Abstract
Introduction:
Women comprise 55-65% of living kidney donors. Most studies focus on individuals who underwent donor nephrectomies, rather than potential living donors prior to engagement with healthcare system. Therefore, underlying reasons for gender discrepancy are unclear.
Research Question:
Among relatives of patients with renal disease, do men and women differ in willingness to be evaluated for living kidney donation, regardless of prior donation behavior?
Design:
An online survey administered in 2019 to US adult members of Qualtrics Survey Panel whose relatives had weak or failing kidneys. The survey was designed to examine perspectives of living kidney donation from realistic potential donors. Self-reported willingness compared between men and women for statistically significant differences. Average marginal effects of male gender on willingness and interaction effects estimated with multivariable logistic regression, adjusted for respondent/patient demographics and relationship.
Results:
A total of 1647 responses showed 7.1% higher willingness among men (P=0.016). Among those whose relatives (N=808) were seeking transplants [subgroup], men had 13.1% higher willingness (p=0.002). Interaction effect analysis showed men aged 70-79 years, with insurance, self-reported very good health, and self-reported medical contraindications had significantly higher willingness than corresponding women. In transplant subgroup, men aged 18-39 years and with full-time employment also had higher willingness.
Conclusion:
Men showed 7.1% higher willingness to be evaluated for living kidney donation. Rather than reflecting a fixed difference, the existence and degree of gender difference were context-dependent. Identifying strategic interventions to facilitate male donation in contexts where they reported high willingness could improve access to transplantation.
Keywords: Research, quantitative methods, descriptive comparative, Research, quantitative methods, regression, Clinical outcomes, education, living donor, Ethics, organ donation, Procurement, donor campaigns
INTRODUCTION
Women constitute most people who donate living kidneys, which has increased steadily from 55% in 1988 to 65% in 2025.1 However, it is unknown if this outcome was reflective of gender differences in willingness throughout the donation process. Living donation is a complex process that involves medical, financial, and psychosocial considerations. Numerous factors, linked to gender-based norms rather than sex differences, have been proposed to explain gender disparities in living donation rates, although these explanations were supported by limited empirical evidence.1-3 For example, some have suggested that women may be more inclined to donate due to greater altruistic tendencies, increased social-psychological pressure, or relational expectations that place a greater burden of interpersonal sacrifices on women.1-3 Concerns about income loss has been cited as a barrier to men’s donation, under the assumption that they were the primary income earners.1,2
A key limitation of prior research was its predominant focus on individuals who had completed donation,4-6 overlooking those who were disqualified at earlier stages or never recruited. The handful of studies focusing on those who presented for living donor evaluation have yielded mixed results.7,8 For example, a recent study showed that women had significantly higher rates of self-referral, which contributed to their higher donation rates.8 In contrast, an earlier study found that gender discrepancy arose at the final step after medical and psychological approval in which fewer men proceeded with donation.7
Given the limited scope of past investigations, the evidence largely failed to consider individuals who had not yet initiated the evaluation process but may be amenable to doing so. The insights of prospective donors who have not undergone evaluation were likely important to understanding the observed gender discrepancies in living donation1-3 A handful of studies have examined the perspectives and characteristics of relatives of patients with renal disease prior to evaluation,9-13 with none specifically focusing on gender differences. With over 140 000 individuals awaiting kidney transplantation annually,14 understanding gender differences in living kidney donation is critical as facilitating donation by men could significantly increase organ availability and access to transplantation.
Therefore, this study investigated whether there were gender differences in self-reported willingness to be evaluated for living kidney donation among a diverse sample of relatives of patients with renal disease, unconditional on prior donation behavior. Specifically, this study aimed to answer 2 research questions: 1) Among relatives of patients with renal disease, do men and women differ in willingness to be evaluated for living kidney donation? 2) What are the associations between sociodemographic characteristics (e.g. age, race/ethnicity, educational attainment, marital status) and differences in willingness to be evaluated for living kidney donation, stratified by gender?
METHODS
Design
The present study used descriptive comparative analyses to examine differences in willingness to donate between men and women, accounting for demographic characteristics, relationship to the patient, and closeness to the patient. The study protocol was reviewed and deemed exempt by the university Institutional Review Board (Protocol#00005932).
Setting
Respondents completed the study survey on a personal device in a setting of their choosing. The survey was self-administered online, allowing respondents to complete it in at their own convenience outside the constraints of a clinical or transplant center setting. This allowed for the inclusion of potential donors who may not have engaged with the formal transplant process at the time of survey but are nevertheless part of the social network of a patient with kidney disease.
Population
The target population was United States-based individuals who have a relative with kidney disease, regardless of whether they had previously engaged in living donor -related behaviors. Although the full demographic profile of the pre-screened Qualtrics panel used for FoRPS is not publicly available, prior research suggests that Qualtrics panels more closely approximate national probability samples compared to other online platforms like MTurk and Facebook.15 Qualtrics’ samples tend to overrepresent women, younger individuals, Non-Hispanic Whites, and those with higher levels of education, which is consistent with characteristics in this respondent sample. 15 While these biases in the respondent sample are acknowledged, the primary concern was to ensure that the reported relatives of the patients closely resembled the broader end-stage kidney disease population. This was addressed through the application of poststratification weights. After weighting, the sample of relatives in FoRPS closely resembled the end-stage kidney disease patient population, who were predominantly male, older, and identifying as either White or Black.
Sampling
The sample was a non-probability sample recruited through Qualtrics (Provo, UT), a national online survey panel. Panel members are US resident adults (≥ 18 years) who were recruited through various methods, including advertisements (e.g. pop-ups, banners, and embedded messages) on websites and social media platforms, member referral, or curated email lists. All panel members undergo third-party verification by Qualtrics prior to joining to respondent authenticity. Respondents receive indirect compensation administered by Qualtrics; no incentive was provided directly by the study investigators.
Potential respondents accessed the survey through embedded links in the recruitment material. After third-party verification and providing electronic informed consent, individuals were screened for eligibility via 2 questions. Eligible respondents were those who 1) reported having a relative diagnosed with weak or failing kidneys, and 2) identified a qualifying relationship with that individual. Qualifying relationships included spouse/partner, parents, children, siblings, grandparents, aunts, uncles, cousins, nieces, nephews, and grandchildren.
Data Collection
This study examined difference in willingness to donate between men and women. The analysis also included a range of factors potentially influencing willingness such as the sociodemographic characteristics of both the respondent and the identified patient, the respondent’s health and contraindications, their relationship to the patient, and indicators of closeness (specifically communicated frequency and geographic proximity). All patient characteristics were reported by the respondent.
Families of Renal Patients Survey
The Families of Renal Patients Survey (FoRPS) was a 57-item, cross-sectional online survey designed to examine perspectives on living kidney donation from realistic potential donors – individuals who have relatives with kidney disease and thus plausibly situated to consider donation. This survey was administered in two waves: April-May 2019 (Wave 1) and August-September 2019 (Wave 2). Respondents were recruited through the Qualtrics Online Panel (Provo, UT) and completed the survey electronically and at their convenience.
The survey was divided into 6 sections. In the first section, respondents were asked whether any of their family members had been diagnosed with weak or failing kidneys (the patient), their relationship to the patient, and whether the relationship was genetic or non-genetic (e.g., through marriage, adoption, or step-relations). The second section collected demographic information about the patient. The third section focused on discussions about transplantation. In Wave 2, this section also included additional items assessing whether specific factors, such as financial considerations or the nature of the respondent’s relationship to the patient would influence their willingness to pursue medical evaluation as a living donor.
The fourth section assess respondents’ own health status including medical contraindication. Two key differences existed between waves in this section. First, due to a survey error, weak or failing kidneys was omitted from the list of contraindications in Wave 1 but was included in Wave 2. Second, Wave 2 added 3 questions to improve the reliability of the hypertension and non-melanoma cancer measures. Specifically, respondents who reported having hypertension were asked if they had been told on 2or more different visits that they had the condition, and whether they were currently taking prescribed medication for it. Those reporting a cancer diagnosis within the past 5 years were asked whether the cancer was in remission. Multiple imputation was used to account for differences in contraindication measures between waves, as described in the Data Analysis section.
The fifth section assessed respondents’ knowledge of issues related to kidney donation, such as wait times for recipients of living versus deceased donor kidneys. The final section collected demographic information about the respondent.
All measures were adapted from established government surveys like the American Community Survey or Current Population Survey 16-17 or were previous validated items regarding kidney transplantation. All other measures were developed by the survey investigators. To improve generalizability, post-stratification weights were applied to align the demographic characteristics of the reported patients (i.e., the sick relatives) with those of the national transplant candidate population, as documented in the 2016 Renal Data Extraction and Referencing System (RenDER).
Demographic characteristics
Gender refers to an individual’s identity and is closely linked to socially constructed norms regarding behavior, appearance, and communication. Importantly, gender identity may align with or differ from the biological sex assigned at birth. In the survey, gender of the respondent and patient were self-reported by the respondent, with forced-response options of male, female, and other. The term gender was used throughout to reflect respondents’ self-identified category.
Due to limited sample size, respondents who marked other gender were excluded from the analysis (N=13). Age was categorized as: <20-29, 30-39, 40-49, 50-59, 60-69, or 70+. Race/ethnicity selections were American Indian/Alaskan Native, Asian American/Pacific Islander, Black or African American, White, Hispanic, Other. Education selections were High school or less, Some college or community/technical college degree, Bachelor’s degree or more. Marital status selections were Married, Single, Significant other, not living together, and Significant other, living together.
Number of children was based on response to: How many living children do you have (including biological, step-, adopted, and fostered children) with options: 0, 1, 2, or 3+. Full-time employment was coded as a binary variable (yes vs no). Health insurance status was categorical variable: yes, no, or don’t know. Respondent health was measured using 2 variables. 1) presence of medical contraindications (e.g., hypertension, diabetes, melanoma, HIV/AIDS), and 2) self-reported health with the categories: excellent, very good, good, fair, or poor. Financial precarity indices were calculated based on the estimated impact of losing one cycle of monthly income.
Relationship to patient was recoded into 3 categories: 1) spouse/partner, 2) nuclear family (child, parent, sibling), and 3) extended family (e.g., grandparent, cousin, niece/nephew). Closeness to patient was measured using 2 variables: frequency of communication (most/everyday, 1-3 times/week, 1-3 times/month, <1 time/year, <1 time/year) and estimated travel time to the patient’s home (<15 minutes, 16-45 minutes, 46 minutes–2 hours, 2-6 hours, 6 hours–24 hours, >24 hours).
Willingness to donate
Willingness to donate was a binary variable derived from 2 survey items, using skip logic based on initial responses. First, respondents indicated which of the following applied to themselves and the patient: a) This person is seeking a kidney transplant; b) We have discussed me becoming a donor to this person; c) I have agreed to be medically evaluated as a potential living donor to this person; d) I was medically evaluated as a potential donor to this person; e) I was medically approved as a potential donor to this person; f) I donated my kidney to this person. Respondents who indicated agreement to be evaluated, evaluation, approval, or donation were categorized as having firm willingness, reflecting concrete steps toward donation. Those who had not taken any of these steps were asked: Would you agree to be medically evaluated for donating a kidney to the person you are thinking of if they asked you to? Response options were yes, no, or don’t know. Affirmative responses were classified as soft willingness, indicating intent without action. The final binary willingness variable includes both firm and soft willingness categories, capturing either substantive behaviors or affirmative intent toward donation.
Data Analysis
Differences in demographic characteristics by gender were described with chi-square tests. Self-reported willingness to undergo evaluation was compared between respondent genders, combining firm and soft willingness into a single binary outcome. To assess whether combining samples across survey rounds and type of willingness (firm vs. soft) was empirically justifiable, chi-square tests were conducted to ensure there were no statistically significant differences in the gender distribution of willingness responses between Waves 1 vs. 2 and firm vs. soft willingness. The average marginal effect (AMEs) of male gender on willingness to undergo evaluation was estimated using multivariable logistic regression, adjusted for respondent and patient sociodemographic characteristics (i.e. age, race/ethnicity, educational attainment, marital status, number of children) and the respondent’s relationship to the recipient.
Interaction effects were examined between male gender and full time-employment, as well as male gender and medical contraindication status. This analysis was performed using all respondents, as well as the subgroup whose relatives were actively seeking transplantation. Multiple imputation was used to address cross-wave differences. Imputation was preformed using chained equations (M=10), as a function of respondent and patient age, race, education, marital status, number of children, and gender, relationship to patient, communication frequency, travel time to patient, respondent insurance status, and self-reported health. 18 The imputed data was used in 2 regression models to address item-specific missingness, and used a more specific measure of hypertension (at least 2 instances of diagnosis, uncontrolled by medications) in the computation of contraindication status, as opposed to the use of a general measure of any history of hypertension in the unimputed contraindication measure. All analyses were conducted in STATA 18 (StataCorp, College Station, TX).
Procedure
Participants were recruited through the Qualtrics panel using targeted criteria. Survey links were distributed via online advertisements, email lists, and member referrals. Following third-party identity verification and electronic informed consent, eligible respondents completed the 57-item survey. All respondents were anonymous, and respondents were compensated by Qualtrics upon survey completion.
RESULTS
Baseline Respondent and Patient Characteristics
Overall, 1647 eligible respondents completed the survey with 559 (33.9%) men and 1088 (66.1%) women. Table 1 displays the general demographic characteristics of respondents and patients by gender. Significantly, women were more likely to report any living children and greater numbers of children (P = .003) while men were more likely to have full-time employment (P < .001) and higher self-rated health assessments (P = .001). In terms of relationship dynamics, women reported higher communication frequency (P < .001) and closer geographical proximity (P = .001) with the patient. Men reported having more male sick relatives (64.0% vs. 35.6% female patients) while women reported a more balanced gender composition (53.1% male vs. 46.5% female patients) (P = .002).
Table 1.
General Characteristics of Respondents and Patients in Sample
| Respondent gender | P value | |||
|---|---|---|---|---|
| Women N = 1088 |
Men N = 559 |
|||
| N (%) | N (%) | |||
| Respondent characteristics | ||||
| Age | < 20-29 | 361 (31.2) | 144 (24.8) | 0.066 |
| 30-39 | 264 (23.1) | 158 (24.8) | ||
| 40-49 | 179 (16.7) | 111 (21.0) | ||
| 50-59 | 153 (17.0) | 74 (16.3) | ||
| 60-69 | 100 (9.4) | 51 (8.1) | ||
| ≥ 70 | 31 (2.6) | 21 (5.0) | ||
| Race/Ethnicity | American Indian or Alaska Native | 9 (0.8) | 7 (1.3) | 0.201 |
| Asian American or Pacific Islander | 40 (4.0) | 30 (7.5) | ||
| Black or African American | 172 (28.1) | 85 (26.2) | ||
| White | 675 (46.0) | 352 (46.9) | ||
| Hispanic | 147 (18.2) | 68 (16.1) | ||
| Other | 45 (3.0) | 17 (2.0) | ||
| Education attainment | High school or less | 356 (30.4) | 176 (30.9) | 0.137 |
| Some college or community/technical college degree | 445 (39.9) | 191 (34.2) | ||
| Bachelor’s degree or higher | 287 (29.7) | 192 (34.9) | ||
| Marital status | Married | 437 (38.7) | 228 (27.1) | 0.304 |
| Single | 305 (29.1) | 177 (33.5) | ||
| Significant other, not living together | 108 (11.1) | 56 (12.3) | ||
| Significant other, living together | 238 (21.1) | 98 (17.2) | ||
| Number of children | 0 | 204 (13.4) | 136 (20.1) | 0.003 |
| 1 | 144 (12.1) | 104 (16.2) | ||
| 2 | 287 (26.3) | 128 (22.2) | ||
| 3 or more | 453 (48.2) | 191 (41.6) | ||
| Full-time employment | No | 211 (57.4) | 86 (34.5) | < 0.001 |
| Yes | 159 (42.6) | 144 (65.5) | ||
| Health insurance status | Don' know | 46 (3.9) | 21 (3.7) | 0.700 |
| No | 175 (17.6) | 98 (15.5) | ||
| Yes | 867 (78.6) | 440 (80.7) | ||
| No | 119 (32.8) | 81 (37.1) | 0.373 | |
| Yes | 251 (67.3) | 149 (62.9) | ||
| Self-reported medical contraindications | ||||
| Self-rated health assessment | Excellent | 168 (15.0) | 118 (19.1) | 0.001 |
| Very good | 278 (25.5) | 184 (35.2) | ||
| Good | 353 (33.2) | 138 (23.9) | ||
| Fair | 220 (21.2) | 93 (17.0) | ||
| Poor | 69 (5.1) | 26 (4.9) | ||
| Mean (SD) | Mean (SD) | |||
| Financial precarity index | 12.1 (4.0) | 11.7 (3.9) | 0.233 | |
| Patient characteristics as reported by relatives | ||||
| Gender | Female | 582 (46.5) | 227 (35.6) | 0.002 |
| Male | 502 (53.1) | 329 (64.0) | ||
| Other | 4 (0.4) | 3 (0.5) | ||
| Age | < 20-29 | 135 (3.5) | 69 (3.8) | 0.679 |
| 30-39 | 116 (6.0) | 75 (7.9) | ||
| 40-49 | 159 (13.0) | 86 (13.8) | ||
| 50-59 | 191 (21.8) | 104 (22.4) | ||
| 60-69 | 236 (28.4) | 108 (25.8) | ||
| ≥ 70 | 251 (27.3) | 117 (26.2) | ||
| Race/Ethnicity | American Indian or Alaska Native | 14 (0.8) | 9 (0.7) | 0.713 |
| Asian American or Pacific Islander | 50 (5.0) | 33 (6.3) | ||
| Black or African American | 194 (31.7) | 85 (29.2) | ||
| White | 680 (44.8) | 363 (47.5) | ||
| Hispanic | 135 (17.5) | 59 (16.0) | ||
| Other | 15 (0.2) | 10 (0.3) | ||
| Education attainment | High school or less | 540 (50.4) | 245 (43.2) | 0.042 |
| Some college or community/technical college degree | 339 (28.6) | 161 (30.3) | ||
| Bachelor’s degree or higher | 209 (20.8) | 153 (26.5) | ||
| Marital status | Married | 628 (61.1) | 342 (60.8) | 0.888 |
| Single | 260 (23.6) | 118 (22.4) | ||
| Significant other, not living together | 57 (4.8) | 32 (5.8) | ||
| Significant other, living together | 143 (10.5) | 67 (11.1) | ||
| Relationship to respondent | Nuclear family | 436 (43.0) | 210 (39.7) | 0.456 |
| Spouse/partner | 249 (19.5) | 151 (19.1) | ||
| Extended family | 403 (37.5) | 198 (41.2) | ||
| Indicators of closeness | ||||
| Communication frequency | Most/every day | 631 (57.1) | 264 (45.6) | < 0.001 |
| 1-3 times/week | 159 (16.6) | 105 (19.7) | ||
| 1-3 times/month | 114 (10.6) | 83 (16.0) | ||
| < 1 time/month | 93 (7.4) | 68 (12.6) | ||
| < 1 time/year | 91 (8.3) | 39 (6.1) | ||
| Travel time between respondent and patient | < 15 min | 542 (48.8) | 232 (40.1) | 0.004 |
| 15 - 45 min | 224 (21.5) | 126 (22.4) | ||
| > 45 min and < 2 hours | 113 (9.2) | 86 (15.4) | ||
| > 2 hours and < 6 hours | 94 (9.4) | 44 (7.9) | ||
| > 6 hours and ≤ 24 hours | 54 (6.0) | 47 (9.9) | ||
| > 24 hours | 61 (5.2) | 24 (4.3) | ||
Note: Proportions in each cell are reflective of the weighted sample distribution (post-stratification weights align the demographic characteristics of the reported patients with those of the national transplant candidate population). Sample sizes in each cell are reflective of the original unweighted sample distribution.
Combining Results Across Survey Rounds and Types of Willingness
The distribution of responses to the multiple items comprising the binary composite outcome are displayed (data available upon request). There was no significant difference in the distribution of willingness responses by survey round (66.6% Yes and 33.4% No for both rounds, P = .67), including when stratified by gender (female P =.34, male P = .07). There was no significant difference in the gender distribution of willingness between firm vs. soft willingness (data not shown). Therefore, it was deemed empirically appropriate to combine results across survey rounds and types of willingness for further analyses.
Willingness to be Evaluated for Living Kidney Donation
Table 2 displays the respondents’ willingness to be evaluated for living donation. A significantly higher percentage of men indicated willingness to be evaluated (71.5% vs. 64.2% of women, P = .02). The majority of the cohort had not discussed donation with their relatives (75.8% of men, 72.9% of women, P = .29). Among those who had this discussion, there was no statistically significant difference in the direction of discussion by gender (P = .10).
Table 2:
Willingness To Be Evaluated for Living Kidney Donation by Respondent Gender
| Respondent gender | χ2
test P- value |
|||
|---|---|---|---|---|
| Women N = 1088 |
Men N = 559 |
|||
| N (%) | N (%) | |||
| Willingness | No | 350 (35.8) | 149 (28.5) | 0.019 |
| Yes | 738 (64.2) | 410 (71.5) | ||
| Discussed living donation | No | 802 (75.8) | 398 (72.9) | 0.292 |
| Yes | 286 (24.2) | 161 (27.1) | ||
| Discussion direction | I initiated | 193 (69.2) | 119 (73.5) | 0.095 |
| Someone else initiated | 50 (16.6) | 14 (8.2) | ||
| They initiated | 43 (14.2) | (28 (18.3) | ||
Note: Proportions in each cell are reflective of the weighted sample distribution (post-stratification weights align the demographic characteristics of the reported patients with those of the national transplant candidate population). Sample sizes in each cell are reflective of the original unweighted sample distribution.
Average Marginal Effect of Gender on Willingness to be Evaluated, with Interaction Effects
Table 3 displays the multivariable logistic regression analyses for the full cohort (N = 1647) and subgroup whose relatives were actively seeking transplantation (n = 808). The adjusted AMEs of male gender on willingness to be evaluated were 7.1% (P = .02) and 13.1% (P = .002) for the full cohort and subgroup, respectively.
Table 3:
Multivariable Logistic Regression Analyses of Respondent Characteristics on Willingness to Donate
| All respondents (N = 1647) |
Relatives of transplant
candidates (N = 808) |
|||||||
|---|---|---|---|---|---|---|---|---|
| Probability
of willingness (adjusted) |
AME* (adjuste d) |
P value |
Probability
of willingness (adjusted) |
AME (adjusted) |
P value |
|||
| Women | Men | Women | Men | |||||
| Unadjusted (Ref: Female) | .64 | .72 | .07 | .02 | .53 | .65 | .12 | .01 |
| Adjusted (Ref: Female) | .64 | .71 | .07 | .016 | .53 | .66 | .13 | .002 |
| Relationship to recipient | ||||||||
| Nuclear family | .71 | .74 | .03 | .46 | .58 | .66 | .08 | .26 |
| Spouse/partner | .70 | .81 | .11 | .04 | .65 | .75 | .10 | .20 |
| Extended family | .55 | .64 | .09 | .06 | .44 | .62 | .18 | .005 |
| Age (years) | ||||||||
| < 20-29 | .70 | .79 | .08 | .10 | .60 | .74 | .14 | .05 |
| 30-39 | .69 | .75 | .06 | .31 | .60 | .77 | .17 | .02 |
| 40-49 | .63 | .70 | .07 | .32 | .46 | .61 | .16 | .14 |
| 50-59 | .58 | .62 | .04 | .62 | .45 | .41 | −.04 | .73 |
| 60-69 | .54 | .56 | .03 | .82 | .39 | .48 | .09 | .60 |
| ≥ 70 | .42 | .74 | .32 | .02 | .10 | .68 | .58 | .006 |
| Marital status | ||||||||
| Married | .65 | .69 | .04 | .44 | .55 | .57 | .02 | .76 |
| Single | .65 | .75 | .10 | .05 | .52 | .74 | .23 | .001 |
| Significant other, not living together | .61 | .69 | .08 | .40 | .45 | .63 | .18 | .15 |
| Significant other, living together | .64 | .73 | .09 | .19 | .53 | .67 | .14 | .15 |
| Number of children | ||||||||
| 0 | .62 | .65 | .03 | .66 | .55 | .57 | .03 | .79 |
| 1 | .72 | .77 | .05 | .45 | .61 | .75 | .14 | .18 |
| 2 | .60 | .75 | .15 | .006 | .45 | .71 | .26 | .001 |
| 3 or more | .65 | .71 | .05 | .27 | .54 | .64 | .11 | .10 |
| Health insurance status | ||||||||
| Don' know | .54 | .71 | .17 | .25 | .27 | .70 | .43 | .03 |
| No | .64 | .66 | .02 | .77 | .45 | .55 | .11 | .33 |
| Yes | .65 | .72 | .07 | .02 | .56 | .67 | .11 | .01 |
| Self-rated health assessment | ||||||||
| Excellent | .76 | .74 | −.01 | .85 | .59 | .69 | .10 | .31 |
| Very good | .70 | .80 | .10 | .04 | .60 | .77 | .17 | .03 |
| Good | .63 | .69 | .05 | .34 | .49 | .60 | .11 | .24 |
| Fair | .59 | .61 | .03 | .71 | .48 | .56 | .07 | .49 |
| Poor | .37 | .53 | .15 | .25 | .30 | .56 | .25 | .12 |
| Full-time employment | ||||||||
| No | .60 | .63 | .02 | .69 | .49 | .54 | .05 | .52 |
| Yes | .70 | .78 | .08 | .09 | .57 | .73 | .16 | .02 |
| Self-reported medical contraindications | ||||||||
| No | .66 | .70 | .05 | .33 | .53 | .64 | .11 | .09 |
| Yes | .63 | .72 | .09 | .02 | .52 | .67 | .15 | .01 |
Average marginal effect
Within both the full cohort and subgroup, interaction effect analysis showed that men aged 70-79 years (AME 32.2%, P = .02 full cohort; AME 57.9%, P = .006 subgroup), men with health insurance (AME 7.4%, P = .02 full cohort; AME 11.4%, P = .01 subgroup), men in very good health by self-assessment (AME 10.1%, P = .04 full cohort; AME 16.5%, P = .03 subgroup), and men with self-reported medical contraindications (AME 9.0%, P = .02 full cohort; AME 14.8%, P = .01 subgroup) had higher probabilities of willingness than corresponding women with the same trait subsets.
In the subgroup analysis, men aged 18-29 years (AME 14.2%, P = .05) and 30-39 years (AME 17.3%, P = .02), men who reported not knowing their health insurance status (AME 42.9%, P = .03), and men with full-time employment (AME 15.9%, P = .02) also had higher probabilities of willingness than corresponding women with the same trait subsets. Within the full cohort, men reported higher willingness when the sick relative was their spouse/partner (AME 10.9%, P = .04) while in the subgroup, they did so when the sick relative was an extended family member (AME 17.8%, P = .005). Results from models using the unimputed sample were qualitatively similar to the above (data not shown).
DISCUSSION
In this study of relatives of patients with renal disease across multiple stages of the donation process, it was observed that even after adjusting for demographic differences that varied by gender, men had 7.1% higher willingness to be evaluated compared to women. In the subgroup analysis involving respondents whose relatives were actively seeking transplantation, men had 13.1% higher willingness. These findings challenge the prevailing narrative that women comprise 55-65% of kidney donors due simply to higher willingness, suggesting that factors beyond personal attitudes contribute to the observed gender difference. While some studies suggested that living donor transplant outcomes were primarily a result of greater innate altruistic or caregiving tendencies among women,1,3,19,20 they have notable caveats: the majority were conducted in other countries or in earlier decades, which, although providing valuable data, represent different sociocultural contexts than that in which current US patients live.
This study provides an important contribution to the growing literature arguing for recognition of the complex interplay of social, cultural, behavioral, and economic factors that influence gender differences in the process of living kidney donation.3 The analyses highlighted 3 areas in which gender differences may contribute to the observed imbalance between men’s greater expressed willingness to donate and women’s greater donation rates: health and age, employment and financial security, and relationship dynamics with the transplant candidate.
First, men with contraindications reported higher willingness, suggesting they may lack knowledge of the exclusion criteria for donation. Men also reported a more favorable perception of their health, despite epidemiological evidence indicating men have higher prevalence of comorbidities which preclude donation. 21,22 These were likely influenced by different healthcare use patterns between genders. For example, the Centers of Disease Control and Prevention have (CDC) reported significantly higher rates of physician visits among women, potentially leading to better awareness of health status. 23 Furthermore, studies have shown that between 7-33% of potential living donors were diagnosed with previously unknown medical problems during the formal evaluation process. 24,25 While those studies did not examine gender differences, it is possible that men in this sample were less aware of having any underlying comorbidities. Additionally, men at the oldest ages expressed increased willingness to be evaluated than women in the same age group, despite the fact that many transplant centers follow guidelines that favor donors younger than 65 years, which may limit donation opportunities for older adults. 26 These findings underscore the need for improved health screening among men, better education of patients and family members on the ineligibility criteria for living donation, and targeted recruitment efforts of younger male donors.
Second, the findings suggest that indicators of economic stability and the ability to absorb the financial consequences of donation play a more significant role in predicting men’s willingness to undergo evaluation compared to women. It is often suggested that men, typically assumed to be breadwinners, face greater obstacles to donation due to the potential disruptions to their income.4 Interaction analysis within the subgroup whose relatives were transplant candidates revealed an unexpected pattern where full-time employment was associated with greater willingness to undergo evaluation, while having a limited impact on women’s willingness. This may reflect men’s greater tolerance for ambiguity or a more optimistic perception of their financial security.
Third, women reported significantly closer ties to their relatives through greater communication frequency and geographical proximity. Based on this, relationship dynamics created an environment where women implicitly experienced and/or perceived greater social pressure to assist their relatives through donation, 27,28 despite reporting less initial willingness. The current study design does not allow for an in-depth assessment of these factors. Taken together, these study findings demonstrated that rather than reflecting a fixed difference, the existence and degree of gender differences in willingness depend heavily on context, including the respondent’s perception of their health and indicators of socioeconomic standing. Identifying actionable elements to facilitate donation from men in circumstances where they report high willingness could significantly improve organ availability and access to living donor transplantation. Transplant centers may consider implementing preventive health screenings for relatives to identify undiagnosed, but modifiable, medical conditions early in the patients’ disease process. Developing programs to educate and partner with employers to offer job protection and paid leave for individuals who donate living kidneys could remove significant barriers for many. 29 In this context, federal legislation such as the Living Donor Protection Act, which seeks to prevent insurance discrimination against those who donate and ensure job security during recovery from surgery, could play a pivotal role in reducing disincentives and structural barriers that disproportionately affect willing individuals, including men who are employed full-time. With the recognition that there may be more interest in donation among male relatives than previously acknowledged, healthcare teams should encourage patients to discuss donation with a broad range of individuals to maximize the chances of finding a donor, with a renewed interest in men aged < 20-39 years and extended male relatives. Designing gender-specific outreach and educational materials, to be used by transplant candidates, addressing the unique motivations and concerns of men could support this effort.
Limitations
Due to limited subsample sizes, the study adopted the simplified model of binary gender categories, which did not capture the full spectrum of gender identities and their impact on donation. An important avenue for future research is the consideration of donor willingness among individuals with gender identities other than male and female, which may include genderqueer and non-binary individuals among other diverse identities.
Other limitations include the reliance on self-reported data, which may be subject to recall and social desirability biases. Social desirability bias refers to the tendency of respondents to answer questions in a manner they believe will be viewed favorably by others. This is especially relevant here as most respondents expressed only a soft willingness, often without having taken concrete steps without donation. Willingness was partially assessed based on hypothetical scenarios, which may not accurately reflect real-world decision-making processes. Respondents may feel pressure to appear altruistic or supportive of donation, even if their true inclination to proceed with evaluation is lower. While there was no reason to believe social desirability bias disproportionately affects male versus female respondents, it is important consider the possibility that this contributed to the discrepancy between the findings and previous research reporting higher donation rates among women.
Lastly, the use of an online survey panel may introduce selection bias, potentially underrepresenting individuals with limited internet access or familiarity with online platforms. Despite these caveats, this study provides valuable insights regarding the often-overlooked population of potential living donors who have not engaged with the transplant healthcare system.
CONCLUSION
The findings of this study challenged prevailing assumptions about gender disparities in living donation that men are simply less willing to donate, which has important implications for policy and practice. Men demonstrated higher willingness to be evaluated for living donation (or to be a donor), particularly among relatives of transplant candidates. However, the magnitude of these gender differences in willingness were influenced by specific social and demographic factors. Markers of socioeconomic standing, such as full-time employment and health insurance, were associated with higher probabilities of willingness among men compared to women. Men in this cohort exhibited higher willingness in contexts that were less practical for donation, such as having medical contraindications and being in the 70-79 years age range. These findings underscored the complexity of the donation decision-making process and highlighted the need for a nuanced approach to donor recruitment and education, such as age cutoff flexibility, early health screening and risk factor modification for potential donors, and enhanced coordination with employers. By tailoring outreach strategies based on these insights on gender differences among potential donors, the transplant community has the opportunity to increase access to living donor transplantation and improve outcomes for patients with renal disease.
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