Saketh Amasa, MHA¹*, Vedant S Agrawal, BS¹, Mert Karabacak, MD², Apurvakumar Patel, BS¹, Konstantinos Margetis MD, PhD²

¹University of Texas Medical Branch John Sealy School of Medicine, Galveston, TX, United States

²Department of Neurosurgery, Mount Sinai Health System, New York, NY, United States

*Corresponding Author: Saketh Amasa MHA; John Sealy School of Medicine, University of Texas Medical Branch, Galveston Texas, USA.

Received: 19 February 2026; Accepted: 26 February 2026; Published: 03 March 2026

Article Information

Citation: Saketh Amasa, MHA Vedant S Agrawal, BS, Mert Karabacak, MD, Apurvakumar Patel, BS, Konstantinos Margetis MD, PhD. Healthcare Access Barriers Among Minority Groups with Low Back Pain. Journal of Spine Research and Surgery. 8 (2026): 22-38.

DOI: 10.26502/fjsrs0098

Abstract

Keywords

Low Back Pain; Healthcare Access Barriers; Sexual and Gender Minority; Racial and Ethnic Disparities

Article Details

Introduction

Low back pain (LBP) is the leading cause of disability worldwide, with approximately 75% of affected individuals reporting some form of limitation and nearly 60% experiencing mobility or work restrictions [1-3]. Early, coordinated interventions, including physical therapy, specialist consultations, and pharmacotherapy, are essential to prevent chronicity and reduce the economic and social burden of LBP.4,5 Yet, financial, logistical, and interpersonal barriers frequently impede timely care. Although disparities in access have been documented among sexual and gender minority (SGM) and different racial/ethnic populations in other chronic conditions, [6-8] little is known about these barriers to care amongst individuals with LBP. Furthermore, a recent systematic review found studies on the potential role of social determinants of health in low back pain are poorly defined, with most studies limited by narrow populations or settings [9]. In this study, we used survey data on healthcare access and utilization from the National Institutes of Health’s All of Us Research Program to prevalence of cost and non-cost barriers among SGM, non-SGM, and different racial/ethnic groups of patients diagnosed with LBP.

Methods

The All of Us Research Program

All of Us is a longitudinal, nationwide cohort study designed to study the effects of environment, lifestyle, and genomics on health outcomes. Recruitment is facilitated through collaborating healthcare organizations and Federally Qualified Health Centers, with additional opportunities for individuals to join directly by visiting local enrollment facilities (https://joinallofus.org). After enrollment, participants are invited to undergo preliminary clinical evaluations and provide biological samples at partner healthcare sites. Participant data is maintained passively through integration of electronic health records (EHRs) and actively through periodic follow-up questionnaires. This study incorporates data from individuals who enrolled between May 6, 2018 and July 1, 2022 (release 7, N=413,537). This study was reported in accordance with the  Consensus- Based Checklist for Reporting of Survey Studies [10]. All analyses were performed in accordance with the All of Us Code of Conduct and participants granted informed consent upon joining the program, which included authorization for All of Us to access their EHR data. This study has been deemed not human subjects research by the University of Texas Medical Branch Institutional Review Board and is exempt from IRB review.

Data extraction and variable coding

The All of Us program employs the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to standardize EHR data from various sources [11,12]. Diagnoses for low back pain were defined based on the OMOP CDM Concept ID for low back pain (194133) within the All of Us Research Program Database [11,12]. Our analyses included measures for age, sex, gender identity, sexual orientation, race and ethnicity, educational attainment, insurance status, and US census region. Age was defined at the date of the data pull (July 23, 2024). SGM status was defined according to survey responses on sex assigned at birth, gender identity, and sexual orientation, where participants were categorized as SGM if they reported being intersex at birth, identifying as transgender or nonbinary, or identifying as lesbian, gay, bisexual, or other gender identities and sexual orientations. Non-SGM participants were defined as individuals who identified as either men or women whose sex assigned at birth aligned with their gender identity and who identified as heterosexual. Patients were categorized into the following groups based on self-reported race and ethnicity: Hispanic, Latino, or of Spanish origin (HL); non-Hispanic Asian (NHA); non-Hispanic Black (NHB); non- Hispanic Middle Eastern or North African (NHMENA); non-Hispanic Native Hawaiian or other Pacific Islander (NHNHPI); non-Hispanic White (NHW); non-Hispanic and multiple races; or another race and ethnicity not listed on the survey. Socioeconomic characteristics, including insurance coverage, educational attainment, household income, and census region were constructed by All of Us utilizing information from “The Basics Survey” which contains demographic information, coupled with zip code data. The outcome variables were responses to eight questions on The Healthcare Access and Utilization survey regarding broadly applicable healthcare barriers used in previous studies.3 Additional data on methods and questionnaires is available in Supplementary materials.

Statistical Analysis

Univariable and multiple logistic regression were used to study the association of race/ethnicity, SGM status, and gender with experiencing barriers to care. Due to limitations in the sample size, only patients identifying as NHW, HL, and NHB were included. Regression models excluded participants with missing data. Analyses were conducted in the All of Us Researcher workbench using Juptyer Notebook software, version 6.4.8 using Python language (Python Software Foundation), version 3.10.12. A two sided P < .05 was considered statistically significant for all analyses.

Results

Study Population

Our analysis included 25,597 patients with LBP, of whom 2,169 were identified as SGM and 23,428 as non-SGM (Table 1). The SGM group had a median age of 54.0 years [interquartile range (IQR), 41.0-66.0], with 1,389 (64.0%) assigned female sex, 779 (35.9%) male sex, and <20 (0.1%) intersex at birth. The racial/ethnic composition of the SGM group was: 228 (10.5%) HL, 38 (1.8%) NHA, 214 (9.9%) NHB, 1,525 (70.3%) NHW, 84 (3.9%) non-Hispanic and multiple races, and <20 (0.1%) NHNHPI.

Table 1: Characteristics of the study population with low back pain grouped by SGM status.

^aBecause all patients did not complete all demographic questions, percentages may not sum to 100. In compliance with the All of Us Data and Statistics Dissemination Policy, cells with participant counts of 1 to 20 have been marked with NA.

^bThe welch t test was used to compare the mean age between groups. All other characteristics were compared using Pearson χ2 tests.

^cPatients may have identified with more than one gender and sexual orientation. Additional data are available in eTable 4.

(SGM, sexual gender minority; IQR, interquartile range; MENA, Middle Eastern or North African; NHPI, Native Hawaiian or Pacific Islander).

The non-SGM group had a median age of 65.0 years (IQR, 53.0-74.0), with 16,037 (68.5%) assigned female sex and 7,391 (31.5%) male sex at birth. The racial/ethnic composition was: 2,532 (10.8%) HL, 374 (1.6%) NHA, 2,955 (12.6%) NHB, 16,618 (70.9%) NHW, 340 (1.5%) non-Hispanic and multiple races, and <20 (0.1%) NHNHPI.

Regarding gender identity among SGM patients, 755 (34.8%) identified as men, 103 (4.7%) as nonbinary, 55 (2.5%) as transgender, and 1,299 (59.9%) as women. In terms of sexual orientation, 868 (40.0%) identified as bisexual, 560 (25.8%) as gay, 421 (19.4%) as lesbian, and 33 (1.5%) as heterosexual. Among non-SGM patients, 7,400 (31.6%) identified as men and 16,028 (68.4%) as women. SGM patients were generally younger and more likely to be assigned female at birth compared to non-SGM patients (p < 0.001). Detailed information on responses to questions about sex assigned at birth, gender identity, and sexual orientation are available in eTable 5.

Insurance coverage patterns varied significantly, with a higher proportion of SGM patients enrolled in Medicaid (16.6% vs. 10.5% for non-SGM) and a lower enrollment in Medicare (9.2% vs. 14.4%). Income levels were also significantly different; SGM patients were more likely to report incomes below $25,000 (28.9% vs. 18.4%) and between $25,000 and $50,000 (19.5% vs. 16.0%), while non-SGM patients more frequently reported incomes between $50,000 and $100,000 (25.4% vs. 21.4% for SGM).

When grouped by race/ethnicity, the LBP cohorts included 3,169 (12.4%) NHB, 18,143 (70.9%) NHW, and 2,760 (10.8%) HL patients (Table 2). Age distributions varied, with median ages of 55 years (IQR 44-66) for HL, 60 years (IQR 51-68) for NHB, and 67 years (IQR 54-75) for NHW patients. A higher proportion of NHB (76.5%) and HL (76.3%) patients were assigned female at birth compared to NHW patients (65.5%). Regarding insurance status, HL patients had the highest rates of Medicaid coverage (28.5%), while NHW patients more commonly had employer-based (32.1%) or Medicare (15.3%) insurance. NHB and HL patients reported lower income levels, with 42.0% and 34.9% respectively having annual incomes below $25,000, compared to 13.0% of NHW patients. Educational attainment also varied, with NHW patients having substantially higher rates of college education (60.5%) than NHB (30.1%) and HL (28.2%) patients.

Table 2. Characteristics of the study population with low back pain grouped by race and ethnicity.

^aBecause all patients did not complete all demographic questions, percentages may not sum to 100. In compliance with the All of Us Data and Statistics Dissemination Policy, cells with participant counts of 1 to 20 have been marked with NA

^bThe welch t test was used to compare the mean age between groups. All other characteristics were compared using Pearson χ2 tests

(IQR, interquartile range).

Cost and Non-cost Barriers Stratified by SGM Status

After adjusting for demographic and socioeconomic factors, SGM patients faced significantly more healthcare-related delays compared to non-SGM patients (Table 2). While the difference in delaying general doctor visits was not significant [adjusted odds ratio (aOR) 1.07, p-value (p) 0.340, 95% confidence interval (CI) 0.90-1.28], SGM patients had significantly increased odds of delaying mental health care (aOR 1.72, p<0.001, 95% CI 1.50-1.97), prescription filling (aOR 1.27, p<0.001, 95% CI 1.13-1.43), and specialist visits (aOR 1.18, p<0.021, 95% CI 1.02-1.35). Additionally, SGM patients were significantly more likely to report non-cost barriers, including inability to take time off work (aOR 1.18, p<0.020, 95% CI 1.03-1.36), lack of transportation (aOR 1.36, p<0.001, 95% CI 1.18-1.56), perceived disrespect by healthcare providers (aOR 1.40, p<0.001, 95% CI 1.27-1.54), and delayed care due to differences in provider background (aOR 1.42, p<0.001, 95% CI 1.26-1.60).

Table 3: Odds Ratios and p values for experiencing barriers to care in univariate and multivariate analysis by SGM status.

^aThese odds ratios and p-values are for univariate analysis comparing SGM individuals versus non-SGM individuals and the prevalence of barriers.

^bThese odds ratios and p-values are comparing SGM individuals vs Non-SGM individuals and prevalence of barriers, adjusting for age, census region, race, income, insurance, and education level.

^cPatients who skipped the question or responded “don’t know” were excluded from the calculations for that barrier. 

(SGM, sexual gender minority; OR, odds ratio; aOR, adjusted odds ratio).

Cost and Non-cost Barriers Stratified by Race and Ethnicity

Analysis across racial and ethnic groups revealed significant disparities in healthcare access among NHB and HL patients compared to NHW patients (Table 3). NHB patients exhibited higher odds of delaying general doctor visits due to cost (aOR 1.38, 95% CI 1.19-1.61) and delaying prescription filling due to cost (aOR 1.25, 95% CI 1.13-1.39). They also faced increased transportation issues (aOR 1.33, 95% CI 1.17-1.50) and were more likely to delay care due to differences with their healthcare practitioner (aOR 1.28, 95% CI 1.14-1.43). However, they reported lower odds of perceiving disrespect from healthcare providers (aOR 0.71, 95% CI 0.64-0.78).

HL patients similarly showed higher odds of delaying general doctor visits due to cost (aOR 1.39, 95% CI 1.18-1.65), delaying specialist visits due to cost (aOR 1.24, 95% CI 1.09-1.42), delaying care due to an inability to take time off work (aOR 1.51, 95% CI 1.32-1.73), and were more likely to delay care due to differences with healthcare practitioners (aOR 1.29, 95% CI 1.14-1.45). Similar to NHB patients, HL patients reported lower odds of perceiving disrespect from healthcare providers (aOR 0.77, 95% CI 0.69-0.86).

Cost and Non-cost Barriers Stratified by Both SGM Status and Race and Ethnicity

HL SGM patients, compared to NHW non-SGM patients, were significantly more likely to delay care for general doctor visits (aOR 2.41, 95% CI 1.61-3.62), mental health (aOR 2.50, 95% CI 1.76-3.56), prescription filling (aOR 1.49, 95% CI 1.07-2.07), and specialist visits (aOR 1.76, 95% CI 1.22-2.52). They also faced greater challenges in taking time off work (aOR 2.36, 95% CI 1.65-3.37) and with transportation (aOR 1.70, 95% CI 1.18-2.45).

NHB SGM patients showed increased delays in mental health visits (aOR 1.61, 95% CI 1.08-2.40) and prescription filling (aOR 1.92, 95% CI 1.41-2.61). They also experienced more difficulties with transportation (aOR 1.86, 95% CI 1.31-2.64) and healthcare provider differences (aOR 2.39, 95% CI 1.74-3.29). Notably, NHW SGM patients were more likely to face all eight healthcare barriers compared to their NHW non-SGM counterparts.

A post hoc sensitivity analysis compared the prevalence of barriers to care between patients with and without LBP. Patients with LBP were more likely to delay filling a prescription (aOR 1.23, 95% CI 1.17-1.28), delay specialist visits (aOR 1.07, 95% CI 1.02-1.12), and experience transportation-related delays (aOR 1.10, 95% CI 1.05-1.16). No significant differences were observed in the prevalence of the remaining barriers between patients with and without LBP (eTable 6).

Table 4. Odds ratios and p values for experiencing barriers to care in multivariate analysis by race and ethnicity.

^aThese odds ratios and p-values are comparing NHW, NHB, and HL groups and the prevalence of cost barriers, adjusting for age, census region, income, insurance, and education level.

^bPatients who skipped the question or responded “don’t know” were excluded from the calculations for that barrier. 

(SGM, sexual gender minority; OR, odds ratio; aOR, adjusted odds ratio; NHW, non-Hispanic White; HL, Hispanic/Latino; NHB, non-Hispanic Black).

Discussion

In this cross-sectional analysis of survey data on healthcare access and utilization of US adults with LBP, we observed that SGM individual disproportionately reported a broad range of cost-related and non-cost barriers to care compared with their non-SGM counterparts. The prevalence of barriers was particularly high among SGM patients who also identified with racially or ethnically minoritized groups, highlighting the potential for compounded disparities at the intersection of SGM status and race/ethnicity. These findings extend prior evidence of racial and socioeconomic inequities in LBP management by highlight disparities associated with sexual orientation and gender identity. [13] Of note, sexual minority adults were found to have a higher prevalence of chronic pain than their heterosexual counterparts, suggesting that the greater burden of LBP in SGM populations may be exacerbated by these care barriers. [14] Some of the disparities observed may also be partially explained by underlying socioeconomic disadvantages. For example, lower-income and less-educated patients are more likely to receive non-guideline-concordant LBP treatments, which can delay appropriate care. [13]

Our results also suggest that identity concordance between patient and provider plays an important role in LBP care. Many SGM patients – especially women of color in our cohort – reported discomfort or even delaying care when their clinician did not share their background with regard to race, ethnicity, or SGM identity. This identity-based mistrust is perhaps unsurprising given the persistent lack of diversity in the healthcare workforce. [15] Only 7.8% of family-medicine residents are Black and 9.1% are Hispanic, compared with 13.4% and 18.5% of the U.S. population, respectively. [16] Representation gaps are still wider in procedure-oriented spine disciplines; in the most recent AAOS census, practicing orthopedic surgeons were 1.9% Black, 2.2% Hispanic, and 7.6% women – versus 14%, 19%, and 50% of the population respectively. [17] Neurosurgery shows a similar mismatch, with 4% Black, 5% Hispanic, and 8% female neurosurgeons.18 Observational orthopedic data indicate that patients have better outcomes when they share racial or gender backgrounds with their surgeon, although these studies cannot fully disentangle concordance from unmeasured system-level variables. [19-21] Our finding that NHB-SGM women more frequently delayed care because clinicians did not share their background may be a possible explanation for poor LBP care outcomes, [22] but should be interpreted cautiously, as residual confounding of socioeconomic factors (e.g., insurance tiers, regional supply of specialists) remains a competing explanation.

Reports of disrespect and clinical alienation point toward deficits in culturally responsive spine-care training. In a recent national survey, only 34% of U.S. primary-care practices – and fewer in resource-limited regions—provided any LGBTQ+-specific training for clinicians;1 comparable estimates for surgical spine specialties are unavailable. While the impact of such training on measurable LBP outcomes has yet to be prospectively tested, the gap itself may perpetuate minority stress, reinforce mistrust, and compound existing access barriers. Developing, validating, and disseminating SGM-affirming curricula tailored to musculoskeletal and interventional pain settings is an actionable research priority.

The conducted intersectional analyses underscore that racial/ethnic minority status and SGM identity may be multiplicative in their association with delayed or forgone LBP care. Registry data show that, after three years of follow-up, Black patients with chronic LBP had 40% higher odds of long-term opioid therapy yet 55% lower odds of lumbar-spine surgery than White patients, alongside worse pain and function trajectories. [22] Additionally, non-white patients have been found to experience higher rates of nonhome discharge, readmissions, and ED visits after posterior lumbar fusion. [23] Coupled with the elevated pain prevalence in SGM communities, [14] these findings raise the possibility that structural factors underlie observed disparities in LBP care outcomes.

Limitations

The findings of this study should be viewed with consideration of several limitations. First, survey responses were not exclusively related to LBP care, and the results may not be specific to individuals with this condition. Our post hoc sensitivity analysis indicated that most barriers were equally prevalent among adults with and without LBP, suggesting that these obstacles may affect patients overall. One notable exception was that individuals with LBP were significantly more likely to delay filling prescriptions due to cost. This may be tied to the increasing expense of medications frequently prescribed for chronic pain. [24] Additionally, although the All of Us Research Program offers a large and diverse sample, the patients in this study may not be fully representative of the broader US population. Furthermore, the survey design did not provide details on how often these barriers were encountered or the extent to which they delayed care. Future studies should work to examine these barriers in greater depth, disaggregating data by specific gender identity, racial and ethnic backgrounds, and specific clinical diagnoses.

Conclusion

This study reveals significant healthcare barriers faced by SGM and racial/ethnic minority groups diagnosed with LBP. SGM patients experienced heightened challenges in accessing care, including both cost-related delays and non-cost obstacles. These challenges were further exacerbated by intersecting identities such as race and ethnicity. Our findings highlight structural barriers that impact minority groups from achieving parity in healthcare access and outcomes.

Funding/Support:

No funding.

Non-Author Contributions:

None.

Author Contributions:

Conceptualization, VA, MK, SA; Methodology, VA; Software, VA; Formal Analysis, VA; Data Curation, VA; Writing – Original Draft Preparation, SA, VA, AP; Writing – Review & Editing, KM, MK, SA, VA, AP; Visualization, VA, SA; Supervision, KM; Project Administration, MK and KM

Access to Data and Data Analysis:

Vedant Agrawal had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Data Availability Statement:

Restrictions apply to the availability of these data. Data were obtained from the All of Us Research Program and are available at (https://www.researchallofus.org) for qualified researchers associated with affiliated institutions.

Conflicts of Interest:

The authors declare no conflict of interest.

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Supplementary data

Supplement 1. Consensus-Based Checklist for Reporting of Survey Studies.

eMethods

These supplemental methods will focus on the inclusion criteria for sexual and gender minority (SGM) individuals.

Patients with Low Back Pain (LBP) were selected from the All of Us Controlled Tier V7 cohort containing individuals enrolled between May 31, 2017 and July 1, 2022. The codes used to select for individuals with generalized anxiety disorders is displayed in eTable 1. Individuals must also have completed the “Basics” survey, containing basic demographic information, and the “Health Care and Access Utilization” survey, which contains survey questions relating to the cost and non-cost barriers assessed in this study.

Patients with LBP were then categorized as a SGM individual if they identified with one or more than one of the following identities (additional data on sexual and gender identity responses available in eTable 3):

- Sex assigned at birth: Assigned intersex at birth

- Gender identity: transgender (including transgender men and transgender women), non-binary, genderqueer, genderfluid, gender variant, or two spirit

- Sexual orientation: gay, lesbian, bisexual, queer, polysexual, omnisexual, sapiosexual, pansexual, asexual, two spirit, not figured out, mostly straight, no sexuality, or no labels

Patients with LBP were categorized as non-SGM if they match one of the following criteria and do not meet any of the criteria listed above. 

- Assigned male at birth, identify as a man, and are heterosexual

- Assigned female at birth, identify as a female, and are heterosexual

Participants were also classified into the following groups based on self-reported race and ethnicity:

- Hispanic, Latino, or of Spanish Origin

- Non-Hispanic Asian

- Non-Hispanic Black

- Non-Hispanic Middle Eastern or North African

- Non-Hispanic Native Hawaiian or other Pacific Islander

- Non-Hispanic White

- Non-Hispanic and multiple races

- Another race and ethnicity not listed on the survey

For coding purposes when running analysis, individuals identifying as Non-Hispanic Asian, Non-Hispanic Middle Eastern or North African, Non-Hispanic Native Hawaiian or other Pacific Islander, Non-Hispanic and multiple races, and Another race and ethnicity not listed on the survey were categorized as “non-Hispanic Other”.

eTable 1: SNOMED Code and OMOP Id utilized for cohort identification.

SNOMED Code and OMOP Id utilized to collect cohorts from the All of Us researcher workbench are detailed below. From left to right, the columns include the prospective cohort, followed by utilized SNOMED Code, and lastly followed by OMOP Concept Id.

eTable 2: Data Sources within All of Us Researcher Workbench.

The first column indicates the data source within All of Us researcher workbench, the second indicates how the data was accessed, and the third lists information taken from each source to conduct our study.

eTable 3: Details on terminology used for sex assigned at birth, gender identity, and sexual orientation.^a

^aThis table is not inclusive of all possible terms related to sexual and gender identity, and includes only those terms that are used in the All of Us survey questions. Here, we have provided definitions from leading organizations and other researchers. These definitions are fluid and may be defined differently by different people and organizations. Here, we have provided definitions from leading organizations and other researchers.

eTable 4: Survey items used as outcome measures for analysis.

The first column indicates the question stem within All of Us researcher workbench, the second indicates how the data was accessed, and the third lists information taken from each source to conduct our study.

eTable 5: Full sexual orientation and gender identity breakdown of the study population.^a,b

^aIn accordance with All of Us data dissemination policies, categories with less than 20 participants are marked as NA

^bParticipants can identify with more than one gender identity or sexual orientation

eTable 6: Prevalence of barriers based on low back pain diagnosis.

^aOdds ratios adjusted for age, region, race, income, insurance, and education level

^bPatients who skipped the question or responded “don’t know” were excluded from the calculations for that barrier.

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