Revealing Economic and Racial Injustices: Demographics of Abortion Fund Callers on the U.S.–Mexico Border

Abstract

There are multiple accessibility challenges to abortion care in the United States. Most abortion research relies on clinic data, whereas we utilized data from an abortion fund on the U.S.–Mexico border. The majority of the sample were Latinx (62.2%), were 20–29 years old (59.7%), were in the first trimester (65.4%), and traveled hundreds of miles to an abortion clinic. Younger age, being in the third trimester, not having insurance, and having some resources were associated with likelihood of receiving aid for an abortion procedure. There is still a great need for abortion funding and access, particularly for young, economically disadvantaged people of color.

Abortion is common in the United States and is a critical component of comprehensive reproductive health care, yet it is routinely excluded from most health insurance coverage. Thus, 70% of those who seek abortion must pay for the procedure out-of-pocket (Jerman & Jones, 2014), even if they fall below the federal poverty level (Ibis Reproductive Health, 2016). The average cost of an abortion is $500–$675 in the first trimester, $825–$2,500 in the second semester, and $750–$5,000 in the third trimester (Jerman & Jones, 2014; Jones et al., 2013; Jones & Finer, 2012; Shattuck, 2017). These costs are substantial because most patients seeking abortions are not financially stable (Ibis Reproductive Health, 2016). Furthermore, the ranges presented above do not include associated costs, such as childcare, lodging (Jones et al., 2013), and travel, which are often necessary because many towns in the United States do not have nearby clinics and some states require a 24-hour waiting period between the required first and second appointments (e.g., Karasek et al., 2016). These barriers can delay abortion care beyond the first trimester, which further elevates the cost and the procedure’s risk (Bitler & Zavodny, 2001; Jones et al., 2010, 2013; Joyce & Kaestner, 2001), although abortions are generally low-risk procedures.

Barriers to abortion access extend beyond financial constraints, as safe abortion has been under legal and cultural attack in the United States, particularly in some Southern states such as Texas, waged through tactics such as Targeted Regulations of Abortion Providers (TRAP) laws (Gold & Hasstedt, 2016; NARAL, 2018). Examples of TRAP laws include requirements that clinic physicians have admission privileges to local hospitals and that clinics have the infrastructure of a mini-hospital. Although these laws were eventually overturned for Texas clinics by the U.S. Supreme Court in 2016 (Arons, n.d.), they have resulted in clinic closures throughout the state over the past 25 years. In 1992 there were 79 clinics in Texas, in 2000 there were 65 (Finer & Henshaw, 2003), in 2014 there were 44, and in 2017 only 35 clinics remained (“State Facts,” 2019). To place these numbers into context, the 35 facilities in 2017 were located in only 4% of the 254 counties in Texas (Jones & Jerman, 2017). There are also fewer clinics that offer later-gestation abortions; thus, those who are later in their pregnancies are more likely to have to travel. Twenty-nine million Texans (Population USA, n.d.) reside in a state that is approximately 800 miles long and 800 miles wide (Hlavaty, 2014). For many individuals in the West Texas/Texas panhandle region where the present study took place, the nearest abortion clinic is more than 250 miles away (Crary, 2019).

There has also been a steady stream of other anti-abortion bills (Grossman et al., 2014; Texas Tribune, 2017). For example, Texas has enacted many state-level restrictions, such as banning clinic abortions after 16 weeks’ gestation (or up to 20 gestational weeks at an ambulatory surgical center or hospital) and requiring that patients obtain a sonogram and read information that presents the possibility of adoption and describes medical risks and stages of fetal development. After the sonogram, patients have a 24-hour waiting period before they can obtain the abortion, and both appointments must be with the same physician. Furthermore, Texas laws prohibit insurers from covering abortion expenses as part of a health plan, and military insurance and Medicaid (i.e., public insurance) can only provide coverage in cases of rape, incest, or a life-threatening medical condition (American Civil Liberties Union Texas [ACLUTX], 2019).

Anti–reproductive rights policies affect access to abortion services for all people, yet they disproportionately affect marginalized populations who have fewer resources to identify early pregnancies, afford safe and timely abortions, and/or travel and stay over-night in a town hundreds of miles away from home (Colman & Joyce, 2011; Gerdts et al., 2016; Gold & Hasstedt, 2016). Access is a key issue because safety and quality are higher, and costs are lower, when abortion is performed as early in pregnancy as possible (Foster et al., 2008). Earlier abortions may also afford individuals more privacy if they are able to visit local clinics, versus having to travel out of town, which may require revealing travel plans to their families and/or workplaces.

Charitable organizations known as abortion funds provide critical assistance for individuals who need help with abortion costs due to insurance regulations and other policy and structural barriers. Many patients served by these organizations would be forced to continue their pregnancies against their will if not for the funding assistance received (Ely et al., 2017a). Most abortion funds are small and regional. These funds operate autonomously, yet the National Network of Abortion Funds (NNAF) is the main umbrella organization that provides leadership development, infrastructure, and technical support (NNAF, 2019). Practical support funds help patients with expenses related to items such as travel, lodging, and childcare, and direct support funds provide funding assistance for the abortion procedure in the form of clinic vouchers, also known as “pledges.” Many funds also engage in advocacy to promote reproductive justice and reform abortion policy. As a group, U.S. abortion funds address the financial needs of approximately 30,000 patients seeking abortions each year (NNAF, 2019). Texas has both practical and direct support funds. Most funds cover a regional geographic area in the state and are run by a combination of volunteers and paid staff. All funds also offer emotional support and organize movement building for reproductive and economic justice.

To date, very few researchers have studied abortion fund data. In this small body of research, two studies focused on specific U.S. states. Bessett et al. (2011) conducted interviews with English speakers who had called any of three abortion funds in Massachusetts and who had attempted to enroll in state-subsidized insurance that would cover abortion costs. They found that these individuals had difficulty navigating the health insurance enrollment process, which resulted in delayed abortion care; most interviewees were unable to utilize health insurance for their abortion costs. The second study presented abortion fund recipient demographic data from a Florida abortion fund (Ely et al., 2020). That sample was mainly unemployed, single, and African American; they reported hardships due to unemployment, lack of insurance, domestic violence, rape, and having multiple children.

The rest of the abortion fund research comes from multiyear, national data from NNAF’s Tiller Memorial Fund, which include only callers who received a pledge, and it is unknown whether they used the pledge or actually obtained an abortion. That national abortion fund sample differed from national samples of patients receiving abortions obtained from clinic data; the latter represent patients who received abortions and who may or may not have obtained financial help from abortion funds. The NNAF sample, compared to national clinic data, tended to be younger and predominantly single, African American, and in their second trimesters (Ely et al., 2017a). Although younger, married, and Asian women had higher procedure costs, they also had more personal economic resources available to them. Hardships reported in the NNAF data included living in the South or in states that restrict private insurance coverage for abortion, having multiple children, currently receiving some form of public assistance, having to travel distances greater than 50 miles to obtain an abortion procedure, not being on birth control or having birth control failure, being unemployed or seeking employment, and experiencing housing insecurity (Ely, Hales, Jackson, Bowen, et al., 2017). Thus, most NNAF pledges were made to residents of the South or Midwest (where more abortion restrictions exist), states without expanded Medicaid access to abortion, and states that have private insurance restrictions on abortion coverage. These individuals anticipated traveling approximately 140 miles to obtain an abortion, a distance that increased during the 2010–2015 time frame, particularly for second-trimester patients (Ely et al., 2017b). Ely et al. (2017b) concluded that this increase in travel is likely due to the dearth of clinics that provide later-term abortion care, which may also relate to the fact that a sizable amount of abortion restrictions were implemented between 2011 and 2015.

NNAF data also reveal that the highest pledge amounts and other assistance were given to adolescents, perhaps in part because they were more likely to travel farther than other age groups. Moreover, adolescents were more likely to report seeking an abortion due to lack of contraception and/or rape, whereas adult patients were more likely to be seeking abortions due to contraceptive failure, fetal anomaly, and/or partner violence (Ely et al., 2018).

In sum, the few studies based on abortion fund data reveal that these samples are different from national abortion clinic data, whence most clinical and social science information on abortions is derived. Abortion fund data seem to capture the realities of those who suffer the most hardships; thus, it is imperative to continue to study abortion fund data to reveal information needed to enact positive change.

The Present Study

West Fund (www.westfund.org), the fund under study for this research, is an El Paso, Texas–based nonprofit organization affiliated with NNAF. El Paso is located on the western corner of the state of Texas; it borders the U.S. state of New Mexico and the country of Mexico. West Fund’s mission is to provide assistance, information, and gap funding for individuals in the form of a clinic voucher (a “pledge”) for an abortion procedure. The organization also engages in community outreach, local programming, and fundraising. West Fund started in 2014 and is run by bilingual (Spanish/English) volunteers who receive information by telephone and online from people who are seeking assistance for an abortion procedure. Intake managers answer phone calls, evaluate applications submitted online, and assess potential patient economic need based on gestation stage and whether individuals can get to a clinic in their service area. Based on the organization’s current monthly budget, the intake managers allot a certain dollar amount to qualified individuals (those in their service area) in the form of a voucher for a nearby clinic. Sometimes West Fund will contribute a “solidarity pledge,” which is a donation to another fund.

West Fund callers offer a novel and interesting sample to study because information about individuals who have abortions is limited in general (Jerman et al., 2016) and almost exclusively comes from abortion clinic data. Studies of abortion funds are even more limited yet reveal different populations from those captured in clinic data. Whereas Ely and colleagues (Ely, Hales, Jackson, Bowen, et al., 2017; Ely et al. 2017a, 2017b, 2018, 2020) derived data from NNAF and a Florida fund, and Bessett et al. (2011) from Massachusetts funds, their data do not have the information necessary to compare those who did and did not receive pledges or whether those who received the pledges actually used them. Our West Fund data are unique in that they offer insight into a larger Latinx population on the U.S.-Mexico border and include those who called but did not receive financial assistance. We are also able to track whether these individuals used their clinic vouchers. Given this, our study research questions were as follows: (1) What are the demographic characteristics of West Fund callers? (2) What are West Fund caller demographic associations between those who received/did not receive pledges and those who used/did not use the pledges? We believe that this information can reveal regional demographic differences that may be useful to other researchers, to policy makers, and to abortion funds for their planning and allocation of monies.

Method

Our study received an exempt determination from the University Institutional Review Board. Due to the first author’s long-standing relationship with West Fund, West Fund provided a de-identified (i.e., no names, phone numbers, or emails) Excel spreadsheet with information collected on all West Fund callers. Data were both quantitative (i.e., represented by numbers) and qualitative (i.e., in the form of short text descriptions or more extended notes/comments).

Sample

The final sample size was 2,285 and included information on every individual who had called the fund, regardless of whether the person received or used funding, from December 2014 to February 2018 and September 2018 to April 2019. Most of the sample were heterosexual and English speakers, yet there were too many missing data to determine reliable numbers. The sample’s race/ethnicity was Latinx (62.2%), African American (18.7%), White (14.2%), and Asian/Pacific Islander/Native American/multiracial (4.9%). Their age in years was 11–19 (20.0%), 20–29 (59.7%), 30–39 (18.1%), and 40+ (2.2%). Pregnancy trimesters were first (65.4%), second (26.5%), and third (8.1%), and the most frequent procedure cost was $540. The overall pledge claim/use rate was 64.9% (n = 564) of those who had received pledges. About one-quarter of the callers (25.2%) heard about West Fund from a clinic or another fund, 6.3% from the Internet, 1.2% from a friend/family member, and 0.2% from “other” (missing n = 1,533, 67.1%).

West Fund pledges were offered to 34.6% (n = 791) of callers in amounts that ranged from $15 to $1,000; the most frequent pledge was $150. Those who used their pledge traveled a mean distance of 273 miles (the 320-mile standard deviation was due to a huge variation of distances, which went up to 1,800 miles) to a clinic. The mode was 0 miles (i.e., those who resided in and visited a clinic in El Paso, Texas), which accounts for 38% of the callers.

Measures

Income was impossible to determine. Individuals who reported multiple races (as opposed to using the overarching term “multiracial”) were classified by giving first priority to identification as “Latinx” and second priority to identification as “Black” or “White.” Age was divided into four groups that are consistent with the ranges provided by NNAF and other national clinic data: 11–19, 20–29, 30–39, and 40+ years of age.

“Language,” “employment,” and “insurance” were string variables (reported as text) and recoded into quantitative variables. If Spanish language was indicated as preferred, or if it was spoken during the phone call (we examined the comments sections for any indicators that Spanish was spoken), the individual was coded as a “Spanish speaker.” Coding the employment variable was a similar process; we examined multiple columns (including notes/comments) for indications of whether people were considered employed, which included full-time, part-time, or intermittent work. Insurance status was determined by caller self-report and grouped into “no insurance,” “public insurance” (e.g., CHIP, Medicaid, military), “private insurance” (e.g., coverage from an employer, coverage from spouse or parents’ employers, personal insurance coverage), and “other” (i.e., reports that the person had health insurance but details on type were unavailable).

Patient resources were determined by examining the notes, the circumstances, and the specific column where people who called indicated whether they had some sort of resource to provide money for their procedure (e.g., savings, loans, selling personal items such as computers or clothing to a pawn or consignment shop). Trimester was determined by self-reported gestational weeks: first trimester, 0–12 weeks; second trimester, 13–24 weeks; and third trimester, 25–40 weeks. For procedure cost, if a dollar range was given, we entered the midpoint. We converted this continuous variable into quartiles that seemed best to capture the break points. The first quartile was $1–$500, the second was $501–$550, the third was $551–$1,850, and the fourth was $1,851 or greater.

“Where did you hear about us” was recoded into “Clinic” (e.g., clinicians, clinics, professional organizations including other abortion funds),“Internet” (i.e., people who reported a Google search or specific websites that provide direction to abortion funding), “Friend/family” (e.g., a parent, a relative, a friend, a boyfriend), and “Other” (e.g., word of mouth, unknown initials).

Distance to the clinic was calculated by Google Maps’ report of distance in miles between the caller’s city and state of residence (no exact addresses were given) and the clinic city and state where the appointment was scheduled. Some clinic entries did not have their location specified, so research was done to find their location. Distance was recoded into three categories based on frequencies. Zero miles had the highest frequency; these were individuals who resided in El Paso and utilized a clinic in El Paso. The second highest frequency was 46 miles. Most of these were individuals who called from El Paso, Texas, and utilized a clinic in Las Cruces, New Mexico. The third category was 47+ miles, which consisted primarily of individuals who traveled beyond the El Paso–Las Cruces area, most likely those who traveled to Albuquerque, New Mexico, for later gestation procedures. Because individuals call West Fund from out of the area and thus are not eligible for pledges, travel distance was only analyzed for those who received pledges.

Receipt of a West Fund pledge variable was coded as having received a financial pledge of any amount. Creating this variable required examining the notes, circumstances, pledge sent, and invoice received columns because some callers were not shown to have received a pledge, yet there were indications they had received a pledge in other columns. Pledge redemption was determined by whether West Fund had received an invoice for an abortion service. Those who had not used their pledge showed a “no” or had a blank space in the invoice-received column.

Procedure

Duplicates were removed from the Excel spreadsheet and data were converted into an SPSS file. All variable recoding and analyses were performed on SPSS. We created measurable variables by converting text into numeric categories, and we recoded multiple quantitative variables into categorical variables.

Univariate statistics were used to evaluate continuous variable frequencies to ascertain the number and the increments of the categories for recoding variables into categorical variables (see also “Measures” section above). Univariate statistics were also run to get sociodemographic frequencies. Missing data for univariate statistics were accounted for by SPSS as a system missing value (data that were completely absent), which are reported in the table legends (see Tables 1 and 2).

Table 1.

Chi-square comparisons of demographics for people who did and did not receive a pledge.

Variable	Received pledge (n [%])	Did not receive pledge (n [%])	p *
Race			.278
African American	132 (19.0)	10 (15.4)
Latinx	429 (61.9)	42 (64.6)
Caucasian	101 (14.6)	7 (10.8)
Asian/Pacific Islander/Other	31 (4.5)	6 (9.2)
Age, years**			.005
11–19	130 (18.1)	32 (33.7)
20–29	441 (61.3)	46 (48.4)
30–39	134 (18.6)	14 (14.7)
40+	15(2.1)	3(3.2)
Spanish language			.831
Yes	22 (2.5)	38 (2.7)
No	846 (97.5)	1379 (97.3)
Employment status			.967
Employed	256 (43.2)	33 (43.4)
Unemployed	337 (56.8)	43 (56.6)
Insurance status*			.010
No insurance	367 (56.3)	151 (52.2)
Private insurance	46 (7.1)	38 (13.1)
Public insurance	157 (24.1)	74 (25.6)
Other	82 (12.6)	26 (9.0)
Patient resources***			.001
No	374 (44.1)	1378 (97.4)
Yes	474 (55.9)	37 (2.6)
Trimester*			.015
First	545 (63.6)	644 (67.2)
Second	226 (26.4)	254 (26.5)
Third	86 (10.0)	61 (6.4)
Cost of procedure (USD)***			.001
1–500	208 (25.2)	95 (27.1)
501–550	251 (30.5)	63 (17.9)
551–1,850	154 (18.7)	111 (31.6)
1,851+	211 (25.6)	82 (23.4)

^*p < .05;

^**p < .01;

^***p ≤ .001.

Table 2.

Comparison of demographics for people who used or did not use their pledge.

Variable	Used pledge (n [%])	Did not use pledge (n [%])	p *
Race			.234
African American	85 (19.0)	47 (19.1)
Latinx	267 (59.7)	162 (65.9)
Caucasian	72 (16.1)	29 (11.8)
Asian/Pacific Islander/Other	23 (5.1)	8 (3.3)
Age, years*			.029
11–19	86 (18.9)	44 (16.7)
20–29	288 (63.2)	153 (58.0)
30–39	77 (16.9)	57 (21.6)
40+	5 (1.1%)	10 (3.8)
Spanish language			.295
Yes	16 (2.8)	6 (2.0)
No	547 (97.2)	299 (98.0)
Employment status			.158
Employed	165 (45.5)	91 (39.6)
Unemployed	198 (54.5)	139 (60.4)
Insurance status			.270
No insurance	235 (56.8)	132 (55.5)
Private insurance	33 (8.0)	13 (5.5)
Public insurance	91 (22.0)	66 (27.7)
Other	55 (13.3)	27 (11.3)
Patient resources			.316
No	253 (44.9)	121 (39.7)
Yes	298 (52.9)	176 (57.7)
Trimester*			.034
First	342 (61.2)	203 (68.1)
Second	151 (27.0)	75 (25.2)
Third	66 (11.8)	20 (6.7)
Cost of procedure (USD)			.110
1–500	136 (25.6)	72 (24.6)
501–550	153 (28.8)	98 (33.4)
551–1,850	93 (17.5)	61 (20.8)
1,851+	149 (28.1)	62 (21.2)
Travel distance to procedure (miles)*			.017
0	192 (37.9%)	115 (43.6%)
1–46	43 (8.5%)	34 (12.9%)
47+	271 (53.6%)	115 (43.6%)

^*p < .05.

Chi-square statistics were used for bivariate comparisons of those who received and did not receive pledges and those who used or did not use their pledges. Exact tests were used for small cell sizes consisting of fewer than six people. For crosstabs, if missing data were not accounted for by SPSS, we selected out the missing cases.

Results

Patient resources were not significantly associated with race/ethnicity. People in the 20- to 29-year-old age category had lower-cost procedures, and people in the 40+ age category had more expensive procedures (p = .05). As expected, cost was significantly associated with trimester (p = 0.001); first trimester costs were most frequently less than $550, second trimester costs were most frequently between $550 and the highest cost quartile, and third trimester costs were in the highest cost quartile.

Chi-square statistics calculated to compare callers who did and did not receive a pledge and who used or did not use the pledge revealed no statistically significant differences by race/ethnicity, Spanish language, or employment status. The youngest age categories and individuals who had private insurance, who were in the first trimester, who were in a mid-cost procedure range, and who were unable to contribute resources to the cost of the procedure were less likely to receive a pledge (see Table 1). Individuals in the oldest age categories, first trimester, and lowest travel distance category were less likely to use the pledge (see Table 2).

Of note, both age and trimester were significant variables in both bivariate analyses. Individuals in the youngest age categories had higher percentages who did not receive a pledge than did the other age groups, yet they used their pledges at higher rates than those in the older age categories. Individuals in the first trimester were less likely both to receive and to use pledges than were those in the second and third trimesters.

Discussion

We believe that our results reveal the economic and racial injustices inherent in abortion access in the United States. West Fund is located in El Paso, Texas, on the U.S.–Mexico border—a region with a high poverty rate that is predominantly Latinx (US Census Bureau, 2018). Most of West Fund’s funding is utilized in local clinics by the local population. Given that financial constraints are often cited as a barrier to obtaining an abortion (Finer et al., 2005), it is imperative to have timely and safe abortion access in this region, particularly as there continues to be a steady stream of Texas anti-abortion bills (Grossman et al., 2014; Texas Tribune, 2017).

Moreover, restrictive policies disadvantage not only poor people but also people of color. This is particularly salient for the sample under study, which is 62.2% Latinx and 18.7% African American. The racial/ethnic makeup of the West Fund sample starkly contrasts with U.S. national abortion clinic data, which shows that 35% of patients receiving abortions are White and 38% are Black (Jatlaoui et al., 2019). Consequently, we see that abortion experiences are regional and deserve more focused attention by region.

Similar to other abortion fund research, we found that those who receive funding assistance differ from abortion clinic patients at the national level. Thus, abortion fund samples are important to study and, in this case, draw attention to the need to revise and revoke regressive abortion policies that particularly affect people of color and economically disadvantaged populations. Data from abortion funds can add crucial information needed to enact change at state and federal levels.

The focus on state and federal policy reform is essential, but abortion funds also deserve attention and funding because they are an avenue to combat economic and racial injustice through reproductive justice. West Fund data reveal that the overall pledge claim/use rate was 61.7% of those who had received pledges, which means that thousands of dollars have gone to help individuals to access abortion care. A large abortion clinic sample in an Arizona city revealed that nearly two-thirds of women reported having some assistance paying their expenses, from family (14%), a partner (46%), or a private abortion fund (4%) (Karasek et al., 2016). To us, this indicates that more patients and potential fundraisers/granters could be aware of abortion funds, and we hope that our research is one step in the direction of raising that awareness.

The West Fund callers with a procedure cost of $501–$550 were much more likely to receive a pledge than were those in the $551–$1,850 procedure cost range. This is most likely because it was easiest for West Fund to provide small gap funding for lower-cost procedures. In addition, people with some ability to contribute personal resources both received and used a pledge at higher rates than did those without available resources. At the time of this analysis, West Fund was unable to provide coverage for the total expenses requested, but since the time of this analysis, the fund has received a grant that will allow them to fully fund first-trimester abortions and increase the dollar amount of pledges for abortions that are past the Texas gestational limit (i.e., for those that require services at the Albuquerque clinic), at least during the duration of the grant. This may improve their pledge claim rate and also decrease the need for later-gestation abortions (if first-trimester abortions are more accessible), which is imperative to reduce individuals’ emotional burdens as well as the reduction of both personal and community health care costs. Future researchers could examine any potential impacts of this new funding structure.

Increased funding can aid patients with abortion procedure costs and also potentially increase the number of people being served. West Fund’s service area is large, yet they are only able to provide assistance to patients who receive abortions at two specific clinics: one in El Paso and another in Albuquerque, which requires a 4-hour drive each way. More funding could expand the number of clinics that work with West Fund so that they could potentially service a wider geographic area and/or bring more people to the El Paso region. Forty-three percent of Texas women live in counties with no abortion clinic (Guttmacher Institute, 2019), and due to this dearth of clinics, the clinics that offer abortions in El Paso serve individuals who must travel from hundreds of miles away. Studies show that travel distance is a hardship (Ely, Hales, Jackson, Bowen, et al., 2017) and reduces abortion utilization, which particularly affects Hispanic Americans (Brown et al., 2001; Brown & Jewell, 1996; Grossman et al., 2014). Thus, it is also imperative to maintain and improve the El Paso clinics as well as offer more abortion services at clinics across Texas.

Trimester was another meaningful variable of study. Most West Fund callers were in their first trimester, with an average procedure cost of $540. This differs from the majority second-trimester callers in the NNAF data (Ely et al., 2017a), because NNAF prioritizes second-trimester funding, yet it is consistent with national clinic sample data, which indicate that 90% or more of abortions in the United States occur in the first trimester (Jatlaoui et al., 2019). This suggests that most patients seeking abortions want to terminate pregnancy in the first trimester. This points to the importance of not only maintaining and improving local abortion funds but also working to repeal policies that delay abortion access.

Moreover, those who were past 25 weeks pregnant (and past Texas’s 20-week limit) received a pledge and used the pledge at statistically significant higher rates than did first-trimester patients. It is possible that some individuals in their first trimester used other means such as crossing the border to Mexico to get abortion-inducing medication at a pharmacy, choosing to carry the pregnancy to term, or utilizing an abortion clinic with which West Fund does not partner. Those in the highest-cost category, $1,851 or more, used the pledge at higher rates, which probably reflects the later-gestation patients as the procedures become costlier as the pregnancy progresses. Given the urgency, those with higher-cost procedures used all the help that they could receive. People who are bordering or past the gestational limit cutoff tend to have significant and multiple hardships (Ely et al., 2017b) or medical anomalies that were not discovered until the pregnancy had progressed or could not be attended to quickly due to other hardships. More accessible, comprehensive health care is one policy that would help eliminate barriers for this population of patients seeking abortions.

Age proved to be an interesting and hard-to-interpret finding. The West Fund sample was similar to national clinic data samples where women in their 20s account for most patients seeking abortions, yet differed from national data where the youngest patients only account for 10% of all patients receiving abortion (Jatlaoui et al., 2019; Jerman et al., 2016). It is interesting that the NNAF data (Ely et al., 2017a) also contain higher percentages of younger callers than the national clinic data do. We also found that young West Fund callers were less likely to receive pledges. Perhaps fund data contain more younger callers due to their increased economic insecurity. Adolescents often lack a steady income, and they may feel uncomfortable asking parents or others for abortion funding assistance (Ely et al., 2018), which may be needed if they do not have insurance coverage because they do not want to use their parents’ health insurance for abortion services out of privacy concerns or due to an inadequate insurance system. Our analyses indicated that most people in the youngest age group had public insurance, yet Texas Medicaid does not cover abortion services. Thus, we recommend that Texas Medicaid include abortion coverage and prioritize affordable access to all reproductive health services, including contraception, which limits unintended pregnancies and abortions (Deschner & Cohen, 2003).

Adolescents may also experience unique hardships, such as co-occurring psychosocial problems, which could delay awareness of the pregnancy and thus impact abortion timing. Adolescents are also more likely to report nonuse of contraceptives and rape (Ely et al., 2018), so trauma services may be needed/recommended by abortion fund volunteers. In Texas, minors have to get the consent of their parents in order to obtain an abortion; otherwise they have to go through the process of obtaining a judicial bypass (i.e., appear in court to ask a judge’s permission to obtain an abortion) (Texas LawHelp.org, 2020). This regulation exists despite empirical evidence that adolescents have the cognitive capacity to make the decision to choose abortion (Steinberg et al., 2009). In our sample, those in the youngest age categories were less likely to receive a pledge than the two older age groups, yet they used their pledges at higher rates. Thus, there may be an unmet need among younger people who seek abortion care that funds and clinics may be overlooking.

To help people of all ages, we recommend that practitioners discuss abortion as an option to pregnant women as indicated in ACOG’s (2007) professional guidelines regarding imparting accurate and unbiased information, because currently up to one-third of health professionals do not discuss abortion with patients (Zurek & O’Donnell, 2019). Moreover, the 2019 U.S. domestic gag rule that prohibits family planning services from obtaining funds from a federal grant program if they engage in comprehensive reproductive health care (Population Connection Action Fund, n.d.) needs to be repealed so that Planned Parenthood and other independent clinics can return to providing neutral counseling regarding pregnancy resolution options and abortion referrals for those who experience unintended pregnancies. This will help patients to make informed decisions and ensure timely referrals to clinics in order to avoid costlier procedures later on in pregnancies, particularly because a lack of correct information about where to locate abortion services leads to delayed care (Drey et al., 2006; Jerman et al., 2017; Upadhyay et al., 2014). We also recommend that practitioners familiarize themselves with national and local abortion funds and refer clients to those resources.

Future research should include multivariate analyses and/or more closely examine age, as it appears to be a complex variable related to many other variables. Future research should continue to investigate individuals who did not use their pledges in order to understand more about this group so that funds may strategize better about how to expand or redistribute their funding to better serve callers’ needs. Moreover, future research, including both qualitative and multivariate quantitative analyses, is still needed on a plethora of related variables, such as partner-related issues, which Chibber et al. (2014) found to be important.

As others have found limitations with use of existing health records (Strongman et al., 2019), we too were limited by our data. Abortion fund intake caller data were entered by various staff members, which resulted in a great variation in how responses were noted, which we had to transform into discrete variables, and which ultimately meant a great number of missing data on some variables. We were also limited by the amount and types of data in the intake caller database; we had to work with the information that West Fund had decided to collect. West Fund data are local and not generalizable beyond those in the study, but they are useful to understand regional needs. Last, we were missing 6 months of data from February to September 2018 due to West Fund’s bookkeeping. These missing data may or may not have changed our results, depending on structural, economic, or policy occurrences during that time.

Whereas all studies have limitations, and despite the limitations of our study outlined above, the information we garnered is important because the work in this area is so limited, and data such as those represented here are very difficult to access. We were still able to obtain more than 2,000 entries for an exploratory study of a regionally specific Latinx sample, and we could compare those who received and did not receive abortion vouchers and those who used or did not use the vouchers. Our study also adds to the very small amount of research based on abortion fund data. Our findings can be useful guides for abortion fund staff, clinicians, researchers, and policy makers as they help people to navigate the legal, financial, and other constraints that serve as barriers to obtaining reproductive health care, particularly for younger, economically disadvantaged, people of color.