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Abstract

Objective:

COVID-19 disproportionally affected Hispanic/Latinx populations exacerbating systemic health inequities. The pilot study aimed to explore barriers to COVID-19 vaccination across Hispanic/Latinx communities in Southern California.

Methods:

Cross-sectional survey of 200 participants to identify common barriers to vaccine hesitancy among Hispanics/Latinx individuals in Southern California utilizing a 14-item survey and questionnaire in English and Spanish.

Results:

Of the 200 participants that completed questionnaires, 37% identified a knowledge deficit, 8% identified misinformation, and 15% identified additional barriers such as awaiting appointments, immigration status, transportation issues, or religious reasons as barriers to not receiving the COVID-19 vaccine. Wald statistics denoted that household members with COVID-19 infection within the past 3 months saw a medical provider within the last year, wearing a mask in public often, and barriers to vaccination (not knowing enough about the vaccine) predicted vaccine. These variables indicated changes in the likelihood of obtaining vaccination.

Conclusion:

The most crucial factor for increasing vaccination rates was directly reaching out to the community and actively conducting surveys to address the barriers and concerns encountered by Hispanic/Latinx participants.

Keywords

COVID-19 COVID-19 vaccination vaccine barriers vaccine hesitancy Hispanic/Latinx vaccine misinformation

Introduction

The coronavirus pandemic of 2019 (COVID-19) highlighted severe public health issues worldwide.¹ In the United States, the pandemic exacerbated stark inequalities suffered by underserved communities, including Hispanics/Latinx.^2-4 Thus, demonstrating the detrimental effects of health inequality and social determinants of health (SDOH) that continue to plague people of color.⁵ Many grassroots organizations in the United States continue vaccination programs designed to go directly to communities affected and provide services, including education and vaccination. Besides the multicomponent community strategies backed by elected officials at all levels of the government, there was still a gap in COVID-19 vaccinations, including in Hispanic/Latinx communities.⁶

Moore¹ stressed the role of health inequities and longstanding SDOH as causal factors associated with outcomes related to COVID-19 and its harmful effect on Hispanic/Latinx communities. The Centers for Disease Control and Prevention⁷ defined Health Equity as “The opportunity for each person to attain their full health potential regardless of social position or socially determined circumstances” (para. 1). On the other hand, The World Health Organization⁸ defined SDOH as “Conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems, such as social norms and policies, that shape the conditions of daily life” (para. 1). Examples of SDOH include (a) safe housing, (b) racism, (c) discrimination, (d) pollution, (e) access to education and jobs, (f) access to health care and nutritious foods, and (g) language and literacy skills.²

Macias Gil et al.⁴ argued that health inequities plaguing communities of color had been documented since the founding of the colonial United States while further exacerbated by historical and contemporary SDOH. Thus, Cuellar et al.² proposed that Hispanics/Latinx came into the pandemic disenfranchised while experiencing increased risks of SDOH exacerbated by years of social inequalities. Consequently, Hispanics/Latinx have a higher burden of poverty with a rate of 14.9% compared to 9.6% among Non-Hispanic Whites, high risk of comorbid conditions (including obesity, kidney disease, and heart disease), crowded housing, and lack of access to health care due to immigration status or lack of resources.^2,4,9 Moreover, Hispanic/Latinx have the lowest medical insurance coverage rates, with 19.8% of individuals uninsured compared to 5.4% of non-Hispanic Whites; therefore, preventing Latinx from accessing preventative and primary care that could preclude or treat comorbid conditions associated with COVID-19 outcomes.^2,4 Extant study on COVID-19 vaccine barriers and hesitancy in Hispanic/Latinx communities was limited or nonexistent when this study was conducted. This study aims to explore barriers to COVID-19 vaccination across Hispanic/Latinx communities in Southern California.

Methods

Study Design

A cross-sectional survey study explored barriers to COVID-19 vaccination across Hispanics/Latinx in Southern California. The data collection was conducted during the peak of COVID-19 from March to December 2021. The primary outcomes were participants’ barriers to the COVID-19 vaccine and self-reported demographic information.

Participants

A convenience sample of participants was included in the pilot study (n = 200). The 10-month data collection period provided a sufficient sample size to examine preliminary findings regarding barriers to COVID-19 vaccinations. The participants were recruited from 4 community events in 3 different cities after receiving approval from the university Institutional Review Board and the event organizers. The participants were recruited in the Southern California community, a large urban setting with diverse populations, where 34.8% are Hispanic/Latinx. The cities where participants were recruited were selected for their large Hispanic/Latinx populations (54%, 60.3%, and 90.5%).^10-12

Survey

The predominantly Hispanic/Latinx community participants were asked to complete a demographic survey and questionnaire (See Appendix A). The 14-item survey and questionnaire included sociodemographic questions (eg, “Besides yourself, how many people live in your household?”), COVID-19 knowledge questions (eg, “I understand how to protect myself and others from contracting COVID-19?” Strongly Agree, Agree, Neutral, Disagree, and Strongly disagree), health maintenance questions (eg, “Have you had the flu shot this season 2020-2021”), and barriers to COVID-19 vaccination questions (eg, If offered to you, would you get the COVID-19 vaccine?). The questionnaires were available in English and Spanish and inquired about the participants’ COVID-19 knowledge, health maintenance, and barriers toward the COVID-19 vaccine. Each questionnaire was identical and compliant with the Health Insurance Portability and Accountability Act of 1996 (HIPPA). Sensitive participant identifiers were not collected except for age and ethnicity; no information was collected from minors under 18. Details of the study were provided to participants; assurances were given about the voluntary nature of their participation. Verbal informed consent was obtained from participants. Confidentiality of the collected data was maintained.

Data Analysis

A descriptive analysis was conducted to describe select sociodemographics, COVID-19 knowledge, barriers to the COVID-19 vaccine, health maintenance, and likelihood of COVID-19 vaccination. A sample size of 200 participants was considered adequate to detect a moderate effect size (d = 0.32) using a 2-tailed significance test with a power of .80, a significance level of .05, and ten factors.^13,14 Prevalence of intent to get the COVID-19 vaccine among Hispanics/Latinx in the current study was 70% (n = 140). All statistical analysis was performed using IBM SPSS Statistics, software version 28.0.

Pearson r was performed for continuous data to test relationships among independent variables. Spearman’s rho, Chi-square, and Kruskal Wallis H tests were conducted for categorical data to test relationships among independent and dependent variables. Finally, logistic regression was used to describe the likelihood of vaccination as it accounted for select sociodemographics, COVID knowledge, health maintenance, and barriers to the COVID-19 vaccine. The study was approved by the university Institutional Review Board (#2021370).

Results

A total of 200 participants completed the survey with a response rate of 100%. Table 1 shows the participants’ demographics, with a mean age of 49.4 ± 16.4 and a mean household size was 3.05 ± 1.6. Of the 200 participants that completed questionnaires, 37% identified a knowledge deficit (not knowing enough about the vaccine and where and how to sign up for the vaccine), 8% identified misinformation (being told the vaccine is dangerous or not to get the vaccine), and 15% identified additional barriers such as awaiting appointments, immigration status, transportation issues, or religious reasons as barriers to not receiving the COVID-19 vaccine (Table 2). The descriptive analysis allows us to determine the data distribution, means, and standard deviations that assist in conducting inferential statistics.

Table 1.

Participants Self-reported Demographics (n = 200).

Characteristic	M (±SD)
Age	49.4 (±16.4)
Household size	3.05 (±1.6)
	n (%)
Living with a household member older than 65	87 (43.5)
COVID-19 Infection for the past 3 months	77 (38.5)
Household member older than 65 with COVID-19 infection in the past 3 months	64 (32.0)
Visit with a medical provider within the last year	116 (58.0)
Flu Shot 2020-2021	75 (37.5)
Comorbidities
Diabetes	24 (12.0)
Hypertension	32 (16.0)
Kidney disease	5 (2.5)
Obesity	13 (6.5)
Other	2 (1.0)

Abbreviations: M, mean; SD, standard deviation.

Table 2.

Descriptive Analysis of Participants Self-reported Response to COVID-19 Attitude, Knowledge, and Barriers (n = 200).

Variable	n (%)
Knowledge^*
I understand how to protect yourself and others from contracting COVID-19	167 (83.5)
I understand the current rules on quarantining after being expose to COVID-19	168 (84)
Attitude^†
When in public, how often do you wear a mask?	145 (72.5)
If offered to you, would you get the COVID-19 vaccine?
Yes	140 (70.0)
No	58 (29.0)
Are there any barriers that would prevent you from getting the vaccine?
Lack of transportation	3 (1.5)
I don’t know enough about the vaccine	11 (5.5)
I don’t know where and how to sign up for the vaccine	63 (31.5)
Someone told me that the vaccine is dangerous	13 (6.5)
My relative/friend told me I should not get it	4 (1.5)
Other (eg, government conspiracy, religion, recent COVID-19 infection, fear, language barrier, news/media, insurance, etc.)	30 (15.0)

Knowledge questions on a 1 to 5 Likert scale (strongly agree, agree, neutral, disagree, strongly disagree).

†

Attitude questions on a 1 to 5 Likert scale (always, often, sometimes, rarely, never).

Further analysis was conducted to test relationships between the independent and dependent variables (Table 3). There was a negative correlation between age and living with a household member older than 65 (r = −.21, P = .003). The results indicated that knowledge about COVID-19 and the risk (intent) of getting vaccinated were significantly correlated. In this sample, knowledge of how to protect self against COVID-19 (P = .002), knowledge of the current quarantine rules (P < .001), and mask-wearing (P < .001) decreased the possibility of getting vaccinated. The participants who saw a medical provider within the last year were more likely to get the COVID-19 vaccine (χ² = 7.04, P = .008; Table 4); 78.1% (n = 89) indicated they would get a COVID-19 vaccine, and only 21.9% (n = 25) would not. The reason(s) why participants were prevented from getting the vaccine was also statistically significant (χ² = 34.8, P < .001). For example, participants who were told the vaccine was dangerous (76.9%, n = 10) indicated they would not get the vaccine, and only 23.1% (n = 3) would (Table 4). Notably, the majority of participants would get the COVID-19 vaccine if it was offered to them, despite the reported barriers (Table 4). Furthermore, contracting COVID-19 within the past 3 months (χ² = 19.5, P < .001) and household members contracting COVID-19 within the same time frame (χ² = 13.3, P < .001) were statistically significant. Eighty-two percent (n = 100) of participants who had not tested positive for COVID-19 infection 3 months before data collection indicated they would get the vaccine, and only 18% (n = 22) would not. Similarly, 78.7% (n = 107) of participants with household members who had not tested positive for COVID-19 infection indicated they would get the vaccine, and only 21.3% (n = 29) would not (Table 4).

Table 3.

Correlational Analysis With COVID-19 Vaccination Hesitancy (n = 198).

Characteristic	r	P-value
Age and living with a household member older than 65 years	−.208	.003
	U	P-value
Age	4811.0	.041
Household size	4184.5	.667
	r _s	P-value
Knowledge: Protecting self against COVID-19^*	−.222	.002
Knowledge: Quarantine rules after exposure^*	−.262	<.001
Attitude: Mask-wearing^†	−.267	<.001

For continuous data, P-values are Pearson r (2-sided). For categorical data, P-values are Mann-Whitney U or Spearman’s rho (2-sided).

Knowledge questions on a 1 to 5 Likert scale (strongly agree, agree, neutral, disagree, strongly disagree).

†

Attitude questions on a 1 to 5 Likert scale (always, often, sometimes, rarely, never).

Table 4.

Prevalence of Health Maintenance, Comorbidities, Barriers to Vaccination and COVID-19 Exposure by Vaccination Hesitancy (n = 198).

	Would get vaccine		Would not get vaccine
Characteristic	n	%	n	%	χ²	P-value
Visit with a medical provider within the last year					7.03	.008
Yes	89	78.1	51	60.7
No	25	21.9	33	39.3
Issues making an appointment due to COVID-19					0.48	.489
Yes	38	74.5	102	69.4
No	13	25.5	45	30.6
Flu vaccine 2020-2021					0.29	.588
Yes	54	73.0	86	69.4
No	20	27.0	38	30.6
Comorbidities					5.81	.214
Diabetes	17	70.8	7	29.2
Hypertension	22	71.0	9	29.0
Kidney Disease	4	80.0	1	20.0
Obesity	7	53.8	6	46.2
Other	0	0.0	2	100.0
Barriers to COVID-19 vaccination					34.82	<.001
Lack of transportation	2	66.7	1	33.3
Not enough information	7	63.6	4	36.4
Don’t know where/how to get it	58	95.1	3	4.9
Was told vaccine is dangerous	3	23.1	10	76.9
Was told not to get the vaccine	2	66.7	1	33.3
Other	67	63.2	39	36.8
COVID-19 infection in past 3 months					19.46	<.001
Yes	40	52.6	36	47.4
No	100	82.0	22	18.0
Household member with COVID-19 infection in past 3 months					13.32	<.001
Yes	33	53.2	29	46.8
No	107	78.7	29	21.3

P-values are Pearson Chi-square (2-sided).

Logistic regression was conducted to determine which factors (age, household size, household member older than 65, COVID-19 infection within the past 3 months, a household member with COVID-19 infection within the past 3 months, wearing a mask in public, visit with a medical provider, issues getting appointments, getting the flu shot, and not knowing enough about the COVID-19 vaccine) are predictors of getting the vaccine versus not getting it (comparison group). Regression results indicated that the overall model fit of 4 predictors (household member with COVID-19 infection within the past 3 months, often wearing a mask in public, medical provider visits within the last year, and not knowing enough about the COVID-19 vaccine) was questionable (−2 Log Likelihood = 168.6). Still, they were statistically significant in discriminating the probability of vaccination (χ² = 70.2, P < .001). The model accurately classified 83.8% of the cases. Regression coefficients are presented in Table 5. Wald statistics denoted that household members with COVID-19 infection within the past 3 months, seen a medical provider within the last year, wearing a mask in public, and not having enough knowledge about the vaccine predicted getting the vaccine. The odds ratio for these variables indicated changes in the likelihood of obtaining vaccination.

Table 5.

Multivariate Analysis of Factors Related to Vaccination Compliance (n = 197).

Variable	B	OR	95% CI	Wald Statistic	P-value
Age	<0.01	1.00	0.97-1.03	0.03	.865
Household size	0.07	1.07	0.85-1.36	0.33	.566
Living with HM older than 65	0.57	1.76	0.78-3.95	1.87	.172
COVID-19 infection in past 3 months	−0.74	0.48	0.17-1.37	1.89	.170
HM with COVID-19 infection in past 3 months	−1.10	0.33	0.12-0.97	4.03	.045
Wearing a mask in public often	1.24	3.47	1.48-8.11	8.22	.004
Visit with a medical provider within the last year	0.98	2.67	1.13-6.30	5.03	.025
Issues getting appointments due to COVID-19	−0.09	0.91	0.35-2.33	0.04	.847
Flu Shot 2020-2021	−0.16	0.85	3.40-2.12	0.12	.728
Not knowing enough about the vaccine (barrier)	2.63	13.80	3.81-49.92	16.00	<.001
χ² = 70.2, P < .001
−2 Log Likelihood = 168.6

Abbreviations: B, unstandardized beta; CI, confidence interval for odds ratio (OR). Reference category for all categorical factors was No. P-value for logistic regression using 2-tailed significance <.05.

Discussion

Our study adds to the literature describing the barriers to the COVID-19 vaccine among Hispanic/Latinx communities. The participants were recruited primarily from urban areas in Southern California. Most people in this community have access to the internet and social media. At the time of this study, there was much misinformation about the COVID-19 vaccine in English and Spanish.^3,15,16 In this study, select sociodemographic variables, and questionnaire responses were analyzed using descriptive and inferential statistics. Most of the variables in this study were categorical, which limits our choices for statistical analysis. The correlation analysis demonstrated that age and household size had a negative correlation, which suggests that younger people have larger household sizes.

The relationships between the intent of vaccination and age were statistically significant. However, we cannot establish causation. It was interesting to find out that the participant’s COVID-19 knowledge was negatively correlated with the likelihood of vaccination, and the results were statistically significant. The results suggest that participants know about COVID-19 and how to protect themselves, but their knowledge about COVID-19 infection did not influence their desire to be vaccinated. Unsurprisingly, participants who saw medical providers within the last year were more likely to get vaccinated. The barriers to the COVID-19 vaccine were associated with the participant’s desire to be vaccinated. Being told the vaccine was dangerous was a significant barrier to getting the vaccine. Yet, the majority of participants would get the vaccine if it was offered to them, despite the other barriers reported. Most participants (or participants who had household members) who had not tested positive for COVID-19 3 months before data collection would get the vaccine if offered to them. Concerns about getting COVID-19 or the vaccine itself may contribute to wanting to get it, notwithstanding the barriers. The logistic regression analysis suggested that not all variables are predictors of getting the vaccine. The model accurately classified 83.8% of the cases and provided additional information on the odds of getting the COVID-19 vaccine were predicted by the number of household members with COVID-19 infection within the past 3 months, seeing a medical provider within the last year, and barriers to vaccination.

The study explored the knowledge and barriers to COVID-19 vaccination of a population with limited or no access to healthcare and vulnerable to misinformation. The study limitations include the study design. The study was cross-sectional, in which the participants were not followed up. Thus, we cannot assess the incidence and make a causal inference. The sample size was 200. Few participants did not completely fill out the survey. Some missing data were excluded from the analysis. However, the number was small enough that it did not affect the result of the study. Further research should include a larger sample size and a longer timeframe, checking for the reliability and validity of the study questionnaire in English and Spanish. We did not collect gender, income level, and years of education. Future studies should collect this demographic data to analyze if they are possible predictors for COVID-19 vaccination. Study results suggest participants may have concerns about COVID-19 and the vaccine itself. Research should evaluate the impact of those concerns on vaccine hesitancy. Although the study has several limitations, it contributed to the body of knowledge about the unique needs of this population.

Conclusions

Hispanics are at higher risk of morbidity and mortality from COVID-19. They must be vaccinated against the virus.⁶ Based on the data collected at all 4 sites, this study is recommended for community outreach to promote COVID-19 awareness and education in Hispanic communities to reduce vaccine hesitancy. The most crucial factor for increasing vaccination rates was directly reaching out to the community and actively conducting surveys to address the barriers and concerns encountered by Hispanic participants. Furthermore, it is crucial that bilingual Spanish-speaking health professionals and volunteers also be present to provide vaccination-related education and dispel any misinformation in a culturally meaningful manner.⁶ A strong focus should also be placed on social media to disseminate evidence-based information and notify potential locations where vaccination for COVID-19 will occur.¹⁷ There was also a recommendation to engage in an outreach program directed at undocumented residents in the community to know that their immigration status will not be affected and that they are eligible to receive free COVID-19 vaccinations and testing.¹⁷

As a result of the data collected at all 4 sites, this study suggests that elected officials pay greater attention to communities such as Hispanics/Latinx and increase their efforts toward vaccine uptake. In the initial stages of the pandemic, it became evident that Hispanics/Latinx, especially those living in communities in Southern California, were affected mainly by COVID-19. Lack of awareness and vaccination only contributed to the disproportionate rise among Hispanic communities. To mitigate the barriers of COVID-19, local government and academic partnerships should proactively strategize to apply this multimodal interventional approach. As vaccines and boosters continue to be distributed, healthcare professionals must disseminate culturally appropriate and accurate information to patients. Lawmakers must consider the immediate actions needed to prevent further financial hardship and suffering among the Hispanic community.

Supplemental Material

sj-docx-1-jpc-10.1177_21501319231174810 – Supplemental material for Understanding the Barriers to COVID-19 Vaccine Among Hispanic/Latinx Communities

Supplemental material, sj-docx-1-jpc-10.1177_21501319231174810 for Understanding the Barriers to COVID-19 Vaccine Among Hispanic/Latinx Communities by Razel Bacuetes Milo, Claudia Aguayo, Allison Rae Chico, José Andrés Rozo, Iris Vásquez, Patricia Calero and Joseph Burkard in Journal of Primary Care & Community Health

Footnotes

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) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Razel Bacuetes Milo

Supplemental Material

Supplemental material for this article is available online.

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Supplementary Material

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