Introduction
Community-based veterinary clinic models work to create accessible veterinary care for underserved communities1; however, more research on access to veterinary care is needed to address systemic and historical disparities in the field. Limited access to veterinary care could impact health outcomes of not only animals but also their owners, making disparities in equitable access to veterinary care an important One Health issue. This study explored pet owners’ reported ease of access to veterinary services through an analysis of survey data from a national sample of American pet owners to better understand how demographic characteristics of pet owners may relate to veterinary access.
Financial limitations and the cost of veterinary care are the most commonly reported barriers to receiving care and must be addressed when access to veterinary medicine is discussed.1,2 The Access to Veterinary Care Coalition found that 8 out of 10 pet owners who were unable to receive needed veterinary care for their animal indicated it was because they were not able to afford it.3 Pet owners are often surprised at the cost of veterinary care, and 59% agree or strongly agree that the costs of routine visits are higher than expected.4,5 Additionally, pet owners across the income spectrum perceive veterinary care to be expensive, and 29% of pet owners have reported at least one instance of not being able to afford veterinary services.6 While community veterinary models often provide subsidized services for low-income pet owners, financial constraints are still an access issue in low-cost clinic models. A recent study found that financial barriers were still a significant problem facing clients in a community clinic model, suggesting that the cost of care is a pressing issue even in a subsidized clinic.7 The cost of veterinary care may be one of the reasons people feel veterinary care is inaccessible in their community, but more research is needed on how financial vulnerability more broadly relates to veterinary care in the US in order to better understand the scope of this problem on a national level.
One possible way to explore financial vulnerability and how it is associated with veterinary care access is through financial fragility or the ability to cope with an unexpected expenditure or income shock. Financial fragility is often measured by assessing an individual’s capacity to come up with $2,000 in 30 days.8 Using data from 2015, Hasler et al9 found that one-third of all Americans were financially fragile, with especially vulnerable populations in middle-aged people 40 to 49 years of age, lower-income individuals, women, and people with lower educational attainment. However, even in the median income category ($50,000 to $75,000), almost 30% of households were financially fragile and in the next higher income band of $75,000 to $100,000, 20% of households were financially fragile.9 More recently, in 2019, one study found that 37% of the US adult population could not come up with $400 to cover an emergency expense using cash.10 Given the pervasiveness of financial fragility in the US, the cost of emergency or unexpected veterinary care is a considerable problem. More research is needed to understand how pet owners experience financial fragility, as well as how clients with varying financial means perceive their access to veterinary care. Financial fragility is a novel approach to understanding financial constraints of pet owners and provides a unique measure that evaluates owners’ ability to cope with financial costs over a month’s time frame. Additionally, this measure allows owners to consider other resources they could access, other financial obligations, and nuanced factors such as confidence and future expectations for their financial status.9 Because people of almost all income brackets experience financial fragility and also think veterinary care is expensive, it is necessary to explore the relationship specifically between veterinary access and financial fragility in pet owners.
In addition to financial burden, systemic and historical racism have helped to perpetuate a lack of access to animal resources, especially veterinary care, through segregation and redlining of communities.11 In the human health-care system, racial disparities are prevalent even when controlling for insurance status, income, age, and severity of conditions.12 Given the similar infrastructure of veterinary medicine to human medicine, more research is needed to address potential racial inequities in veterinary medicine. The Humane Society of the United States Pets for Life program found that when structural barriers steeped in racial inequality like limited transportation and distant clinic locations were deliberately resolved, race and ethnicity of pet owners were not determinants of veterinary use of spay and neuter services.13 Many pet owners in low-income communities may rely on public transportation, which does not allow animals; therefore, clients cannot travel to a veterinarian with their pet on the bus or subway.12,13 Issues of veterinary access are exacerbated due to animal resource deserts or areas with a lack of veterinary offices, pet food stores, groomers, or animal welfare organizations. In addition, language barriers between veterinarians and clients are another common access issue, with only 8% of small animal practice staff prepared to communicate in Spanish with limited English-proficient pet owners.14 A client’s levels of education attainment and knowledge about animal health are also cited as barriers for veterinary care1; therefore, it is important to investigate whether educational attainment levels are related to perceived access to veterinary care. These findings suggest that access and utilization of veterinary services may be an equity issue; research focused on equitable veterinary medicine will enable community-based clinic models to better address specific barriers to care, like pet-friendly transportation, in order to meet community needs. More research is needed that utilizes a nationally representative data set of pet owners in order to understand how demographic predictors may relate to perceived access to veterinary care.
This study is one of the first to analyze pet owners’ perceptions of access to veterinary care related to financial fragility and other demographic characteristics. While current literature in the field often reports on the frequency of veterinary visits by pet owners,15 few studies examine perceptions of accessibility. The goal of this study was to examine a national survey of pet owners in order to understand perceived ease of access to veterinary care among pet owners and how demographics such as race or ethnicity, financial fragility, and education levels may predict ease of access. By exploring demographics that may predict veterinary access, we will be able to target specific factors for improving veterinary access and community health.
Materials and Methods
Procedure
Data for this study were from a larger cross-sectional survey conducted by the Tufts University Equity Research Group. Noninstitutionalized adults aged 18 years or older living in the US were initially recruited to a survey panel (KnowledgePanel; Ipsos) via a probability-based recruitment methodology and random sampling of residential addresses and telephone numbers. Participants who did not have internet access were provided with a laptop and internet connection at no cost. Participants were sent emails a few times each month inviting them to participate in research initiatives. Demographics and a wide range of descriptive variables (personal and household characteristics, personal health, lifestyle, finance, politics, media usage, etc) collected by Ipsos annually are used in this analysis (Ipsos profile surveys).
The Tufts University Equity Research Group’s survey to the panel was fielded in English and Spanish from May 29, 2020, to June 10, 2020, and a representative sample of 1,980 participants were invited to complete the survey. All nonresponding panel members were sent an automatic reminder email on day 3, and for purposes of oversampling, additional reminders were sent to Black and Hispanic members on day 11. The median completion time was 17 minutes, and upon completion, qualified respondents received their standard incentive payment (for most respondents, 1,000 points, the cash equivalent of $1, and an entry into the KnowledgePanel sweepstakes for completing a survey longer than 15 minutes). Of the 1,980 panel members, 1,267 eligible members responded, of whom 750 (59.2%) were pet owners and were included in these analyses.
We examined measures from both the Tufts Equity Research Group survey (access to care and veterinary-related questions) and Ipsos’ own profile surveys (demographics, financial fragility, income status, etc). For further information on the sampling frame and the Equity in Health, Wealth, and Civic Engagement Survey, see Stopka et al16 and the Tufts University Equity in America website.17 All research was approved by the Tufts University Institutional Review Board.
Measures
Demographics—Participants were asked standard demographic questions such as gender identity (male or female), age (continuous variable), and racial or ethnic identity (white/non-Hispanic, Black/non-Hispanic, Hispanic, other/non-Hispanic, or ≥ 2 races/non-Hispanic). Because of small sample sizes, ≥ 2 races/non-Hispanic and other/non-Hispanic were recoded into one category. Education was measured by a categorical variable in which participants were asked to select their highest completed level of education (less than high school, high school, some college, or Bachelor’s degree plus).
Pet ownership and use and ease of access to veterinary care—Pet ownership was measured by means of asking participants if they owned a pet and, if yes, what species they owned (dog, cat, fish, bird, small animal, reptile, horse, or other). If participants selected yes to owning a pet, they were asked how often their pet sees a veterinarian (several times a year, once a year, rarely, never, or don’t know/not sure). Respondents who selected don’t know/not sure were recoded to missing data. Pet owners were also asked about ease of access to veterinary care. Respondents rated how much they agreed or disagreed with the following statement on a Likert-type response scale that was considered a continuous variable for the purpose of analysis: “I can easily access veterinary care for my pet in my community” (strongly disagree = 1, disagree = 2, neutral = 3, agree = 4, strongly agree = 5, and don’t know/not sure = coded to missing data).
Financial status and government assistance programs—Income status was measured incrementally in 21 categories starting with “< $5,000” (1) and ending with “≥ $250,000” (21). Participants were asked about their income stability, “in the past 12 months, which one of the following best describes you and your spouse or partner’s income: roughly the same amount each month, occasionally varies from month to month, or varies quite often from month to month.” In order to measure financial fragility, participants were asked how confident they were that they could come up with $2,000 if an unexpected need arose within the next month (0 = not at all confident, 1 = only slightly confident, 2 = somewhat confident, or 3 = very confident).
To measure the use of government assistance programs, participants were asked to select whether they or a member of their household had received any of the following in the past 12 months: food stamps (Supplemental Nutrition Assistance Program [SNAP]); Women, Infants, and Children nutrition program; cash assistance from welfare (Temporary Assistance for Needy Families [TANF]); social security; unemployment insurance; housing assistance from a government program (Section 8 or Public Housing); disability benefits; survivors benefits; free or reduced-price school lunches for their children; or none of the above. A sum score was calculated for total number of programs utilized by a participant, and due to small sample sizes, a condensed category was created for “3 or more.” At the time of data collection, COVID-19 relief packages were not yet available.
Analysis plan
The sample was weighted to match the US population with regard to age, gender, race, ethnicity, income, education, Census region, urbanicity, and owning a home. Sampling weights were based on the 2019 Current Population supplement and ranged from 0.174 to 3.7 with a median of 0.843. Additional sampling and collection details are reported in Stopka et al.16 Weighted descriptive statistics and frequencies are reported for all data as well as tests for normality. ANOVA was used to compare ease of access to care ratings. Additionally, because there is debate about using parametric versus nonparametric testing for a single item using a Likert-type response,18 Kruskal-Wallis tests were also used to compare ease of access to care ratings. A Pearson correlation was conducted to examine the relationship between financial fragility and income.
A sequential multiple regression model was conducted to evaluate if education level, race or ethnicity, and financial fragility predicted ratings of ease of access to veterinary care. Because financial fragility was pervasive throughout income levels and could be related to affording veterinary care, this measure was used in the model to understand finances. Data were tested for regression assumptions, including independence of observations, linearity, homoscedasticity, normal distribution of residuals, and multicollinearity. Dummy codes were created for education level (with less than high school as the reference category) and race or ethnicity (with white, non-Hispanic as reference category). Financial fragility was used as a continuous scale variable. Model 1 included education level, model 2 added race/ethnicity, and model 3 incorporated income fragility. All data were analyzed by use of data analysis software (SPSS version 27; IBM Corp), and an α level of .05 was used to determine significance for all statistical tests.
Data screening
Preliminary analyses were conducted to determine the distribution of access to care responses and identify outliers. Histograms and P-P plots showed data to be negatively skewed (–1.58; SE = 0.094) with a kurtosis of 2.46 (SE = 0.187). Given that this was a large sample size and skewness or kurtosis values were within a reasonable range,19 data were considered normally distributed and suited for regression analysis.
In order to address univariate outliers, z scores of access to care were calculated and box plots were used to identify outliers. z Scores ranged from 0.74 to –3.58, and data points with a z score of 3.58 accounted for 2.25% of the responses. On the basis of the results of box plots and because 14 data points were at the 3.58 level, no data points were excluded from analysis.
Results
Participants
Respondents of this survey (n = 750 pet owners) ranged in age from 18 to 89, with an average age of 47 years (SD = 16.44). Nearly half (54.3% [407/750]) were women. When asked to identify their race or ethnicity, 68.6% (514/750) identified as white, non-Hispanic; 16.5% (124/750) as Hispanic; 7.8% (59/750) as Black, non-Hispanic; and 7.1% (53/750) as other/≥ 2 races, non-Hispanic. Education of pet owners varied, with 12.1% (91/750) completing less than high school, 28.7% (215/750) completing high school, 29.7% (223/750) completing some college, and 29.5% (221/750) completing a Bachelor’s degree or higher. The mean income category of pet owners was $60,000 to $74,900, with a median of $75,000 to $84,999.
Of the 750 participants, 727 had complete data regarding income stability, with 67.6% (507/750) of participants’ income roughly remaining the same amount each month, 19.3% (145/750) occasionally varying from month to month, and 9.9% (75/750) varying quite often from month to month. Regarding the 689 participants who answered the question on financial fragility, 46.6% (321/689) were very confident they could come up with $2,000 if an unexpected need arose, 20.8% (143/689) were somewhat confident, 11.7% (81/689) were only slightly confident, and 20.9% (144/689) were not confident at all. On average, participants scored a 1.93 (SD = 1.19) on financial fragility, with a median of 2 (somewhat confident). Income and financial fragility were correlated, with r(689) = 0.45 and P < .001, reflecting a moderately strong positive relationship. Financial fragility was present in each income bracket (Table 1).
Financial fragility rating by income bracket level (n = 689).
| Financial fragility (confidence to produce $2,000 for unexpected expense) | |||||
|---|---|---|---|---|---|
| Household income | Not at all confident (n) | Only slightly confident (n) | Somewhat confident (n) | Very confident (n) | Total (n) |
| < $5,000 | 80.0% (8) | 10.0% (1) | 0.0% (0) | 10.0% (1) | 100.0% (10) |
| $5,000–$7,499 | 66.7% (4) | 33.3% (2) | 0.0% (0) | 0.0% (0) | 100.0% (6) |
| $7,500–$9,999 | 85.7% (6) | 0.0% (0) | 0.0% (0) | 14.3% (1) | 100.0% (7) |
| $10,000–$12,499 | 63.6% (7) | 9.1% (1) | 18.2% (2) | 9.1% (1) | 100.0% (11) |
| $12,500–$14,999 | 60.0% (6) | 10.0% (1) | 20.0% (2) | 10.0% (1) | 100.0% (10) |
| $15,000–$19,999 | 37.5% (9) | 25.0% (6) | 20.8% (5) | 16.7% (4) | 100.0% (24) |
| $20,000–$24,999 | 31.0% (9) | 10.3% (3) | 34.5% (10) | 24.1% (7) | 100.0% (29) |
| $25,000–$29,999 | 38.1% (16) | 19% (8) | 16.7% (7) | 26.2% (11) | 100.0% (42) |
| $30,000–$34,999 | 22.2% (4) | 16.7% (3) | 22.2% (4) | 38.9% (7) | 100.0% (18) |
| $35,000–$39,999 | 47.8% (11) | 4.3% (1) | 26.1% (6) | 21.7% (5) | 100.0% (23) |
| $40,000–$49,999 | 13.5% (5) | 24.3% (9) | 21.6% (8) | 40.5% (15) | 100.0% (37) |
| $50,000–$59,999 | 16.7% (7) | 26.2% (11) | 21.4% (9) | 35.7% (15) | 100.0% (42) |
| $60,000–$74,999 | 11.9% (8) | 6.0% (4) | 32.8% (22) | 49.3% (33) | 100.0% (67) |
| $75,000–$84,999 | 27.9% (12) | 9.3% (4) | 30.2% (13) | 32.6% (14) | 100.0% (43) |
| $85,000–$99,999 | 21.4% (9) | 21.4% (9) | 7.1% (3) | 50.0% (21) | 100.0% (42) |
| $100,000–$124,999 | 11.5% (11) | 9.4% (9) | 25% (24) | 54.2% (52) | 100.0% (96) |
| $125,000–$149,999 | 7.0% (3) | 7.0% (3) | 18.6% (8) | 67.4% (29) | 100.0% (43) |
| $150,000–$174,999 | 14.8% (8) | 3.7% (2) | 24.1% (13) | 57.4% (31) | 100.0% (54) |
| $175,000–$199,999 | 3.4% (1) | 0.0% (0) | 10.3% (3) | 86.2% (25) | 100.0% (29) |
| $200,000–$249,999 | 0.0% (0) | 7.4% (2) | 11.1% (3) | 81.5% (22) | 100.0% (27) |
| ≥ $250,000 | 0.0% (0) | 6.9% (2) | 6.9% (2) | 86.2% (25) | 100.0% (29) |
| Total | 20.9% (144) | 11.8% (81) | 20.9% (144) | 46.4% (320) | 100.0% (689) |
Seven hundred twenty-eight pet owners answered questions about use of any government social programs over the past 12 months. Nearly half of pet owners (48.7% [354/728]) participated in at least 1 program. Over 12% (12.8% [93/728]) of pet owners received SNAP food stamps; 2.5% (18/728) Women, Infants, and Children nutrition program; 1.4% (10/728) TANF; 24.2% (176/728) social security; 13.7% (100/728) unemployment; 2.3% (17/728) housing assistance from a government program; 10.8% (79/728) disability benefits; 2.4% (18/728) survivors’ benefits; and 6.1% (44/728) free or reduced-price school lunches for children.
Access to veterinary care
A total of 679 participants (90.5%) answered the access to care question, and 654 (87.2%) responded to the veterinary use question. On a scale of strongly disagree (1) to strongly agree (5), the mean rating of access to care was 4.31 (SD = .93). The majority of participants agreed they could easily access veterinary care for their pets, as follows: 53.6% (364/679) strongly agreed, 31.7% (215/679) agreed, 9.3% (215/679) were neutral, 3.2% (21/679) disagreed, and 2.2% (15/679) strongly disagreed.
When looking at frequency of veterinary use, 23% (n = 152) of participants took their pet to the veterinarian several times a year, 45% of participants (291) took their pet once a year, 25% (162) rarely took their pet, and 7% (48) of participants had never taken their pet to the veterinarian. Mean scores for access to care by veterinarian visit frequency are summarized (Table 2). An ANOVA revealed a statistically significant difference in ease of access scores by veterinarian visit frequency (F[3, 627] = 34.05; P < .001). A Kruskal-Wallis test had similar findings (H[4] = 100.66; P < .001). ANOVA post hoc tests revealed that each category of frequency of veterinary use was statistically different from one another in ease of access ratings, where a higher frequency of veterinary visits per year was significantly associated with higher ease of access ratings.
Mean ease of access to veterinary care rating stratified by use of veterinary care, income stability, and use of government assistance programs.
| Ease of access to care rating | ||
|---|---|---|
| Variable | Mean | SD |
| Veterinary use (n = 654) | ||
| Several times a year | 4.70 | 0.64 |
| Once a year | 4.47 | 0.77 |
| Rarely | 3.98 | 1.01 |
| Never | 3.46 | 1.25 |
| Income stability (n = 727) | ||
| Roughly the same amount each month | 4.36 | 0.94 |
| Occasionally varies from month to month | 4.42 | 0.67 |
| Varies quite often from month to month | 3.71 | 1.06 |
| Government assistance (n = 661) | ||
| Does not participate in programs | 4.51 | 0.74 |
| Participates in 1 program | 4.28 | 0.88 |
| Participates in 2 programs | 3.93 | 1.23 |
| Participates in ≥ 3 programs | 3.55 | 1.24 |
Missing data accounted for varied n between variables. Ease of veterinary access was scored as follows: 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, and 5 = strongly agree.
Access to care, financial stability, and government assistance—An ANOVA demonstrated a significant relationship between income stability and ease of access ratings where participants who had income that varied quite often month to month reported significantly lower ratings of access to care than the other 2 income categories (F[2, 665] = 12.92; P < .001; Table 2). Kruskal-Wallis test results indicated similar relationships (H[4] = 27.59; P < .001). Participants who did not utilize government assistance programs had significantly higher scores for ease of access than participants who participated in 1, 2, or 3 or more programs (F[3, 657] = 19.50; P < .001; Table 2). A Kruskal-Wallis test supported these findings (H[4] = 48.11; P < .001).
Demographic predictors of ease of access
In model 1, education level predicted 10.3% of the variance in ease of access to veterinary care (F[3, 621] = 23.75; P < .001). A person with less than a high school education would have a predicted score of 3.71 (SE = 0.10) on access to care (Table 3). Adding race or ethnicity in model 2 significantly increased the predictive value of the model by 3.4% (F[6, 618] = 16.30; P < .001; ΔF [3, 617] = 8.04; P < .001; R2 = 0.137), with white, non-Hispanic participants with less than a high school education having a predicted score of 3.97 (SE = 0.11) on access to care. Finally, when financial fragility was added to model 3, an additional 4.7% of the variation in ease of access was explained for a total of 18.3% (F[7, 617] = 19.80; P < .001; ΔF [1, 616] = 35.36; P < .001). The predicted ease of access score for white, non-Hispanic participants with less than a high school education and no confidence in the ability to come up with $2,000 for an unexpected need was 3.67 (SE = 0.12). Hispanic participants (β = –0.17, P <.001) and other/≥ 2 races, non-Hispanic (β = –0.09; P = .01) with less than a high school education and no confidence in the ability to come up with $2,000 had significantly lower scores than white participants with the same education and financial status. Additionally, white participants with no confidence in the ability to come up with $2,000 had significantly different access scores per education level (Table 3).
Sequential regression coefficients for ease of veterinary access rating.
| 95% CI | ||||||||
|---|---|---|---|---|---|---|---|---|
| Model (n = 624) | B | SE | β | t | P | Lower bound | Upper bound | |
| 1 | ||||||||
| High school | 0.589 | 0.123 | 0.291 | 4.804 | < 0.001 | 0.348 | 0.830 | |
| Some college | 0.482 | 0.122 | 0.239 | 3.941 | < 0.001 | 0.242 | 0.723 | |
| Bachelor’s degree or higher | 0.977 | 0.122 | 0.486 | 7.994 | < 0.001 | 0.737 | 1.217 | |
| 2 | ||||||||
| High school | 0.455 | 0.126 | 0.225 | 3.611 | < 0.001 | 0.208 | 0.702 | |
| Some college | 0.354 | 0.126 | 0.175 | 2.809 | 0.010 | 0.106 | 0.601 | |
| Bachelor’s degree or higher | 0.843 | 0.128 | 0.419 | 6.590 | < 0.001 | 0.592 | 1.094 | |
| Black, non-Hispanic | –0.200 | 0.138 | –0.055 | –1.454 | 0.150 | –0.471 | 0.070 | |
| Hispanic | –0.445 | 0.102 | –0.175 | –4.364 | < 0.001 | –0.645 | –0.244 | |
| Other/≥ 2 races, non-Hispanic | –0.343 | 0.137 | –0.096 | –2.501 | 0.01 | –0.613 | –0.074 | |
| 3 | ||||||||
| High school | 0.416 | 0.123 | 0.205 | 3.385 | < 0.001 | 0.175 | 0.657 | |
| Some college | 0.255 | 0.124 | 0.127 | 2.064 | 0.04 | 0.012 | 0.498 | |
| Bachelor’s degree or higher | 0.643 | 0.129 | 0.320 | 4.985 | < 0.001 | 0.389 | 0.896 | |
| Black, non-Hispanic | –0.113 | 0.135 | –0.031 | –0.839 | 0.40 | –0.378 | 0.152 | |
| Hispanic | –0.428 | 0.099 | –0.168 | –4.313 | < 0.001 | –0.623 | –0.233 | |
| Other/≥ 2 races, non-Hispanic | –0.336 | 0.134 | –0.094 | –2.515 | 0.01 | –0.598 | –0.074 | |
| Financial fragility | 0.183 | 0.031 | 0.232 | 5.946 | < 0.001 | 0.122 | 0.243 | |
Discussion
This research evaluated a national survey of pet owners in order to understand patterns and differences in ease of access to veterinary care among pet owners. The majority of participants (85.5%) strongly agreed or agreed that they could access veterinary care. However, the remaining 14.5% of participants would translate to an estimated 12.5 million households if these results are generalizable to the 85 million households that own pets in the US.19 Perceived ease of access to the veterinarian was associated with more frequent use, which speaks to the importance of accessibility in veterinary medicine. Those who had the highest ease of access scores took their pet to the veterinarian most often. However, it is not possible to draw a causal conclusion about access and frequency of veterinary use with this correlational data. For example, a person may feel that they can easily access veterinary care but think their pet is healthy and does not need to see a veterinarian on a routine basis. Conversely, an owner with a pet that needs extensive repetitive veterinary care could feel more comfortable navigating the system and therefore think the system is easier to access compared to an owner facing the same barriers to care without repetitive exposure. Future research could explore issues related to owner perception of when they need to access veterinary care and cannot access it as well as how often they visit the veterinarian on a regular basis.
Financial limitations are the most common barrier to receiving veterinary care for low-income families,2 so it is understandable why financial fragility improves the predictive value of the statistical model and why those with more stable income have higher ease of access scores. On average, most pet owners only feel somewhat confident that they could come up with $2,000 if an unexpected need arose, and 21% were not confident at all. Veterinary trips can be a surprise or emergency, and therefore people who do not have a consistent income or emergency funds available may have a more challenging time affording services. Interestingly, while financial fragility was moderately correlated with income in that higher income participants reported more confidence in managing an unexpected expense, the “no confidence” level of fragility existed in every income bracket under $200,000. For example, even in the $150,000 to $174,999 income bracket, 14.9% of participants said they were not confident at all that they could come up with $2,000. This speaks to the ability of all pet owners to afford veterinary care, and while some owners may plan ahead for yearly appointments, unexpected costs could be a barrier to individuals of almost all income brackets.
Many subsidized veterinary service providers use means testing of income or government assistance programs as a way to screen eligible clients; however, given the large population of pet owners who are financially fragile or receiving government assistance, other metrics to measure client need may need to be explored. Among government assistance programs, 48.7% of pet owners receive assistance from at least one program (including social security) and have lower ease of access scores than participants not utilizing programs. Given that almost half of the sample of pet owners received assistance, the need for veterinary services to accommodate a large population of owners who may have limited means is compelling. Interestingly, 12.8% of pet owners received SNAP benefits, which, if generalizable, would mean there are about 10 million SNAP pet-owning households in the US. Our finding is slightly lower than the Access to Care Coalition3 (2018) estimate of 13 million SNAP pet households, which used the total number of SNAP households in the US (about 20.8 million) and applied the 64% pet ownership rate in the US (per the American Pet Products Manufacturers Association).20 Though a close estimate, it could be that pet ownership rates are more nuanced in certain low-income populations and targeted sampling strategies are needed to collect data, which supports findings in Hawes et al.21 Additionally, this survey found that 59.2% of the overall survey respondents owned pets, a figure consistent with the most recent AVMA survey finding of a 56.8% pet ownership rate overall.15
Results also indicated that ease of veterinary access is associated with race and ethnicity, with Hispanic participants not agreeing as much as white participants that they could easily access veterinary care for their pet in their community, regardless of fragility status. Participants of ≥ 2 races/other, non-Hispanic also rated lower ease of access than white participants with the same education level and financial indicators. This could be because historically marginalized communities have experienced care deserts of veterinary practices when compared to affluent or wealthier communities.11 Additionally, use of interpretation and translation services in veterinary medicine is still extremely limited and Spanish-speaking clients are significantly less satisfied with their communication with veterinarians when family and friends are used to interpret instead of bilingual staff.14 This dissatisfaction and lack of access to translation and interpretation services could be one explanation for this study’s findings.
Client education is another common barrier to veterinary care,1 and although this term usually refers to information sharing about animal health and wellness, it could be that pet owners with less formal education have additional difficulty navigating the veterinary health-care system due to low health literacy levels. Education levels are highly correlated with health literacy level, which is “the degree to which individuals have the capacity to obtain, process and understand basic health information and services needed to make appropriate health decisions.”22,23 Many of the human health-care tasks that are difficult for low–health literacy adults, like reading instructions and understanding treatment plans,22,23 could be similar in veterinary medicine. While this study did not measure health literacy levels, future research should explore compounding factors of education, as well as how health literacy could be applied to veterinary medicine.
This study had several limitations, including the undersampling of minority and underrepresented groups, especially because the topic focuses on issues of equity. Additionally, because the race and ethnicity questions were based on Census items, the categories were very narrow and did not allow participants to fully explain how they identify by race or ethnicity (eg, by country of origin rather than Hispanic). Pet owners who may have the most difficulty in accessing veterinary care (eg, vulnerably housed or no internet or phone access) may not have been reached through the panel company sample. Future research needs to focus on broad and diverse sampling strategies that target minority pet owners. Additionally, because only 2 Likert scale questions asked about veterinary access and use, these data did not allow us to assess specific barriers that may make veterinary care more difficult to access for certain people. In the future, research should work to develop a more sophisticated scale to measure veterinary access that can explore why participants feel they cannot easily access animal health care. Finally, while data about participants’ financial status were collected annually via Ipsos’ profile survey, data on access to veterinary care were collected during the spring of 2020; therefore, responses may have been impacted by the emerging COVID-19 pandemic. While participants were not instructed to answer these questions specifically about COVID-19 experiences with veterinary medicine, the start of the pandemic may have impacted their views on access to care.
Veterinary access is crucial to animal, human, and community health. Much like human health care, animal health care has many challenges that are steeped in historical inequity. This study revealed that differences exist between racial or ethnic groups in terms of perceived ease of veterinary access; therefore, more attention needs to be paid to the challenges non-white pet owners may face in receiving care for their pet. In addition, financial fragility is a significant predictor of ease of veterinary access, prevalent among pet owners of almost all income brackets. The cost of veterinary care is a considerable burden, which may be impacting pet owners in a wide range of income brackets. Future studies should examine in what ways veterinary medicine can be more equitable to all pet owners in order to encourage healthier pets and communities.
Acknowledgments
No third-party funding or support was received in connection with this study or the writing or publication of the manuscript. The authors declare that there were no conflicts of interest.
The authors thank the Tufts University Equity Research Group for collaborating on this research project.
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