The association between influenza vaccination and the perception of COVID-19 as well as COVID-19 vaccination behavior among community residents in Anhui province, China

ABSTRACT

Influenza is a significant public health threat associated with high morbidity and mortality globally. This study investigated the influenza vaccination rate (IVR) among community residents in Anhui province, China, and explored the association between participants’ influenza vaccination and their key sociodemographic characteristics, perception of COVID-19 as well as COVID-19 vaccination behavior. We found that the IVR among respondents in Anhui province was 27.85% in 2020. Regression analyses revealed that males (OR = 1.41, 95% CI: 1.01 ~ 1.96), residents with above middle school education (OR = 1.88, 95% CI: 1.04 ~ 3.39), considered themselves likely to be infected with COVID-19 (OR = 1.53, 95% CI: 1.04 ~ 2.24), had received the COVID-19 vaccine (OR = 9.85, 95% CI: 3.49 ~ 27.78), did not plan to receive COVID-19 vaccine in the future (OR = 1.70, 95% CI: 1.17 ~ 2.47), and had no adverse reactions after COVID-19 vaccination (OR = 1.54, 95% CI: 1.04 ~ 2.27) were associated with a higher IVR. The acceptance of influenza vaccination was mainly associated with respondents’ gender, education, perception of COVID-19, history of COVID-19 vaccination in city and countryside community residents in Anhui province.

KEYWORDS:

• Influenza vaccine
• influenza vaccination rate (IVR)
• COVID-19
• perception
• behavior
• Anhui province

Introduction

Seasonal influenza is an acute respiratory infection caused by seasonal influenza virus.¹ Influenza causes a large number of cases and deaths worldwide through its seasonal wave of infection, and an average of 389,000 respiratory deaths are associated with influenza globally each year.² The Global Influenza Surveillance and Response System (GISRS) reported that even in mild years, influenza can result in 290,000 to 650,000 fatalities, 3 million to 5 million severe cases worldwide, and create more social and economic damage when it is an epidemic.³ Influenza vaccination is the most cost-effective way to prevent and control influenza.⁴ In addition, influenza vaccine is also a powerful tool to reduce the risk of serious illness, hospitalization, and death.^5,6

The knowledge about IVR and its influencing factors is still limited in China. In recent years, studies on influenza vaccine in China mainly focused on influenza vaccine coverage and willingness to receive vaccine in some priority populations such as aged people and children.^7–9 It seems that there were few studies on influenza vaccination and influencing factors among community residents of Anhui in recent 10 years. Relatively few studies focused on general residents. Yao’s indicated that IVR in Chinese general people was only 2%.¹⁰ A meta-analysis showed the pooled IVR in 35 studies conducted in mainland China was only 16.74%, significantly lower than neighboring countries, such as South Korea (35.61%) and Japan (32.62%).¹¹ Some studies showed that low perceived risk of influenza, poor knowledge of vaccines, non-confidence in vaccine safety, adverse reactions after vaccination, and inconvenient transportation for vaccination were main influencing factors on influenza vaccination.^12,13

Currently, the Technical Guidelines for Influenza Vaccination in China (2022 ~ 2023) suggest that all persons ≥6 months of age who are willing to be vaccinated and have no relevant contraindications be vaccinated against influenza.¹⁴ However, the influenza vaccine has not been included in the National Expanded Programme on Immunization (NEPI), which means that it is self-funded and optional in China. Only in a few large cities influenza vaccines can be provided for free to some priority populations such as senior citizens, children, and healthcare workers, which may motivate the targeted population to receive influenza vaccine.¹⁵ Therefore, IVR may vary a lot because of the policy diversity in different areas. As a central province in China, Anhui province is an agricultural province with a large population (the total number of permanent residents in Anhui was 61.27 million) and a less developed economy.¹⁶ Influenza vaccine is regarded as a non-NEPI vaccine in Anhui province. It is optional and self-funded for all types of residents including priority population.¹⁷

COVID-19 has been managed as a Category B infectious disease in China since the beginning of 2023.¹⁸ The WHO also has indicated that it no longer constitutes a Public Health Emergency of International Concern (PHEIC) though it is an ongoing health issue.¹⁹ Moreover, Tedros Adhanom Ghebreyesus (the director-general of the WHO) and Wannian Liang (the chief expert on COVID-19 prevention and control in China) emphasized that COVID-19 is no longer a PHEIC does not mean that it is not a global health threat or it can be ignored.^20,21 It is still necessary to pay sufficient attention to the potential of COVID-19 emerging during influenza season.²² And relevant research should be conducted to help understand the relationship between influenza vaccination and public perception of COVID-19, as well as COVID-19 vaccination behavior. The present study aimed to investigate IVR among community residents in Anhui province, China, and explored the association between participants’ influenza vaccination and their key sociodemographic characteristics, perception of COVID-19 as well as COVID-19 vaccination behavior.

Author introduction

The authors of this study, Mengjie Guo and Jian’ an Li (two first authors with equal contribution), are postgraduate students, majoring in Social Medicine and Health Management at the School of Health Management, Anhui Medical University. Mengjie Guo published a paper “Government-society collaborative participation in the prevention and control of major epidemics in rural communities: Case Analysis” (second author) in the Chinese Rural Health Service Administration. The corresponding author of this study, Li Wang, holds a doctorate degree and is an associate professor and master’s supervisor. Currently, she teaches at the School of Health Management, Anhui Medical University. Her research field primarily focused on vaccine hesitancy and public health policy. She has published more than 50 papers, including “Vaccine attitudes among young adults in Asia: a systematic review” in Human Vaccines & Immunotherapeutics (first author), “Understanding medical students’ practices and perceptions toward vaccination in China: A qualitative study in a medical university” in Vaccine (first author), “The development and reform of public health in China from 1949 to 2019” in Globalization & Health (first author) and “Experiences and Challenges of Implementing Universal Health Coverage with China’s National Basic Public Health Service Program: Literature Review, Regression Analysis, and Insider Interviews” in JMIR Public Health Surveill (third author).

Materials and methods

Study design and participants

This study used data from a community survey done by the School of Health Management of Anhui Medical University in Anhui Province from July to December 2021 with a daily review of returned questionnaires. Participants who returned incomplete questionnaires were revisited or contacted on the following day.

Purposive sampling was used. Four countryside communities and four city communities were selected at first in Anhui province. Two of the four countryside communities were located in southern areas of Anhui, one close to the county city and the other in mountain areas far from the city. Another two countryside communities were in the northern areas of Anhui, one close to urban areas and one far away. Four city communities included one new community, one old community, one relocated community, and one unit community in^a Hefei, the capital of Anhui province. Handy sampling had been used to select around 100 residents who meet the requirements (≥16 years old, conscious, and can cooperate with the survey without communication barriers) in each community.

The sample size, N, was estimated according to the formula:

(1) $N=Z_{1-\alpha /2}^2\times P\times \left(1-P\right)/{\delta }^2$(1)

where Z is equal to 1.96 (when α is 0.05, the 95% confidence interval) and α is 0.1. Based on previous studies, it was assumed that IVR in China (P) was 23.2%.²³ Since this study sampled eight communities, the group effect coefficient was 8, and the total sample size was 548. Considering the possible nonconforming feedback, the sample size should be at least 785, with a margin of 30%.

Questionnaire investigators were recruited from undergraduate and graduate students at the School of Health Services Management after passing the interview examination. Then they received unified training. Each respondent was interviewed face-to-face by one of the investigators. Before filling out the questionnaire, the purpose of the study was explained to the respondents, and informed consent was obtained. Figure 1.

Figure 1. This study’s programming flowchart.

Study tool

A self-made questionnaire based on the literature review and expert consultation was applied to collect information. It was revised according to the comments from 30 respondents in the pretest survey. The final questionnaire included four sections:

1. Socio-demographic characteristics, including age, gender, marital status, community type, level of education and career;

2. Influenza vaccination (self-reported whether they had received at least one shot of influenza vaccine in 2020);

3. Perception about COVID-19, including cognition of the long-term existence of COVID-19, cognition of the possibility of infecting by COVID-19, cognition of the severity of COVID-19;

4. COVID-19 vaccination behavior, including the status of receiving the COVID-19 vaccine, the willingness to receive COVID-19 vaccine in the future, as well as whether there are some adverse reactions after COVID-19 vaccination.

Statistical analysis

The database was established using Epi Data 3.1 software through double entry and verification. Stata SE 12 software was used for statistical analysis. Descriptive statistics were used to analyze the basic characteristics of the participants. Categorical variables were summarized by number and percent (%), and the comparisons between groups were calculated by the chi-square test, which was the univariate analysis. Univariate analysis is a two-variable analysis, including only one independent variable and one dependent variable. That means all questions in the questionnaire were independent variables (except for residents’ influenza vaccination), which were validated and analyzed separately with residents’ influenza vaccination (dependent variable).

Multivariate analysis includes a dependent variable with two or more independent variables. We used multivariate analysis to explore the association between influenza vaccination and the perception of COVID-19 as well as COVID-19 vaccination behavior. Residents’ influenza vaccination as the dependent variable and other questions in the questionnaire as independent variables are included in the regression model together. OR (95% CI) was calculated by logistic regression analysis for categorical variables. A two-tailed significance, defined as p-value <.05, was used for all analyses. In multivariate analysis, to ensure the stability of statistical results, some variables in which there are more than three categories were adjusted into two or three categories.

1. “Age” was re-categorized as “16 ~ 60” and “>60.” “Community type” was re-categorized as “countryside community” (including four communities in rural countryside) and “city community” (including four communities in city). And “educational level” was adjusted as two categories, “middle school or below” and “above middle school.” Moreover, “career” was adjusted to three categories, “farmer/freelance/other,” “work in government, public institutions or military” and “student.”

2. The perceptions about “the long-term existence of COVID-19 or nor,” “possibility of contracting COVID-19,” and “the severity of COVID-19” were re-categorized as “no” (including the former two categories shown in Table 2) and “yes” (including the latter one or two categories shown in Table 2). And “the status of receiving COVID-19 vaccine” was adjusted to “no” (not getting any COVID-19 vaccine) and “yes” (getting one or two shots of COVID-19 vaccines).

Table 1. Univariate analysis of influenza vaccination across sociodemographic characteristics in Anhui province, China in 2020.

Variables	N (case)	%	n (vaccination)	%	x^2	p
Age group (years)					31.79	.000
16 ~ 40	352	42.26	131	37.22
41 ~ 60	311	37.33	76	24.44
≥61	170	20.41	25	14.71
Gender					2.41	.12
Female	431	51.74	110	25.52
Male	402	48.26	122	30.35
Marital status					16.30	.000
Unmarried	308	36.97	111	36.04
Married	525	63.03	121	23.05
Community type					68.78	.000
The community closing in the city in southern Anhui	93	11.16	22	23.66
The community in the mountain area in southern Anhui	130	15.61	9	6.92
The community closing in the city in northern Anhui	99	11.88	33	33.33
The community far away the city in northern Anhui	106	12.73	19	17.92
The new community	75	9.00	17	22.67
The old community	92	11.04	31	33.70
The relocated community	85	10.20	34	40.00
The unit community	153	18.37	67	43.79
Level of education					45.07	.000
Illiterate	111	13.33	17	15.32
Primary school or middle school	225	27.01	34	15.11
High school or vocational school	178	21.37	66	37.08
College or above	319	38.30	115	36.05
Career					39.51	.000
Farmer	261	31.33	38	14.56
Employee, self-employed or temporary worker	304	36.49	91	29.93
Work in government, public institutions or military	81	9.72	28	34.57
Students	187	22.45	75	40.11
Total	833	100	232	27.85

Table 2. Univariate analysis of influenza vaccination rate and the perception of COVID-19 as well as COVID-19 vaccination behavior.

Variables		No. (%) of subjects	No. vaccinated	Coverage rate（%）	x^2	p
COVID-19 perception	The COVID-19 will last for a long time				12.36	.002
	No	319 (38.30)	72	22.57
	Not sure	278 (33.37)	75	26.98
	Yes	236 (28.33)	85	36.02
	The possibility to be infected by COVID-19				21.07	.000
	No possibility	170 (20.41)	50	29.41
	Few possibilities	460 (55.22)	103	22.39
	A few possibilities	188 (22.57)	71	37.77
	A lot possibilities	15 (1.80)	8	53.33
	The severity of being infected by COVID-19				3.79	.285
	Not serious	292 (35.05)	89	30.48
	A little serious	352 (42.26)	100	28.41
	Serious	134 (16.09)	29	21.64
	Very serious	55 (6.60)	14	25.45
COVID-19 vaccination behavior	Status of receiving the COVID-19 vaccine				42.25	.000
	Not receiving COVID-19 vaccine	111 (13.33)	4	3.60
	Getting a shot of COVID-19 vaccine	80 (9.60)	17	21.25
	Getting two shots of COVID-19 vaccine	642 (77.07)	211	32.87
	Willing to continue to get the COVID-19 vaccine in the future				0.66	.415
	Yes	567 (68.07)	153	26.98
	No	266 (31.93)	79	29.70
	Experiencing adverse reactions after COVID-19 vaccination
	Yes	193 (23.65)	52	26.94	0.10	.748
	No	640 (76.83)	180	28.13
	Total	833	232	27.85

Results

Univariate analysis

A total of 978 questionnaires were received in this survey, of which 833 (85.17%) were valid. Among them, 352 (42.26%) were aged between 16 ~ 40, 311 (37.33%) were aged between 41 ~ 60, and 170 (20.41%) were aged between 61 and above; 402 (48.26%) of the participants were males, and 431 (51.74%) were females. A total of 232 respondents reported that they received the influenza vaccine in 2020, and IVR in 2020 was 27.85%. See Figure 2 for details. Univariate analysis showed that there was a correlation in responses to all socio-demographic characteristics (p < .05) with influenza vaccination except for gender (p = .12). See Table 1 for details.

Figure 2. Differences in IVR based on socio-demographic characteristics. 1) n/N and % indicate IVR in residents with different socio-demographic characteristics. Taking 131/352 and 37.22% in “age group (years)” as an example, n = 131 (the number of residents who have received influenza vaccine), N = 352 (the number of participants aged 16 ~ 40). 37.22% refers to the IVR of participants aged 16 ~ 40. 2) in the “community type,” countryside community 1 and countryside community 2 are villages located in southern Anhui. Countryside community 1 is close to the city and countryside community 2 is far from the city in the mountain area. Countryside community 3 and countryside community 4 are villages located in northern Anhui. Countryside community 3 is close to the city and countryside community 4 is far from the city. 3) in the “career,” business includes “employee, self-employed, and temporary worker.” Government including “work in government, public institutions, and military”.

Univariate analysis also showed that there was a correlation between influenza vaccination and some variables about the perception of COVID-19 as well as COVID-19 vaccination behavior (cognition of the long-term existence of COVID-19 (p = .02), the possibility of being infected by COVID-19 (p < .001), and status of the COVID-19 vaccination (p < .001)). See Table 2 for details.

Multivariate analysis

The logistic regression assessed the association between influenza vaccination and the perception of COVID-19 as well as COVID-19 vaccination behavior, adjusting for age, gender, marital status, community type, level of education, and career. Only statistically significant variables were presented in Table 3.

Table 3. Multivariate logistic regression analysis of influenza vaccine coverage rate among survey subjects (N = 883).

Variables	β	SE	Wald x^2	p	OR (95% CI)
Gender
Female					1.00
Male	0.34	0.24	4.12	.042	1.41 (1.01 ~ 1.96)
Level of education
Middle school or below					1.00
Above middle school	0.63	0.57	4.41	.036	1.88 (1.04 ~ 3.39)
The possibility to be infected by COVID-19
No					1.00
Yes	0.42	0.30	4.68	.031	1.53 (1.04 ~ 2.24)
Status of receiving the COVID-19 vaccine
No					1.00
Yes	2.88	5.21	18.86	.000	9.85 (3.49 ~ 27.78)
Willing to continue to get the COVID-19 vaccine in the future
Yes					1.00
No	0.43	0.33	7.70	.006	1.70 (1.17 ~ 2.47)
Experiencing adverse reactions after COVID-19 vaccination
Yes					1.00
No	0.43	0.31	4.70	.030	1.54 (1.04 ~ 2.27)
Total	−4.34	0.01	44.75	.000	0.01 (0.00 ~ 0.05)

Those participants who thought they might be infected by COVID-19 were associated with a higher IVR (p = .031, 95% CI: 1.04 ~ 2.24). In addition, participants who have been vaccinated against COVID-19 had an IVR of 9.85 higher than others (p = .000, 95% CI: 3.49 ~ 27.78). Residents who would not to vaccinated with the COVID-19 vaccine in the future (p = .006, OR=1.70, 95% CI: 1.17 ~ 2.47) and who had no adverse effect after COVID-19 vaccination (p = .030, OR = 1.54, 95% CI: 1.04 ~ 2.27) had a higher IVR. Moreover, IVR was higher among males (p = .042, OR = 1.41, 95% CI: 1.01 ~ 1.96) and respondents with education above middle school (p = .036, OR = 1.88, 95% CI: 1.04 ~ 3.39). See Table 3 for details.

Discussion

To the best of our knowledge, this paper may be the first study to show IVR among residents in Anhui, and it may also be one of the few studies focusing on the relationship between residents’ influenza vaccination and COVID-19 perceptions and behaviors in China. We saw a relatively high influenza vaccine coverage among residents who considered themselves likely to be infected with COVID-19. Different COVID-19 behaviors were associated with IVRs. Males and participants with a higher education level were associated with a higher influenza vaccination coverage.

It was found that IVR among 833 respondents in 8 communities in Anhui was 27.85%, which is consistent with the study conducted in Hong Kong (29.1%), and higher than the pooled IVR of 16.74% in different studies.^11,24 Chinese residents demonstrated a clear shift in attitudes toward influenza vaccination, with more enthusiasm for vaccination, under the background of COVID-19. The study conducted in Shanghai, China, showed that children’s willingness to receive influenza vaccine has increased significantly compared to that of pre-COVID-19-pandemic (78.4% VS 64.8%).²⁵

The great majority of influenza vaccinations were organized by schools or work units in China.²⁶ After the COVID-19 outbreak, most influenza vaccinations were still organized by schools and work units.²⁷ Silva discovered that students generally had positive attitudes toward influenza vaccine, and most students indicated that influenza vaccination was the best way to reduce healthcare visits for them.²⁸ This survey was conducted during the summer vacation. Compared to other studies, there were more students (22.45%). They may be organized to get the influenza vaccine by their schools. Compared to the IVR of elderly people in Taizhou, Zhejiang province (43.15%), we have a lower influenza vaccination rate.²⁹ The fact that some cities with higher development and Gross Domestic Product (GDP) have provided free influenza vaccine for the high-risk groups, has served as a remarkable stimulus for local influenza vaccination.¹⁵ However, the strategy of free influenza vaccination for high-risk populations has not been implemented in Anhui province.

The study showed that there was a relationship between residents’ perception of susceptibility to COVID-19 virus with their influenza vaccination, which was consistent with Sulis G’s findings.³⁰ It was contended that perceived disease susceptibility and severity were significantly related to human health-related behaviors, and people with a stronger perceived susceptibility to COVID-19 infection had stronger motivation to receive influenza vaccine.^31,32 In the early period of COVID-19 outbreak, great panic was generated globally, owing to its unknown virus characteristic. The public awareness of health risks was changed a lot by the emergence of COVID-19 in 2019.³³ People began to notice the seriousness of respiratory infectious diseases. COVID-19 and influenza have similar symptoms.³⁴ Therefore, the COVID-19 was also regarded as an “action prerequisite” for influenza vaccination. The findings provide suggestions to increase the willingness of residents to receive influenza vaccines, for example, by educating the public on the susceptibility and severity of COVID-19 and widely disseminating the positive effects of influenza vaccination on the prevention of COVID-19.

It was found that there was a significant association between respondents’ influenza vaccination and COVID-19 vaccination. Although we don’t know whether the respondents were vaccinated with influenza vaccine or COVID-19 vaccine first, it is worth noting that there is a certain relationship between them. It was indicated that prior vaccination experiences could shape positive attitudes toward vaccines and contribute to subsequent vaccine uptake.³⁵ Parker also reported that COVID-19 vaccination was positively correlated with influenza vaccination.³⁶ A study of influenza and COVID-19 vaccination found that residents who received the last seasonal influenza vaccine increased their willingness to receive COVID-19 vaccine.³⁷

Our findings showed that 23.65% of respondents experienced adverse reactions after receiving COVID-19 vaccine, which was similar to previous research results.³⁸ They also had a lower IVR. It was found that adverse reactions after vaccination could cause vaccination refusal. Minor adverse reactions after vaccination might illustrate that the vaccine was arousing recipient’s immune system, while serious adverse reactions could pose a perilous danger, and thus cause vaccination hesitancy.^39–41 It is suggested that governments should conduct health education programs regarding adverse reactions after vaccination.

Our study also showed that the residents who expressed their reluctance to receive COVID-19 vaccines in the future exhibited a higher influenza vaccination rate compared to other people. It was notable that a rise in COVID-19 vaccination rate might be related to the decrease in IVR.⁴² This might be a sign that people were likely to just choose one from influenza vaccine or COVID-19 vaccine. Simultaneous immunization with the COVID-19 vaccine and influenza vaccine is being seriously studied by academics.^43,44 It was discussed that co-administration of COVID-19 and influenza vaccination could effectively reduce health system pressure because of organizing and providing vaccination services.^45,46 The Joint Committee on Vaccination and Immunisation (JCVI) in the United Kingdom recommended a synergistic program of vaccination for influenza and COVID-19, and indicated that this approach might maximize uptake of both vaccines.^47,48 A Chinese study found immune interference for individuals was more significant when the influenza vaccine was co-administrated with a booster dose of the COVID-19 vaccine.^49,50 Vaccination strategy was suggested to consider the capacity of vaccination services in different regions and health conditions aimed at different populations.⁴⁴ It is also important to investigate residents’ attitudes toward co-administration, which could help policymakers and healthcare workers gain valuable insights into public perceptions, concerns, and preferences regarding receiving multiple vaccinations simultaneously.

It was suggested in the present study that a higher education level was associated with a higher influenza vaccination rate. It was consistent with prior studies which showed that higher educational levels were associated with increased acceptance and utilization of influenza vaccination.⁵¹ However, Prada-Garcia figured out that the person with a lower education level was associated with a better willingness to vaccinate, because of their heightened conformity to medical advice and the influence of others in their decision-making process.⁵² We argued that residents with higher education levels have a more comprehensive understanding of disease susceptibility and vaccine effectiveness during the epidemic of COVID-19. These may have a positive effect on their vaccination willingness.

Additionally, there was a significant correlation between gender and influenza vaccination. Studies showed that females were far more hesitant to receive vaccines than males.^53,54 Such variances primarily stemmed from the physiological difference between males and females. Females roughly had twice the protective antibody reactions in vaccination as males and females typically experienced more frequent both local and general side adverse reactions to vaccines.⁵⁵ Women’s commonly perceived caregiving roles may delay their healthcare-seeking behaviors, and reduce their vaccination willingness.⁵⁴

The study has some limitations. First, it is not a random sampling. Therefore, it may be not prudent to extend our research findings to other cities in China without full discussion. Second, this paper was only a cross-sectional study. The individual’s perception and willingness toward influenza vaccine might change over time, and it was limited in establishing a causal relationship between influenza vaccination and sociodemographic variables, the perception of COVID-19, as well as COVID-19 vaccination behavior.

Conclusion

Although public enthusiasm for influenza vaccination has increased a little after the COVID-19 outbreak, there is still a large gap between the influenza vaccination rate in China and recommended by the WHO (75%).⁵⁶ The provision of free influenza vaccines remains limited, catering solely to certain populations in China. Our study showed that the higher IVR was associated with a better perception of COVID-19 and fewer adverse reactions to COVID-19 vaccination. The lower IVR was among residents who would continue to receive COVID-19 vaccine in the future, which has not been discussed in other studies.

The government should thoroughly examine the feasibility of simultaneous immunization with COVID-19 and influenza vaccines. Additionally, there is a need to enhance the supply of influenza vaccines to meet the increased demand. This can also involve incorporating the influenza vaccine into the NEPI, which would help ensure wider accessibility and coverage. Furthermore, providing monitoring and assistance for residents who experience adverse reactions after vaccination is crucial. Improving the satisfaction of residents in the whole process of vaccination and encouraging them, especially the high-risk residents, is also important.

To overcome the inherent limitations of cross-sectional analysis, continuing this study and conducting cohort studies in the future are necessary. We should also expand the scope of this study to reduce bias and make study results more representative.

Author contributions

MG and JL contributed equally to this work. LW and RC designed the study described in this article. JL and YW conducted the investigation and participated in data collection, and GC oversaw all aspects of data collocation. MG conducted the statistical analyses, and LW and JL participated in some of the statistical analyses. MG and JL wrote the preliminary and the corrected versions of the manuscript with advice from RC and LW. All authors contributed to the study design, conduct of the study, and the final manuscript. All authors have read and approved the final manuscript.

Ethics approval and consent to participate

Approval to conduct this study was obtained from the Biomedical Ethics Committee at Anhui Medical University (IRB number: 20210614). Informed consent to utilize the collected information for research purposes was obtained from all participants.

Disclosure statement

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

Additional information

Funding

This work was supported by the Key Natural Science Foundation for Universities in Anhui Province, China, under Grant [KJ2021A0260]; Scientific Research Projects for Higher Education of Anhui Province under Grant [2023AH010036]; NHC Key Laboratory of Health Economics and Policy Research (Shandong University) under Grant [NHC-HEPR2019009]; National Natural Science Foundation of China under Grant [72111530207]; and the Excellent Scholar Talents’ Training in Universities of Anhui Province, China, under Grant [gxyq2020153].

Notes

[a] The new community is defined as a community newly developed in the past 10 years, and usually located in the new investment and development zone in the city. Old community refers to community that has been built and used for more than 10 years and is generally located in old downtown in the city. The relocated community means a community built by the government for resettling residents whose own houses were used for public affairs. Unit community refers to the community built by the work unit to solve its employees’ living and housing problems, and most of the residents in the community are employees from the same work unit.