of reasons for delaying care beyond what is available in the BRFSS. Our findings should also be interpreted in the context of limitations. We relied on self-reported delayed care. Most All of Us participants were recruited from health centers, and insurance rates were high across all groups, both potentially reflecting greater access compared with the general population. Finally, not every participant in All of Us completed the healthcare access and utilization survey, yielding potential for response bias.
In summary, our findings suggest that lowering out-of-pocket costs, addressing constraints like dependent care, improving patient comfort, and addressing discrimination in healthcare settings may mitigate gender disparities in access to care. These findings highlight the need to address common and distinct barriers to care access among marginalized groups.
Data Availability
Researchers may request data access at https://www.researchallofus.org/.
References
Office of Disease Prevention and Health Promotion. Healthy People 2030: Healthcare Access and Quality.
Reisner SL, Poteat T, Keatley JA, et al. Global health burden and needs of transgender populations: a review. The Lancet. 2016;388(10042):412-436. https://doi.org/10.1016/S0140-6736(16)00684-X
Turpin RE, Akré ERL, Williams ND, Boekeloo BO, Fish JN. Differences in health care access and satisfaction across intersections of race/ethnicity and sexual identity. Academic Medicine. Published online 2021:1592–1597. https://doi.org/10.1097/ACM.0000000000004243
Al Rifai M, Mahtta D, Kherallah R, et al. Prevalence and Determinants of Difficulty in Accessing Medical Care in U.S. Adults. Am J Prev Med. 2021;61(4):492-500. https://doi.org/10.1016/j.amepre.2021.03.026
Daher M, Al Rifai M, Kherallah RY, et al. Gender disparities in difficulty accessing healthcare and cost-related medication non-adherence: The CDC behavioral risk factor surveillance system (BRFSS) survey. Prev Med (Baltim). 2021;153. https://doi.org/10.1016/j.ypmed.2021.106779
Gonzales G, Henning-Smith C. Barriers to Care Among Transgender and Gender Nonconforming Adults. Milbank Quarterly. 2017;95(4):726-748. https://doi.org/10.1111/1468-0009.12297
Adams N, Pearce R, Veale J, et al. Guidance and Ethical Considerations for Undertaking Transgender Health Research and Institutional Review Boards Adjudicating this Research. Transgend Health. 2017;2(1):165-175. https://doi.org/10.1089/trgh.2017.0012
White Hughto JM, Reisner SL, Pachankis JE. Transgender stigma and health: A critical review of stigma determinants, mechanisms, and interventions. Soc Sci Med. 2015;147:222-231. https://doi.org/10.1016/J.SOCSCIMED.2015.11.010
Casey LS, Reisner SL, Findling MG, et al. Discrimination in the United States: Experiences of lesbian, gay, bisexual, transgender, and queer Americans. Health Serv Res. 2019;54(S2):1454-1466. https://doi.org/10.1111/1475-6773.13229
MacDougall H, Henning-Smith C, Gonzales G, Ott A. Access to Health Care for Transgender and Gender-Diverse Adults in Urban and Rural Areas in the United States. Medical Care Research and Review. Published online August 7, 2023. https://doi.org/10.1177/10775587231191649
The GenIUSS Group. Best Practices for Asking Questions to Identify Transgender and Other Gender Minority Respondents on Population-Based Surveys.; 2014.
Lett E, Everhart A. Considerations for transgender population health research based on US national surveys. Ann Epidemiol. 2022;65:65-71. https://doi.org/10.1016/j.annepidem.2021.10.009
The All of Us Research Program Investigators. All of Us Research Program.; 2021. Accessed July 9, 2023. https://allofus.nih.gov/about/all-us-research-program-protocol
All of Us Research Program. FAQ Category Archives. Published 2023. Accessed July 9, 2023. https://www.researchallofus.org/category_faq/researcher-faqs/
The All of US Research Program Investigators. The “All of Us” Research Program. Published online 2019. https://doi.org/10.1056/NEJMsr1809937
Tran NK, Lunn MR, Schulkey CE, et al. Prevalence of 12 Common Health Conditions in Sexual and Gender Minority Participants in the All of Us Research Program. JAMA Netw Open. 2023;6(7):e2324969. https://doi.org/10.1001/jamanetworkopen.2023.24969
Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis. 1987;40(5):373-383. https://doi.org/10.1016/0021-9681(87)90171-8
Gosho M, Ohigashi T, Nagashima K, Ito Y, Maruo K. Bias in Odds Ratios From Logistic Regression Methods With Sparse Data Sets. J Epidemiol. 2023;33(6):JE20210089. https://doi.org/10.2188/jea.JE20210089
Rodriguez A, Agardh A, Asamoah BO. Self-Reported Discrimination in Health-Care Settings Based on Recognizability as Transgender: A Cross-Sectional Study Among Transgender U.S. Citizens. Arch Sex Behav. 2018;47(4):973-985. https://doi.org/10.1007/s10508-017-1028-z
Kattari SK, Walls NE, Speer SR. Differences in Experiences of Discrimination in Accessing Social Services Among Transgender/Gender Nonconforming Individuals by (Dis)Ability. J Soc Work Disabil Rehabil. 2017;16(2):116-140. https://doi.org/10.1080/1536710X.2017.1299661
Robertson L, Akré ER, Gonzales G. Mental Health Disparities at the Intersections of Gender Identity, Race, and Ethnicity. LGBT Health. 2021;8(8):526-535. https://doi.org/10.1089/lgbt.2020.0429
DeRigne L, Stoddard-Dare P, Collins C, Quinn L. Paid sick leave and preventive health care service use among U.S. working adults. Prev Med (Baltim). 2017;99:58-62. https://doi.org/10.1016/j.ypmed.2017.01.020
Heymann J, Rho HJ, Schmitt J, Earle A. Ensuring a Healthy and Productive Workforce: Comparing the Generosity of Paid Sick Day and Sick Leave Policies in 22 Countries. International Journal of Health Services. 2010;40(1):1-22. https://doi.org/10.2190/HS.40.1.a
The Organisation for Economic Co-operation and Development (OECD). Public Spending on Childcare and Early Education. https://www.oecd.org/els/family/publications.htm,
Ranji U, Rosenzweig C, Gomez I, Salganicoff A. Executive Summary: 2017 Kaiser Women’s Health Survey. Accessed May 8, 2023. https://files.kff.org/attachment/Executive-Summary-2017-Kaiser-Womens-Health-Survey
Hoskote M, Hamad R, Gosliner W, Sokal-Gutierrez K, Dow W, Fernald LCH. Social and Economic Factors Related to Healthcare Delay Among Low-Income Families During COVID-19: Results from the ACCESS Observational Study. J Health Care Poor Underserved. 2022;33(4):1965-1984. https://doi.org/10.1353/hpu.2022.0148
Tingey JL, Lum J, Morean W, Franklin R, Bentley JA. Healthcare coverage and utilization among caregivers in the United States: Findings from the 2015 Behavioral Risk Factor Surveillance System. Rehabil Psychol. 2020;65(1):63-71. https://doi.org/10.1037/rep0000307
Acknowledgements:
The All of Us Research Program is supported by the National Institutes of Health, Office of the Director: Regional Medical Centers: 1 OT2 OD026549; 1 OT2 OD026554; 1 OT2 OD026557; 1 OT2 OD026556; 1 OT2 OD026550; 1 OT2 OD 026552; 1 OT2 OD026553; 1 OT2 OD026548; 1 OT2 OD026551; 1 OT2 OD026555; IAA #: AOD 16037; Federally Qualified Health Centers: HHSN 263201600085U; Data and Research Center: 5 U2C OD023196; Biobank: 1 U24 OD023121; The Participant Center: U24 OD023176; Participant Technology Systems Center: 1 U24 OD023163; Communications and Engagement: 3 OT2 OD023205; 3 OT2 OD023206; and Community Partners: 1 OT2 OD025277; 3 OT2 OD025315; 1 OT2 OD025337; 1 OT2 OD025276. In addition, the All of Us Research Program would not be possible without the partnership of its participants.
Funding
Dr. Toribio is supported by the National Heart, Lung, and Blood Institute (K23HL147799); the American Heart Association-Harold Amos Medical Research Faculty Development Program by the Robert Wood Johnson Foundation; and Physician Scientist Development Award from the Massachusetts General Hospital Executive Committee on Research and Center for Diversity and Inclusion. Dr. Natarajan is supported by a Hassenfeld Scholar Award from the Massachusetts General Hospital; grants from the National Heart, Lung, and Blood Institute (R01HL1427, R01HL148565, and R01HL148050); and from Fondation Leducq (TNE-18CVD04). Dr. Honigberg is supported by the National Heart, Lung, and Blood Institute (K08HL166687) and American Heart Association (940166, 979465).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest:
Dr. Natarajan reports grant support from Amgen, Apple, AstraZeneca, Boston Scientific, and Novartis, spousal employment and equity at Vertex, consulting income from Apple, AstraZeneca, Novartis, Genentech / Roche, Blackstone Life Sciences, Foresite Labs, and TenSixteen Bio, and is a scientific advisor board member and shareholder of TenSixteen Bio and geneXwell, all unrelated to this work. Dr. Honigberg reports consulting fees from CRISPR Therapeutics, advisory board service for Miga Health, and grant support from Genentech, all unrelated to this work.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Finneran, P., Toribio, M.P., Natarajan, P. et al. Delays in Accessing Healthcare Across the Gender Spectrum in the All of Us Research Program. J GEN INTERN MED 39, 1156–1163 (2024). https://doi.org/10.1007/s11606-023-08548-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11606-023-08548-y