Abstract
Purpose
In 2015, assisted reproductive technology (ART) accounted for 1.7% of all U.S. births, donor eggs accounted for over 17,000 started cycles in 2015, and donor sperm accounting for 6.2% of all cycles started in 2014. With increasing utilization of donor gametes as a method of assisting patients with infertility, the number of babies born each year utilizing gamete donation will also continue to increase. This study aimed to elucidate factors impacting decision to donate, amongst a representative national population.
Methods
A survey was distributed via the internet utilizing SurveyMonkey Enterprise with HIPAA compliance. Univariate regressions and frequencies were conducted between each demographic and personal characteristic and the willingness to donate. Log Binomial and linear regression was used categorical and continuous variables, and Risk ratios were calculated.
Results
In this large survey study, 64% of men and 50% of women reported they would be willing to donate gametes, with the majority desiring monetary compensation. Men with a high Consumer Financial Protection Bureau score were less likely to report that they would consider donating sperm compared to a medium high CFPB score. No other financial indicators were associated with considering donating sperm. There were no associations between CFPB score and egg donation outcomes. Black or African American women were less likely to consider donating their eggs compared to other groups, and more likely to desire > $5000 in compensation.
Conclusions
In this large survey study, a small minority of participants reported they would be willing to donate to an unknown infertility patient for reproductive purposes. High and very high CFPB scores were associated with willingness to donate games, but not with desire for monetary compensation or amount.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10815-024-03194-7.
Keywords: Oocyte donation, Sperm donation, Gamete donation, Third party IVF
Introduction
In 2015, assisted reproductive technology (ART) accounted for 1.7% of all U.S. births [1]. Donor eggs accounted for over 17,000 started cycles [2]. Since the early 1990’s, the number of practices that participate in oocyte donation services has increased from roughly 60% [3] to 89% in 2020% [4]. Donor sperm, has been used in both donor insemination and assisted reproductive technology. Donor sperm accounted for 6.2% of all IVF cycles in the US in 2014. In 2015–2017, an estimated 440,986 women had undergone donor insemination using donor or mixed sperm. With increasing utilization of donor gametes as a method of assisting patients with infertility, the number of babies born each year utilizing gamete donation will also continue to increase.
The two most important motivating factors identified in the literature for donating eggs are altruism and money [5–7]. In the US, payment of gamete donors is considered favorably, with only 2% of people opposing paying oocyte donors and only 4% opposing paying sperm donors [8]. This is consistent with donor’s motivation for donating, as nearly 74% were motivated by monetary compensation [9].
Oocyte donors who received higher compensation ($4,453 ± $1,285 compared with $3,413 ± $3,397) more often report financial compensation as a very significant reason for being a donor [9]. Additionally, more than one third of women report they feel that they have been inadequately compensated [9]. The Ethics Committee of the American Society for Reproductive Medicine (ASRM) attempted to address the issue of fair compensation, concluding that “compensation based on a reasonable assessment of the time, inconvenience, and discomfort associated with oocyte retrieval can and should be distinguished from payment for the oocytes themselves” [10]. Establishing appropriate compensation is difficult secondary to the inability to set a standard price. There were official recommendations of a maximum of $10,000 by the ASRM, but those were removed secondary to a lost class action lawsuit stating this was akin to illegal price-fixing and would lead to product scarcity [11]. It has been suggested the compensation scheme should take into account the oocyte donor’s current hourly wage to compensate for the time and effort required [12], but the Ethics Committee Opinion subsequently states this method of establishing payment could unfairly reimburse women from lower income groups [10]. There are currently no official recommendations for maximum oocyte donor compensation and the free market would appear to have taken over. We are unsure of the amount oocyte donors are being offered by private corporations as they have no incentive or mandate to disclose this information.
A number of large international studies have been conducted assessing sperm donor recruitment. Graham et al. [13] compared the characteristics, motivations, preferences and expectations of men donating sperm online or through a sperm bank, and found that financial payment was important to those donating through a sperm bank, though not at all important to those donating online. They did not report these findings by employment status.
As ART utilization continues to grow, it is important to understand those factors which will influence private corporations and gamete donors alike. This study aimed to elucidate factors impacting decision to donate, amongst a representative national population. It is unknown if a person’s financial stability would alter the desire and minimum amount a person would be willing to donate for. We hypothesize there will be an association between desire for higher compensation with higher financial well-being.
Materials and methods
Survey
A survey (Supplement) created by the authors of this paper was distributed utilizing SurveyMonkey Enterprise with HIPAA compliance. SurveyMonkey is a professional online survey company who recruits from a diverse panel of participants from around the United States. This SurveyMonkey online poll was conducted among a national sample of 695 adults ages 18 and up. Respondents for this survey were selected from the nearly 3 million people who take surveys on the SurveyMonkey platform each day. Data was weighted for age, gender, and income using the Census Bureau’s American Community Survey to reflect the demographic composition of the United States. The survey was written at a seventh-grade reading level and recruitment completed in August 2019.
CFPB score
The Consumer Financial Protection Bureau (CFPB) is a group formed under the United States Government with a core function to “Provide a single point of accountability for enforcing federal consumer financial laws and protecting consumers in the financial marketplace.” The CFPB created a financial well-being survey consisting of 5 questions and a standardized scoring system to quantify the extent to which someone’s financial situation and the financial capability that they have developed provide them with security and freedom of choice [14]. They define a person’s financial well-being as coming “from their sense of financial security and freedom of choice—both in the present and when considering the future.” The score is between 0–100 and the score is divided into 6 categories: Very Low, Low, Medium Low, Medium High, High, and Very High. These categories then allow one to estimate the likelihood individuals are able to come up with an emergency fund, have experienced issues with debt collectors, stay on budget, have varying amounts of savings, ability to make ends meet, ability to obtain lines of credit, have health insurance, and make regular deposits for savings or retirement. The lower the score the worse the financial well-being. The 5 questions were embedded into the larger questionnaire and scored as recommended by the CFPB. This information was utilized to compare financial well-being and predictors of gamete donation.
Statistical analysis
We calculated summary statistics to describe demographics, personal characteristics and opinions regarding gamete donation. Number and percentiles were calculated for each variable stratified by participant’s gender. Univariate regressions and frequencies were conducted between each demographic and personal characteristic and the willingness to donate. Log Binomial regression was used for all dichotomous and categorical variables. For the continuous variable, CFPB, linear regression was used. Risk ratios were calculated for each analysis. Using a subset of the data containing the 264 men and 166 women who would be willing to donate gametes, univariate regressions and frequencies were conducted between each demographic and personal characteristic and desire of monetary compensation for donation. Then using a subset of the data containing the 208 men and 140 women who said they would require monetary compensation for gamete donation, the median of the minimum amount of money necessary to donate gametes and their interquartile ranges were calculated. Minimum monetary amount required to donate was then dichotomized, greater and less than $100 for men and greater and less than $5000 for women. In the same population, univariate regressions and frequencies were conducted between each demographic and personal characteristic and the minimum required monetary compensation. In those willing to donate gametes (men and women combined), univariate regression and frequencies were conducted between the reason to donate gametes with demographic and personal characteristics. Lastly, between the 155 men and the 183 women who were not willing to donate, frequencies were calculated for the reasons not willing to donate gametes.
Results
784 people completed the survey. The average age of men who responded to the survey was 29, and the majority identified as straight (85%), and white (68% vs 10% black, 10% Hispanic or Latino) (Table 1). Respondents were evenly geographically distributed, most located in urban (40%) or suburban (40%) areas, and highly educated with 49% college degree or higher (with only 17% having just high school diploma/GED or less) and 22% currently studying. 46% identified as Christian and 30% atheist/agnostic. Almost half of male respondents (47%) earned < $60,000, 37% had < $ 1,000 in debt while 6% > $100,000 in debt. Most (85%) had a low medium, medium or medium high CFPB score. The average age of women who responded to the survey was also 29, and other demographics were similar to men, although there were fewer Black/African American respondents compared to men (women: 6% vs men: 10%) and more reported having children compared to men (34% women vs 27 men%) (Table 2). More women than men also reported identifying as Democrat (51% vs 41%) and more women were in a relationship/married/domestic partnership (62%) compared to men (50%). Women reported earning less than men, with 70% earning < $60,000, 16% not currently earning, and just 0.5% earning > $200,000. Reported household income was similar to men, and the distribution of burden of debt was similar, as were CFPB scores.
Table 1.
Association of willingness to be a sperm donor, desire for compensation, and minimum desired compensation by financial characteristics
| Would consider donating sperm | Would desire monetary compensation if donating sperm | Minimum amount of money necessary to donate sperm | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| N (%) N = 436 |
n (%) Yes n = 264 |
n (%) No n = 148 |
RR (95% CI) | n (%) Yes n = 208 |
n (%) No n = 54 |
RR (95% CI) | n (%) less than $100 n = 108 |
n (%) greater than $100 n = 100 |
RR (95% CI) | |
| Current yearly personal earnings | ||||||||||
| Not currently employed (including full-time student) | 53 (12.59) | 28 (54.90) | 23 (45.10) | 1.00 (referent) | 27 (96.43) | 1 (3.57) | 1.00 (referent) | 16 (59.26) | 11 (40.74) | 1.00 (referent) |
| $30,000 or less | 102 (24.23) | 63 (63.4) | 36 (36.36) | 1.16 (0.87—1.55) | 54 (87.10) | 8 (12.90) | 0.90 (0.80—1.02) | 33 (61.11) | 21 (38.89) | 0.95 (0.54—1.68) |
| $30,000—$60,000 | 99 (23.52) | 68 (68.69) | 31 (31.31) | 1.25 (0.94—1.66) | 51 (76.12) | 16 (23.88) | 0.80 (0.68—0.92) | 26 (50.98) | 25 (49.02) | 1.20 (0.71—2.05) |
| $60,000—$80,000 | 71 (16.86) | 45 (65.22) | 24 (34.78) | 1.19 (0.88—1.61) | 33 (73.33) | 12 (26.67) | 0.76 (0.63—0.92) | 17 (51.52) | 16 (48.48) | 1.19 (0.67—2.11) |
| $80,000—$100,000 | 40 (9.50) | 26 (66.67) | 13 (33.33) | 1.21 (0.87—1.69) | 20 (76.92) | 6 (23.08) | 0.80 (0.64—1.00) | 7 (35.00) | 13 (65.00) | 1.60 (0.91 -2.79) |
| $100,000—$200,000 | 44 (10.45) | 29 (67.44) | 14 (32.56) | 1.22 (0.89—1.70) | 21 (72.41) | 8 (27.59) | 0.75 (0.59—0.95) | 8 (38.10) | 13 (61.90) | 1.52 (0.86—2.67) |
| Greater than $200,000 | 12 (2.86) | 5 (41.67) | 7 (58.33) | 0.76 (0.37—1.55) | 2 (40.00) | 3 (60.00) | 0.41 (0.14—1.22) | 1 (50.00) | 1 (50.00) | 1.23 (0.29—5.28) |
| CFPB Score | ||||||||||
| Very Low | 8 (1.94) | 4 (57.14) | 3 (42.86) | 0.88 (0.46 – 1.69) | 4 (100.00) | 0 (0) | 2 (50.00) | 2 (50.00) | 0.99 (0.36 – 2.69) | |
| Low | 21 (5.08) | 13 (61.90) | 8 (38.10) | 0.95 (0.67 – 1.36) | 12 (92.31) | 1 (7.69) | 1.18 (0.98 – 1.43) | 7 (58.33) | 5 (41.57) | 0.82 (0.41 – 1.66) |
| Medium Low | 148 (35.84) | 105 (70.95) | 43 (29.05) | 1.09 (0.94 – 1.27) | 85 (81.73) | 19 (18.27) | 1.05 (0.92 – 1.20) | 48 (56.47) | 37 (43.53) | 0.86 (0.62 – 1.19) |
| Medium High | 172 (41.65) | 111 (64.91) | 60 (35.09) | 1.00 (referent) | 85 (77.98) | 24 (22.02) | 1.00 (referent) | 42 (49.41) | 43 (50.59) | 1.00 (referent) |
| High | 58 (14.04) | 26 (46.43) | 30 (53.57) | 0.72 (0.53 – 0.97) | 18 (66.67) | 9 (33.33) | 0.85 (0.64 – 1.14) | 7 (38.89) | 11 (61.11) | 1.21 (0.79 – 1.85) |
| Very High | 6 (1.45) | 2 (33.33) | 4 (66.67) | 0.51 (0.16 – 1.60) | 2 (100.00) | 0 (0) | - | 1 (50.00) | 1 (50.00) | 0.99 (0.24 – 4.02) |
| Debt amount | ||||||||||
| $1,000 or less | 154 (36.58) | 93 (62.42) | 56 (37.58) | 1.00 (referent) | 77 (84.62) | 14 (15.38) | 1.00 (referent) | 41 (53.25) | 36 (46.75) | 1.00 (referent) |
| $1,000—$10,000 | 97 (23.04) | 66 (68.75) | 30 (31.25) | 1.10 (0.92—1.32) | 50 (75.76) | 16 (24.24) | 0.90 (0.76 – 1.05) | 26 (52.00) | 24 (48.00) | 1.03 (0.71—1.49) |
| $10,000—$50,000 | 115 (27.32) | 72 (63.16) | 42 (36.84) | 1.01 (0.84—1.22) | 58 (81.69) | 13 (18.31) | 0.97 (0.84 – 1.11) | 32 (55.17) | 26 (44.83) | 0.96 (0.66—1.39) |
| $50,000—$100,000 | 32 (7.60) | 21 (67.74) | 10 (32.26) | 1.09 (0.83—1.43) | 14 (66.67) | 7 (33.33) | 0.79 (0.58 – 1.08) | 4 (28.57) | 10 (71.43) | 1.53 (1.02—2.30) |
| Greater than $100,000 | 23 (5.46) | 12 (54.55) | 10 (45.45) | 0.87 (0.59—1.31) | 9 (69.23) | 4 (30.77) | 0.82 (0.56 – 1.19) | 5 (55.56) | 4 (44.44) | 0.95 (0.44—2.05) |
Table 2.
Association of willingness to be an egg donor, desire for compensation, and minimum desired compensation with financial characteristics
| Would consider donating eggs | Would desire monetary compensation if donating eggs | Minimum amount of money necessary to donate eggs (dichotomous variable) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| N (%) = 348 | n (%) Yes n = 166 | n (%) No n = 166 | RR (95 CI) | n (%) Yes n = 140 | n (%) No n = 25 | RR (95 CI) | n (%) less than $5000 n = 75 |
n (%) greater than $5000 n = 65 |
RR (95 CI) | |
| Current yearly personal earnings | ||||||||||
| Not currently employed (including full-time student) | 55 (16.27) | 26 (49.91) | 27 (50.94) | 1.00 (referent) | 22 (84.62) | 4 (15.38) | 1.00 (referent) | 17 (77.27) | 5 (22.73) | 1.00 (referent) |
| $30,000 or less | 89 (26.33) | 43 (49.43) | 44 (50.57) | 1.01 (0.71—1.43) | 38 (90.48) | 4 (9.52) | 1.07 (0.88—1.29) | 24 (63.16) | 14 (36.84) | 1.62 (0.68—3.89) |
| $30,000—$60,000 | 103 (30.47) | 50 (50.00) | 50 (50.00) | 1.01 (0.72—1.42) | 45 (91.84) | 4 (8.16) | 1.09 (0.90—1.30) | 18 (40.00) | 27 (60.00) | 2.64 (1.18—5.91) |
| $60,000—$80,000 | 48 (14.20%) | 27 (56.25) | 21 (43.75) | 1.15 (0.79—1.66) | 23 (85.19) | 4 (14.81) | 1.01 (0.80—1.26) | 10 (43.48) | 13 (56.52) | 2.49 (1.06—5.82) |
| $80,000—$100,000 | 16 (4.73) | 9 (56.25) | 7 (43.75) | 1.15 (0.69—1.91) | 6 (66.67) | 3 (33.33) | 0.79 (0.48—1.29) | 1 (16.67) | 5 (83.33) | 3.67 (1.56—8.57) |
| $100,000—$200,000 | 25 (7.40) | 12 (48.00) | 13 (52.00) | 0.97 (0.60—1.60) | 6 (50.00) | 6 (50.00) | 0.59 (0.33—1.07) | 5 (83.33) | 1 (16.67) | 0.73 (0.10—5.14) |
| Greater than $200,000 | 2 (0.59) | 0 (0) | 2 (100) | - | 0 (0) | 0 (0) | 0 (0) | 0 (0) | - | |
| CFPB Score | ||||||||||
| Very Low | 8 (2.40) | 7 (87.50) | 1 (12.50) | 1.71 (1.25 – 2.33) | 6 (85.71) | 1 (14.29) | 1.08 (0.78 – 1.50) | 5 (83.33) | 1 (16.67) | 0.36 (0.06 – 2.20) |
| Low | 19 (5.71) | 10 (52.63) | 9 (47.37) | 1.03 (0.65 – 1.63) | 10 (100.00) | 0 (0) | - | 4 (40.00) | 6 (60.00) | 1.30 (0.72 – 2.32) |
| Medium Low | 138 (41.44) | 65 (48.15) | 70 (51.85) | 0.94 (0.73 – 1.20) | 58 (90.63) | 6 (9.38) | 1.14 (0.99 – 1.32) | 31 (53.45) | 27 (46.55) | 1.01 (0.68 – 1.50) |
| Medium High | 133 (39.94) | 68 (51.13) | 65 (48.87) | 1.00 (referent) | 54 (79.41) | 14 (20.59) | 1.00 (referent) | 29 (53.70) | 25 (46.30) | 1.00 (referent) |
| High | 29 (8.71) | 14 (48.28) | 15 (51.72) | 0.94 (0.63 – 1.42) | 10 (71.43) | 4 (28.57) | 0.90 (0.63 – 1.28) | 4 (40.00) | 6 (60.00) | 1.30 (0.72 – 2.32) |
| Very High | 6 (1.80) | 1 (16.67) | 5 (83.33) | 0.33 (0.05 – 1.97) | 1 (100.00) | 0 (0) | - | 1 (100.00) | 0 (0) | - |
| Debt amount | ||||||||||
| $1,000 or less | 113 (33.33) | 49 (44.14) | 62 (55.86) | 1.00 (referent) | 38 (77.55) | 11 (22.45) | 1.00 (referent) | 24 (63.14) | 14 (36.84) | 1.00 (referent) |
| $1,000—$10,000 | 91 (23.89) | 46 (57.50) | 34 (42.50) | 1.30 (0.98—1.73) | 38 (82.61) | 8 (17.39) | 1.07 (0.87 – 1.30) | 21 (55.26) | 17 (44.74) | 1.21 (0.70 -2.10) |
| $10,000—$50,000 | 86 (25.37) | 42 (50.00) | 42 (50.00) | 1.13 (0.84—1.53) | 37 (90.24) | 4 (9.76) | 1.16 (0.97 –1.39) | 17 (45.95) | 20 (54.05) | 1.47 (0.88—2.44) |
| $50,000—$100,000 | 34 (10.03) | 17 (50.00) | 17 (50.00) | 1.13 (0.76—1.68) | 16 (94.12) | 1 (5.88) | 1.21 (1.00– 1.47) | 7 (43.75) | 9 (56.25) | 1.53 (0.84—2.78) |
| Greater than $100,000 | 25 (7.37) | 12 (54.55) | 10 (45.45) | 1.24 (0.80—1.90) | 11 (91.67) | 1 (8.33) | 1.18 (0.94 –1.48) | 6 (54.55) | 5 (45.45) | 1.23 (0.57—2.66) |
34% men knew someone who required fertility treatment, compared to 52% women. More men than women reported considering donating gametes (64% vs 50%), while similar numbers of men and women would desire compensation (80% vs 85%). Men reported they would desire a mean minimum amount of $2064 to donate, whilst women reported a much higher figure ($90,608). Few participants reported having donated gametes (4% men, 1% women). Fifteen men (3.6%) reported donating sperm in the past, while 5 (1.52%) women reported donating oocytes in the past.
Of men who reported that they would consider donating sperm, there were few significant associations with financial (Table 1) or other demographic characteristics (Supplementary Table 1).
Men with a high CFPB score were less likely to report that they would consider donating sperm compared to a medium high CFPB score (RR 0.72 (0.53 – 0.97). Men with a very high CFPB score were also less likely to report that they would consider donating sperm, but there was a very small number in this group (n = 6) and it did not reach statistical significance (RR 0.51 (0.16 – 1.60). No other financial indicators were associated with considering donating sperm.
Black/African American men, Republican men or other political party affiliates (men who belong to a party other than the Republican or Democratic Party in the US) were more likely to report that they would desire monetary compensation if donating sperm, while men who were married or already had children were less likely. Compared to men who were unemployed, the number who reported desiring monetary compensation if donating sperm decreased as yearly personal earnings increased, although the median amount reported did not differ between groups.
Compared to women who reported being unemployed, those who earned up to $100,000$30,000 were no more likely to consider donating their eggs, or desire compensation, but when they did desire compensation, they were more likely to desire > $5000 in compensation. There were no associations between CFPB score and egg donation outcomes. There were no associations seen between burden of debt and egg donation.
Further demographic associations are presented in supplementary Table 2. Compared to straight women, bisexual women were more likely to consider donating their eggs, and more likely to desire compensation for egg donation Black or African American women were less likely to consider donating their eggs compared to other groups, and more likely to desire > $5000 in compensationFull time students were more likely to consider egg donation compared to women who were unemployed, or employed. Married women were less likely to desire compensation.
Overall, 426 participants stated they would be willing to donate gametes (Table 3), but only 36 (8.5%) would be willing to donate to an unknown infertility patient and 87 (20.4%) would be willing to donate to a friend or family member. The numbers considering donating to unknown patients were low and are included in supplementary tables (Supplemental Table 3). Those with Hispanic/Latino ethnicity were more likely to donate to family/friend, but less likely to donate for research compared to other ethnic groups. Conversely, those who identified as atheist/agnostic, or who did not know someone who required fertility treatment, were more likely to donate to research, but less likely to donate to a family/friend compared to other groups. Those with a very high CFPB score, or children who were not their biological children were more likely to donate to friends/family. Libertarians were more likely to donate for research compared to other groups.
Table 3.
Association of reason to donate gametes with demographic and personal characteristics
| N = 426 | Would donate to friend/family n = 87 men = 23 women = 64 |
Would donate to research n = 303 men = 218 women = 85 |
||
|---|---|---|---|---|
| Variable | n (%) Yes | RR (95% CI) | n (%) Yes | RR (95% CI) |
| Gender Identity | ||||
| Straight | 75 (21.68) | 1.00 (referent) | 241 (69.65) | 1.00 (referent) |
| Lesbian/Gay | 3 (10.71) | 0.49 (0.17—1.46) | 22 (78.57) | 1.13 (0.92—1.39) |
| Bisexual | 9 (19.15) | 0.88 (0.47—1.64) | 35 (74.47) | 1.07 (0.89—1.28) |
| Transgender | 0 (0) | - | 2 (100.00) | - |
| Other | 0 (0) | - | 4 (100.00) | - |
| Race/Ethnicity | ||||
| White or Caucasian | 65 (20.12) | 1.00 (referent) | 289 (73.99) | 1.00 (referent) |
| Black or African American | 6 (21.43) | 1.06 (0.51—2.23) | 21 (75.00) | 1.01 (0.81—1.27) |
| Asian (including Indian subcontinent and Philippines) | 2 (10.53) | 0.52 (0.14—1.97) | 12 (63.16) | 0.85 (0.60—1.21) |
| Hispanic or Latino | 14 (32.56) | 1.61 (1.00—2.61) | 24 (55.81) | 0.76 (0.57—0.99) |
| Other | 0 (0) | - | 8 (57.14) | 0.77 (0.49—1.22) |
| Religion | ||||
| Christian (non-Catholic) | 37 (25.52) | 1.00 (referent) | 94 (64.83) | 1.00 (referent) |
| Catholic | 21 (35.59) | 1.39 (0.90—2.17) | 33 (55.93) | 0.86 (0.67—1.11) |
| Atheist/Agnostic | 15 (11.11) | 0.44 (0.25—0.76) | 112 (82.96) | 1.28 (1.11—1.47) |
| Other | 14 (15.91) | 0.63 (0.36—1.10) | 65 (73.86) | 1.13 (0.95—1.35) |
| Children | ||||
| No | 54 (18.06) | 1.00 (referent) | 224 (74.92) | 1.00 (referent) |
| Yes, biological | 29 (26.36) | 1.45 (0.98—2.16) | 71 (64.55) | 0.86 (0.74—1.00) |
| Yes, biological and not biological (i.e. adopted, step-children, etc.) | 1 (7.14) | 0.39 (0.06—2.65) | 9 (64.29) | 0.86 (0.58—1.28) |
| Yes, not biological (i.e. adopted, step-children, etc.) | 3 (75.00) | 4.14 (2.24—7.66) | 0 (0) | - |
| Political party affiliation | ||||
| Democrat | 44 (21.67) | 1.00 (referent) | 145 (71.43) | 1.00 (referent) |
| Republican | 12 (18.75) | 0.88 (0.50 -1.56) | 40 (62.50) | 0.87 (0.70—1.07) |
| Independent | 25 (21.01) | 0.97 (0.63—1.50) | 85 (71.43) | 1.00 (0.87—1.15) |
| Libertarian | 3 (12.00) | 0.55 (0.19 -1.65) | 22 (88.00) | 1.23 (1.04—1.46) |
| Other | 3 (18.75) | 0.87 (0.30—2.48) | 12 (75.00) | 1.05 (0.78—1.41) |
| Marital Status | ||||
| Single/never married | 27 (15.88) | 1.00 (referent) | 131 (77.06) | 1.00 (referent) |
| Married | 23 (23.71) | 1.51 (0.92—2.48) | 65 (67.01) | 0.87 (0.73—1.02) |
| Long-term partner/Domestic partnership | 36 (24.49) | 1.54 (0.99—2.41) | 99 (67.35) | 0.87 (0.76—1.00) |
| Widowed or Divorced or separated | 1 (7.69) | 0.48 (0.07—3.29) | 9 (69.23) | 0.90 (0.62—1.30) |
| Current yearly personal earnings | ||||
| Not currently employed (including full-time student) | 12 (22.22) | 1.00 (referent) | 39 (72.22) | 1.00 (referent) |
| $30,000 or less | 20 (19.05) | 0.86 (0.45—1.62) | 74 (70.48) | 0.98 (0.79—1.20) |
| $30,000—$60,000 | 30 (25.86) | 1.16 (0.66—2.09) | 79 (68.10) | 0.94 (0.77—1.16) |
| $60,000—$80,000 | 11 (15.49) | 0.71 (0.34—1.48) | 54 (76.06) | 1.05 (0.85—1.30) |
| $80,000—$100,000 | 6 (17.14) | 0.77 (0.32—1.87) | 24 (68.57) | 0.95 (0.72—1.25) |
| $100,000—$200,000 | 7 (17.07) | 0.77 (0.33—1.78) | 30 (73.17) | 1.01 (0.79—1.30) |
| Greater than $200,000 | 1 (20.00) | 0.90 (0.15—5.57) | 4 (80.00) | 1.11 (0.69—1.77) |
| CFPB Score | ||||
| Very low | 3 (27.27) | 1.42 (0.82 – 3.90) | 7 (63.64) | 0.84 (0.53 – 1.32) |
| Low | 4 (18.18) | 0.95 (0.37 – 2.41) | 15 (68.18) | 0.90 (0.67 – 1.21) |
| Medium low | 34 (20.12) | 1.05 (0.68 – 1.60) | 117 (69.23) | 0.91 (0.80 – 1.04) |
| Medium high | 34 (19.21) | 1.00 (referent) | 134 (75.71) | 1.00 (referent) |
| High | 9 (22.51) | 1.17 (0.61 -2.24) | 27 (67.50) | 0.89 (0.71 – 1.12) |
| Very high | 2 (66.67) | 3.47 (1.48 – 8.16) | 1 (33.33) | 0.44 (0.09 – 2.18) |
| Personally knows someone who required infertility treatment | ||||
| Yes | 48 (24.74) | 1.00 (referent) | 125 (64.43) | 1.00 (referent) |
| No | 39 (16.74) | 0.67 (0.46 – 0.98) | 179 (76.82) | 1.20 (1.05 – 1.26) |
Of the 338 participants who stated they would not be willing to donate gametes for any reason (Table 4), 105 men (67.7%) and 65 women (35.5%) stated it was because they were concerned for having biological children they did not know. Another 59 women (32.2%) stated it was secondary to the concern about the potential medical risk.
Table 4.
Reasons for not willing to be a gamete donor
| Reason not willing to donate sperm (n = 155) N (%) |
Reason not willing to donate eggs (n = 183) N (%) |
|
|---|---|---|
| Too time consuming | 8 (5.16) | 15 (8.20) |
| Bad experience donating in the past | 1 (0.65) | 1 (0.55) |
| I find it unethical | 2 (1.29) | 5 (2.73) |
| It goes against my religion | 7 (4.52) | 6 (3.28) |
| Concern for having biological children I don’t know | 105 (67.74) | 65 (35.52) |
| Concerned about the potential medical risk | N/A | 59 (32.24) |
| Other | 32 (20.65) | 32 (17.49) |
Discussion
Principal findings
In this large survey study, 64% of men and 50% of women reported they would be willing to donate gametes with the majority desiring monetary compensation (79% of men and 85% of women). Overall financial well-being was not associated with desire for compensation or compensation amount. Current yearly personal earnings did seem to follow a threshold for desire for compensation when donating sperm, with those earning between $30,000-$200,000 having a decreased desire for monetary compensation compared to those who are unemployed. When earning more than $200,000 this decreased desire was no longer present, although the number of respondents in this group was low (n = 5). The desire for compensation for women was not significant when accounting for current yearly personal earning, but a trend in desire for higher compensation was found for those earning between $30,000–100,000 compared to those who are currently unemployed or a full-time student. Comparable to the male participants, this desire for higher compensation was no longer significant above the threshold value of $100,000.
Results in the context of what is known
Previous studies have shown one of the primary motivators for gamete donation is monetary compensation [5–7, 15, 16] and this practice is generally supported among a representative United States population [8] and was further validated in our study. However, there was no association with overall financial well-being on the CFPB score and the desire for or amount of monetary compensation. We did find the individual annual income for women, but not for men, was associated with a desire for a larger sum of money to be willing to donate eggs. For sperm donation, none of our financial indicators were significant for donation above and below $100, except for a weak association with debt amount between $50,000-$100,00. Notably, respondents who identified as Black were more likely to desire compensation for gamete donation, and desire more compensation compared to other groups. In the US currently, there is a shortage of Black sperm donors, with 3–4% samples available at sperm banks being provided by Black donors. This suggests that this group may require higher compensation in order to donate sperm, which raises an ethical concern. The ethical justification for payment of donors at is based on payment for the discomfort and/or inconvenience of donating. Differing payments for select characteristics, including race, implies that payment is for the gametes themselves, and this steps toward the commodification of human life. Thus, if more Black sperm donors are desired, the compensation threshold should be raised for all donors, regardless of the financial indicators.
With regard to oocyte donation, multiple financial indicators were associated with a desire for higher compensation. The most useful indicator seems to be current yearly personal earnings with those earning between $30,000-$100,000 desiring compensation above $5,000. This indicates an industry range for oocyte donation would likely be best to optimize the donor pool while not simultaneously increasing potential for coercion. The 75th-percentile for desired monetary compensation in this study was $10,000 likely indicating this would be a satisfactory maximum to suggest. This recommended amount for egg donation is also consistent with a public opinion survey study which showed 90% of a national survey of 1,427 people believed egg donation compensation should not exceed $10,000 [17].
Clinical implications
While it was initially encouraging to see that 54% of our representative sample would be willing to donate gametes, it is primarily for research and not for procreative purposes. 15.7% (123 respondents) of respondents reported they would be willing to donate for the purpose of procreation and only 4.6% of the total respondents stated they would donate to an unknown infertility patient. The Centers for Disease Control reported an increase in cycles utilizing donor eggs from 16,161 to 24,300 from 2005 to 2016, respectively. This may partly be due to the increased availability of frozen donor oocytes as oocyte vitrification is no longer considered experimental. However, it is expected the need for donor eggs will continue to increase as the number of women delaying childbearing becomes more common. It will be important to address this increasing need for donor gametes and to ensure there is not a lack of availability of acceptable donors.
Furthermore, the desire for compensation, and the amount of compensation desired (particularly for oocyte donation) raises equity concerns, as by and large gamete donation is not covered by insurance in the US and is an out of pocket expense. This will limit who can afford to use donor gametes.
Research implications
There is currently no publicly available repository of demographic information being kept that describes those who are donating gametes in the US. SART only gives the age of the donor, and private companies who control this information are neither legally obligated, nor offer this information publicly. This scarcity of information leaves us with only retrospective data on those willing to report their information after donation. Tober et al. [18], evaluated perceptions of previous egg donors regarding information communicated about risks of the donor process. 81.5% of their participants were from the USA with the majority having a higher education (72.8% having a bachelor’s or graduate level degree), and 73.3% having Euro-white/mix ancestry. In our survey, we found there was a more even distribution of education levels of women who would be willing to donate, but we did find 78.9% of the women who stated they would be willing to donate eggs were also white or Caucasian. Perhaps this noted skew in those who have donated and those who would be willing to donate is due to the locations that women are targeted by advertising, which often occurs on college campuses. Education and outreach to communities of color is imperative to increase available donor gametes for these communities. A number of prior studies have assessed sperm donors’ motivations, but have not explicitly assessed financial motivators. Freeman et al. evaluated potential sperm donors who were donating for altruistic reasons [19]. As such, financial incentives were not assessed in this study. Pacey et al. looked at factors associated with dropout from the sperm donor process, in both the USA and Denmark, but did not assess demographic factors or the impact of financial background and renumeration on sperm donor status [20].
Strengths and limitations
There are some limitations of our study. This is a representative sample population of the United States, but those included had to be English speaking, literate, members of SurveyMonkey, and motivated to complete the study which could skew the responses in several different ways. It is also difficult to truly assess financial well-being as this is not a strict cutoff point and requires understanding of how a person feels about their finances which can be difficult to quantify. There is also the possibility the participants in the study did not truly understand the risks or process involved in assisted reproductive technology, despite describing it in the questionnaire, which could change the results. Finally, we did not assess donor identification and its potential impact on survey participants’ responses in this study. This is particularly relevant given the advent of straight-to-consumer DNA testing, and the increasing improbability of remaining anonymous as a donor. The strengths of this paper are its large size and representative population, which was possible through balancing on SurveyMonkey’s platform.
Conclusion
In this large survey study, 64% of men and 50% of women reported they would be willing to donate gametes with the majority desiring monetary compensation. A small minority of participants reported they would be willing to donate to an unknown infertility patient for reproductive purposes. High and very high CFPB scores were associated with willingness to donate games, but not with desire for monetary compensation or amount.
Supplementary Information
Below is the link to the electronic supplementary material.
Authors’ contribution
All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Ian Waldman, Jordana Leader, Malinda Lee and Andrea Lanes. The first draft of the manuscript was written by Roisin Mortimer and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Funding
No funding was received for conducting this study.
Data availability
Data will be made available to the editors upon request.
Declarations
Ethics approval
The study was approved by the Partners Healthcare Institutional Review Board under Protocol number 2019P000564.
Consent
Informed consent was obtained from all individual participants included in the study.
Competing interests
The authors have no competing interests to declare that are relevant to the content of this article.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data will be made available to the editors upon request.