The factors correlated with COVID-19 vaccination coverage in Chinese hypertensive patients managed by community general practitioner

ABSTRACT

This study aims to describe COVID-19 vaccination coverage and its influential factors in hypertensive patients who were administered by community general practitioners in China. A cross-sectional survey was carried out using data from electronic health record systems. The subjects were hypertensive patients who had been involved in the health management of the Essential Public Health Service (EPHS) program in Hangzhou City, China. As of Aug 3, 2022, the full and booster vaccination rates were 77.53% and 60.97% in randomly selected 96,498 subjects. There were disparities across regions, age, and gender in the distribution of COVID-19 vaccination coverage. Obesity and daily alcohol consumption were factors in the promotion of COVID-19 vaccination. Current smoking, non-daily physical exercise, irregular medication adherence, and comorbidities were risk factors for COVID-19 vaccination. Coverage rates have decreased depending on the number of risk factors. The ORs (95% CI) were 1.78 (1.61 ~ 1.96) of full vaccination and 1.74 (1.59 ~ 1.89) of booster vaccination in subjects with ≥4 risk factors, compared to those without risk factors. In summary, the progress of COVID-19 vaccination among community hypertensive patients lagged behind that of the general population during the same period. Individuals who lived in urban areas, were elderly, and had an irregular medication adherence, comorbidities, and multiple risk factors should be highlighted in the COVID-19 vaccination campaign.

Introduction

The COVID-19 vaccination could provide strong protection against serious illness and death caused by the Omicron and Delta variants of the virus that causes COVID-19 according to the WHO recommendation.¹ Oliver JW² and colleagues using a mathematical model estimated that COVID-19 vaccination had prevented 14.4 million deaths from COVID-19 in 185 countries and territories between Dec 8, 2020, and Dec 8, 2021. The comparison of the case fatality ratio during the Omicron pandemic between Hong Kong and Singapore indicated that ≥1 dose, full vaccination, and booster vaccination, especially in the older population, received any type of accessible vaccine, would be all effective at reducing case fatality ratio.³ China has developed several types of COVID-19 vaccines, including an inactivated virus vaccine, a recombinant protein vaccine, a viral vector vaccine, and more. As early as March 29, 2021, the National Health Commission of People’s Republic of China issued the COVID-19 vaccination program for the public population.⁴ On July 23, 2022, the coverage rate of the first dose of the COVID-19 vaccine was 92.1%, the full vaccination rate was 89.7%, and the booster vaccination rate was 71.7% among the whole population in mainland China.⁵ However, compared to the United States, a lower coverage of full and booster vaccination was found in the older people in China.⁶ Disparities in COVID-19 vaccination rates were also observed between rural and urban counties of United States,⁷ among people with different socio-economic status⁸ and countries with different income levels.⁹

In the analysis of the association between hypertension and mortality, the average RR (95% CI) for hypertensive patients compared with those without hypertension was 1.42 (1.30 ~ 1.54).¹⁰ According to the Chinese Technical Vaccination Recommendations for COVID-19 vaccines, the vaccination is recommended for individuals with comorbidities who are healthy or have conditions that are controlled well with medicine.⁴ It was reasonable to include hypertensive patients with well-controlled blood pressure in the COVID-19 vaccination priority. However, few studies have evaluated the coverage in this population through the ongoing COVID-19 vaccination campaign in mainland China. During the initial period of COVID-19 vaccination, higher coverage was reported among adults with high-risk medical conditions than among those who did not report these conditions.¹¹ However, according to the latest review, acceptance of COVID-19 vaccines among people with chronic diseases was inadequate.¹² The Chinese government no longer emphasized the strict ‘zero policy’ for the COVID-19 pandemic from Dec 7, 2022. It is important to assess the coverage of COVID-19 vaccination among vulnerable populations like hypertensive patients. Based on data from electronic health record (EHR) system and the electronic immunization system, the present study aimed to describe COVID-19 vaccination coverage and its influential factors in hypertensive patients who are administered by community-based general practitioners (GPs).

Methods

Subjects

The subjects in this study were hypertensive patients who had been involved in the health management of the Essential Public Health Service (EPHS) program in Hangzhou City, Zhejiang Province, China. The EPHS program in China is a national financial support project, proposed and approved by the National Health Commission, aims to reverse the major health burden of priority populations as hypertension or type 2 diabetes patients. Confirmed hypertensive patients who aged 35 y at least and agreed to accept health management by GPs in Community Health Center (CHC) will be established an EHR archive and then receive comprehensive interventions by a team grouped with GPs, nurses, and public health doctors in located CHC. The health management contains physical examination, medication, healthy diets and lifestyle modifications, and vaccination consultation. The EHR system was designed by a licensed software company and was assigned to all CHCs for the collection of correlated information.

The sample size was estimated using the 400 × P/(1-P) formula by the reference coverage of 65%,¹² and obtained the final sample size of 892 with a 20% nonresponse rate. In 2021, more than 0.86 million of hypertensive patients registered in 198 CHCs in Hangzhou city. This study used the automatic procedure used in the EHR system, 20% of the managed patients were randomly selected by a multistage stratified sampling method. First, hypertensive patients with type 2 diabetes were excluded from the present study. Then, the random sampling was stratified by CHCs and age distribution per 10 y. Subsequently, 98,083 subjects were randomly selected from the sampling population. Overall, 1,585 subjects were excluded because of missing required variables. A total of 96,498 subjects in the present study had qualified data. All participants signed an informed consent document when they agreed to accept the EPHS program or COVID-19 vaccination. The procedures and activities of the two projects above complied with the 1975 Helsinki Declaration. The personal information was protected by anonymity and was only used for analysis of the characteristics of the population. Ethical approval for this study does not require further approval.

Data source

A unified electronic vaccination platform was used to record the COVID-19 vaccination information including personal identification, vaccination status and time, and vaccine varieties. Once an individual is vaccinated, COVID-19 vaccination information is recorded on the digital server and uploaded to the regional electronic platform in a timely manner. The EHR system records information including personal identification, managed CHC, sex, birth, body measurements, lifestyle factors, medication adherence, and comorbidities. The analyzed database, including information on COVID-19 vaccination and health administration, was produced using the digital exchange platform with personal identification. The latest vaccination time when executing platform exchange was August 3, 2022. The specific procedure of sampling is shown in Figure 1.

Figure 1.

Specific procedure of subjects sampling.

Variables and criterion

The analysis factors contained age, gender, body mass index (BMI), waist circumference (WC), current smoking, daily alcohol consumption and physical exercise, urban-rural disparities, medication adherence, and comorbidities such as cardiovascular disease and cancer. Definitions of cardiovascular factors were followed by the Chinese Guidelines for Prevention and Treatment of Hypertension, one of the primary technical manuals for GPs when managing patients.¹³ Smoking status is a dichotomous variable, and one cigarette per day, at least during the last 6 months, considered current smoking. Use of weekly periods to define the frequency of alcohol consumption and physical exercise. Five days a week is defined as the “daily” frequency. The BMI is calculated as Weight/Height² (kg/m²). BMI ≥28.0 kg/m2 and (or) WC ≥90 cm (male), ≥85 cm (female) were considered obesity. The area of CHCs was divided into urban, suburban, and rural groups.

The COVID-19 vaccine species in this study included inactivated virus vaccine, recombinant protein vaccine, and viral vector vaccine. Full vaccination was defined as two doses of inactivated virus vaccine, three doses of recombinant protein vaccine, or one dose of viral vector-based vaccine. Booster vaccination was defined as three doses of inactivated virus vaccine or two doses of viral vector-based vaccine. An additional dose of viral vector-based vaccine with two doses of inactivated vaccine was also considered as booster vaccination. Because the recombinant protein vaccine did not have an official guideline for the booster program in current, 1,101 subjects were excluded from the analysis of booster vaccination. Having a vaccination record, but not receiving the required dose was defined as incomplete vaccination. The interval time between different vaccination doses must meet the minimum requirement of the official guideline, otherwise the next vaccination would define invalid vaccination.

Statistical analysis

Variables were summarized using means with standard deviations for continuous data and percentages and proportions for categorical data. One-way ANOVA tests and chi-squared tests were used to compare continuous and categorical variables between different groups. Logistic regression models were used to calculate the odds ratio (OR) and 95% CI for risk factor associations with COVID-19 vaccination. The dependent factor was the status of full and booster vaccination (0 = complete, 1 = unvaccinated or incomplete). The independent factors contained obesity, smoking, alcohol consumption, physical exercise, medication adherence, and comorbidities. Age, gender, and area were considered as adjusted factors. The logistic analysis was carried out in two models. The adjusted OR (95% CI) was calculated separately for each independent factor in Model 1 and was calculated by including all independent factors simultaneously in Model 2. Furthermore, this study grouped the obesity, current smoking, daily alcohol consumption, non-daily physical exercise, irregular medication adherence, with cardiovascular disease or cancer as risk factors associated with the rate of COVID-19 vaccination, and calculated the adjusted OR (95% CI) for individuals with one item, two items, three items, and ≥four items of risk factors, compared to those without risk factors. All statistical analyses were performed using R version 4.1.1 (URL https://www.R-project.Org/). All p values were two-sided, and the statistical significance was defined as p < .05.

Results

The general characteristics of subjects

The regional distribution of participants was 31.16% in urban areas, 53.36% in suburban areas, and 14.47% in rural areas. Males accounted for 47.40% and females 52.60%. The average age was 69.43 ± 10.05 y and most age groups were 60 y~ (33.93%) and 70 y~ (31.27%). The rate of obesity, current smoking, daily alcohol consumption, and daily physical exercise were 40.78%, 17.60%, 12.83%, and 26.39%, respectively. 92.62% of subjects had regular medication adherence. The proportions of comorbidities were 15.64% of cardiovascular disease and 5.49% of cancer. The overall distribution of characteristics was different among regional groups (Table 1).

Table 1.

The general characteristics of subjects.

Variable			Area		Total	P value
		Urban	Suburban	Rural
N (%)		31037 (31.16)	51494 (53.36)	13967 (14.47)	96498 (100.00)
Gender (%)	Male	49.59	46.88	44.48	47.40	<.001
	Female	50.41	53.12	55.52	52.60
Age (year)		69.94 ± 10.40	68.88 ± 9.83	70.33 ± 9.96	69.43 ± 10.05	<.001
Age groups (%)	35y～	2.88	2.23	1.51	2.33	<.001
	50y～	14.90	18.28	16.06	16.87
	60y～	33.27	34.93	31.73	33.93
	70y～	31.07	31.09	32.34	31.27
	80y～	15.71	11.91	16.57	13.81
	90y～	2.18	1.56	1.79	1.79
BMI (kg/m2)		24.59 ± 3.20	24.60 ± 3.32	24.01 ± 3.29	24.51 ± 3.29	<.001
Waist (cm)		84.93 ± 8.60	85.38 ± 8.89	83.61 ± 8.99	84.97 ± 8.83	<.001
Obesity (%)	No	60.96	56.92	63.82	59.22	<.001
	Yes	39.04	43.08	36.18	40.78
Current smoking (%)	No	83.43	81.86	82.14	82.40	<.001
	Yes	16.57	18.14	17.86	17.60
Daily drinking (%)	No	89.13	86.04	87.03	87.17	<.001
	Yes	10.87	13.96	12.97	12.83
Daily physical exercise (%)	Yes	41.52	18.84	20.58	26.39	<.001
	No	58.48	81.16	79.42	73.61
Medication adherence (%)	Regular	95.74	93.75	81.46	92.62	<.001
	Irregular	4.26	6.25	18.54	7.38
With cardiovascular disease (%)	No	76.59	89.18	83.90	84.36	<.001
	Yes	23.41	10.82	16.10	15.64
With cancer (%)	No	93.36	94.68	96.44	94.51	<.001
	Yes	6.64	5.32	3.56	5.49

Distribution of COVID-19 vaccination rates by gender, age group, and area

The full and booster vaccination rates of subjects were 77.53% and 60.97% by Aug 3, 2022. A minority of subjects were vaccinated but did not follow the required vaccination procedures. These proportions were 4.52 of full vaccination and 20.87% of booster vaccination (Figure 2). Compared to urban and suburban areas, the rural area had the highest rate of full (83.80%) and booster (71.98%) vaccination (p < .001). Both the full and booster rates decreased along with age groups (p < .001). The full rates of 80y~ groups and 90y~ groups were 52.41% and 22.04%. Correspondingly, the booster rates were 29.78% and 7.98%. By the gender groups, the male had a higher full rate (79.94%) and booster rate (64.38%) than the female (75.35%, 57.93%) (p < .001) (Figure 3).

Figure 2.

The rates of full and booster COVID-19 vaccination.

Note that the difference in the rate of unvaccinated group between full and booster groups was due to the difference in the count of denominators. Overall, 1,101 subjects for the recombinant protein vaccine were excluded from the analysis of booster vaccination.

Figure 3.

The distribution of COVID-19 vaccination rate by area, age and gender.

Factors associated with COVID-19 vaccination rates

Compared to individuals who were not obese, those who were obese had a higher rate of full vaccination, but no difference in booster vaccination. The ORs (95% CI) were 0.94 (0.91 ~ 0.97) and 0.99 (0.96 ~ 1.02). Similarly, subjects with daily alcohol consumption behavior were more willing to complete full and booster vaccination. The ORs (95% CI) were 0.79 (0.75 ~ 0.84) and 0.85 (0.82 ~ 0.89). Current smoking and non-daily physical exercise were risk factors for the COVID-19 vaccination. The ORs (95% CI) were 1.17 (1.11 ~ 1.23) and 1.21 (1.17 ~ 1.26) for full vaccination, were 1.21 (1.16 ~ 1.27) and 1.26 (1.22 ~ 1.30) for booster vaccination. The ORs (95% CI) of medication adherence were 1.08 (1.01 ~ 1.15) for full vaccination and 0.96 (0.91 ~ 1.02) for booster vaccination in comparison. Comorbidities were a disadvantage in vaccinating against COVID-19. The ORs (95% CI) were 1.47 (1.41 ~ 1.53) of full vaccination and 1.36 (1.31 ~ 1.41) of booster vaccination for cardiovascular disease, were 2.76 (2.60 ~ 2.93) and 2.26 (2.13 ~ 2.40) for cancer (Table 2).

Table 2.

Factors correlated with the full and booster COVID-19 vaccination rates.

Variables		Rate of vaccination (%)		OR (95% CI) in Model 1*		OR (95% CI) in Model 2#
		Full	Booster	Full	Booster	Full	Booster
Obesity	No	76.93	60.63	1		1
	Yes	78.38	61.45	0.94 (0.91～0.98)	0.99 (0.97～1.02)	0.94 (0.91～0.97)	0.99 (0.96～1.02)
Current smoking	No	76.62	60.01	1		1
	Yes	81.73	65.44	1.09 (1.04～1.15)	1.16 (1.11～1.21)	1.17 (1.11～1.23)	1.21 (1.16～1.27)
Daily alcohol consumption	No	76.62	59.96	1		1
	Yes	83.66	67.85	0.78 (0.74～0.82)	0.85 (0.81～0.89)	0.79 (0.75～0.84)	0.85 (0.82～0.89)
Daily physical exercise	Yes	78.33	62.28	1		1
	No	77.23	60.50	1.19 (1.15～1.24)	1.24 (1.20～1.29)	1.21 (1.17～1.26)	1.26 (1.22～1.30)
Medication adherence	Regular	77.52	60.74	1		1
	Irregular	77.56	63.81	1.11 (1.04～1.18)	0.98 (0.92～1.03)	1.08 (1.01～1.15)	0.96 (0.91～1.02)
With cardiovascular disease	No	79.72	63.41	1		1
	Yes	65.65	47.78	1.45 (1.39～1.51)	1.34 (1.29～1.39)	1.47 (1.41～1.53)	1.36 (1.31～1.41)
With cancer	No	78.69	62.10	1		1
	Yes	57.41	41.53	2.72 (2.56～2.89)	2.21 (2.08～2.34)	2.76 (2.60～2.93)	2.26 (2.13～2.40)

*Model 1, OR (95% CI) adjusted by age, sex, and area.

^#Model 2, OR (95% CI) adjusted by age, sex, area, and all independent factors.

The correlation between number of risk factors and COVID-19 vaccination rates

The COVID-19 vaccination rate of subjects decreased along with the number of risk factors. In subjects without risk factors, full vaccination and booster rates were 80.02% and 64.53%, respectively. Rates decreased to 78.53% and 59.71% in individuals with ≥4 risk factors. The ORs (95% CI) were 1.15 (1.08 ~ 1.22) of 1 item, 1.30 (1.22 ~ 1.39) of 2 items, 1.60 (1.49 ~ 1.72) of 3 items, and 1.78 (1.61 ~ 1.96) of ≥4 items for the full vaccination; 1.20 (1.13 ~ 1.26) of 1 item, 1.36 (1.29 ~ 1.43) of 2 items, 1.58 (1.48 ~ 1.68) of 3 items, and 1.74 (1.59 ~ 1.89) of ≥4 items for the booster vaccination (Figure 4).

Figure 4.

The correlation between number of risk factors and COVID-19 vaccination rates.

Discussion

This study estimated COVID-19 vaccination coverage based on EHR data in hypertensive patients who were managed by GPs in mainland China. Currently, the COVID-19 vaccination coverage among the Chinese population was mostly investigated through online surveys. For example, several online cross-section surveys reported 93.4% of adolescents,¹⁴ 75.4% of ICU clinicians¹⁵ and 80.46% of primary healthcare¹⁶ had completed the full vaccination. The present study had advantages like random sampling, large sampling size, and in real-world data, showed that the COVID-19 vaccination rates of subjects were 77.53% of full vaccination and 60.97% of booster vaccination. Hypertensive patients involved in community health management had the advantage of regularly receiving health recommendations from GPs and were the priority population who proposed to receive COVID-19 vaccines. However, the vaccination rates of them were lower than the estimated rates (89.7%, 71.7%) among the whole population according to the official press in the same period.⁵ The poor vaccination rates among patients with chronic disease might because doubts about the vaccine efficacy, the vaccination may cause disease by itself, and fear of adverse effects.¹⁷ Inversely, there was a study that showed that the COVID-19 vaccination coverage among adults with self-reported risk medical conditions was significantly higher compared with those without such conditions.¹¹ Current unsuitable vaccination rates may be linked to the limited COVID-19 outbreak due to strict restrictions in mainland China. People living in poor health have not been directly affected by the threat of COVID-19. As a result, a small proportion of subjects had been vaccinated, but did not continue to receive the required doses, although they have plenty of time to consider the benefit. From the comparison between Hong Kong and Singapore, a higher vaccination coverage could partly explain a lower fatality rates of COVID-19.¹⁸ There is an urgent need to speed up the COVID-19 vaccination process for hypertensive patients, in particular, strict restrictions were canceled in December 2022.

In the United States, the COVID-19 vaccination coverage presented disparity across rural and urban counties, gender, age groups, race, and socioeconomic groups.^19,20 The present study showed that the full and booster vaccination rates were higher in rural area than that in suburban and urban area, and this regional distribution was different from previous studies.^19,21 Shortage of health-care facilities, lower educational attainment, sociocultural identities and political ideologies, and higher degree of vaccine hesitancy usually contribute to a lower COVID-19 vaccination coverage in rural areas.^19–21 The reasons for the contrary findings in this study may be as follows: First, rural vaccination has been emphasized several times by the government as part of the overall COVID-19 vaccination campaign. Measures such as temporary vaccination clinics and specialized vaccination vehicles were used to accelerate the COVID-19 vaccination in convenience.²² Secondly, the media headlines could affect public awareness and interest in vaccine hesitancy and anti-vaccination during the period of COVID-19.²³ In the present study, the constituent ratio of ≥60 y was more than 80%, and the rural area had the highest ratio. It was reasonably speculated that subjects in the rural area had the lowest rate of usage and the least interference in terms of Internet-media usage. The government encouraged the proposal to play the distinguishing role in COVID-19 vaccination in rural areas. According to the statistics by China CDC, the full vaccination rate was 85.6% and the booster vaccination coverage was only 67.8% for older adults, which was lower than countries such as the United States, Germany, and Japan.⁶ The inverse relationship was seen between COVID-19 vaccination coverage and age groups in this study. In particular, the rates in the 80 y~ and 90 y~ were at extremely low level. Experience in HongKong showed that equivalent effectiveness of three doses of BNT162b2 and CoronaVac were obtained for protection against COVID-19 severe or fatal outcomes at very high levels.²⁴ The promotion of COVID-19 vaccination for older people needs strategies such as paying attention to home dwelling older adults, emphasizing GPs’ role in vaccination campaigns, developing domestic mRNA vaccines, improving the AEFI surveillance system, and providing additional COVID-19 vaccination accident insurance, as suggestions from the China CDC.⁶ In terms of gender disparity, the current coverage for male hypertensive patients was greater than in the female. A previous review reported that females were less likely to accept vaccination compared to males for other vaccines like influenza.²⁵ The COVID-19 vaccine safety monitoring in the United States showed 79.1% of female had side effects based on 61.2% of vaccination constituent ratio.²⁶ The female disparity of COVID-19 vaccination hesitance or acceptance seemed been confirmed.²⁷ However, another study suggested that the female with healthier lifestyles was associated with a higher COVID-19 vaccination coverage compared to the male.²⁸ It could be assumed that the gender gap has varied outcomes in different specific populations.

Serval surveys suggested that the lifestyle correlated with COVID-19 vaccine hesitancy and acceptance in varied outcomes.^28–30 Healthy lifestyle factors such as healthy weight, never smoking, and alcohol consumption were positively correlated with enhanced COVID-19 vaccination by an online survey.²⁸ The study by Wu and colleagues showed smoking and frequent drinking could increase the COVID-19 hesitancy rate.²⁹ On the contrary, the alcohol drinkers were less hesitant than nondrinkers about getting the COVID-19 vaccine by the HongKong study.³⁰ Individuals with a healthy lifestyle are more likely to receive the necessary vaccination. Nevertheless, the previous study indicated that better health condition was associated with lower willingness to get vaccinated.³¹ The influence of lifestyle factors on the COVID-19 vaccination showed different results in the present study. Obesity, non-current smoking, daily alcohol consumption, and physical exercise were positive factors in encouraging COVID-19 vaccination. The reason for these paradoxes could be the hypothesis that healthy lifestyles are not equal to a healthy state, particularly, the subjects were hypertensive patients.

The regular medication adherence was found in most of the subjects and was associated with a higher rate of COVID-19 vaccination. Individuals who took medication regularly were more concerned about their health and more likely to follow the medical advice of general practitioners. The research on influenza vaccination found that vaccinated individuals had significantly higher GP consultation rates than non-vaccinated individuals.³² A review found that the most trustworthy source to help individuals decide whether to take the COVID-19 vaccine was health-care workers, compared to religious leaders and celebrities.³³

Data in the early COVID-19 pandemic showed that the case fatality ratio of patients with cardiovascular disease, diabetes, chronic respiratory disease, hypertension, and cancer was 10.5%, 7.3%, 6.3%, 6.0%, and 5.6%, respectively.³⁴ Patients with cancer are particularly vulnerable to severe COVID‐19 outcomes, such as leukemia, non‐Hodgkin’s lymphoma, and lung cancer.³⁵ Therefore, patients co-existed comorbidities were high‐risk population groups and should be at the top of the priority list for receiving the COVID-19 vaccination. However, the vulnerable population with comorbidities would not usually be included in vaccination trials, and data on the efficacy and safety of these populations were insufficient. The observation of vaccine efficacy and safety in vulnerable individuals was largely dependent on vaccination in the mass population. Simultaneously, concern about effectiveness and side effects is the most commonly cited reason for vaccine hesitancy.³³ This study confirmed that hypertensive patients with cardiovascular disease and cancer had lower rates than those who did not have comorbidities.

In the analysis of association between healthy lifestyle and outcome events such as death and cardiovascular disease, the count of risk factors was usually considered as a predictor for incidence of outcomes.³⁶ The present study used a similar approach to show the number of risk factors correlated with the COVID-19 vaccination coverage, including obesity, current smoking, daily alcohol consumption, non-daily physical exercise, irregular medication adherence, and comorbidities. Regardless of the contribution with a single risk factor, the number of risk factors was in negative correlation with COVID-19 vaccination coverage. A similar study contained 12 lifestyle behaviors basing on the American Medical Association Healthy Lifestyle scale and the Likert 5-point scale, found that the COVID-19 vaccination coverage increased with the lifestyle score.²⁸ Furthermore, the COVID-19 vaccine hesitancy rate decreased along with the increase of lifestyle score.²⁹ In summary, subjects with more risk factors were more likely to threaten by severe outcomes and had additional risk of inadequate COVID-19 vaccination. Hypertensive patients with multiple risk factors should be highlighted during the COVID-19 vaccination campaign.

The present study had some limitations. Firstly, since this study collected data in real terms, no specific survey collected subjects’ perceptions of COVID-19 and attitudes toward vaccination. Secondly, the COVID-19 vaccine could vaccinate hypertensive patients who are healthy or have a well-controlled medical status. Cardiovascular factors such as blood pressure, blood glucose, and lipids were usually used to assess the condition of the disease. The absence of these factors might lead to an incomprehensible assessment of the factors affecting COVID-19 vaccination. Thirdly, the subjects were hypertensive patients who managed by GPs in CHC. They had more opportunities to receive medical advice and could be aggressive for COVID-19 vaccination, could not represent the whole population with hypertension. However, the present study using EHR data originally reported COVID-19 vaccination coverage among hypertensive patients managed in the community in mainland China, showed disparities in COVID-19 vaccination across regional, age, and gender groups, and found that lifestyle, medication adherence, and comorbidities could affect COVID-19 vaccination coverage.

Funding Statement

The author(s) reported that there is no funding associated with the work featured in this article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Declarations

All participants had signed an informed consent document when they took part in the EPHS program and COVID-19 vaccination. Procedures and activities of the above two projects were consistent with the 1975 Helsinki Declaration. The personal information of participants was protect anonymity and used in terms of characteristics of the population. The ethics approval of this study does not require re-approval.