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Globally, the rollout of COVID-19 vaccine had been faced with a significant barrier in the form of vaccine hesitancy. This study adopts a multi-stage perspective to explore the prevalence and determinants of COVID-19 vaccine hesitancy, focusing on their dynamic evolutionary features. Guided by the integrated framework of the 3Cs model (complacency, confidence, and convenience) and the EAH model (environmental, agent, and host), this study conducted three repeated national cross-sectional surveys. These surveys carried out from July 2021 to February 2023 across mainland China, targeted individuals aged 18 and older. They were strategically timed to coincide with three critical vaccination phases: universal coverage (stage 1), partial coverage (stage 2), and key population coverage (stage 3). From 2021 to 2023, the surveys examined sample sizes of 29 925, 6659, and 5407, respectively. The COVID-19 vaccine hesitation rates increased from 8.39% in 2021 to 29.72% in 2023. Urban residency, chronic condition, and low trust in vaccine developer contributed to significant COVID-19 vaccine hesitancy across the pandemic. Negative correlations between the intensity of vaccination policies and vaccine hesitancy, and positive correlations between vaccine hesitancy and long COVID, were confirmed. This study provides insights for designing future effective vaccination programs for emerging vaccine-preventable infectious X diseases.

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BACKGROUND: Vaccination plays an important role in preventing COVID-19 infection and reducing the severity of the disease. There are usually differences in vaccination rates between urban and rural areas. Measuring these differences can aid in developing more coordinated and sustainable solutions. This information also serves as a reference for the prevention and control of emerging infectious diseases in the future. OBJECTIVE: This study aims to assess the current coverage rate and influencing factors of COVID-19 (second booster) vaccination among Chinese residents, as well as the disparities between urban and rural areas in China. METHODS: This cross-sectional study used a stratified random sampling approach to select representative samples from 11 communities and 10 villages in eastern (Changzhou), central (Zhengzhou), western (Xining), and northeast (Mudanjiang) Mainland China from February 1 to February 18, 2023. The questionnaires were developed by experienced epidemiologists and contained the following: sociodemographic information, health conditions, vaccine-related information, information related to the Protective Motivation Theory (PMT), and the level of trust in the health care system. Vaccination rates among the participants were evaluated based on self-reported information provided. Binary logistic regression models were performed to explore influencing factors of vaccination among urban and rural participants. Urban-rural disparities in the vaccination rate were assessed using propensity score matching (PSM). RESULTS: A total of 5780 participants were included, with 53.04% (3066/5780) being female. The vaccination rate was 12.18% (704/5780; 95% CI 11.34-13.02) in the total sample, 13.76% (341/2478; 95% CI 12.40-15.12) among the rural participants, and 10.99% (363/3302; 95% CI 9.93-12.06) among the urban participants. For rural participants, self-reported health condition, self-efficacy, educational level, vaccine knowledge, susceptibility, benefits, and trust in the health care system were independent factors associated with vaccination (all P＜.05). For urban participants, chronic conditions, COVID-19 infection, subjective community level, vaccine knowledge, self-efficacy, and trust in the health care system were independent factors associated with vaccination (all P＜.05). PSM analysis uncovered a 3.42% difference in vaccination rates between urban and rural participants. CONCLUSIONS: The fourth COVID-19 vaccination coverage rate (second booster) among the Chinese population was extremely low, significantly lower than the previous vaccine coverage rate. Given that COVID-19 infection is still prevalent at low levels, efforts should focus on enhancing self-efficacy to expand the vaccine coverage rate among the Chinese population. For rural residents, building awareness of the vaccine's benefits and improving their overall health status should be prioritized. In urban areas, a larger proportion of people with COVID-19 and patients with chronic illness should be vaccinated.

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This study aimed to evaluate how the duration of travel affects the behavior of urban and rural residents regarding free COVID-19 vaccination, and provide scientific evidence for promoting free vaccination and building an immune barrier to cope with future epidemics. From August 3, 2022 to February,18,2023, A follow-up survey was conducted in urban and rural adults in four cities in China to collect information on socio-demographic factors, vaccination status and travel time for vaccination. Propensity score matching (PSM) analysis was deployed to measure the net difference of the enhanced vaccination rate between urban and rural residents in different traffic time distribution. A total of 5780 samples were included in the study. The vaccination rate of the booster dose of COVID-19 vaccine among rural residents was higher than that of urban residents with a significant P-value (69.36% VS 64.49%,p < .001). The traffic time had a significant negative impact on the COVID-19 booster vaccination behavior of urban and rural residents. There was a significant interaction between the travel time to the vaccination point and the level of trust in doctors. Travel time had a negative impact on the free vaccination behavior of both urban and rural residents. The government should optimize and expand the number of vaccination sites and enhance residents' trust in the medical system. This is crucial for promoting free vaccination and effective epidemic management in the future.

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BACKGROUND: The public health service capability of primary healthcare personnel directly affects the utilization and delivery of health services, and is influenced by various factors. This study aimed to examine the status, factors, and urban-rural differences of public health service capability among primary healthcare personnel, and provided suggestions for improvement. METHODS: We used cluster sampling to survey 11,925 primary healthcare personnel in 18 regions of Henan Province from 20th to March 31, 2023. Data encompassing demographics and public health service capabilities, including health lifestyle guidance, chronic disease management, health management of special populations, and vaccination services. Multivariable regression analysis was employed to investigate influencing factors. Propensity Score Matching (PSM) quantified urban-rural differences. RESULTS: The total score of public health service capability was 80.17 points. Chronic disease management capability scored the lowest, only 19.60. Gender, education level, average monthly salary, professional title, health status, employment form, work unit type, category of practicing (assistant) physician significantly influenced the public health service capability (all P < 0.05). PSM analysis revealed rural primary healthcare personnel had higher public health service capability scores than urban ones. CONCLUSIONS: The public health service capability of primary healthcare personnel in Henan Province was relatively high, but chronic disease management required improvement. Additionally, implementing effective training methods for different subgroups, and improving the service capability of primary medical and health institutions were positive measures.

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BACKGROUND: Healthy lifestyle behaviors (LBs) have been widely recommended for the prevention and management of cardiovascular disease (CVD). Despite a large number of studies exploring the association between combined LBs and CVD, a notable gap exists in integration of relevant literatures. We conducted a systematic review and meta-analysis of prospective cohort studies to analyze the correlation between combined LBs and the occurrence of CVD, as well as to estimate the risk of various health complications in individuals already diagnosed with CVD. METHODS: Articles published up to February 10, 2023 were sourced through PubMed, EMBASE and Web of Science. Eligible prospective cohort studies that reported the relations of combined LBs with pre-determined outcomes were included. Summary relative risks (RRs) and 95% confidence intervals (CIs) were estimated using either a fixed or random-effects model. Subgroup analysis, meta-regression, publication bias, and sensitivity analysis were as well performed. RESULTS: In the general population, individuals with the healthiest combination of LBs exhibited a significant risk reduction of 58% for CVD and 55% for CVD mortality. For individuals diagnosed with CVD, adherence to the healthiest combination of LBs corresponded to a significant risk reduction of 62% for CVD recurrence and 67% for all-cause mortality, when compared to those with the least-healthy combination of LBs. In the analysis of dose-response relationship, for each increment of 1 healthy LB, there was a corresponding decrease in risk of 17% for CVD and 19% for CVD mortality within the general population. Similarly, among individuals diagnosed with CVD, each additional healthy LB was associated with a risk reduction of 27% for CVD recurrence and 27% for all-cause mortality. CONCLUSIONS: Adopting healthy LBs is associated with substantial risk reduction in CVD, CVD mortality, and adverse outcomes among individuals diagnosed with CVD. Rather than focusing solely on individual healthy LB, it is advisable to advocate for the adoption of multiple LBs for the prevention and management of CVD. TRIAL REGISTRATION: PROSPERO: CRD42023431731.

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Objective: To evaluate the prevalence and influencing factors of long COVID, and measure the difference in health status between long COVID and non-long COVID cases. Methods: A cross-sectional survey was conducted from February 1 to 8, 2023, using a stratified random sampling method in four regions (eastern [Changzhou], central [Zhengzhou], western [Xining] and northeastern [Mudanjiang]) of China. The survey collected COVID-19 patients' socio-demographic characteristics and lifestyles information. The scores of lifestyles and health status range from 5 to 21 and 0 to 100 points, respectively. The criteria of "persistent health problems after 4 weeks of COVID-19 infection" issued by the US Centers for Disease Control and Prevention was used to assess long COVID. Multiple linear regression was used to analyze the influencing factors of the health. The bootstrap method was used to analyze the lifestyles' mediating effect. Propensity score matching (PSM) was used to evaluate the net difference in health scores between long COVID and non-long COVID cases. Results: The study included 3165 COVID-19 patients, with 308 (9.73%) long COVID cases. The health score of the long COVID cases (74.79) was lower than that of the non-long COVID cases (81.06). After adjusting for potential confounding variables, we found that never focused on mental decompression was a common risk factor for the health of both groups. Lifestyles was the mediating factor on individuals' health. After PSM, the non-long COVID cases' health scores remained higher than that of long COVID cases. Conclusion: The proportion of long COVID cases was low, but they were worse off in health. Given the positive moderating effect of healthy lifestyles on improving the health of long COVID cases, healthy lifestyles including mental decompression should be considered as the core strategy of primary prevention when the epidemic of COVID-19 is still at a low level.

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During the COVID-19 pandemic, the vaccine hesitancy has significantly affected the vaccination. To evaluate the booster vaccine hesitancy and its influencing factors among urban and rural residents, as well as to estimate the net difference of booster vaccine hesitancy between urban and rural residents. We conducted a nationwide, cross-sectional Internet survey on 1-8 February 2023, and employed stratified random sampling technique to select participants (≥18 years old) from urban and rural areas. Multivariate logistic regression was used to determine the factors impacting booster vaccine hesitancy. Propensity Score Matching was used to estimate the net difference of COVID-19 booster vaccine hesitancy between urban and rural residents. The overall COVID-19 booster vaccine hesitancy rate of residents was 28.43%. The COVID-19 booster vaccine hesitancy rate among urban residents was found to be 34.70%, among rural residents was 20.25%. Chronic diseases, infection status, vaccination benefits, and trust in vaccine developers were associated with booster vaccine hesitancy among urban residents. Barriers of vaccination were associated with booster vaccine hesitancy among rural residents. PSM analysis showed that the urban residents have a higher booster vaccine hesitancy rate than rural residents, with a net difference of 6.20%. The vaccine hesitancy rate increased significantly, and the urban residents have a higher COVID-19 booster vaccine hesitancy than rural residents. It becomes crucial to enhance the dissemination of information regarding the advantages of vaccination and foster greater trust among urban residents toward the healthcare system.

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AIMS AND OBJECTIVES: To investigate whether chronic diseases are associated with higher COVID-19 vaccine hesitancy and explore factors that influence COVID-19 vaccine hesitancy in patients with chronic diseases. BACKGROUND: Vaccine hesitancy has been acknowledged as one of the greatest hazards to public health. However, little information is available about COVID-19 vaccine hesitancy among patients with chronic diseases who may be more susceptible to COVID-19 infection, severe disease or death. METHODS: From 6 to 9 August 2021, we performed an internet-based cross-sectional survey with 22,954 participants (14.78% participants with chronic diseases). Propensity score matching with 1:1 nearest neighbourhood was used to reduce confounding factors between patients with chronic diseases and the general population. Using a multivariable logistic regression model, the factors impacting COVID-19 vaccine hesitancy were identified among patients with chronic diseases. RESULTS: Both before and after propensity score matching, patients with chronic diseases had higher COVID-19 vaccine hesitancy than the general population. In addition, self-reported poor health, multiple chronic diseases, lower sociodemographic backgrounds and lower trust in nurses and doctors were associated with COVID-19 vaccine hesitancy among patients with chronic diseases. CONCLUSIONS: Patients with chronic diseases were more hesitant about the COVID-19 vaccine. Nurses should focus on patients with chronic diseases with poor health conditions, low socioeconomic backgrounds and low trust in the healthcare system. RELEVANCE TO CLINICAL PRACTICE: Clinical nurses are recommended to not only pay more attention to the health status and sociodemographic characteristics of patients with chronic diseases but also build trust between nurses and patients by improving service levels and professional capabilities in clinical practice. PATIENT OR PUBLIC CONTRIBUTION: Patients or the public were not involved in setting the research question, the outcome measures, or the design or implementation of the study. However, all participants were invited to complete the digital informed consent and questionnaires.

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Background: COVID-19 vaccine hesitancy has been cited as one of the main obstacles impacting vaccine coverage. However, factors that affect hesitancy may change over time. Understanding these evolving concerns and adapting strategies accordingly are crucial for effectively addressing vaccine hesitancy effectively and promoting public health. We aimed to explore the temporal changes in factors associated with COVID-19 VH during the COVID-19 pandemic and assess the dynamic evolution of VH. Methods: In August 2022 and February 2023, repeated online surveys were undertaken to collect information from 5378 adults across four regions of China. Multiple linear regression models assessed the influencing factors of COVID-19 VH. The association between protective motive theory (PMT) (perceived severity, susceptibility, benefits, barriers, and self-efficacy) and VH was evaluated by structural equation modeling (SEM). Results: Repeated measures showed that 573 (10.7%) and 1598 (29.7%) of the 5378 participants reported COVID-19 VH in the baseline and follow-up surveys, respectively. Educational levels, chronic disease, history of allergy, COVID-19 infection, and trust in medical staff and vaccine developers were positively associated with COVID-19 VH (P＜0.05). The application of SEM revealed that perceived severity, susceptibility, vaccination barriers, and self-efficacy in the PMT directly impacted on VH (P＜0.05). In addition, severity, susceptibility, benefits, and barriers had a significant direct effect on self-efficacy as ß = 0.113, ß = 0.070, ß = 0.722, ß = -0.516 respectively with P < 0.001. Conclusion: The prevalence of COVID-19 VH was relatively low in the baseline survey and much higher in the follow-up survey, with a significant increase in hesitancy rates among mainland Chinese residents. Acknowledging the substantial impact on the shaping of COVID-19 VH, one must consider factors including perceived severity, susceptibility, vaccination barriers, and self-efficacy.

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BACKGROUND: COVID-19 is still prevalent in most countries around the world at the low level. Residents' lifestyle behaviors and emotions are critical to prevent COVID-19 and keep healthy, but there is lacking of confirmative evidence on how residents' lifestyle behaviors and emotional expressivity affected COVID-19 infection. METHODS: Baseline study was conducted in August 2022 and follow-up study was conducted in February 2023. Baseline survey collected information on residents' basic information, as well as their lifestyle behaviors and emotions. Follow-up study was carried out to gather data on COVID-19 infection condition. Binary logistic regression was utilized to identify factors that may influence COVID-19 infection. Attributable risk (AR) was computed to determine the proportion of unhealthy lifestyle behaviors and emotional factors that could be attributed to COVID-19 infection. Sensitivity analysis was performed to test the robustness of the results. RESULTS: A total of 5776 participants (46.57% males) were included in this study, yielding an overall COVID-19 infection rate of 54.8% (95%CI: 53.5 - 56.0%). The findings revealed that higher stress levels [aOR = 1.027 (95%CI; 1.005-1.050)] and lower frequency in wearing masks, washing hands, and keeping distance [aOR = 1.615 (95%CI; 1.087-2.401)], were positively associated with an increased likelihood of COVID-19 infection (all P < 0.05). If these associations were causal, 8.1% of COVID-19 infection would have been prevented if all participants had normal stress levels [Attributable Risk Percentage: 8.1% (95%CI: 5.9-10.3%)]. A significant interaction effect between stress and the frequency in wearing masks, washing hands, and keeping distance on COVID-19 infection was observed (ß = 0.006, P < 0.001), which also was independent factor of COVID-19 infection. CONCLUSIONS: The overall COVID-19 infection rate among residents is at a medium level. Residents' increasing stress and decreasing frequency in wearing masks and washing hands and keeping distance contribute to increasing risk of infection, residents should increase the frequency of mask-wearing, practice hand hygiene, keep safe distance from others, ensure stable emotional state, minimize psychological stress, providing evidence support for future responses to emerging infectious diseases.

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RATIONALE: Although urban-rural residency has been shown to influence individual COVID-19 vaccine hesitancy, the differences between urban and rural China have yet to be uncovered. OBJECTIVE: This study aims to assess the current prevalence and factors associated with COVID-19 vaccine hesitancy in urban and rural areas and explore whether the rural versus urban residency is associated with COVID-19 vaccine hesitancy. METHODS: A national, cross-sectional, online survey among Chinese urban and rural adults (≥18 years old) was conducted from 6th to August 9, 2021. A questionnaire was used to collect data on sociodemographic factors, perceptions of the COVID-19 pandemic and vaccination status. A multivariable logistic regression model was used to identify the factors that influence COVID-19 vaccine hesitancy. Propensity score matching (PSM) analysis was performed to explore the association between urban versus rural residency and COVID-19 vaccine hesitancy. RESULTS: In total, 29,925 participants (80.56% urban participants) were recruited. Urban participants had a higher COVID-19 vaccine hesitancy than their rural counterparts (9.39% vs. 4.26%). After adjusting for potential confounders, we found that COVID-19 vaccine hesitancy among females was lower than that in males in both urban (aOR = 0.78, 95% CI [0.69-0.88]) and rural areas (aOR = 0.54, 95% CI [0.39-0.75]). The lack of trust towards vaccine producers was found to be associated with vaccine hesitancy among the urban participants (aOR = 2.76, 95% CI [2.22-3.43]). The rural floating population had a lower COVID-19 vaccine hesitancy than the rural permanent residents (aOR = 0.58, 95% CI [0.42-0.80]). PSM analysis revealed a 2.38% difference in COVID-19 vaccine hesitancy between urban and rural participants. CONCLUSIONS: Urban participants were more hesitant to receive the COVID-19 vaccine than rural participants. Priority should be placed on boosting confidence in the healthcare system to reduce COVID-19 vaccine hesitancy among urban residents. Furthermore, we advocate for extra incentives and vaccination education for rural permanent residents.

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OBJECTIVE: To assess the association between lifestyle and COVID-19 vaccine hesitancy among Chinese adults and provide recommendations for increasing vaccination rates. METHODS: From August 6, 2021 to August 9, 2021, we recruited 29,925 participants from 31 Chinese provinces via an online questionnaire. We designed a question to assess COVID-19 vaccine hesitancy and used 16 items to assess lifestyle by calculating lifestyle scores. Odds ratios (OR) with 95 % confidence intervals (CI) were used to estimate the association by using binary logistic regression models. RESULTS: The overall prevalence of COVID-19 vaccine hesitancy was 8.40 % (95 % CI: 8.09-8.72), and the median lifestyle score was 65.00 (interquartile range: 59.00-71.00). After adjusting for potential confounders, the COVID-19 vaccine hesitancy rate decreased significantly with an increase in lifestyle score (P for Trend <0.001). Low COVID-19 vaccine hesitancy rate was associated with lifestyle factors including adequate sleep, never smoking, intermittent drinking, good relationships, working and studying, using hand sanitizer, wearing masks, less gathering activities, and keeping social distance (P < 0.05). CONCLUSION: Our findings indicate that high lifestyle score is associated with low vaccine hesitancy rate among Chinese. The government should view the smokers (or the drinkers) as the key to further boosting the vaccination rate. In addition, the publicity and education about wearing masks and keeping social distance should be prioritized.

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