The Association of Socioeconomic Status on Kidney Transplant Access and Outcomes: Cohort Studies of England and Northern Ireland
Michael Corr 1,2,✉, Jenni Beck 2, Aisling E Courtney 2, Christopher Cardwell 1, Pippa K Bailey 3,4, Paul Cockwell 5,6, Ciaran OβNeill 1, Alexander P Maxwell 1, Gareth J McKay 1
Abstract
Background.
While socioeconomic status (SES) is an established determinant of kidney transplant access and outcomes, less is known about how these disparities vary within universal healthcare systems. This study hypothesized that, despite shared healthcare and organ allocation systems, regional differences would be observed in the magnitude and pattern of the association between SES and transplant access and outcomes between England and Northern Ireland (NI).
Methods.
We conducted a retrospective cohort study using national transplant registry data from England (nβ =β 42β220) and NI (nβ =β 1615) from 2000 to 2020. SES was measured using national deprivation indices. Outcomes included transplant incidence, preemptive and living donor transplantation, graft survival, and patient survival. Statistical analyses included Poisson regression, Cox proportional hazards models, and concentration indices to assess equity.
Results.
In England, lower SES was significantly associated with reduced transplant access (incidence rate ratio for most versus least deprived quintile, 0.71; 95% confidence interval [CI], 0.69-0.73), lower rates of preemptive and living donor transplantation, and poorer graft (hazard ratio, 1.41; 95% CI, 1.32-1.50) and patient survival (hazard ratio, 1.49; 95% CI, 1.39-1.59). These disparities persisted across ethnic groups. In contrast, NI showed no significant SES-related differences in transplant access, despite a more deprived population overall.
Conclusions.
SES remains strongly associated with transplant access in England but not in NI, suggesting that regional models of healthcare delivery may mitigate or exacerbate inequities.These findings suggest a role of system design in promoting equity.
INTRODUCTION
Socioeconomic status (SES) is a well-established determinant of chronic kidney disease (CKD) incidence, progression, and outcomes. A 2018 meta-analysis of 43 cohorts reported that lower-income individuals have 34% higher odds of developing CKD (odds ratio, 1.34; 95% confidence interval [CI], 1.18-1.53).1 In the UKβs publicly funded National Health Service (NHS), the lowest SES quintile exhibits CKD prevalence up to 1.5 times that of the most affluent group.2 These gradients persist across high-income countries regardless of differences in overall healthcare spending and organization.3
Despite the promise of universal healthcare coverage to mitigate disparities in kidney replacement therapy (KRT), SES continues to shape access to transplantation. In the United Kingdom, socioeconomically deprived patients are less likely to be listed for transplant and even less likely to receive a living donor kidney (which demonstrate better outcomes). A study of 71 renal centers found that social deprivation independently predicted both lower rates of preemptive (before requiring KRT such a dialysis) and overall listing for transplantation.4,5 The most deprived quintile has been shown to have only 40% of the odds of receiving a living donor transplant compared with the least deprived.4 These inequalities also persist posttransplant: international data demonstrate lower graft and patient survival for those from deprived areas, including a Canadian cohort showing a 9% reduction in mortality with functioning graft per $10β000 increase in average neighborhood income.6
Much of the UK-based research linking SES to transplant inequity was published using data from before 2015,4,5,7 and since then, the NHS has undergone major service reorganizations, including the centralization of transplant services8 and updated national organ allocation algorithms intended to increase equitable access.9 However, there is little recent evidence evaluating whether these changes have narrowed the SES gap in transplantation. Notably, nearly all previous studies have treated the United Kingdom as a homogeneous entity, overlooking possible regional differences.4,5,7
England and Northern Ireland (NI) provide a natural experiment for better understanding these issues. Both nations operate under NHS universal healthcare and a single national organ allocation system. However, they differ markedly in population structure (England being larger, more urban, and with higher levels of ethnic diversity; NI being smaller, more rural, and more ethnically homogeneous), levels and patterns of deprivation, and models of service delivery. Understanding whether these systems attenuate the effects of demographic differences and modulate the impact of SES is critical for designing regionally sensitive, equity-focused interventions.
We hypothesized that despite a shared universal healthcare system and national organ allocation policy; socioeconomic deprivation will remain independently associated with poorer access to, and outcomes from, kidney transplantation in both England and NI. However, the magnitude and pattern of these disparities may differ by region, reflecting local population structure and health service delivery. As such, further consideration for region-sensitive interventions, both in the United Kingdom and other countries where regional variation is evident in national healthcare systems may be necessary.
MATERIALS AND METHODS
Study Design
This was a retrospective observational cohort study linking 2 established national kidney transplant databases. This study adheres to the STrengthening the Reporting of OBservational studies in Epidemiology reporting guidelines for the dissemination of observational research. A completed checklist is provided in Appendix A (SDC, https://links.lww.com/TP/D337).
Ethical Review
NHS Blood and Transplant (NHSBT) and UK Renal Registry have Human Research Authority Confidentiality Advisory Group approval to collect data on individuals under section 251 of the NHS Act 2006 and the Health Service (Control of Patient Information) Regulations 2002. NI data were collected from the NI Kidney Transplant database (REC 23/NI/0034).
Study Setting
English data were collated by NHSBT and obtained from the UK Transplant Registry (UKTR). England has a population of approximately 57 million (population density 279/km2). The region has an annual incidence of approximately 7000 patients (122.8 per million population) commencing KRT and is serviced by 20 transplant centers.10
NI data were collected from the NI Kidney Transplant database. NI has a population of 1.9 million (population density: 135/km2). The region has an annual incidence of approximately 205 patients (107.8 per million population) starting KRT within a single transplant center.10
The healthcare systems in England and NI are both part of the UKβs NHS, providing comprehensive healthcare services. In both regions, kidney transplant allocation is coordinated by NHSBT through an allocation system designed to ensure equity based on medical need and donor-recipient organ compatibility to maximize transplant success.
Study Population
All patients (both pediatric and adult) who received a kidney transplant in England and NI in the years 2000β2020 were included. Recipients of dual kidney-pancreas or other multiple organ transplants were excluded.
Estimated Minimum Detectable Differences
We estimated the minimum detectable difference in transplantation rates between deprivation quintiles, assuming equal group sizes and a baseline rate of 20%. For the NI cohort (nβ =β 1615; 320 per quintile), the smallest absolute difference detectable at Ξ± = 0.05 with 76% power was 8% points (20% versus 12%). In contrast, the larger English cohort (nβ =β 43β917; 8783 per quintile) could detect a difference as small as 1.7 percentage points with 80% power.
Study Measures
UK Government deprivation indices were used to determine SES. The English Index of Multiple Deprivation 2010 (IMD)11 and the NI Multiple Deprivation Measure 2017 (NIMDM)12 are constructed from data collected across multiple domains, including income, employment, health, education, crime, barriers to housing and services, and living environment. Data are then aggregated and weighted to produce a composite deprivation score/rank for small geographic areas with a range of population size of approximately 1500β2100 facilitating the identification of regions experiencing relative deprivation. The UKTR routinely collects IMD data for all transplant recipients in England. NIMDM was obtained through the NI Kidney Transplant Database. Direct comparison between both indices is not possible as deprivation is relative to each specific region. However, based on previous work to harmonize deprivation indices across the United Kingdom, individual deprivation scores were converted to a composite UK-wide score using methods outlined by Abel et al.13
Covariates
Covariates previously reported to be associated with designated endpoints were collected including recipient age, sex, ethnicity, number of HLA mismatches (0β6), year of transplant, donor type, and KRT before transplantation.
Study Endpoints
Rates of transplantation, including preemptive and living donor transplantation, were recorded. Graft failure was captured as an endpoint based on the time from transplantation until a requirement for dialysis or retransplant. Participants were censored on the last day of follow-up or the length of time from transplantation until death.
Statistical Analysis
All analyses were performed using R (Version [4.2.2]). Statistical significance was set at Pβ <β 0.05.
Missing Data
Descriptive analyses quantified missingness across key variables. We addressed missing data in the English cohort using multiple imputation by chained equations as part of sensitivity analysis. Five imputations were generated using predictive mean matching for continuous variables and multinomial logistic regression for categorical variables. Imputation models incorporated relevant clinical and demographic variables. Rubinβs rules were used to pool estimates across imputations. Sensitivity analysis was performed to measure effect of missing data on robustness of analysis. There was no missing data in the NI dataset so full-case analysis was used.
Descriptive and Inferential Analyses
We used incidence rate ratios (IRRs) for transplantation by dividing transplant counts by mean annual prevalent KRT populations per deprivation quintile, scaled per 1000 individuals. IRRs comparing deprivation quintiles in England and NI were calculated via Poisson regression models, with the least deprived quintile as the reference group. Population denominators for deprivation ranks were derived from UK Renal Registry data for each nationβs total KRT population. Exponentiated IRRs and 95% CIs were reported for interpretability. Formal testing for overdispersion was not feasible because the Poisson models were saturated and based on aggregated quintile-level counts. If minor overdispersion were present, SEs would be slightly underestimated, producing marginally narrower CIs and smaller P values; this would not materially affect interpretation. We performed k-means clustering of English transplant centersβ IRR profiles to assess center-variation of access to transplantation.
Inequality Metrics and Visualization
We plotted concentration curves and calculated the Erreygers concentration index annually to assess changes in inequality over time. Erreygers was used because of the binary, bounded nature of the outcome.14
Survival Analysis
Cox proportional hazards regression models were used to evaluate posttransplant graft and patient survival. Models were adjusted for, sex, ethnicity, donor type, preemptive status, recipient age, and total HLA mismatch burden. Proportional hazards assumptions were evaluated using Schoenfeld residuals.
RESULTS
For the study period between 2000 and 2020, 43β917 English kidney transplant recipient records were retrieved from the UKTR. SES data were missing for 3.9% of cases, leaving 42β220 for complete-case analysis. Missingness was associated with younger age, minority ethnicity, and transplant center. Given the relatively small rate of missingness, primary analyses used complete cases. Sensitivity analyses using multiple imputation for SES and covariates yielded similar results to the primary analysis (see Supplementary File [SDC, https://links.lww.com/TP/D336], section 1.0).
In NI, 1615 recipient records were retrieved. Table 1summarizes the cohort characteristics and transplants numbers by UK IMD quintile. The English cohort was more ethnically diverse, while the NI cohort had higher rates of preemptive and living donor transplants.
TABLE 1.
Demographic details of English and Northern Irish kidney transplant recipients 2000β2020
| Demographic | English data, nβ =β 42β220 | Northern Irish data, nβ =β 1615 | Descriptive statistical test | P |
| Age, y | Median, 48 (range, 1β85) | Median, 47 (range, 3β82) | Mann-Whitney U test | 0.42 |
| Sex | Male 25β754 (61%) | Male 976 (60%) | Ο2 test | 0.52 |
| Female 16β044 (38%) | Female 639 (40%) | |||
| Unknown 270 (<1%) | ||||
| Not reported 152 (<1%) | ||||
| Ethnicity | White 31β665 (75%) | White 1599 (99%) | Ο2 test (Fisher exact test) | <0.001 |
| Asian 5911 (14%) | Other 16 (1%) | |||
| Black 2955 (7%) | ||||
| Other 843 (2%) | ||||
| Unknown 434 (1%) | ||||
| Not reported 412 (1%) | ||||
| Donor type | DBD 19β421 (46%) | DBD 765 (47%) | Ο2 test | 0.02 |
| DCD 8866 (21%) | DCD 167 (10%) | |||
| Living donor 13β933 (33%) | Living donor 683 (43%) | |||
| Previous KRT | Preemptive 8021 (19%) | Preemptive 398 (25%) | Ο2 test | 0.01 |
| Previous KRT 33β776 (80%) | Previous KRT 1217 (75%) | |||
| Not reported 357 (<1%) | ||||
| Unknown 66 (<1%) | ||||
| HLA mismatch | Total: Median 3 | Total: Median 3 | Mann-Whitney U test (total HLA) | 0.88 |
| AA: Median 1 | AA: Median 1 | |||
| BB: Median 1 | BB: Median 1 | |||
| DR: Median 1 | DR: Median 1 | |||
| Matchability score | 8 | 8 | Mann-Whitney U test | 0.15 |
| UK IMD (No. and % of total transplant population) | 1. Most deprived 6594 (15.6%) | 1. Most deprived 528 (32.7%) | Ο2 test | <0.01 |
| 2. 7380 (17.5%) | 2. 476 (29.5%) | |||
| 3. 7931 (18.8%) | 3. 333 (20.6%) | |||
| 4. 9264 (21.9%) | 4. 252 (15.6%) | |||
| 5. Least deprived 11β045 (26.2%) | 5. Least deprived 26 (1.6%) |
Ethnicity for the England cohort is presented in full to reflect population diversity. The Northern Ireland cohort is shown as βWhite vs Otherβ owing to very small numbers in minority groups. For statistical comparisons, ethnicity was analyzed as a binary variable (βWhite vs ethnic minorityβ) in both cohorts to ensure comparability.
DBD, donation after brainstem death; DCD, donation from circulatory death; KRT, kidney replacement therapy; UK IMD, UK Index of Multiple Deprivation.
Comparison of Rates of Kidney Transplantation Across Deprivation for England and NI
We divided English and Northern Irish cohorts into deprivation quintiles using the UK IMD, assigning quintiles within each country. This was necessary because >60% of NI residents fall into the 2 most deprived UK-wide quintiles, resulting in sparse and unstable groups for direct comparison.
To provide context for the IRR analyses, crude denominators and transplant counts by nation-specific deprivation quintile are shown in Table 2. In England, the number of transplants was relatively similar across quintiles despite larger KRT populations in more deprived groups, resulting in lower crude transplant rates per 1000 individuals with increasing deprivation. In NI, crude transplant rates were more evenly distributed across quintiles, consistent with the absence of a clear deprivation gradient.
TABLE 2.
Mean annual prevalent kidney replacement therapy population, number of kidney transplants, and crude transplant rates per 1000 population, stratified by national deprivation quintile for England and Northern Ireland 2000β2020
| Deprivation quintile | England KRT population | England kidney transplants | England transplant rate/1000 of KRT population | NI KRT population | NI kidney transplants | NI transplant rate/1000 of KRT population |
| Q1 (most deprived) | 12β587 | 8257 | 656 | 352 | 343 | 974 |
| Q2 | 12β090 | 8409 | 696 | 349 | 321 | 920 |
| Q3 | 11β273 | 8119 | 720 | 351 | 314 | 895 |
| Q4 | 9283 | 8544 | 920 | 323 | 321 | 994 |
| Q5 (least deprived) | 9079 | 8891 | 979 | 322 | 316 | 981 |
KRT, kidney replacement therapy; NI, Northern Ireland.
IRRs for kidney transplantation were calculated across national deprivation quintiles, using the least deprived group as the reference and UK Renal Registry data for denominators. Table 3 shows a clear deprivation gradient in England, with those in the most deprived quintile significantly less likely to receive a transplant (IRR, 0.71; 95% CI, 0.69-0.73; Pβ <β 0.01), consistent across all ethnic groups. In NI, IRRs were close to 1 across all quintiles, with no significant differences observed. Sensitivity analysis solely using UK IMD score and imputation for missing data did not significantly alter results observed (Tables S1 and S2, SDC, https://links.lww.com/TP/D336). As part of a sensitivity analysis, IRRs were also estimated for NI based on NIMDM quintiles with similar results and no clear deprivation gradient across NI transplant rates (Table S3, SDC, https://links.lww.com/TP/D336).
TABLE 3.
Association between socioeconomic deprivation and transplant rates in England (including stratification by ethnicity) and Northern Ireland 2000β2020
| Deprivation quintile | Northern Ireland, nβ =β 1615 | England Whole population, nβ =β 42β220 | England White population, nβ =β 31β665 | England Asian population, nβ =β 5911 | England Black population, nβ =β 2955 | |||||
| IRR (95% CI) | P | IRR (95% CI) | P | IRR (95% CI) | P | IRR (95% CI) | P | IRR (95% CI) | P | |
| Q1 (most deprived) | 0.99 (0.85-1.16) | 0.91 | 0.71 (0.69-0.73) | <0.01 | 0.71 (0.69-0.74) | <0.01 | 0.71 (0.65-0.77) | <0.01 | 0.70 (0.63-0.79) | <0.01 |
| Q2 | 0.93 (0.80-1.09) | 0.39 | 0.72 (0.70-0.74) | <0.01 | 0.73 (0.77-0.83) | <0.01 | 0.73 (0.68-0.80) | <0.01 | 0.74 (0.66-0.79) | <0.01 |
| Q3 | 0.91 (0.78-1.07) | 0.25 | 0.80 (0.78-0.83) | <0.01 | 0.80 (0.77-0.83) | <0.01 | 0.80 (0.74-0.87) | <0.01 | 0.80 (0.72-0.90) | <0.01 |
| Q4 | 1.01 (0.87-1.18) | 0.87 | 0.89 (0.87-0.92) | <0.01 | 0.89 (0.86-0.93) | <0.01 | 0.89 (0.82-0.96) | <0.01 | 0.86 (0.77-0.96) | <0.01 |
| Q5 (least Deprived) | Reference | Reference | Reference | Reference | Reference | |||||
CI, confidence interval; IRR, incidence rate ratio.
IRRs With 95% CIs
Sensitivity analyses stratified by age (<18 and <30 y) showed similar patterns of deprivation effect for transplant access in England to the overall cohort. However, in NI, the numbers were too small for meaningful subgroup analyses, and in both cohorts event rates for graft failure and mortality in younger patients were too low to support stable modeling (Tables S4 and S5, SDC, https://links.lww.com/TP/D336).
Cluster analysis of English transplant centers identified 3 groups with distinct equity patterns. The majority of centers (cluster 2, nβ =β 11) showed reduced access for the most deprived, matching the national trend. A subset (cluster 1, nβ =β 8, generally larger centers) had more variable access for deprived groups (Tables S6 and S7, Figure S1, SDC, https://links.lww.com/TP/D336).
Interpretation of center-level variation is limited by anonymization of center identity and the use of national rather than regional KRT denominators. Hence, centers serving more deprived areas may appear more equitable because of an underestimation of the levels of social deprivation in the populations they serve. These findings do however demonstrate substantial heterogeneity in equity of access across English centers but with a caution against over-interpreting apparent center performance.
Concentration Curves and Indices
Figure 1 presents concentration curves for kidney transplant access by deprivation in England and NI, comparing the cumulative proportion of kidney transplants to the cumulative proportion of the KRT population ranked from most to least deprived. For England, the concentration curve lies below the line of equality, indicating individuals from less deprived areas receive a disproportionately greater share of kidney transplants relative to their representation in the KRT population. In NI, the concentration curve closely follows the line of equality, indicating that kidney transplants are generally distributed proportionally across deprivation groups indicating little or no socioeconomic gradient in transplant access within NIβs KRT population.
FIGURE 1.
Concentration curves of kidney transplant access by deprivation in England and Northern Ireland (2000β2020). Curves show the cumulative proportion of transplants versus the kidney replacement therapy population, ranked from most to least deprived. In England, the curve falls below the line of equity (dashed line), indicating preferential pro-affluent access. In Northern Ireland, the curve aligns with the equity line, showing equitable access across deprivation groups.
The concentration curves for preemptive and living donor transplantation in England are displayed in Figure 2. In both, the concentration curves lie below the line of equality, representing a predominance of preemptive and living donor transplantation for the least deprived English transplant recipients.
FIGURE 2.
Concentration curves of living donor and preemptive kidney transplant access by deprivation in England (2000β2020). Curves plot the cumulative proportion of living donor (left) and preemptive (right) transplants against the cumulative proportion of recipients, ranked from most to least deprived. Both curves fall below the line of equity (dashed line), indicating that less deprived groups are overrepresented among recipients of these transplant types.
The concentration curves for preemptive and living donor transplantation in NI are displayed in Figure 3. In NI, the curves lie along the line of equality representing a more progressive pattern to preemptive and living donor transplantation.
FIGURE 3.
Concentration curves of living donor and preemptive kidney transplant access by deprivation in Northern Ireland (2000β2020). Curves show the cumulative proportion of living donor (left) and preemptive (right) transplants by deprivation rank. Both curves closely follow the line of equity (dashed line), indicating equitable access to these transplant types across deprivation groups in Northern Ireland.
Concentration indices shown in Figure 4, demonstrate that in England, socioeconomic inequalities in access to both total and living donor transplantation have persisted throughout the study period, indicating no improvement in equity of access. In contrast, concentration indices in NI fluctuate around zero each year, indicating more equitable access to transplantation regardless of SES. To assess whether the NHS reforms altered transplant equity, we repeated analyses stratified into pre- (2000β2014) and post-reform (2015β2020) periods. Results (Tables S8 and S9, SDC, https://links.lww.com/TP/D336) showed persistent deprivation gradients in England across both eras, with only modest attenuation post-2015. In contrast, NI continued to demonstrate no consistent evidence of socioeconomic inequity across either period.
FIGURE 4.
Yearly concentration index of kidney transplant access by deprivation in England and Northern Ireland (2000β2020). The concentration index quantifies the degree of socioeconomic inequality in access to kidney transplantation, with positive values indicating preferential pro-affluent access (favoring the least deprived) and values near zero indicating equity. Annual indices are shown separately for total transplants (blue) and living donor transplants (red) in England (left) and Northern Ireland (right).
Association of Socioeconomic Status and Transplant Graft Survival
Both the English and NI cohorts were divided into quintiles based on their rank UK IMD score, respectively. Cox regression was used to assess associations between deprivation quintile and transplant graft survival; the least deprived quintile being used as the reference category. The results of both regression models can be viewed in Table 4. Impact of ethnicity as a variable in NI was not included given the small total number of ethnic minority recipients (nβ =β 16). English data were stratified according to self-reported White, Black, and Asian ethnic backgrounds. Sensitivity analysis imputation for missing data in the English cohort did not change the overall results (Table S10, SDC, https://links.lww.com/TP/D336).
TABLE 4.
Adjusted Cox regression analysis of factors associated with graft survival in England and Northern Ireland 2000β2020
| Variable | Northern Ireland, HR (95% CI), nβ =β 1615 | England Whole population, HR (95% CI), nβ =β 42β220 | England White population, HR (95% CI), nβ =β 31β665 | England Asian population, HR (95% CI), nβ =β 5911 | England Black population, HR (95% CI), nβ =β 2955 |
| Q1 (most deprived) | 1.40 (0.92-2.13; Pβ =β 0.121) | 1.41 (1.32-1.50; Pβ <β 0.001) | 1.46 (1.35-1.57; Pβ <β 0.001) | 1.16 (0.95-1.41; Pβ =β 0.138) | 1.35 (0.98-1.87; Pβ =β 0.074) |
| Q2 | 1.30 (0.84-1.99; Pβ =β 0.238) | 1.29 (1.20-1.37; Pβ <β 0.001) | 1.30 (1.21-1.40; Pβ <β 0.001) | 1.06 (0.86-1.30; Pβ =β 0.584) | 1.24 (0.89-1.73; Pβ =β 0.205) |
| Q3 | 1.72 (1.14-2.60; Pβ <β 0.001) | 1.19 (1.11-1.27; Pβ <β 0.001) | 1.17 (1.09-1.26; Pβ <β 0.001) | 1.21 (0.98-1.50; Pβ =β 0.071) | 1.20 (0.84-1.71; Pβ =β 0.307) |
| Q4 | 1.48 (0.98-2.25; Pβ =β 0.064) | 1.12 (1.05-1.20; Pβ =β 0.001) | 1.13 (1.05-1.21; Pβ <β 0.001) | 1.12 (0.89-1.42; Pβ =β 0.339) | 1.11 (0.75-1.64; Pβ =β 0.615) |
| Q5 (least deprived and reference population) | Reference | Reference | Reference | Reference | Reference |
| Female sex | 1.19 (0.93-1.54; Pβ =β 0.173) | 1.04 (1.00-1.09; Pβ =β 0.037) | 1.03 (0.98-1.08; Pβ =β 0.19) | 1.13 (1.01-1.25; Pβ =β 0.032) | 1.10 (0.96-1.25; Pβ =β 0.070) |
| Ethnic minority | Not adjusted | 1.09 (1.04-1.15; Pβ <β 0.001 | Not adjusted | Not adjusted | Not adjusted |
| Nonpreemptive transplant | 1.37 (0.94-2.01; Pβ =β 0.11) | 1.39 (0.52-2.70; Pβ =β 0.51) | 1.29 (0.32-3.23; Pβ =β 0.72) | 1.22 (0.29-1.68; Pβ =β 0.136) | 1.23 (0.34-1.84; Pβ =β 0.231) |
| Deceased donor transplant | 1.56 (1.04-2.05; Pβ =β 0.01) | 2.07 (1.11-2.39; Pβ =β 0.004) | 1.16 (0.29-4.65; Pβ =β 0.83) | 1.67 (0.87-2.64; Pβ =β 0.068) | 1.76 (0.67-2.33; Pβ =β 0.118) |
| HLA mismatch | 1.07 (1.01-1.16; Pβ =β 0.03) | 1.04 (1.02-1.06; Pβ <β 0.001) | 1.03 (1.01-1.05; Pβ <β 0.001) | 1.07 (1.02-1.11; Pβ =β 0.004) | 1.03 (1.00-1.12; Pβ =β 0.037) |
HRs with 95% CIs are shown for each variable. Models are adjusted for socioeconomic quintile, ethnic minority (England whole population only), nonpreemptive transplantation, deceased donor transplantation, and HLA mismatch. HR > 1 indicates increased risk of graft failure (worse graft survival).
CI, confidence interval; HR, hazard ratio.
Socioeconomic deprivation was strongly associated with poorer graft survival in England, with the most deprived quintile having a 41% higher risk of graft failure compared with the least deprived (hazard ratio [HR], 1.41; 95% CI, 1.32-1.50; Pβ <β 0.001). This deprivation gradient was also evident in White recipients and, although not statistically significant, effect estimates for Asian and Black recipients were similar in direction but less precise, reflecting smaller sample sizes.
Association of Socioeconomic Status and Patient Survival
Cox regression was used to assess associations between deprivation quintile and patient survival; the least deprived quintile being used as the reference category. The results of both regression models can be viewed in Table 5.
TABLE 5.
Adjusted Cox regression analysis of factors associated with patient survival in England and Northern Ireland 2000β2020
| Variable | Northern Ireland, HR (95% CI), nβ =β 1615 | England Whole population, HR (95% CI), nβ =β 42β220 | England White population, HR (95% CI), nβ =β 31β665 | England Asian population, HR (95% CI), nβ =β 5911 | England Black population, HR (95% CI), nβ =β 2955 |
| Q1 (most deprived) | 1.24 (0.88-1.73; Pβ =β 0.221) | 1.49 (1.39-1.59; Pβ <β 0.001) | 1.56 (1.45-1.69; Pβ <β 0.001) | 1.28 (1.05-1.56; Pβ =β 0.016) | 1.06 (0.72-1.55; Pβ =β 0.774) |
| Q2 | 1.14 (0.82-1.60; Pβ =β 0.434) | 1.21 (1.13-1.30; Pβ <β 0.001) | 1.26 (1.17-1.36; Pβ <β 0.001) | 1.06 (0.86-1.31; Pβ =β 0.574) | 0.82 (0.56-1.22; Pβ =β 0.332) |
| Q3 | 0.94 (0.66-1.34; Pβ =β 0.748) | 1.18 (1.10-1.26; Pβ <β 0.001) | 1.19 (1.11-1.28; Pβ <β 0.001) | 1.08 (0.87-1.34; Pβ =β 0.501) | 0.93 (0.62-1.41; Pβ =β 0.732) |
| Q4 | 1.33 (0.96-1.85; Pβ =β 0.089) | 1.10 (1.03-1.18; Pβ =β 0.005) | 1.09 (1.02-1.17; Pβ =β 0.014) | 1.20 (0.95-1.52; Pβ =β 0.128) | 0.85 (0.54-1.35; Pβ =β 0.497) |
| Q5 (least deprived and reference population) | Reference | Reference | Reference | Reference | Reference |
| Female sex | 1.05 (0.96-1.85; Pβ =β 0.089) | 0.86 (0.82-0.90; Pβ <β 0.001) | 0.86 (0.82-0.91; Pβ <β 0.001) | 0.83 (0.74-0.94; Pβ =β 0.003) | 0.96 (0.80-1.14; Pβ =β 0.625) |
| Ethnic minority | Not adjusted | 0.97 (0.92-1.03; Pβ =β 0.327) | Not adjusted | Not adjusted | Not adjusted |
| Nonpreemptive transplant | 1.92 (1.32-2.81; Pβ =β 0.001) | 1.49 (1.39-1.59; Pβ <β 0.001) | 1.46 (1.36-1.57; Pβ <β 0.001) | 1.59 (1.29-1.96; Pβ =β 0.001) | 1.77 (1.20-2.62; Pβ =β 0.004) |
| Deceased donor transplant | 1.49 (1.15-1.94; Pβ =β 0.003) | 1.33 (1.26-1.40; Pβ <β 0.001) | 1.34 (1.26-1.42; Pβ <β 0.001) | 1.34 (1.13-1.96; Pβ <β 0.001) | 1.28 (1.01-1.63; Pβ =β 0.043) |
| Recipient age | 1.06 (1.05-1.07; Pβ <β 0.001) | 1.07 (1.06-1.08; Pβ <β 0.001) | 1.07 (1.06-1.08; Pβ <β 0.001) | 1.07 (1.06-1.08; Pβ <β 0.001) | 1.06 (1.05-1.07; Pβ <β 0.001) |
HRs with 95% CIs are presented. Models are adjusted for socioeconomic quintile, female sex, ethnic minority (for English whole population data only), nonpreemptive transplantation, deceased donor transplantation, and recipient age. HR > 1 indicates increased risk of death (worse patient survival).
CI, confidence interval; HR, hazard ratio.
Socioeconomic deprivation was strongly associated with reduced patient survival in England, with the most deprived quintile showing a 49% higher risk of death compared with the least deprived (HR, 1.49; 95% CI, 1.39-1.59; Pβ <β 0.001). This was also apparent in White, and to a lesser extent, Asian recipients, but not observed in NI or in the Black English subgroup. Sensitivity analysis imputation for missing data in the English cohort did not change the overall results (Table S11, SDC, https://links.lww.com/TP/D336).
We formally tested whether the effect of SES on graft and patient survival differed by ethnicity. Interaction terms between deprivation quintile and ethnicity were not statistically significant (likelihood ratio test Pβ =β 0.10 for graft; Pβ =β 0.08 for patient survival). Ethnicity-specific HRs are provided in Table S12 (SDC, https://links.lww.com/TP/D336). These analyses indicate that while both deprivation and ethnicity were independently associated with outcomes, there was no strong evidence that their effects differed across groups.
DISCUSSION
This study demonstrates that socioeconomic deprivation is associated with lower rates of kidney transplantation and poorer graft and patient survival in England. In contrast, NI showed less evidence of socioeconomic inequity in transplant access or outcomes, despite a more deprived population overall. These findings highlight significant national variation in equity of kidney transplant care within the UKβs universal healthcare system. Importantly as seen in Figure 4, there appears to be no evidence of improvement over the last 20 y of practice. Nearly all previous research has combined the whole United Kingdom or focused on England alone, leaving a gap in knowledge about intra-UK regional variation.4,5,7
We also explored age stratification in sensitivity analyses. Numbers were small, particularly in NI, and event rates for graft failure and mortality were too low in younger groups to permit stable modeling. Nevertheless, the observed deprivation gradient in access among younger recipients in England was similar to that of the overall cohort. This finding is notable given that pediatric patients received prioritization within UK allocation policies until 2019, underscoring that this central policy nationally failed to ensure socioeconomic equity in transplant access.
Our results are consistent with recent registry studies showing that free universal healthcare provision does not alone eliminate socioeconomic inequity in access to kidney transplantation.15–17 A Swedish cohort study found that lower income was associated with a reduced likelihood of being waitlisted and receiving a transplant.15 Similarly, a Canadian population-based study reported a 2-fold to 4-fold variation in transplant rates across regional renal programs, with neighborhood income identified as an independent predictor.16 Our findings also echo French registry evidence suggesting that the degree of SES disparity varies according to local program organization and that while deprivation limits access to the transplant waitlist in different centers, once listed, subsequent access to transplantation is less unequal.17 Hence, our analysis extends the international evidence base, directly demonstrating that local context and service organization likely affect the magnitude of socioeconomic inequity.
Our era analyses demonstrated little evidence that the NHS reorganization changes narrowed socioeconomic inequities in England. Deprivation gradients in access and outcomes remained persistent across both eras, whereas NI consistently showed equitable patterns before and after the reforms. These findings underscore that structural reforms at national level, while important, have not on their own addressed entrenched inequities, and highlight the need to consider how service design and local delivery models influence equity in practice.
Limitations
Several limitations should be noted. The NI cohort was considerably smaller than Englandβs, reducing the statistical power to detect subtle deprivation effects or differences between quintiles. However, this is unlikely to explain our findings entirely. Given that >60% of NIβs population fall into the 2 most deprived UK-wide quintiles, if deprivation had the same impact as in England, overall transplant rates in NI would be markedly lower. Instead, higher transplant rates were observed with little evidence of a deprivation gradient and inequity in NI, in contrast to that observed in the English data. Our analysis included only transplant recipients and therefore cannot assess disparities occurring earlier in the pathway, such as access to KRT, waitlisting, or preemptive referral. These remain important potential sources of inequity that warrant investigation using linked datasets.
A further limitation was the inability to include the other 2 nations of the United Kingdom, Scotland and Wales, in our analysis. NHSBT does not currently collect deprivation data for these nations, which makes direct comparisons infeasible. Future research using harmonized deprivation data across all 4 nations would, however, be valuable in providing a comprehensive UK-wide picture of transplant equity.
Because of limitations of available registry data, we could not account for all potential confounders and mediators such as comorbidities, quality of donated organ, health literacy, and social support. Furthermore, the distribution of these confounders may vary between regions and deprivation strata. Our use of national, rather than regional, KRT prevalence as denominators for English center-level analyses may underestimate the true socioeconomic burden in some catchment areas, limiting interpretation of apparent center-level βperformance.β
Interpretation and Implications
The contrast in socioeconomic equity between England and NI invites reflection on how system organization can shape access within a shared national framework. Both nations operate under the same NHS funding and allocation policies, yet their patterns of access diverge. A plausible explanation lies in differences in service configuration and coherence: NIβs single integrated center may enable more consistent referral, assessment, and activation for transplantation, while Englandβs multicenter system introduces procedural variation that can compound existing disadvantage. These structural contrasts, coupled with sustained public engagement with organ donation and close collaboration across renal and transplant services in NI, provide a coherent hypothesis for the absence of a measurable deprivation gradient. These mechanisms remain to be tested formally through pathway and organizational analyses.
Belfast is the UKβs fourth-largest center for living donor transplantation despite serving only 3% of the UK population, and NI maintains the highest organ-donor registration rate nationally (~55% of adults).18 In contrast, Englandβs 20-center system varies in infrastructure and case-mix, conditions that may amplify socioeconomic gaps. Living donor transplantation requires significant personal engagement and support networksβareas where socioeconomic and ethnic characteristics intersect and where disparities can emerge in complex systems.19,20 Historically, NI has simplified donor and recipient pathways, which may assist socioeconomically disadvantaged groups in navigating the transplant journey.21–23
System culture also appears to play a role. While our dataset did not capture organ offer-decline data, NHSBT audits suggest NI has progressively reduced decline rates for standard-criteria kidneys, approaching zero by 2024, compared with 20%β30% at many English centers. Although absolute numbers remain small, this pattern suggests a culture of high utilization and risk acceptance, consistent with a system designed to prioritize transplantation. This aligns with persistently high transplant rates in NI despite greater overall deprivation, reinforcing that system design and organizational culture can mitigate socioeconomic inequities.24–26
Beyond structure, how the service interacts with providers and the public may reinforce equity. The small number of referring renal units facilitates consistent referral practices and close communication with the transplant center. Regular media engagement and political endorsement keep transplantation a salient public issue, while collaboration with general practitioners promotes earlier identification and referral. Together, these features may underpin both high organ utilization and the equitable outcomes observed in NI.
The NI experience highlights several system-level lessons. Sustained investment in surgical capacity, streamlined assessment, and integrated referral pathways can reduce attrition and improve access across socioeconomic groups. Public and professional buy-in, supported by visible political endorsement, helps normalize transplantation and strengthen public trust. Strong regional clinical cohesion enables iterative improvements that cumulatively promote equity. These mechanisms are inevitably interpretive, but they demonstrate that equity can be fostered through deliberate system design.
Nonetheless, ethnic inequity remains a significant challenge. Asian and Black patients in England continue to experience lower living-donor rates and reduced access, consistent with national findings from the Access to Transplant and Transplant Outcome Measure study (odds ratio = 0.55 and 0.64, respectively, even after adjusting for deprivation).27 Structural reform is therefore necessary but insufficient; culturally tailored strategies, education, translator access, community partnerships, and financial support for donors, remain essential. Prior qualitative work underscores that barriers are often social and psychological, including health literacy, navigation, and trust.19 NIβs experience illustrates that such barriers can be mitigated through focused service models, albeit within a less ethnically diverse population.
Policy and Practice
These findings suggest system design, local accountability, and tailored outreach are crucial. Nationally, there should be less tolerance for center-level variation and more active performance management monitoring, similar in approach to organ utilization.8,28 Interventions that directly improve or provide work-around solutions to assist patient navigation, health literacy, and community engagement are urgently needed. It is not sufficient to provide theoretically equal access that require improved provision to ensure better equity in practice.29–32
Future Directions
Understanding why socioeconomic equity differs between England and NI now requires studies that connect clinical, organizational, and behavioral levels of explanation. Linking national renal registry, NHSBT, and hospital datasets would enable pathway analyses mapping progression from CKD stages 4β5 to referral, workup, listing, and transplantation, to identify where deprivation exerts its greatest influence. Comparative case studies of NI and selected English centers should interrogate service configuration, workforce integration, and governance to determine how institutional design affects equity. Qualitative and mixed-methods research with patients and clinicians can examine social support, decision-making, and trust as potential mediators. Finally, center-level evaluations of referral and donor-assessment thresholds, coupled with realist evaluation of service innovations such as one-stop assessment and patient-navigation models, are needed to test which organizational features actively sustain equitable access.
CONCLUSIONS
Socioeconomic deprivation remains a major barrier to equitable kidney transplantation and posttransplant outcomes in England, while the effect appears to be attenuated in NI. These findings highlight how regional variation within a single healthcare system may reflect deeper structural or contextual influences on equity.
ACKNOWLEDGMENTS
The authors acknowledge the National Health Service Blood and Transplant Service for providing data from the UK Transplant Registry. Also, the authors thank all the UK renal centers for providing data to the UK Renal Registry, and the Registry for making the data available.
Supplementary Material
tpa-110-e866-s001.pdf (506.4KB, pdf)
tpa-110-e866-s002.pdf (180.8KB, pdf)
Footnotes
M.C. is supported by the Health Research Board (ICAT-2022β001) and the Irish Clinical Academic Training Programme, which is supported by the Health Service Executive, National Doctors Training and Planning, the Health and Social Care Research and Development Division, the Northern Ireland Medical and Dental Training Agency, the Department of Agriculture, Food and the Marine, and the College of Anaesthesiologists of Ireland. He has also received support from the Northern Ireland Kidney Research Fund.
The authors declare no conflicts of interest.
M.C. was responsible for the conceptualization of the study, data collection, statistical analysis, and drafting the initial article. J.B. contributed to data collection. A.E.C. contributed to data collection and interpretation of the findings. C.C. provided statistical support. P.B. and P.C. assisted in the interpretation of the findings. C.O. contributed to the studyβs conceptualization and provided methodological guidance. A.P.M. and G.J.M. contributed to the conceptualization and supervision of the study. All authors reviewed and contributed to the final preparation of the article.
Data for this study were obtained from National Health Service Blood and Transplant and the UK Renal Registry. Additional data were sourced from the local Northern Ireland Kidney Transplant Database, which cannot be made publicly available because of patient confidentiality and local governance restrictions. However, anonymized data from the local database may be made available upon reasonable request to the corresponding author, subject to appropriate approvals. We are also happy to advice on the specific data that were requested from the national registries to support transparency and potential reproducibility.
Supplemental digital content (SDC) is available for this article. Direct URL citations appear in the printed text, and links to the digital files are provided in the HTML text of this article on the journalβs Web site (www.transplantjournal.com).
The views and opinions expressed in this article are those of the authors and do not reflect the views of the National Health Service Blood and Transplant Service, UK Renal Registry, or UK Kidney Association.
REFERENCES
- 1.Zeng X, Liu J, Tao S, et al. Associations between socioeconomic status and chronic kidney disease: a meta-analysis. J Epidemiol Community Health. 2018;72:270β279. [DOI] [PubMed] [Google Scholar]
- 2.So BH, Methven S, Hair MD, et al. Socio-economic status influences chronic kidney disease prevalence in primary care: a community-based cross-sectional analysis. Nephrol Dial Transplant. 2015;30:1010β1017. [DOI] [PubMed] [Google Scholar]
- 3.Duff R, Awofala O, Arshad MT, et al. Global health inequalities of chronic kidney disease: a meta-analysis. Nephrol Dial Transplant. 2024;39:1692β1709. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Udayaraj U, Ben-Shlomo Y, Roderick P, et al. Social deprivation, ethnicity, and uptake of living kidney donor transplantation in the United Kingdom. Transplantation. 2012;93:610β616. [DOI] [PubMed] [Google Scholar]
- 5.Udayaraj U, Ben-Shlomo Y, Roderick P, et al. Social deprivation, ethnicity, and access to the deceased donor kidney transplant waiting list in England and Wales. Transplantation. 2010;90:279β285. [DOI] [PubMed] [Google Scholar]
- 6.Naylor KL, Knoll GA, Shariff SZ, et al. Socioeconomic status and kidney transplant outcomes in a universal healthcare system: a population-based cohort study. Transplantation. 2019;103:1024β1035. [DOI] [PubMed] [Google Scholar]
- 7.Pruthi R, Robb ML, Oniscu GC, et al. ; ATTOM Investigators. Inequity in access to transplantation in the United Kingdom. Clin J Am Soc Nephrol. 2020;15:830β842. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.NHS Blood and Transplant. Taking organ transplantation to 2020: a UK strategy. Available at https://www.odt.nhs.uk/odt-structures-and-standards/key-strategies/archived-strategies/taking-organ-transplantation-to-2020/. Accessed June 8, 2025. [Google Scholar]
- 9.Johnson RJ, Bradbury LL, Martin K, et al. ; UK Transplant Registry. Organ donation and transplantation in the UK-the last decade: a report from the UK national transplant registry. Transplantation. 2014;97(Suppl 1):S1βS27. [DOI] [PubMed] [Google Scholar]
- 10.UK Kidney Association/UK Renal Registry. UK Renal Registry 26th Annual Reportβdata to 31/12/2022. Available at https://ukkidney.org/audit-research/annual-report. Accessed January 6, 2025. [Google Scholar]
- 11.United Kingdom Government. English indices of deprivation. Available at https://www.gov.uk/government/statistics/english-indices-of-deprivation-2019. Accessed January 8, 2025. [Google Scholar]
- 12.Northern Ireland Statistics and Research Agency. Northern Ireland Multiple Deprivation Measure. Available at https://www.nisra.gov.uk/statistics/deprivation/northern-ireland-multiple-deprivation-measure-2017-nimdm2017. Accessed January 8, 2025. [Google Scholar]
- 13.Abel GA, Barclay ME, Payne RA. Adjusted indices of multiple deprivation to enable comparisons within and between constituent countries of the UK including an illustration using mortality rates. BMJ Open. 2016;6:e012750. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Erreygers G. Correcting the concentration index. J Health Econ. 2009;28:504β515. [DOI] [PubMed] [Google Scholar]
- 15.Zhang Y, Gerdtham UG, Rydell H, et al. Socioeconomic inequalities in the kidney transplantation process: a registry-based study in Sweden. Transplant Direct. 2018;4:e346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Naylor KL, Dixon SN, Garg AX, et al. Variation in access to kidney transplantation across renal programs in Ontario, Canada. Am J Transplant. 2017;17:1585β1593. [DOI] [PubMed] [Google Scholar]
- 17.Kihal-Talantikite W, Vigneau C, Deguen S, et al. Influence of socio-economic inequalities on access to renal transplantation and survival of patients with end-stage renal disease. PLoS One. 2016;11:e0153431. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.NHS Blood and Transplant/Statistics and Clinical Research. Organ and tissue donation and transplantation activity report 2023/2024. Available at https://nhsbtdbe.blob.core.windows.net/umbraco-assets-corp/33778/activity-report-2023-2024.pdf. Accessed June 9, 2025.
- 19.Bailey PK, Ben-Shlomo Y, Tomson CR, et al. Socioeconomic deprivation and barriers to live-donor kidney transplantation: a qualitative study of deceased-donor kidney transplant recipients. BMJ Open. 2016;6:e010605. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Bailey PK, Caskey FJ, MacNeill S, et al. Mediators of socioeconomic inequity in living-donor kidney transplantation: results from a UK Multicenter Case-Control Study. Transplant Direct. 2020;6:e540. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Graham JM, Courtney AE. The adoption of a one-day donor assessment model in a living kidney donor transplant program: a quality improvement project. Am J Kidney Dis. 2018;71:209β215. [DOI] [PubMed] [Google Scholar]
- 22.Corr M, Orr A, Courtney AE. The minimisation of cardiovascular disease screening for kidney transplant candidates. J Clin Med. 2024;13:953. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Gillespie H, OβNeill S, Curtis RMK, et al. When there is no guidance from the guidelines: renal transplantation in recipients with class III obesity. Transpl Int. 2023;36:11428. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.NHS Blood and Transplant. Interim report on kidney transplantation 2018β2021. Available at https://nhsbtdbe.blob.core.windows.net/umbraco-assets-corp/26375/interim-report-on-kidney-transplantation-2021.pdf. Accessed August 27, 2025.
- 25.NHS Blood and Transplant. Kidney annual report 2020β2021. Available at https://nhsbtdbe.blob.core.windows.net/umbraco-assets-corp/24800/kidney-annual-report-2020-21.pdf. Accessed August 27, 2025.
- 26.NHS Blood and Transplant. Kidney transplantation report 2023/24. Available at https://nhsbtdbe.blob.core.windows.net/umbraco-assets-corp/34295/nhsbt-kidney-transplantation-report-2324.pdf. Accessed August 27, 2025.
- 27.Wu DA, Robb ML, Watson CJE, et al. Barriers to living donor kidney transplantation in the United Kingdom: a national observational study. Nephrol Dial Transplant. 2017;32:890β900. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Kidney Research UK. Time to Act: A New Review of Kidney Health Inequalities. Available at https://www.kidneyresearchuk.org/2024/07/16/time-to-act-on-kidney-health-inequalities/#:~:text=Kidney%20Research%20UK%20is%20calling%20for%20urgent%20action,prevent%20patients%20from%20accessing%20appropriate%20care%20and%20treatment. Accessed January 6, 2025.
- 29.Taylor DM, Bradley JA, Bradley C, et al. ; ATTOM investigators. Limited health literacy is associated with reduced access to kidney transplantation. Kidney Int. 2019;95:1244β1252. [DOI] [PubMed] [Google Scholar]
- 30.Barnieh L, Collister D, Manns B, et al. Scoping review for strategies to increase living kidney donation. Clin J Am Soc Nephrol. 2017;12:1518β1527. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Rodrigue JR, Cornell DL, Lin JK, et al. Increasing live donor kidney transplantation: a randomized controlled trial of a home-based educational intervention. Am J Transplant. 2007;7:394β401. [DOI] [PubMed] [Google Scholar]
- 32.Ismail SY, Luchtenburg AE, Timman R, et al. Home-based family intervention increases knowledge, communication and living donation rates: a randomized controlled trial. Am J Transplant. 2014;14:1862β1869. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
tpa-110-e866-s001.pdf (506.4KB, pdf)
tpa-110-e866-s002.pdf (180.8KB, pdf)