Factors Associated With COVID-19 Vaccine Acceptance Among Patients Receiving Care at a Federally Qualified Health Center

Abstract

Background:

COVID-19 vaccine hesitancy in the United States is high, with at least 63 million unvaccinated individuals to date. Socioeconomically disadvantaged populations experience lower COVID-19 vaccination rates despite facing a disproportionate COVID-19 burden.

Objective:

To assess the factors associated with COVID-19 vaccine acceptance among under-resourced, adult patients.

Methods:

Participants were patients receiving care at a Federally Qualified Health Center (FQHC) in St. Paul, Minnesota. Data were collected via multiple modes over 2 phases in 2020 (self-administered electronic survey) and 2021 (study team-administered survey by telephone, self-administered written survey) to promote diversity and inclusion for study participation. The primary outcome was COVID-19 vaccine acceptance. Using logistic regression analysis, associations between vaccine acceptance and factors including risk perception, concerns about the COVID-19 vaccine, social determinants of health (SDOH), co-morbidities, pandemic-induced hardships, and stress were assessed by adjusted odds ratios (AORs) and 95% confidence intervals (CI).

Results:

One hundred sixty-eight patients (62.5% female; mean age [SD]: 49.9 [17.4] years; 32% <$20 000 annual household income; 69% <college education) were included in the study. Sixty-one percent of the patients received or were willing to receive the vaccine. Risk perception was positively associated with vaccine acceptance (AOR: 5.3; 95% CI: 2.5, 11.5, P < .001), while concerns about the vaccine (eg, safety, side effects, rapid development of the vaccine, etc.) were negatively associated with vaccine acceptance (all P < .001). SDOH, co-morbidities, pandemic-induced hardships were not associated with vaccine acceptance.

Conclusions:

Our study in a socioeconomically disadvantaged population suggests that risk perception is associated with an increased likelihood of vaccine acceptance, while concerns about the COVID-19 vaccine are associated with a lower likelihood of vaccine acceptance. As these factors could impact vaccine uptake, consistent, innovative, and context-specific risk communication strategies may improve vaccine coverage in this population.

Keywords

underserved communities community health COVID prevention social determinants of health health disparities COVID-19 vaccines vaccine hesitancy Federally Qualified Health Center health promotion

Introduction

At least 1 million people have died from coronavirus disease 2019 (COVID-19) in the United States (U.S.), with more than 5.6 million hospitalizations as of December 2022.¹ Individuals from socioeconomically disadvantaged groups, particularly racial and ethnic minorities, have been disproportionately affected by the COVID-19 pandemic in the U.S.^2-5 According to the Centers for Disease Control and Prevention (CDC), COVID-19 hospitalizations and deaths among African American, American Indian, and Hispanic/Latino people were approximately twice the rates in non-Hispanic White individuals.¹ Individuals from socioeconomically disadvantaged and racial and ethnic minority communities are at the highest risk for infection with SARS-CoV-2 as they are more likely to be essential workers.⁶ This population also had a greater increase in unemployment during the COVID-19 pandemic compared to non-Hispanic White people.⁷ In addition, disruptions in patient care during the pandemic also aggravated health disparities in chronic disease management such as cardiovascular disease (CVD) and related risk factors (eg, diabetes, hypertension, obesity, etc.) among individuals from low-income households.⁸ The exacerbation of the underlying health disparities significantly increased COVID-19 and CVD-related mortality among Black or African American and Hispanic individuals.⁹

The COVID-19 vaccine, first developed in December 2020, is estimated to have prevented 320 000 deaths in the United States.¹⁰ Despite the widely recognized benefits of vaccination and the availability of 4 FDA-approved or authorized COVID-19 vaccines, vaccination rates in medically underserved populations in the U.S. remain low, especially among racial and ethnic minorities (American-Indian, African-American, Native Hawaiian, and Other Pacific Islander and Hispanic).¹ For example, more than 20 million Black or African American individuals have not received a single COVID-19 vaccine.¹ Further, a nationally representative study among Medicare beneficiaries showed that only 44% of individuals with an annual household income of less than $25 000 had received at least 1 dose of the COVID-19 vaccine, compared to 74% among individuals earning $25 000 or more.¹¹ These racial and socioeconomic disparities in vaccination rates lead to poor COVID-19 outcomes.⁴

One of the reasons for disparities in COVID-19 vaccination rates and vaccine-preventable disease burden in the U.S. is vaccine hesitancy.¹² The World Health Organization (WHO) Strategic Advisory Working Group (SAGE) on Vaccine Hesitancy defines vaccine hesitancy as the delay in acceptance or refusal of vaccination despite the availability of vaccination services.¹³ Conversely, vaccine acceptance is the willingness to get vaccinated. Although not a new phenomenon in the U.S.,¹⁴ the ongoing COVID-19 pandemic has unmasked the magnitude of vaccine hesitancy. A systematic review of COVID-19 vaccine hesitancy in the U.S. found that vaccine acceptance rates ranged from 12 to 91.4%, with lower rates recorded among racial and ethnic minorities, low-income households, and non-college-educated individuals.¹⁵ In general, demographic characteristics (eg, gender, race and ethnicity, level of education), social determinants of health (SDOH), trust in science, and concerns about contracting COVID-19 infection or the vaccine itself appear to predict the likelihood of receiving the COVID-19 vaccine among the U.S. population.^16-19 However, knowledge about drivers of COVID-19 vaccine acceptance among individuals from socioeconomically disadvantaged groups is limited. There are only a few studies that have examined factors related to vaccine acceptance among patients receiving care at Federally Qualified Health Centers (FQHCs), which serve predominantly socioeconomically disadvantaged patients.^20-22 However, these studies did not assess key potential influencers on vaccine acceptance, such as SDOH and co-morbidities. Disparities affecting under-resourced communities and the disproportionate impact of the pandemic on this population may also significantly impact short and long-term trends in COVID-19 vaccine acceptance in this population. Therefore, generating more evidence about the drivers of vaccination among these groups is vital for future pandemics.

Our study addresses this gap in the literature by assessing the factors associated with COVID-19 vaccine acceptance among patients receiving care at an FQHC in St. Paul, Minnesota. Factors of interest included risk perception, concerns about the COVID-19 vaccine, SDOH, co-morbidities, and COVID-19 pandemic hardships, which we hypothesized would be associated with lower vaccine acceptance rates.

Methods

Using a community-based participatory research approach,^23,24 a cross-sectional study was conducted among patients receiving care at Open Cities Health Center (OCHC), an FQHC in St. Paul, Minnesota. OCHC serves a population of over 10 000 patients annually in a county estimated to have a vaccine hesitancy rate of 6.74%.²⁵ Participants were recruited from a randomly selected sample of electronic medical records of 1000 patients aged 18 and above receiving care at OCHC. The study received approval from the Mayo Clinic Institutional Review Board (IRB), and all patients provided written or oral IRB-approved informed consent before participating in the study.

Measures

Data were collected via a survey consisting of predominantly closed-ended questions. The survey was developed by the research team using resources obtained from the National Institutes of Health (NIH) Disaster Research Response (DR2) Resources Portal.²⁶ The survey was administered in multiple modes over 2 phases in December 2020 and April 2021. During the first phase, an electronic Qualtrics© survey was distributed via email and text messaging (as available within the electronic health record [EHR]) to patients in the randomly selected sample. If the 2 methods were unavailable or the patient did not respond in 2 weeks, the survey was attempted by telephone or mailed as a hard copy to the patient if no contact was achieved by telephone. No follow-up contact was made after the paper survey was sent. All patients received a mailed US$10 cash card incentive. Survey questions collected data on sociodemographic characteristics, vaccine acceptance, risk perception, concerns about the COVID-19 vaccine, SDOH (education level, income level, race, employment status, occupation, and housing status), and hardships due to the COVID-19 pandemic. Our survey response rate was 22% which is lower than the average online survey response rate of 44%.²⁷ This pattern is consistent with reduced population-level survey response rates observed during the COVID-19 pandemic.²⁸ Survey data were securely stored within Mayo Clinic Survey Research Center servers and de-identified to maintain participant privacy and confidentiality.

Primary Outcome

The primary outcome was vaccine acceptance, defined as patient report of their likelihood of receiving the COVID-19 vaccine. The outcome was measured by asking “If a coronavirus/COVID-19 vaccine is recommended for me, I would get it.” Possible answer choices were “Yes,” “Yes, I already received the coronavirus/COVID-19 vaccine,” “No,” and “Maybe.” For analysis, the outcome was dichotomized to vaccine acceptance (“Yes”/“Yes, I already received the coronavirus/COVID-19 vaccine” versus “No”/“Maybe”).

Independent Variables

Independent variables were risk perception, concerns about the COVID-19 vaccine, SDOH (education level, income level, employment status, occupation, and housing status), co-morbidities, and COVID-19 pandemic hardships (unemployment, stress, etc.).

Risk perception

This variable assessed the degree of concern about contracting COVID-19 on a 4-point scale from “Not at all concerned” to “Extremely concerned.” “Not at all concerned” was categorized as “No” and others as “Yes.”

Concerns about COVID-19 vaccine

Several dimensions of concerns about the vaccine were measured, including: vaccine effectiveness, safety, side effects, how quickly the vaccine was developed, concerns about the vaccine being an experiment on racial and ethnic minority groups, and confusing information from the media and health agencies about the vaccine. Response options for each concern were “Yes”/“No,” and patients were asked to specify when they had a concern not mentioned in the survey.

Social determinants of health

Select items of the Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE) tool were used to collect data on education level, income, employment status, occupation, and housing status.²⁹ A list of 18 occupations⁶ was provided with an option to specify other occupations. The occupations were categorized into essential (ie, health care, other (direct) service, necessary support, transportation) and non-essential.

Co-morbidities

Pre-existing medical conditions among respondents, including diabetes, hypertension, hyperlipidemia, and obesity, were extracted from the EHR using the International Classification of Diseases (ICD)-9/10 codes (see Supplemental Table 1). Current smoking status was also obtained from the most up-to-date social history within the EHR of each patient.

COVID-19 pandemic hardships

COVID-19 pandemic impact on aspects of life of patients, including employment, housing, health insurance, food and utilities affordability, ability to follow healthy lifestyle, and pandemic-induced stress were measured. Items were measured using “Yes/No” response options, except for stress which was assessed on a 10-point scale from “Little or no stress” to “Great deal of stress” and dichotomized as low stress levels (< 5 points) versus high stress levels (≥5 points). Difficulty paying for rent/mortgage, food, utilities, and difficulty following a healthy lifestyle were grouped into a COVID-19 pandemic hardships variable in univariate and multivariable logistic models.

Statistical Analysis

Sample size and power calculations

Given the sample size, the minimum detectable odds ratio (OR) with 80% power at the 5% statistical significance level was 2.5 (or 0.4 for an effect associated with lower odds of vaccine acceptance).

Main analyses

Continuous variables were compared using the Kruskal-Wallis test, and the Chi-square test was used for categorical variables. Logistic regression models were used to examine factors associated with COVID-19 vaccine acceptance. After univariate analyses, multivariable logistic regression analysis was conducted adjusting for age, gender, income group, and race to generate adjusted ORs (AORs) with 95% confidence limits. Covariates were determined a priori as potential confounders, and the inclusion of race and ethnicity was based on findings that vaccine acceptance rates in the U.S. differed by race and ethnicity.^16-18 Self-reported race and ethnicity were used, with few patients identifying as Asian, American Indian/Alaska Native/Native, Hawaiian/Pacific Islander, or multiracial grouped into Other/Multiracial. Patients with missing data were excluded from analyses involving variables with missing data. P-values <.05 were considered statistically significant. All statistical analyses were conducted using SAS version 9.4 (SAS Institute Inc., Cary, NC).

Results

A total of 168 patients completed the survey. The majority (63%) were female and white (44%), with a mean (SD) age of 49.9 (17.4) years (see Table 1). About 31% of patients had at least a college degree and 32% had an annual household income below US$ 20 000. Forty-six percent were employed, with 55% being essential workers. Seventy-three percent of the patients had stable housing. The most common co-morbidity among patients was hypertension (35%), followed by smoking (28%), obesity (27%), hyperlipidemia (23%), and diabetes (20%). No respondent reported a prior COVID-19 diagnosis.

Table 1.

Sociodemographic Characteristics and COVID-19 Vaccine Acceptance Among the Study Participants.

	Total (N = 168)	Vaccine acceptance		P-value
	Total (N = 168)	No (N = 65)	Yes (N = 103)
	N (%)
Sociodemographic characteristics
Age (years), mean (SD)	49.9 (17.42)	45.3 (16.34)	52.8 (17.54)	.01 ^a
Gender				.27^b
Female	105 (62.5)	44 (67.7)	61 (59.2)
Male	63 (37.5)	21 (32.3)	42 (40.8)
Race [n = 167]				.25^b
White	73 (43.7)	25 (38.5)	48 (47.1)
Black	69 (41.3)	32 (49.2)	37 (36.3)
Other/multiracial	25 (15.0)	8 (12.3)	17 (16.7)
Potential factors influencing vaccine acceptance
COVID-19 risk perception	91 (54.2)	21 (32.3)	70 (68.0)	<.0001 ^b
Concerns about the COVID-19 vaccine
Side effects	103 (61.3)	56 (86.2)	47 (45.6)	<.0001 ^b
Was developed quickly	78 (46.4)	48 (73.8)	30 (29.1)	<.0001 ^b
Not safe	76 (45.2)	47 (72.3)	29 (28.2)	<.0001 ^b
COVID-19 information too confusing	66 (39.3)	35 (53.8)	31 (30.1)	.002 ^b
Not effective	61 (36.3)	38 (58.5)	23 (22.3)	<.0001 ^b
Experiment on the racial/ethnic minorities	47 (28.0)	32 (49.2)	15 (14.6)	<.0001 ^b
Multiple concerns about COVID-19 vaccine				<.0001 ^b
<3 concerns	87 (51.8)	16 (24.6)	71 (68.9)
≥3 concerns	81 (48.2)	49 (75.4)	32 (31.1)
Social determinants of health
Occupation				.46^b
Health care	29 (17.3)	9 (13.8)	20 (19.4)
Other (direct) service	37 (22.0)	18 (27.7)	19 (18.4)
Necessary support	18 (10.7)	8 (12.3)	10 (9.7)
Transportation	8 (4.8)	4 (6.2)	4 (3.9)
Other/NA	76 (45.2)	26 (40.0)	50 (48.5)
Essential occupation	92 (54.8)	39 (60.0)	53 (51.5)	.28^b
Work status [n = 166]				.19^b
Employed	77 (46.4)	31 (48.4)	46 (45.1)
Student/stay-at-home/retired	46 (27.7)	13 (20.3)	33 (32.4)
Unemployed	43 (25.9)	20 (31.3)	23 (22.5)
Education [n = 167]				.13^b
High school or less	59 (35.3)	26 (40.0)	33 (32.4)
Some college	57 (34.1)	25 (38.5)	32 (31.4)
College graduate or more	51 (30.5)	14 (21.5)	37 (36.3)
Income Group [n = 140]				.04^b
<$20 000	45 (32.1)	23 (45.1)	22 (24.7)
$20 000-39 000	44 (31.4)	14 (27.5)	30 (33.7)
$40 000-74 000	32 (22.9)	11 (21.6)	21 (23.6)
>$75 000	19 (13.6)	3 (5.9)	16 (18.0)
Housing [n = 150]				.43^b
Stable housing	110 (73.3)	39 (69.6)	71 (75.5)
Unstable housing	40 (26.7)	17 (30.4)	23 (24.5)
Co-morbidities
Hypertension [n = 167]	59 (35.3)	21 (32.8)	38 (36.9)	.59^b
Smoking [n = 153]	43 (28.1)	20 (35.1)	23 (24.0)	.14^b
Obesity (BMI ≥ 30 kg/m²)	46 (27.4)	14 (21.5)	32 (31.1)	.18^b
Hyperlipidemia	38 (22.6)	13 (20.0)	25 (24.3)	.52^b
Diabetes [n = 167]	34 (20.4)	15 (23.1)	19 (18.6)	.49^b
Co-morbidities (≥1 pre-existing health condition)	110 (65.5)	42 (64.6)	68 (66.0)	.85^b
COVID-19 pandemic hardships
Difficulty to follow a healthy lifestyle [n = 166]	114 (68.7)	45 (70.3)	69 (67.6)	.72^b
Difficulty to pay for food and utilities [n = 165]	95 (57.6)	38 (58.5)	57 (57.0)	.85^b
Difficulty to pay rent/mortgage [n = 165]	83 (50.3)	34 (52.3)	49 (49.0)	.68^b
Unemployed/laid off/furloughed due to COVID-19 [n = 85]	31 (36.5)	12 (38.7)	19 (35.2)	.75^b
High stress level due to COVID-19 pandemic (stress level ≥ 5) [n = 167]	140 (83.8)	53 (82.8)	87 (84.5)	.78^b
Number of hardships				.53^b
0	12 (7.1)	5 (7.7)	7 (6.8)
1	27 (16.1)	8 (12.3)	19 (18.4)
2	35 (20.8)	13 (20.0)	22 (21.4)
3	24 (14.3)	11 (16.9)	13 (12.6)
4	56 (33.3)	25 (38.5)	31 (30.1)
5	14 (8.3)	3 (4.6)	11 (10.7)

Kruskal-Wallis P-value.

Chi-Square P-value.

Bold values denote statistical significance at the p < .05 level.

Overall, 54% of the patients reported concerns about contracting COVID-19 infection. The most frequent concerns about COVID-19 vaccine were side effects (61%), rapid vaccine development (46%), and vaccine safety (45%). Sixty-nine percent of patients reported that the COVID-19 pandemic hindered them from following a healthy lifestyle. About 50 and 58% of patients reported that the pandemic impacted their ability to pay rent/mortgage and food/utilities, respectively. A high proportion of respondents (84%) reported a pandemic-induced stress level of at least 5 out of 10.

COVID-19 Vaccine Acceptance

Sixty-one percent (N = 103) of the patients reported previous receipt of the COVID-19 vaccine or an intention to receive it upon recommendation (see Table 1). High proportions of individuals accepting the vaccine were female (59%), White (47%), those with less than a college graduate education level (64%) and essential workers (52%). Compared to the patients who had already received the COVID-19 vaccine or would take it upon recommendation, the mean age of the patients not accepting the vaccine was significantly lower (45.3 [SD 16.34] vs 52.8 [SD 17.54] years; P-value = .01). In unadjusted analyses, African American patients were less likely to accept the vaccine (OR: 0.60; 95% CI: 0.31, 1.18), but this was not statistically significant (see Table 2).

Table 2.

Univariate Logistic Regression Model for Factors Associated With COVID-19 Vaccine Acceptance.

Variable	Odds ratio (95% CI)	P-value
Age	1.03 (1.01, 1.05)	.01
Gender: male	1.44 (0.75, 2.77)	.27
Race
White	1.00 (reference)
Black	0.60 (0.31, 1.18)	.14
Other/multiracial	1.11 (0.42, 2.92)	.84
Potential factors influencing vaccine acceptance
COVID-19 risk perception	4.44 (2.29, 8.64)	<.001
Concerns about the COVID-19 vaccine
Not effective	0.20 (0.10, 0.40)	<.001
Not safe	0.15 (0.08, 0.30)	<.001
Side effects	0.13 (0.06, 0.30)	<.001
Was developed quickly	0.15 (0.07, 0.29)	<.001
Experiment on racial/ethnic minorities	0.18 (0.08, 0.37)	<.001
Confusing information about vaccine	0.37 (0.19, 0.70)	<.001
Social determinants of health
Essential worker occupation	0.71 (0.38, 1.33)	.28
Work status
Student/stay-at-home/retired	1.00 (reference)
Employed	0.58 (0.27, 1.28)	.18
Unemployed	0.45 (0.19, 1.09)	.08
Education
High school or less	1.00 (reference)
Some college	1.01 (0.48, 2.10)	.98
College graduate or more	2.08 (0.93, 4.64)	.07
Income group
<$20K	1.00 (reference)
$20-39K	2.24 (0.95, 5.31)	.07
$40-74K	2.00 (0.78, 5.08)	.15
>$75K	5.58 (1.42, 21.82)	.01
Unstable housing	0.74 (0.34, 1.60)	.44
Co-morbidities (≥1 pre-existing health condition)	1.06 (0.55, 2.04)	.85
COVID-19 pandemic hardships
Unemployed/laid off/furloughed due to COVID 19	0.86 (0.34, 2.14)	.74
High stress level due to COVID-19 pandemic (stress level ≥5)	1.13 (0.49, 2.61)	.78
≥1 COVID-19 pandemic hardships (rent/mortgage, food, utilities, following a healthy lifestyle)	0.74 (0.34, 1.60)	.44

Bold values denote statistical significance at the p < .05 level.

Factor Associations With COVID-19 Vaccine Acceptance

COVID-19 risk perception

Respondents concerned with contracting the SARS-CoV-2 virus (AOR: 5.32; 95% CI: 2.48, 11.45) were more likely to accept the vaccine than those who were not (see Figure 1 and Supplemental Table 2).

Figure 1.

Multivariable logistic regression model for factors associated with COVID-19 vaccine acceptance.

Concerns about the COVID-19 vaccine

Overall, concerns about the COVID-19 vaccine were significantly associated with a decreased likelihood of vaccine acceptance. Compared with patients who did not have the concerns, those who expressed their concern about effectiveness of the COVID-19 vaccine (AOR: 0.17; 95% CI: 0.08, 0.37), vaccine safety (AOR: 0.10; 95% CI: 0.04, 0.24), or side effects (AOR: 0.13; 95% CI: 0.05, 0.31) were less likely to accept the vaccine. Similarly, concerns about the rapid development of the vaccine (AOR: 0.11; 95% CI: 0.05, 0.25), the vaccine being an experiment on racial and ethnic minority groups (AOR: 0.15; 95% CI: 0.06, 0.37), and confusing information from the media and health agencies about the vaccine (AOR: 0.29; 95% CI: 0.14, 0.60) were associated with lower odds of vaccine acceptance.

SDOH

When compared to incomes of <$20 000, having an income of >$75 000 (OR: 5.58; 95% CI: 1.42, 21.82) was associated with vaccine acceptance in the univariate analysis (See Table 2). Occupation, employment status, education level, and housing situation were not associated with vaccine acceptance in univariate or adjusted models.

COVID-19 pandemic hardships

Report of experiencing hardships due to the COVID-19 pandemic was not associated with vaccine acceptance. Pandemic-induced stress level, employment issues (eg, becoming unemployed, laid off, or furloughed), and 1 or more pandemic hardships from other factors (eg, difficulty affording housing, food/utilities) did not impact the likelihood of accepting the COVID-19 vaccine.

Co-morbidities

No individual co-morbidity (hypertension, obesity, smoking, hyperlipidemia, diabetes) was associated with vaccine acceptance. This lack of association persisted when these co-morbidities were grouped together as having at least 1 co-morbidity compared to having none of these co-morbidities.

Discussion

In this study of individuals from socioeconomically disadvantaged backgrounds receiving care at an FQHC, COVID-19 vaccine acceptance was significantly associated with COVID-19 risk perception and concerns about the COVID-19 vaccine. Patients with concerns about vaccine safety were least likely to accept the vaccine. Inconsistency in COVID-19 information during the pandemic appeared to influence vaccine acceptance in this population. These findings suggest that lack of knowledge about the vaccine, in conjunction with widespread misinformation and disinformation about the COVID-19 pandemic, may drive vaccine hesitancy. Additionally, our findings stress the importance of continuous engagement with the community via innovative context-specific and culturally tailored science communication in public health responses. Conversely, our study did not find statistically significant associations between vaccine acceptance and pre-existing co-morbidities or social factors, including COVID-19-related hardships.

Our findings are supported by existing evidence linking subjective COVID-19 susceptibility perception by individuals with concerns about the vaccine and vaccine hesitancy. In a study including a predominance of individuals living under the federal poverty level and racial and ethnic minorities, those perceiving susceptibility to COVID-19 were more likely to get vaccinated compared to those who did not feel that they were susceptible.¹⁶ Nguyen and colleagues¹⁸ found that among the reasons for not getting vaccinated, concerns about vaccine side effects and effectiveness were significantly higher in racial and ethnic minority groups (African American, Latinx, and Asian adults) compared to non-Hispanic White adults. While these findings are similar, our study assessed additional concerns about the vaccine (rapid development of the vaccine, concerns about experimenting on racial and ethnic minorities, and confusing vaccine information), which were associated with vaccine acceptance. These observations suggest that any concern about the vaccine is highly likely to influence the decision to receive the COVID-19 vaccine among underserved populations. More importantly, the predominance of statistically significant vaccine safety-related findings suggests that concerns about vaccine safety and processes may play a considerably more critical role in vaccine hesitancy compared to other factors such as SDOH and co-morbidities. Our findings may be explained by an underlying mistrust in government authorities and the pharmaceutical industry^30,31 which worsened during the pandemic due to misinformation and disinformation linked with political partisanship and religious beliefs.^16,19 Co-designing science communication messaging with the community may assist in addressing the mistrust towards vaccines, health institutions, and public health agencies.

Studies on vaccine acceptance across the U.S. have yielded mixed results on the association between SDOH, having pre-existing co-morbidities and the likelihood or willingness to receive the COVID-19 vaccine. In a longitudinal study, willingness to get vaccinated was positively associated with higher income status and education level.³² While Viswanath and colleagues¹⁶ found a significant association between vaccine acceptance and higher income status and education level, they did not find this association with employment status. On the contrary, a nationally representative study found that education level and type of employment were not associated with vaccine acceptance.³³ The lack of association with social factors may be related to similarities in social circumstances within our study population. Regarding the relationship between having chronic conditions and vaccine acceptance, a study examining the association between having multiple co-morbidities (including obesity, hypertension, diabetes, and smoking) and COVID-19 vaccine acceptance found that having ≥5 pre-existing conditions predicted vaccine intent.¹⁷ Conversely, two studies reported that having at least 1 chronic disease, including 2 conditions examined in our study (diabetes and hypertension), predicted vaccination intention.^32,34

The divergence in these findings may be due to the differences in the populations. In contrast to other similar studies probing vaccine acceptance, our study sampled patients of lower socioeconomic status with limited access to healthcare resources. Therefore, these findings on the association between SDOH and having co-morbidities and COVID-19 vaccine acceptance suggests that the decision to get vaccinated in this population is mainly influenced by their level of knowledge regarding vaccines. For instance, a nationally representative survey³⁵ showed that 39 to 41% of Black and Latinx individuals had inadequate knowledge about how vaccines are developed and tested. The lack of knowledge may explain a significant number of racial and ethnic minorities in the undecided group of vaccine-hesitant individuals,³⁶ signaling uncertainty caused by the lack of COVID-19 information. There has been a remarkable decline in COVID-19 vaccine hesitancy among African American people throughout the pandemic, surpassing declines in non-Hispanic White people.³⁷ These differences may be attributed to the ongoing COVID-19 communication efforts across the U.S. prioritizing racial and ethnic minority groups given the devastating COVID-19 outcomes in these groups.^38,39 This underscores the importance of improving access to knowledge in resource-limited communities. Interestingly, vaccine hesitancy in our study sample was considerably higher than the estimated hesitancy rate in the county served by OCHC, Ramsey County (38.7 vs 6.7%). The observed discrepancy may be explained by the difference in the study populations and the methodology used in the 2 studies. The county estimates were obtained via predictive models utilizing data gathered in the Household Pulse Survey (HPS),⁴⁰ which sampled a sociodemographically distinct population (eg, higher education status compared to our sample). In addition, the HPS reports remarkably low survey response rates, increasing the likelihood of response bias.

To our knowledge, this is the first study to assess the association between pandemic-related challenges faced by individuals from groups that are socioeconomically disadvantaged and their vaccine acceptance. While our study did not find a significant association between pandemic-induced hardships and vaccine acceptance, caution should be exercised when interpreting this finding, as the pandemic is ongoing and may have long-term effects on vaccine acceptance trends in this population. In addition, an unequitable distribution of post-pandemic recovery efforts may give rise to antivaccination attitudes in this population.

Implications for Population Health and Public Health Practice

Our study has several potential implications. Specifically, our study builds on the evidence of factors that impact COVID-19 vaccine uptake and coverage among medically underserved populations. The concerns associated with lower vaccine acceptance in this study could inform the content design of future communication strategies targeted at increasing vaccine uptake, including sustaining vaccination series with boosters, among socioeconomically disadvantaged populations receiving care at FQHCs. Public health authorities and healthcare professionals should also ensure the communication of clear, consistent, and unambiguous information to the public. In addition, communicating measures taken by US regulatory agencies to prevent unethical research and medical practices to patients may help dissipate existing concerns about events similar to the U.S. Public Health Service Tuskegee Study of Untreated Syphilis in the Negro Male occurring again.⁴¹ Sustainable and innovative approaches should be directed towards working with marginalized communities to disseminate reliable and culturally relevant health information to improve the impact of health crisis mitigation efforts in future pandemics. Similar academic-community-government efforts leveraging culturally tailored messages to reduce the impact of the COVID-19 pandemic among communities served by FQHCs are warranted.^24,42 In addition, social media platforms should be considered to improve risk perception among young adults who are less likely to receive the COVID-19 vaccine.

Moreover, our study underlines the importance of approaching vaccine hesitancy from a health equity perspective. Overlooking the hardships caused by the pandemic in this population may exacerbate distrust in healthcare systems and federal agencies and worsen vaccine hesitancy. Therefore, efforts to increase vaccine coverage in socioeconomically disadvantaged and racial and ethnic minority populations should be accompanied by measures to improve other non-vaccine-related health services and individual-level needs (such as chronic disease management, housing, food, and utilities, etc.) impacted by the COVID-19 pandemic. Larger longitudinal studies are needed to assess changes in the determinants of COVID-19 vaccine acceptance among socioeconomically disadvantaged groups.

Strengths

To the best of our knowledge, our study is one of the first comprehensive studies assessing vaccine acceptance among patients receiving care at an FQHC. In addition, our study is unique in that it examined the association between pandemic-induced hardships and vaccine acceptance. Lastly, this study employed several data collection methods (ie, via digital technology, telephones) to meet the individual needs and preferences of patients to foster diversity and inclusion in health services research.

Limitations

Our study has limitations worth noting. It is a cross-sectional study, which may not account for temporal changes in COVID-19 vaccine acceptance, considering the rapidly changing nature of the pandemic. However, limited evidence of drivers of vaccine acceptance in such a vulnerable population makes this study necessary and subsequent longitudinal studies may build on our findings. In addition, our study sample was predominantly White and African American and lacked a significant inclusion of other racial and ethnic groups. Further, we recognize that our sample may not be representative of all medically underserved populations across the U.S., limiting the generalizability of our findings. Nevertheless, our study provides additional evidence to inform interventions to address COVID-19 vaccine hesitancy in an understudied group with a high adverse SDOH burden. Lastly, simultaneous testing of several hypotheses increases the likelihood of false significant findings. However, the predominance of statistically significant results with very low P-values (≤.01) reduces the likelihood that our findings are attributed to multiple testing.

Conclusion

Our study suggests that risk perception is associated with an increased likelihood of vaccine acceptance, while concerns about the COVID-19 vaccine are associated with a decreased likelihood of vaccine acceptance among patients receiving care at an FQHC. Efforts to increase COVID-19 vaccine coverage in underserved populations should consider integrating context-specific communication strategies to address these factors.

Supplemental Material

sj-docx-1-jpc-10.1177_21501319231181881 – Supplemental material for Factors Associated With COVID-19 Vaccine Acceptance Among Patients Receiving Care at a Federally Qualified Health Center

Supplemental material, sj-docx-1-jpc-10.1177_21501319231181881 for Factors Associated With COVID-19 Vaccine Acceptance Among Patients Receiving Care at a Federally Qualified Health Center by Mathias Lalika, Cynthia Woods, Aarti Patel, Christopher Scott, Alexander Lee, Jennifer Weis, Clarence Jones, Adeline Abbenyi, Tabetha A. Brockman, Irene G. Sia, Richard O. White, Chyke A. Doubeni and LaPrincess C. Brewer in Journal of Primary Care & Community Health

Footnotes

Acknowledgements

We would like to thank the FAITH! Community Steering Committee members for their input and support of this study. Similarly, we thank the staff at Open Cities Health Center for working tirelessly to provide care to patients during the COVID-19 pandemic. Lastly, we thank the patients who were willing to participate in this study despite the challenging times of a global public health crisis.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This article was supported by the Clinical and Translational Science Awards (CTSA; grant no. UL1 TR000135) from the National Center for Advancing Translational Science (NCATS) to Mayo Clinic and the Mayo Clinic Center for Health Equity and Community Engagement Research. The corresponding author was supported by the American Heart Association-Amos Medical Faculty Development Program (grant no. 19AMFDP35040005), NCATS (CTSA grant no. KL2 TR002379), the National Institutes of Health (NIH) National Institute on Minority Health and Health Disparities (grant no. 1 R21 MD013490-01), and the Centers for Disease Control and Prevention (CDC; grant no. CDC-DP18-1817) during the implementation of this work. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NCATS, NIH, or CDC. The funding bodies had no role in study design; in the collection, analysis, and interpretation of data; writing of the manuscript; and in the decision to submit the manuscript for publication.

ORCID iDs

Mathias Lalika

LaPrincess C Brewer

Supplemental Material

Supplemental material for this article is available online.

References

CDC. COVID data tracker. 2023. Accessed April 8, 2023. https://covid.cdc.gov/covid-data-tracker/#datatracker-home

Yancy

CW.

COVID-19 and African Americans. JAMA. 2020;323(19):1891-1892. doi:10.1001/jama.2020.6548

Cooper

Williams

DR.

Excess deaths from COVID-19, community bereavement, and restorative justice for communities of color. JAMA. 2020;324(15):1491-1492. doi:10.1001/jama.2020.19567

Abedi

Olulana

Avula

, et al. Racial, economic, and health inequality and COVID-19 infection in the United States. J Racial Ethn Health Disparities. 2021;8(3):732-742. doi:10.1007/s40615-020-00833-4

Shortreed

Gray

Akosile

, et al. Increased COVID-19 infection risk drives racial and ethnic disparities in severe COVID-19 outcomes. J Racial Ethn Health Disparities. 2023;10(1):149-159. doi:10.1007/s40615-021-01205-2

Rogers

VanSant-Webb

Yan

Qeadan

Racial disparities in COVID-19 mortality among essential workers in the United States. World Med Health Policy. 2020;12(3):311-327. doi:10.1002/wmh3.358

US Bureau of Labor Statistics. Unemployment rate rises to record high 14.7 percent in April 2020. May 13, 2020. Accessed April 8, 2023. https://www.bls.gov/opub/ted/2020/unemployment-rate-rises-to-record-high-14-point-7-percent-in-april-2020.htm

Gettler

Stern

, et al. Disruption of medical care among individuals in the southeastern United States during the COVID-19 pandemic. J Public Health Res. 2021;11(1):2497. doi:10.4081/jphr.2021.2497

Rodriguez

Solomon

de Lemos

, et al. Racial and ethnic differences in presentation and outcomes for patients hospitalized With COVID-19: findings from the American Heart Association’s COVID-19 cardiovascular disease registry. Circulation. 2021;143(24):2332-2342. doi:10.1161/circulationaha.120.052278

10.

Global Epidemics. Vaccine preventable deaths analysis. 2022. Accessed April 8, 2023. https://globalepidemics.org/vaccinations/

11.

Cheng

Racial and ethnic and income disparities in COVID-19 vaccination among Medicare beneficiaries. J Am Geriatr Soc. 2022;70(9):2638-2645. doi:10.1111/jgs.17920

12.

Olson

Berry

Kumar

Addressing parental vaccine hesitancy towards childhood vaccines in the United States: a systematic literature review of communication interventions and strategies. Vaccines (Basel). 2020;8(4):590. doi:10.3390/vaccines8040590

13.

MacDonald

NE.

Vaccine hesitancy: definition, scope and determinants. Vaccine. 2015;33(34):4161-4164. doi:10.1016/j.vaccine.2015.04.036

14.

Phadke

Bednarczyk

Salmon

Omer

SB.

Association between vaccine refusal and vaccine-preventable diseases in the United States: a review of measles and pertussis. JAMA. 2016;315(11):1149-1158. doi:10.1001/jama.2016.1353

15.

Yasmin

Najeeb

Moeed

, et al. COVID-19 Vaccine hesitancy in the United States: a systematic review. Front Public Health. 2021;9:770985. doi:10.3389/fpubh.2021.770985

16.

Viswanath

Bekalu

Dhawan

Pinnamaneni

Lang

McLoud

Individual and social determinants of COVID-19 vaccine uptake. BMC Public Health. 2021;21(1):818. doi:10.1186/s12889-021-10862-1

17.

Ruiz

Bell

RA.

Predictors of intention to vaccinate against COVID-19: results of a nationwide survey. Vaccine. 2021;39(7):1080-1086. doi:10.1016/j.vaccine.2021.01.010

18.

Nguyen

Anneser

Toppo

Allen

Scott Parott

Corlin

Disparities in national and state estimates of COVID-19 vaccination receipt and intent to vaccinate by race/ethnicity, income, and age group among adults ≥ 18 years, United States. Vaccine. 2022;40(1):107-113. doi:10.1016/j.vaccine.2021.11.040

19.

Rich-Edwards

Rocheleau

Ding

, et al. COVID-19 vaccine uptake and factors affecting hesitancy among US nurses, March–June 2021. Am J Public Health. 2022;112(11): 1620-1629. doi:10.2105/AJPH.2022.307050

20.

Amundson

Sias

Frietze

GA.

Perceptions of COVID-19 vaccines in a predominantly Hispanic patient population from the Texas-Mexico border. J Am Pharm Assoc. 2022; 62(4s):S17-S21.e2. doi:10.1016/j.japh.2021.11.003

21.

Bloom

Verma

Ram

, et al. COVID-19 vaccine concerns and acceptability by language in a marginalized population in Rhode Island. J Prim Care Community Health. 2021;12: 21501327211058976. doi:10.1177/21501327211058976

22.

Kuhn

Henwood

Lawton

, et al. COVID-19 vaccine access and attitudes among people experiencing homelessness from pilot mobile phone survey in Los Angeles, CA. PLoS One. 2021;16(7):e0255246. doi:10.1371/journal.pone.0255246

23.

Israel

Coombe

Cheezum

, et al. Community-based participatory research: a capacity-building approach for policy advocacy aimed at eliminating health disparities. Am J Public Health. 2010;100(11):2094-2102. doi:10.2105/ajph.2009.170506

24.

Brewer

Woods

Patel

, et al. Establishing a SARS-CoV-2 (COVID-19) drive-through collection site: a community-based participatory research partnership with a federally qualified health center. Am J Public Health. 2021;111(4):658-662. doi:10.2105/ajph.2020.306097

25.

CDC. Estimates of vaccine hesitancy for COVID-19. 2021. Accessed April 8, 2023. https://data.cdc.gov/stories/s/Vaccine-Hesitancy-for-COVID-19/cnd2-a6zw/

26.

NIH. Disaster Research Response (DR2) resources portal. 2020. Accessed April 8, 2023. https://tools.niehs.nih.gov/dr2/

27.

M-J

Zhao

Fils-Aime

Response rates of online surveys in published research: a meta-analysis. Comput Hum Behav Rep. 2022;7:100206. doi:https://doi.org/10.1016/j.chbr.2022.100206

28.

Krieger

LeBlanc

Waterman

Reisner

Testa

Chen

JT.

Decreasing survey response rates in the time of COVID-19: implications for analyses of population health and health inequities. Am J Public Health. 2023;113(6): 667-670. doi:10.2105/ajph.2023.307267

29.

National Association of Community Health Centers. PRAPARE implementation and action toolkit. 2016. Accessed April 8, 2023. https://nachc.org/wp-content/uploads/2019/01/PRAPARE-SDH-Risk-Tally-Score-Methodology.pdf

30.

Latkin

Dayton

Konstantopoulos

Boodram

Trust in a COVID-19 vaccine in the U.S.: a social-ecological perspective. Soc Sci Med. 2021;270:113684. doi:10.1016/j.socscimed.2021.113684

31.

Thompson

Manning

Mitchell

, et al. Factors associated with racial/ethnic group-based medical mistrust and perspectives on COVID-19 vaccine trial participation and vaccine uptake in the US. JAMA Netw Open. 2021;4(5):e2111629. doi:10.1001/jamanetworkopen.2021.11629

32.

Daly

Robinson

Willingness to vaccinate against COVID-19 in the U.S.: representative longitudinal evidence from April to October 2020. Am J Prev Med. 2021;60(6):766-773. doi:10.1016/j.amepre.2021.01.008

33.

Savoia

Piltch-Loeb

Goldberg

, et al. Predictors of COVID-19 vaccine hesitancy: socio-demographics, co-morbidity, and past experience of racial discrimination. Vaccines (Basel). 2021;9(7):767. doi:10.3390/vaccines9070767

34.

Trent

Seale

Chughtai

Salmon

MacIntyre

CR.

Trust in government, intention to vaccinate and COVID-19 vaccine hesitancy: a comparative survey of five large cities in the United States, United Kingdom, and Australia. Vaccine. 2022;40(17):2498-2505. doi:10.1016/j.vaccine.2021.06.048

35.

COVID Collaborative. Coronavirus vaccine hesitancy in Black and Latinx communities. November 23, 2020. Accessed April 8, 2023. https://www.covidcollaborative.us/resources/coronavirus-vaccine-hesitancy-in-black-and-latinx-communities

36.

KFF. KFF COVID-19 vaccine monitor: February 2021. February 26, 2021. Accessed April 8, 2023. https://www.kff.org/coronavirus-covid-19/poll-finding/kff-covid-19-vaccine-monitor-february-2021/

37.

Padamsee

Bond

Dixon

, et al. Changes in COVID-19 vaccine hesitancy among Black and White individuals in the US. JAMA Netw Open. 2022;5(1):e2144470. doi:10.1001/jamanetworkopen.2021.44470

38.

National Institutes of Health. NIH community engagement alliance (CEAL). 2022. Accessed April 8, 2023. https://covid19community.nih.gov/

39.

White House. Press Briefings by White House COVID-19 Response Team and Public Health Officials. Spetember 6, 2022. Accessed April 8, 2023. https://www.whitehouse.gov/briefing-room/press-briefings/2022/09/06/press-briefing-by-white-house-covid-19-response-team-and-public-health-officials-88/

40.

Centers for Disease Control and Prevention National Center for Health Statistics. Reduced access to care: household pulse survey. July 20, 2022. Accessed May 16, 2023. https://www.cdc.gov/nchs/covid19/pulse/reduced-access-to-care.htm

41.

Ad Council. Tuskegee legacy stories | COVID-19 vaccine education initiative | Ad council. June 30, 2021. Accessed April 8, 2023. https://www.youtube.com/watch?v=B0Vb7O121_8

42.

Joseph

Glover

Olayiwola

, et al. Mask up: academic-community-government partnerships to advance public health during COVID-19. Popul Health Manag. 2021;24(4):430-432. doi:10.1089/pop.2020.0305

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB