Abstract
Rationale
Social risk factors (SRFs) include potentially intervenable individual-level social and economic conditions that impact health. Limited data exist on the prevalence of SRFs and their impact on transplantation among individuals receiving dialysis.
Study Design
A cross-sectional cohort study.
Exposures
The SRF data (housing, food security, utilities, transportation & personal safety) were collected from maintenance dialysis patients at Dialysis Clinic, Inc. from May 2023 to March 2025 using questions from the Accountable Health Communities Health-Related Social Needs Screening Tool.
Outcome
Most recent transplant status, defined as neither being waitlisted nor having received a transplant through March 2025.
Analytical Approach
A total SRF burden score was assigned to each patient, categorized as screening positive for none (0), one (1), or more than one (>1) SRF. We evaluated the association of SRF burden score and transplant status using logistic regression. Models were adjusted for age, sex, race/ethnicity, dialysis vintage, modality, clinic location, financial status, insurance coverage, and comorbid conditions. Supplementary analyses examined the association between each SRF domain and the outcome.
Results
Among 12,994 patients with SRF data, 1,360 (10.5%) had a score of 1 and 445 (3.4%) had a score of >1. In an adjusted model, having one or more SRF was associated with increased odds of not being transplanted or waitlisted for transplant (odds ratio 1.19 [0.99-1.43] and 1.65 [1.14-2.38] for 1 and >1 SRF). Other associated SRFs included being financially uncomfortable (1.54 [1.33-1.78]) and dialyzing in a rural clinic (1.26 [1.11-1.44]). In supplementary analyses, transportation insecurity (2.59 [1.74, 3.87]) had the strongest association with the outcome.
Limitations
Residual confounding and exposure misclassification.
Conclusions
In a national cohort of maintenance dialysis patients, more than 10% had one or more SRF; this was associated with increased odds of not being transplanted or actively waitlisted. Addressing SRFs, including transportation barriers, may improve access to kidney transplants.
Index Words: social risk factors, dialysis, transplantation, transportation insecurity, health disparities, kidney failure
Plain-Language Summary
Chronic kidney disease disproportionately affects people facing social challenges such as housing instability, food insecurity, and lack of transportation. These social risk factors (SRFs) can make it hard for patients to be placed on a kidney transplant waitlist or receive a transplant. In this study we examined how common SRFs are among people on dialysis and whether they affect access to kidney transplantation. We found that patients with a higher burden of SRFs were much less likely to be waitlisted or transplanted. These findings support the importance of identifying and addressing social needs in dialysis care. Doing so can help reduce barriers and promote more equitable access to kidney transplantation.
Health-related social risk factors (SRFs) are measurable and potentially intervenable individual-level social and economic conditions that are shaped by broader determinants of health.1,2 Since the foundational work by Link and Phelan in 1995, who introduced the theory of Fundamental Causes to explain the association between socioeconomic status and mortality, SRFs have been increasingly recognized as key contributors to adverse health outcomes. The impact of SRFs on mortality stems largely from their association with limited access to critical financial and social resources.3,4 SRFs are typically categorized into five primary domains: housing instability, food insecurity, utility needs, transportation barriers, and personal safety concerns.5
Despite the disproportionately high incidence and prevalence of chronic kidney disease (CKD) among individuals more likely to have a higher burden of social risk factors, there remains a significant gap in the literature regarding the burden of SRFs among patients receiving dialysis, and the influence of SRFs on kidney transplant access.6,7 A growing body of evidence suggests that addressing social risk factors and associated unmet needs can help mitigate—or even reverse—their detrimental impact on health.8,9 This signifies the urgency of understanding both the prevalence and the consequences of SRFs in patients with kidney disease, particularly as they relate to key health outcomes such as kidney transplantation.
In this study, we assessed the prevalence of the five major SRF domains in a large, nationally representative cohort of patients receiving maintenance dialysis and evaluated the association between SRFs and the odds of not being waitlisted for transplant or not being transplanted. We hypothesized that SRFs are highly prevalent in the dialysis population and that the presence of one or more SRF is associated with increased odds of not being waitlisted for or receiving a kidney transplant.
Methods
Study Population
All patients from 240 Dialysis Clinic Inc (DCI) clinics treated with outpatient maintenance dialysis for ≥90 days who completed questions based on the Accountable Health Communities Health-Related Social Needs (AHC-HRSN) screening tool from May 7, 2023 to April 24, 2025 were included in this cross-sectional cohort study. Patients who had dementia, lived in a nursing home facility, or were over 75 years old were excluded, consistent with the Centers for Medicare & Medicaid Services criteria when calculating percentage of prevalent patients waitlisted.10
Social Risk Factor Ascertainment
The AHC-HRSN screening tool includes five domains: housing, transportation, personal safety, utilities, and food security. These domains were transiently included in the end-stage renal disease (ESRD) quality incentive program in 2025. Patient responses were obtained and recorded by dialysis social workers during care plan assessments (Table S1). A total SRF burden score from the 5 domains, ranging from 0 to 5, was calculated and then categorized as screening positive for none (0), one (1), or more than one (>1) SRF domain. For patients who completed the AHC-HRSN questions more than once, the most recent response was utilized.
Waitlisting and Kidney Transplantation Outcome
The most recent kidney transplantation status of patients was ascertained from the electronic health record (EHR). The outcome was defined as not being waitlisted or not having received a transplant through March 2025.
Covariates
Patient characteristics were obtained from the DCI EHR and included age, sex, race/ethnicity classified in mutually exclusive groups as non-Hispanic White, non-Hispanic Black, Hispanic, American Indian, Asian, and other/unknown, dialysis vintage, health insurance type, and dialysis modality. Comorbid conditions including diabetes mellitus, congestive heart failure, peripheral vascular disease, chronic obstructive pulmonary disease, stroke/cerebrovascular disorder, and cancer, were determined from the Centers for Medicare & Medicaid Services form 2728 and updated with new diagnoses from the EHR. International Classification of Diseases (ICD)-10 codes were used to define comorbid conditions (Table S2). Health insurance at the time of the AHC-HRSN survey was also obtained from the EHR. Dialysis clinic location was classified as rural versus urban based on rural-urban commuting area codes.11 Supplemental questions regarding highest educational attainment and financial comfort were also ascertained. Education categories included grade school, high school, and undergraduate/postgraduate. Financial comfort was derived from the question “With the resources the patient has available, do they report that they are: not getting by, barely getting by, comfortable, or very comfortable?” and dichotomized as uncomfortable (not getting by, barely getting by) or comfortable (comfortable, very comfortable).
This study used retrospective clinical care data that were de-identified. It was reviewed and deemed exempt by the WCG IRB Work Order 1-1456342-1.
Statistical Analyses
Descriptive statistics of patients’ characteristics were summarized with numbers and proportions for categorical variables and with means and standard deviations for continuous variables, stratified by SRF group (none [0], one [1], or more than one [>1] SRF domain).
The unadjusted and adjusted odds ratios (ORs) and confidence intervals (CIs) for absence of waitlist/transplanted status were calculated, adjusting for the covariates above. Exploratory analyses examined the association between each SRF domain and the outcome. In addition, an age-stratified analysis was performed with age categorized into the following categories (age ≤55, 56-65, and 66-75) to further explore the association between transportation insecurity, an SRF domain for which access may vary by age group, and the outcome. Additional exploratory analysis was conducted to examine the relationship between an SRF score that incorporates financial strain and rurality and the study outcome. Missingness of the exposure and outcome variables was less than 5%. Statistical analyses were performed using SAS software, version 9.4.
Results
The study population included 12,994 patients receiving maintenance dialysis. The mean age was 57.9 ± 12.4 years, and 41.2% were female. The racial/ethnic distribution was as follows: 38% White, 38% Black, 8% Hispanic, 3% American Indian, 2% Asian, and 11% identifying as other (including unknown or mixed race/ethnicity). Using a total SRF burden score from the 5 domains (housing, transportation, personal safety, utilities, and food security), ranging from 0 to 5 and categorized as screening positive for none (0), one (1), or more than one (>1) SRF domain, 11,189 (86.1%) patients reported no SRFs, 1,360 (10.5%) patients reported one SRF, and 445 (3.4%) patients reported more than one SRF (Table 1). Compared with individuals with no SRFs, those with more than one SRF were younger (mean age 54 vs 58 years), more likely to be female (48% vs 41%), more likely to identify as Black (41% vs 38%) or of other race/ethnicity (14% vs 11%), less likely to be financially comfortable (12% vs 86%), and less likely to have a college education or higher (26% vs 35%).
Table 1.
Baseline Characteristics of Patients Receiving Maintenance Dialysis at DCI Who Completed the Social Risk Survey
| Characteristics | Total (N = 12,994) | 0 (n = 11,189) | 1 (n = 1,360) | >1 (n = 445) |
|---|---|---|---|---|
| Vintage (y) | ||||
| < 1 y | 2,587 (19.9%) | 2,219 (19.8%) | 271 (19.9%) | 97 (21.8%) |
| ≥1 y, < 3 y | 3,916 (30.1%) | 3,361 (30.0%) | 413 (30.4%) | 142 (31.9%) |
| ≥3 y, < 6 y | 3,281 (25.3%) | 2,859 (25.6%) | 326 (24.0%) | 96 (21.6%) |
| ≥ 6 y | 3,210 (24.7%) | 2,750 (24.6%) | 350 (25.7%) | 110 (24.7%) |
| Age | 57.9 (12.4) | 58.3 (12.4) | 56.1 (11.9) | 54.2 (11.5) |
| Male | 7,602 (58.5%) | 6,606 (59.0%) | 765 (56.3%) | 231 (51.9%) |
| Race/ethnicity | ||||
| Non-Hispanic White | 4,972 (38.3%) | 4,377 (39.1%) | 464 (34.1%) | 131 (29.4%) |
| Non-Hispanic Black | 4,884 (37.6%) | 4,198 (37.5%) | 506 (37.2%) | 180 (40.5%) |
| Hispanic | 1,033 (8.0%) | 859 (7.7%) | 138 (10.2%) | 36 (8.1%) |
| American Indian | 376 (2.9%) | 272 (2.4%) | 68 (5.0%) | 32 (7.2%) |
| Asian | 287 (2.2%) | 260 (2.3%) | 22 (1.6%) | 5 (1.1%) |
| Other/Unknown | 1,446 (11.1%) | 1,223 (10.9%) | 162 (11.9%) | 61 (13.7%) |
| Modality | ||||
| In-center | 11,099 (85.4%) | 9,480 (84.7%) | 1,219 (89.6%) | 400 (89.9%) |
| Home | 1,895 (14.6%) | 1,709 (15.3%) | 141 (10.4%) | 45 (10.1%) |
| Clinic location | ||||
| Rural | 2,902 (22.4%) | 2,505 (22.4%) | 305 (22.5%) | 92 (20.8%) |
| Urban | 10,062 (77.6%) | 8,660 (77.6%) | 1,051 (77.5%) | 351 (79.2%) |
| Insurance | ||||
| Commercial | 1,395 (10.7%) | 1,276 (11.4%) | 88 (6.5%) | 31 (7.0%) |
| Dual eligibility | 4,451 (34.3%) | 3,700 (33.1%) | 555 (40.8%) | 196 (44.0%) |
| Medicare advantage | 2,414 (18.6%) | 2,118 (18.9%) | 229 (16.8%) | 67 (15.1%) |
| Medicare/VA | 2,775 (21.4%) | 2,536 (22.7%) | 192 (14.1%) | 47 (10.6%) |
| Medicaid | 1,439 (11.1%) | 1,135 (10.1%) | 226 (16.6%) | 78 (17.5%) |
| Other | 520 (4.0%) | 424 (3.8%) | 70 (5.2%) | 26 (5.8%) |
| Financially comfortable | ||||
| Yes | 10,228 (78.7%) | 9,564 (85.5%) | 611 (44.9%) | 53 (11.9%) |
| No | 2,766 (21.3%) | 1,625 (14.5%) | 749 (55.1%) | 392 (88.1%) |
| Diabetes | 6,028 (46.4%) | 5,130 (45.9%) | 687 (50.5%) | 211 (47.4%) |
| PVD | 711 (5.5%) | 619 (5.5%) | 72 (5.3%) | 20 (4.5%) |
| Cancer | 1,080 (8.3%) | 971 (8.7%) | 90 (6.6%) | 19 (4.3%) |
| CHF | 2,672 (20.6%) | 2,293 (20.5%) | 289 (21.3%) | 94 (21.1%) |
| Pulmonary diseases | 1,266 (9.7%) | 1,067 (9.5%) | 139 (10.2%) | 60 (13.5%) |
| Stroke | 733 (5.6%) | 626 (5.6%) | 81 (6.0%) | 26 (5.8%) |
| Education | ||||
| Grade school | 1,128 (8.7%) | 911 (8.1%) | 161 (11.8%) | 56 (12.6%) |
| High School | 7,506 (57.8%) | 6,415 (57.3%) | 818 (60.2%) | 273 (61.4%) |
| College or higher | 4,360 (33.6%) | 3,863 (34.5%) | 381 (28.0%) | 116 (26.1%) |
Note: Values for categorical variables are given as number (percentage) and for continuous variables as mean ± SD.
Abbreviations: CHF, congestive heart failure; PVD, peripheral vascular disease.
In an adjusted model controlling for demographics, comorbid conditions, and rurality of the dialysis clinic, presence of one (OR 1.19 [0.99-1.3]) or more than one SRF (OR 1.65 [1.14-2.38]) was associated with a higher likelihood of not being currently waitlisted for or having received a kidney transplant. Other social factors significantly associated with this outcome included being financially uncomfortable (OR 1.54 [1.33-1.78]) and receiving dialysis in a rural facility (OR 1.26 [1.11-1.44]). Furthermore, having less than a high school education versus a college education (OR 1.87 [1.51-2.31]) and receiving in-center as opposed to home dialysis (OR 2.15 [1.90-2.42]) were each associated with a near 2-fold increase in the odds of not being listed or transplanted. Compared with individuals with Medicare/VA, those with Medicaid had the highest odds of not being waitlisted or transplanted (OR 2.10 [1.70-2.58]), followed by those with dual eligibility (OR 1.53 [1.33-1.76]) and Medicare Advantage (OR 1.30 [1.11-1.52]). Finally, American Indian (OR 1.69 [1.21-2.34]) and Black non-Hispanic race (OR 1.19 [1.07-1.33]) were both associated with higher odds of not being listed or transplanted in nonadjusted models as compared with White race (data not shown), but these relationships were attenuated after adjustment for SRFs (Table 2).
Table 2.
Health-Related Social Risk Factors and Odds Ratio of Not Being Transplanted or Listed for Transplant
| Variable | Adjusted Odds Ratio | Lower 95% CI | Upper 95% CI |
|---|---|---|---|
| Social risk factor burden | |||
| 0 stated SRF | Reference | ||
| 1 SRF | 1.19 | 0.99 | 1.43 |
| >1 SRF | 1.65 | 1.14 | 2.38 |
| Vintage | |||
| < 1 y | Reference | ||
| ≥1 y, < 3 y | 0.63 | 0.55 | 0.73 |
| ≥3 y, < 6 y | 0.54 | 0.46 | 0.63 |
| ≥6 y | 1.07 | 0.90 | 1.27 |
| Age (5 y) | 1.19 | 1.17 | 1.22 |
| Female vs male | 1.27 | 1.15 | 1.41 |
| Race | |||
| Non-Hispanic White | Reference | ||
| American Indian | 1.36 | 0.96 | 1.92 |
| Asian | 0.50 | 0.37 | 0.67 |
| Non-Hispanic Black | 1.09 | 0.97 | 1.23 |
| Hispanic | 0.75 | 0.62 | 0.92 |
| Other/Unknown | 0.91 | 0.77 | 1.07 |
| In-center vs home dialysis | 2.15 | 1.90 | 2.42 |
| Rural vs urban | 1.26 | 1.11 | 1.44 |
| Insurance | |||
| Medicare/VA | Reference | ||
| Commercial | 0.84 | 0.71 | 0.99 |
| Dual eligibility | 1.53 | 1.33 | 1.76 |
| Medicare advantage | 1.30 | 1.11 | 1.52 |
| Medicaid | 2.10 | 1.70 | 2.58 |
| Other | 1.56 | 1.19 | 2.05 |
| Financially uncomfortable | 1.54 | 1.33 | 1.78 |
| Diabetes | 1.19 | 1.08 | 1.32 |
| PVD | 1.50 | 1.13 | 1.98 |
| Cancer | 1.14 | 0.94 | 1.38 |
| CHF | 1.66 | 1.44 | 1.92 |
| Pulmonary diseases | 3.21 | 2.40 | 4.29 |
| Stroke | 1.47 | 1.13 | 1.91 |
| Education | |||
| College or higher | Reference | ||
| High school graduate | 1.56 | 1.41 | 1.74 |
| Grade school | 1.87 | 1.51 | 2.31 |
Abbreviations: CI, confidence interval; CHF, congestive heart failure; PVD, peripheral vascular disease; SRF, social risk factor.
In exploratory analyses evaluating individual SRF domains, transportation insecurity, described by 473 (3.6%) patients, emerged as the only domain significantly associated with the outcome, demonstrating a large effect size (OR 2.59 [1.74-3.87]) (Table 3). In the analysis of an alternate SRF burden score incorporating financial strain and rurality as separate domains, the association of the SRF burden score with not being listed or transplanted remained similar (SRF = 1 vs SRF = 0: OR 1.33 [1.19-1.50]; SRF > 1 vs SRF = 0: OR 1.98 [1.66-2.35]) (Table S3). The results of the age-stratified analysis of the association of transportation insecurity and the outcome are shown in Table S4. The association between transportation insecurity and not being listed or transplanted remained strong across age-stratified models.
Table 3.
Social Risk Factor Domains and Odds Ratio of Not Being Transplanted or Listed for Transplant
| Social Risk Factor Domain | N (%) of positive screening | Unadjusted Odds Ratio (95% CI) | Adjusted Odds Ratio (95% CI) |
|---|---|---|---|
| Housing instability | 581 (4.5%) | 1.74 (1.33-2.66) | 1.29 (0.98-1.71) |
| Transportation insecurity | 473 (3.6%) | 3.43 (2.33-5.03) | 2.59 (1.74-3.87) |
| Personal safety concerns | 16 (0.1%) | 1.46 (0.33-6.44) | 1.41 (0.31-6.45) |
| Utility needs | 295 (2.3%) | 1.38 (0.98-1.94) | 0.92 (0.63-1.33) |
| Food insecurity | 1006 (7.7%) | 1.58 (1.30-1.92) | 1.10 (0.88-1.38) |
Note: Models adjusted for age, race, gender, incenter versus home dialysis, urban versus rural location, insurance, being financially uncomfortable, level of education, and comorbidities, such as diabetes, peripheral vascular disease, cancer, congestive heart failure, pulmonary disease, and stroke.
Abbreviations: CI: confidence interval, N: total number, %: percentage of patients from total with social risk factor.
Discussion
In a large nationally representative cohort of maintenance dialysis patients with systematic assessment of social risk factors using a validated screening tool, ∼11% reported one SRF, and 3.4% reported more than one. In an adjusted model accounting for demographic characteristics and comorbid conditions, the presence of one or more SRF was significantly associated with increased odds of not being waitlisted or receiving a kidney transplant. These findings highlight the importance of systemically assessing SRFs in maintenance dialysis patients. This is particularly relevant given that some of these SRFs, such as lack of reliable transportation to and from medical appointments, are potentially modifiable through targeted interventions.
In our study, the prevalence of social risk factors was lower than those reported by Taylor et al,12 who found that 36% of patients reported food insecurity and that 18% reported housing instability among a predominantly Black (70%) cohort of 305 patients recieveing hemodialysis in the Baltimore–Washington DC area. This discrepancy might be related to our sample being larger and more diverse with a broader socioeconomic range; only 20.3% of our population reported financial discomfort compared to 61% in Taylor et al12 sample.
Individuals reporting financial strain and lower educational attainment had higher odds of not being transplanted or waitlisted. Given that kidney transplantation is the preferred treatment modality for most people with kidney failure—offering the greatest survival advantage and quality of life—these findings are particularly relevant.13 These findings are consistent with previous studies, including those by Wesselman et al,14 which demonstrated that adverse SRFs such as low income, public insurance, and limited education are associated with a lower probability of receiving a kidney transplant. Similarly, Patzer et al15 found that increasing neighborhood poverty was associated with reduced transplant listing, with Black patients experiencing the lowest likelihood of being listed within each poverty stratum. In our cohort, Black and American Indian patients had significantly higher odds of not being listed or transplanted compared to their White counterparts. These associations were attenuated after adjustment for SRF burden score, suggesting that addressing these SRFs can help address inequities in access to kidney transplantation.
Living in a rural versus urban area was associated with 25% increased odds of not being transplanted or waitlisted for a kidney transplant. These findings are consistent with those from Axelrod et al16 who reported lower kidney transplant waiting list registration rates (RR = 0.92; 95% CI, 0.90-0.95; P < 0.001) and lower kidney transplant rates (RR = 0.90; 95% CI, 0.88-0.93; P < 0.001) for rural/small town residents compared to urban dwelling patients with kidney disease. Understanding the role that SRFs play as barriers to optimal kidney care for rural-dwelling patients on dialysis (ESRD) is essential to effectively addressing these challenges.17
In our study, patients with commercial insurance had 16% lower odds of not being waitlisted or transplanted, while patients with Medicaid had over 2 times higher odds of not being transplanted or waitlisted compared to those with Medicare. Interestingly patients with Medicare Advantage (MA) had 30% higher odds of not being waitlisted or transplanted as compared to those with Medicare. These latter findings are consistent with recently published findings by Adler et al,18 showing increasing enrollment of patients with kidney failure in MA plans, particularly among socially disadvantaged patients, but showing that patients who initiated dialysis on an MA plan had an 18% lower hazard of transplant listing as compared to traditional Medicare plan enrollees. These discrepancies in transplant listing among patients with kidney failure based on insurance, should serve as call to the nephrology community to study barriers in transplant evaluation, waitlisting, and kidney transplant allocation posed by restrictive insurance coverage policies and advocate for insurance plans covering patients with advanced chronic kidney disease to be uniformly responsible for initiating standardized policies and benefits designed to maximize participants’ chances of kidney transplantation, including minimizing or capping patient and donor out-of-pocket expenses. This is particularly relevant given the steady rise in MA coverage and the heterogeneity of MA plans, among patients receiving dialysis since 2021, when the prohibition on dialysis patients enrolling in MA was eliminated.19
In supplemental analyses evaluating the association of each SRF domain with the outcome, transportation insecurity emerged as the single SRF domain strongly associated with not being transplanted or listed for transplant. Our findings are consistent with the recent findings by Razon et al, that in-center dialysis patients who lacked private transportation had higher mortality rates, and those with Medicaid, paratransit, and public transportation were more likely to miss dialysis treatments.20 Transportation insecurity is defined ‘As a condition in which a person is unable to regularly move from place to place in a safe or timely manner’ and is increasingly recognized as an important modifiable health related SRF.20,21 Transportation insecurity is particularly relevant for hemodialysis patients who rely on transportation to receive life sustaining therapy at least three times a week and need reliable transportation frequently with disability assistance to attend the numerous appointments required for kidney transplantation. These findings have practice and policy implications in building reliable transportation options for patients on dialysis for their health care needs beyond hemodialysis itself, including transplantation evaluation and associated testing.22,23
Clearly, ascertaining SRFs among patients with kidney failure requiring dialysis is important for maximizing individual success. While patients with higher SRF burden score were more likely to be younger, female, have Medicaid or be dual eligible, identify as Black and less likely to have a college education, patients reporting SRFs spanned all demographic characteristics. These findings are consistent with USRDS data showing that Medicaid beneficiaries tend to be younger, reside in socially deprived neighborhoods, and are more often of Black or Hispanic descent.6
Recognizing the role that SRFs play in health care and individual patient wellbeing, the Centers for Medicare & Medicaid Services had included screening for SRFs in the 2025 ESRD Prospective Payment System Final Rule; however, due to concerns regarding data acquisition burden, SRF screening was removed from the quality incentive program for 2026.24,25 Despite this, our work highlights the importance of continued assessment of SRFs among maintenance dialysis patients to help guide focused interventions to promote equitable access to kidney transplantation.
This study has several strengths, including the use of a large, diverse, and nationally representative sample that makes it generalizable to US dialysis patients, as well as the incorporation of SRF domains derived from the Accountable Health Communities screening tool. Several of these domains, such as food and housing insecurity, are strongly associated with adverse health outcomes across multiple populations, including patients with chronic kidney disease.26,27 However, this study has limitations, and given its cross-sectional design, the potential for residual confounding and reverse causality cannot be excluded. In addition, the sensitive nature of certain SRFs introduces the possibility of exposure misclassification and social desirability bias. Patients may hesitate to disclose social needs, which could lead to underreporting, biasing associations towards the null. Additionally, resource constraints and variability in processes may further limit the accuracy of SRF ascertainment. It is important to note that, among the SRF domains, transportation needs may be more accurately ascertained as dialysis facilities are aware of challenges with reliable access to dialysis treatments that result in missed hemodialysis sessions. Finally, substance abuse and mental health issues, factors known to be associated with lower transplant likelihood, were not ascertained in this study.28,29
Our findings underscore the need for the nephrology community to assess whether patients are affected by social risk factors and foster cross-sector partnerships to meaningfully address unmet social needs. Transportation insecurity presents itself as a social risk factor particularly relevant to our maintenance dialysis patients, who rely on transportation for life sustaining therapy, as well as to get to and from the many medical appointments required for kidney transplant evaluation and success.
Article Information
Authors’ Full Names and Academic Degrees
Hiba Hamdan, MBBS, MPH, Monica Shieu, PhD, Nien-Chen Li, PhD, Seda Babroudi, MD, MS, Antonia Harford, MD, Karen Majchrzak MS, Doug Johnson, MD, Eduardo Lacson Jr, MD, MPH, and Daniel E. Weiner, MD, MS
Author’s Contributions
Research idea: HH; study design: DW, EL, AH, and SB; data acquisition: MS, NL, EL, and DJ; data analysis/interpretation: HH, MS, NL, SB, AH, KM, EL, and DW; statistical analysis: MS, NL, and EL; supervision or mentorship: DW and EL. Each author contributed important intellectual content during manuscript drafting or revision and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved.
Support
Dr Babroudi is NIH funded: 1K12TR004384 NIH/NCATS Freund/Inker (MPI) 07/05/25-06/30/27.
Financial Disclosure
The authors declare that they have no relevant financial interests.
Acknowledgments
We would like to express our gratitude to Austin Gibson for his effort in preparing the dataset for this study.
Data Sharing
Partial restrictions apply to the availability of data and materials. Please reach out to the corresponding author for details.
Peer Review
Received October 06, 2025. Evaluated by 2 external peer reviewers, with direct editorial input from an Associate Editor and the Editor-in-Chief. Accepted in revised form January 06, 2026.
Declaration of Generative AI and AI-Assisted Technologies
The authors declare that we used Microsoft Co-Pilot for spelling and grammar editing in the preparation of this article. The authors have reviewed and edited the article and take full responsibility for its content.
Footnotes
Complete author and article information provided before references.
Table S1: Accountable Health Communities Health-Related Social Needs (AHC-HRSN) Screening Tool Questions for Each Health-Related Social Risk Domain and Scoring
Table S2: List of ICD Codes Used to Identify Variables in the Study
Table S3: Transportation Insecurity Prevalence and Odds Ratio of Not Being Transplanted or Listed for Transplant-Age Stratified
Table S4: Health-Related Social Risk Factors Including Having Financial Discomfort and Rurality of Dialysis Clinic and Odds Ratio of Not Being Transplanted or Listed for Transplant
Supplementary Materials
Tables S1-S4.
References
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Associated Data
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Supplementary Materials
Tables S1-S4.