Abstract
Background
Influenza-related respiratory diseases account for approximately 88,000 deaths annually in China. Vaccination against influenza is the most effective measure to prevent the virus and its potentially severe complications. This study aims to assess influenza awareness, vaccination coverage, and factors influencing vaccination uptake among rural populations in northern China after the COVID-19 pandemic.
Methods
A cross-sectional study was conducted from June 1 to June 20, 2020, targeting older population residents aged 60 years and above in rural areas of Tianjin, China. A total of 1265 participants were enrolled. Data were collected through pre-designed, face-to-face questionnaires, encompassing demographic information, physical examination results, medical history, awareness of influenza, and vaccination status. The study analyzed the levels of influenza awareness, vaccination rates, and factors associated with vaccine uptake.
Results
The influenza awareness rate among participants was 84.9%, while the 5-year vaccination rate was notably low at 7.4%. Participants with coronary heart disease (CHD) exhibited significantly higher 5-year vaccination rates compared to those without CHD (OR = 2.625, 95% CI: 1.564–4.405, p < 0.001). Additionally, participants in the medium (OR = 6.096, 95% CI: 1.854–20.041, p = 0.003) and high (OR = 7.179, 95% CI: 2.211–23.305, p = 0.001) awareness groups were more likely to be vaccinated compared to those in the low awareness group.
Conclusions
Addressing factors that influence 5-year vaccination rates and enhancing awareness can substantially improve vaccine coverage, thereby mitigating the burden of influenza-related diseases. Future public health strategies should prioritize comprehensive vaccination programs and ongoing education to achieve higher vaccination rates and improved health outcomes for the rural older population.
Supplementary information
The online version contains supplementary material available at 10.1186/s12913-026-14273-z.
Keywords: Influenza, Awareness, Vaccination, Epidemiology, Older population
Background
Seasonal influenza is associated with approximately 290,000– 640,000 deaths worldwide each quarterly, accounting for approximately 0.5%–1.0% of all deaths [1, 2]. Approximately 88,000 people die from influenza-related respiratory diseases in China yearly [2]. Influenza vaccination is the most effective measure for preventing influenza and its potentially serious complications. It can reduce influenza-related morbidity and mortality [3, 4], and it clearly reduces the harm caused by influenza-related diseases in the older population and in patients with chronic diseases [5, 6].
While the influenza vaccination rate for people over 65 years old is above 65% in some developed countries [7–9], the vaccination rate for the older population in China is very low (<1% in some areas). Cities that offer free flu vaccination, such as Beijing and Shanghai, the influenza vaccination rate is 30–40% but is still notably lower than the 75% influenza vaccination coverage proposed by the World Health Organization (WHO) for the older population [8, 10, 11]. A previous study reported that the influenza vaccination rates among children varied significantly between urban and rural areas [12]. During the COVID-19 pandemic, due to the widespread vaccination of the the COVID-19 vaccine, people also have a newer and wider understanding of the influenza vaccine. Research shows that flu vaccination rates have increased during the COVID-19 pandemic. Affected by the COVID-19 pandemic, during the 2020–2021 flu season, the demand for influenza vaccination in China has surged, and the number of vaccinations has doubled. The vaccination rate has increased from 1% to 3% previously to 4% [13].
Previous studies have shown that age, socioeconomic status, education, marital status, smoking, and health status can affect vaccination [14–16]. A multicenter study in China also emphasized the role of vaccination subsidies and the status of healthcare workers [17]. However, data on vaccination rates and influencing factors in rural China remain limited. The Chinese Guidelines on Influenza Vaccine Prevention (2023–2024) recommend the annual influenza vaccination to all non-contraindicated residents aged six months and older [18]. Some major cities, such as Beijing and Shenzhen, have enacted policies offering free influenza vaccines to specific high-risk groups. However, the influenza vaccination rate is still low in many regions of China due to local health policies, the limitations of residents’ knowledge, lack of public vaccine awareness, and prevention education [19].
With the COVID-19 epidemic, the prevention of epidemics is receiving more attention [20]. Therefore, this study aimed to explore the influenza awareness and vaccination status among the older population in rural areas in northern China during the COVID-19 pandemic and to identify factors that affect the influenza vaccination rate.
Methods
Population
The population of this study was obtained from the Tianjin Brain Research Cohort [21], which was a population-based, cross-sectional study conducted from June 1, 2020 to June 20, 2020 in rural areas of Tianjin, China. The Tianjin Brain Study started in 1985 and is a population-based cohort study. Mainly to monitor the incidence of stroke and its risk factors in low-income residents of Tianjin, China, covering 18 administrative villages, which can represent the rural population of Tianjin. Approximately 95% of the individuals in this study were low-income farmers who had low educational levels, with a 2014 disposable income per capita of < 1600 USD [22].
This was a community-based observational study using a stratified cluster sampling design. The sample size was determined by the total number of eligible participants within the selected clusters rather than by a formal a priori sample size calculation. According to the geographical location, Yangjinzhuang Town was divided into 4 areas in the east, south, west, and north directions, and 2 administrative villages are randomly selected in each area. There are 2629 villagers aged 60 and above in the eight administrative villages.
The inclusion criteria for this study were as follows: (1) participant age ≥ 60 years and (2) participants’ household registrations consistent with their current residences. We excluded those (1) unable to communicate due to hearing or visual impairment; (2) who could not visit the physical examination site because of long-term bed rest and mobility issues; (3) who had mental illness and could not cooperate during the questionnaire administration (psychiatric history obtained from the medical records of the health center); and (4) who refused to provide informed consent for the study. A total of 1485 residents ≥ 60 years old participated in this study, and 218 subjects had incomplete information because they did not complete other routine examinations. Questionnaires for 2 subjects were incomplete. Finally, this study included 1265 participants (Fig. 1). Psychiatric history obtained from the medical records of the health center.
Fig. 1.
Flowchart of participant selection. Of the 1485 residents aged 60 years or older who completed the initial survey, 218 did not undergo physical examination. After applying inclusion criteria, 1267 participants were eligible, and 2 were excluded due to missing questionnaire data, resulting in a final analytical sample of 1265 participants
The study has passed the ethics committee of the General Hospital of Tianjin Medical University (IRB2018-100–01, 2018.8.31), and all participants have signed the informed consent.
Data collection
Predesigned questionnaires were used to collect participant information in a face-to-face manner (Supplementary material). All staff participating in the study underwent uniform questionnaire training. The questionnaire was divided into a general section and an influenza-related section.
The general section consisted of three parts: demographics, lifestyle details, and medical history. The influenza section comprised two parts: influenza and vaccine-related awareness and influenza vaccination. The influenza and vaccine-related awareness portion focused on influenza- (influenza symptoms, high-risk groups, transmission routes, hazards, and prevention) and vaccine-related (vaccine action time, effect, population suitable for vaccination, factors affecting influenza vaccination) information. There are a total of 7 questions for influenza and vaccine related awareness scoring, and different scores are obtained based on different options for each question. All scores are accumulated and added together, and the total score ranges from 0 to 9 points (Supplementary Table 1). The Cronbach’s alpha coefficient of the questionnaire is 0.762. Influenza vaccination is defined as having been vaccinated against any type of influenza in the past five years (according to the vaccination records of the health center).
Physical examination
Physical examination including height, weight, waist, hip, blood pressure, heart rate. The instrument used for measuring height and weight is Shanghai Luculent Height and Weight Measuring Instrument LK-300 (Shanghai Luculent Weighing Equipment Co., Ltd.), the height measurement value can be accurate to 1 mm, and the weight measurement value can be accurate to 0.1 kg. Blood pressure measurement adopts Omron HEM-1000 model blood pressure monitor.
Influenza awareness scoring rules
Influenza and influenza vaccine awareness was assessed using a 7-item questionnaire, with individual items scored according to predefined criteria reflecting the correctness and completeness of responses. For Item 1 (transmission routes of influenza), responses were scored as 0 points for incorrect or no answer, 1 point if one correct transmission route was identified, and 2 points if two or more correct routes were identified. Correct routes included droplet transmission, contact transmission, and aerosol transmission. For Item 3 (prevention of influenza), responses were scored as 0 points for incorrect or no answer, 1 point if one correct preventive measure was identified, and 2 points if two or more correct preventive measures were identified. Accepted preventive measures included influenza vaccination, hand hygiene, respiratory etiquette, reduced exposure to crowded places, enhancement of individual immunity, adequate ventilation, avoidance of contact with infected individuals, and timely medical consultation and isolation. Items 2 and 4 were scored on a binary scale (0–1 point), and Items 5–7 were single-choice knowledge questions scored as 1 for a correct response and 0 for an incorrect response. The total awareness score was calculated as the sum of all individual item scores, yielding a possible range from 0 to 9 points. (Supplementary Table 1)
Definition of variables
The participants were divided into three age groups: 60–64, 65–69, and ≥70 years. Participant educational levels were classified into two groups: 0–6 and >6 years of formal education. Cigarette smoking was defined as smoking more than 1 cigarette/day for ≥1 year [23]; participants were categorized as non-smokers, current smokers, or previous smokers. Alcoholism was defined as drinking > 500 g of alcohol/week for ≥1 year; participants were categorized as non-drinkers, past drinkers, or current drinkers [24]. Body mass index (BMI) was classified as low (BMI < 18.5 kg/m2), normal (BMI 18.5–23.9 kg/m2), overweight (BMI 24.0–27.9 kg/m2), and obese (BMI ≥ 28.0 kg/m2) groups [25]. Medical histories were self-reported by the participants (including hypertension, coronary heart disease [CHD], diabetes, stroke, and cancer).
The full score of the influenza-related awareness questionnaire is 9 points. The total score ≥ 6 is the high awareness group; 3–5 is divided into the moderate awareness group, and 0–2 is divided into the low awareness group.
Statistical analyses
The Shapiro-Wilk test was used to detect continuous variables, which all had skewed distributions. Data are presented as proportions, medians, and interquartile ranges (25–75%). Differences between vaccination group and unvaccinated group were analyzed using the Wilcoxon rank-sum and Fisher tests. Categorical variables, including age group, educational level, income group, smoking status, alcoholism, hypertension, CHD, diabetes, stroke, cancer, and influenza awareness levels, are presented as numbers and percentages, and between-group comparisons were performed using the x2 tests.
Multiple logistic regression models was used to evaluate the factors influencing influenza vaccination rates. This study selected variables with p < 0.05 in univariate models to be included in the multivariate model, including CHD history and awareness of influenza. The dependent variable in the multivariate model was history of influenza vaccination within the past five years (yes/no). The relationships are presented as odds ratios (ORs) with 95% confidence intervals (CIs). All analyses were conducted using SPSS for Windows (version 25.0; SPSS, Chicago, IL, USA). Reported probabilities were two-sided; Statistical significance was set at 0.05.
Results
Demographic information
A total of 1265 subjects aged ≥ 60 years were recruited in this study, of which 45.1% were men and 54.9% were women.
The overall median age was 67.5 years. The median duration of formal education was 5 years (men, 6 years; women, 3 years). In this study, 72.9% of participants had a per capita annual income of <2,000 USD. The prevalence of current smoking was 21.8%, current drinking 28.0%, and obesity 23.5% (Table 1).
Table 1.
Demographic characteristics of participants in this study
| Category | Men | Women | Total |
|---|---|---|---|
| Total: | 570 (45.1) | 695 (54.9) | 1265 (100.0) |
| Age, median (IQR) | 67.67 (64.42, 72.58) | 67.5 (64.1, 71.5) | 67.5 (64.25, 71.88) |
| Age group, n (%) | |||
| 60–64 | 175 (30.7) | 226 (32.5) | 401 (31.7) |
| 65–69 | 193 (33.9) | 237 (34.1) | 430 (34.0) |
| ≥70 | 202 (35.5) | 222 (33.3) | 434 (34.3) |
| Education/years, median (IQR) | 6 (5, 9) | 3 (0, 6) | 5 (1, 8) |
| Education, years, n (%) | |||
| 0–6 | 299 (52.9) | 551 (80.7) | 850 (68.1) |
| >6 | 266 (47.1) | 132 (19.3) | 398 (31.9) |
| Income,CNY/person/m, n (%) | |||
| <2000 | 400 (72.1) | 498 (73.6) | 898 (72.9) |
| ≥2000 | 155 (27.9) | 179 (26.4) | 334 (27.1) |
| Marital status, n (%) | |||
| Unmarried | 9 (1.6) | 7 (1.0) | 16 (1.3) |
| Married | 490 (88.6) | 560 (83.2) | 1050 (85.6) |
| Divorce | 1 (0.2) | 2 (0.3) | 3 (0.2) |
| Bereavement | 53 (9.6) | 104 (15.5) | 157 (12.8) |
| BMI, Kg/m2, median (IQR) | 25.3 (23.4, 27.7) | 25.2 (23.1, 27.9) | 25.3 (23.2, 27.8) |
| BMI, n (%) | |||
| Low weight | 9 (1.6) | 11 (1.6) | 20 (1.6) |
| Normal | 178 (31.2) | 242 (34.4) | 420 (33.0) |
| Overweight | 252 (44.1) | 282 (40.1) | 534 (41.9) |
| Obesity | 132 (23.1) | 168 (23.9) | 300 (23.5) |
| Smoking status, n (%) | |||
| Never smoking | 142 (25.6) | 654 (96.5) | 796 (64.6) |
| Ever smoking | 160 (28.8) | 8 (1.2) | 168 (13.6) |
| Current smoking | 253 (45.6) | 16 (2.4) | 269 (21.8) |
| Alcohol consumption, n (%) | |||
| Never drinking | 156 (28.0) | 650 (95.7) | 806 (65.2) |
| Ever drinking | 79 (14.2) | 5 (0.7) | 84 (6.8) |
| Current drinking | 322 (57.8) | 24 (3.5) | 346 (28.0) |
| SBP, median (IQR) | 141 (128, 154) | 140 (127, 153) | 141 (128, 154) |
| DBP, median (IQR) | 81 (73, 89) | 81 (75, 88) | 81 (74, 89) |
| MMSE, median (IQR) | 25 (22, 27) | 21 (17, 25) | 24 (20, 27) |
| Hypertension, n (%) | 26(8.3) | 34(8.2) | 60(8.3) |
| CHD, n (%) | 9(14.3) | 12(14.6) | 21(14.5) |
| Diabetes, n (%) | 6(7.1) | 13(9.1) | 19(8.3) |
| Stroke, n (%) | 2(2.8) | 10(16.7) | 12(9.1) |
| Cancer, n (%) | 1(100.0) | 1(9.1) | 2(16.7) |
| Taking flu vaccine: | |||
| Yes | 41 (7.1) | 53 (7.5) | 94 (7.3) |
| No | 538 (92.9) | 653 (92.5) | 1191 (92.7) |
BMI: Body Mass Index; SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; CHD:Coronary Heart Disease
Awareness rate of influenza vaccine and influenza
Regarding influenza awareness, 34.7%, 39.5%, and 25.8% of the participants showed low, medium, and high awareness of influenza, respectively. The rates of awareness regarding influenza, influenza transmission routes, susceptible populations, prevention methods, and treatment methods were 84.9%, 55.0%, 68.6%, 64.4%, and 69.2%, respectively. The rates of awareness regarding the influenza vaccine, vaccine onset time, vaccination time, and vaccine prioritization for individuals was 56.3%, 6.7%, 14.7%, and 14.7%, respectively (Table 2).
Table 2.
Comparison of baseline characteristics between vaccinated and unvaccinated participants
| Category | Vaccination group | Unvaccinated group | P |
|---|---|---|---|
| Total | 94 (7.3) | 1191 (92.7) | |
| Sex, n (%) | 0.770 | ||
| Men | 41 (43.6) | 538 (45.2) | |
| Women | 53 (56.4) | 653 (54.8) | |
| Age group/year | 0.062 | ||
| 60–64 | 19 (4.9) | 372 (95.1) | |
| 65–69 | 36 (8.3) | 400 (91.7) | |
| ≥70 | 39 (8.9) | 399 (91.1) | |
| Education/years, median (IQR) | 5 (5, 7) | 5 (1, 8) | 0.550 |
| Education, years | 0.397 | ||
| 0–6 | 67 (7.9) | 783 (92.1) | |
| >6 | 26 (6.5) | 372 (93.5) | |
| Income,CNY/person/mon | 0.636 | ||
| <2000 | 69 (7.7) | 829 (92.3) | |
| ≥2000 | 23 (6.9) | 311 (93.1) | |
| BMI, median (IQR) | 25.7 (22.1, 28.1) | 25.3 (23.2, 27.8) | 0.669 |
| SBP, median (IQR) | 143 (128.5, 158.5) | 140.5 (127, 153) | 0.250 |
| DBP, median (IQR) | 81 (75, 90.5) | 81 (74, 89) | 0.401 |
| MMSE, median (IQR) | 23 (19, 26) | 23 (19, 26) | 0.767 |
| Smoking status, n (%) | 0.065 | ||
| Never smoking | 56 (60.2) | 740 (64.9) | |
| Ever smoking | 20 (21.5) | 148 (13.0) | |
| Current smoking | 17 (18.3) | 252 (22.1) | |
| Alcohol consumption, n (%) | 0.517 | ||
| Never drinking | 59 (63.4) | 747 (65.4) | |
| Ever drinking | 9 (9.7) | 75 (6.6) | |
| Current drinking | 25 (26.9) | 321 (28.1) | |
| Marital status, n (%) | 0.806 | ||
| Unmarried | 1 (1.1) | 15 (1.3) | |
| Married | 80 (88.9) | 970 (85.4) | |
| Divorce | 0 (0.0) | 3 (0.3) | |
| Bereavement | 9 (10.0) | 148 (13.0) | |
| Influenza Awareness, n (%) | 0.001 | ||
| Low awareness group | 3 (1.5) | 202 (98.5) | |
| Moderate Awareness Group | 38 (7.9) | 443 (92.1) | |
| High Awareness Group | 53 (9.2) | 526 (90.8) | |
| Hypertension, n (%) | 0.141 | ||
| Yes | 60 (8.3) | 667 (91.7) | |
| No | 34 (6.1) | 524 (93.9) | |
| CHD, n (%) | <0.001 | ||
| Yes | 21 (14.5) | 124 (85.5) | |
| No | 73 (6.4) | 1067 (93.6) | |
| Diabetes, n (%) | 0.673 | ||
| Yes | 14 (8.1) | 159 (91.9) | |
| No | 80 (7.2) | 1032 (92.8) | |
| Stroke, n (%) | 0.408 | ||
| Yes | 12 (9.1) | 120 (90.9) | |
| No | 82 (7.1) | 1071 (92.9) | |
| Cancer, n (%) | 2 (16.7) | 10 (83.3) | 0.211 |
| Yes | 92 (7.2) | 1181 (92.8) | |
| No | 69 (7.7) | 829 (92.3) |
Wilcoxon rank-sum test for continuous variables and Fisher’s exact test for categorical variables
Univariate models of influenza vaccination
Table 2 shows that the influenza 5-year vaccination rate for the entire study population was only 7.3%, with vaccination rates for men and women being 7.2% and 7.6%, respectively. Participants over 70 years of age had the highest vaccination rates (8.9%; p = 0.062). In this study, the high awareness group has the highest vaccination rates (9.2%), followed by the medium (7.9%) and low (1.5%) groups (p = 0.001). The rate of influenza vaccination was significantly higher in those with a history of CHD than in those without a history of CHD (14.5% vs. 6.4%; p < 0.001).
Multivariate regression models of influenza vaccination
After multivariate adjustment, participants with CHD had a higher vaccination rate than those without CHD (OR = 2.625, 95%CI: 1.564–4.405, p < 0.001). Compared with the low awareness group, the medium (OR = 6.096, 95%CI: 1.854–20.041, p = 0.003) and high (OR = 7.179, 95%CI:2.211–23.305, p = 0.001) awareness groups had higher vaccination rates (Table 3).
Table 3.
Multivariable logistic regression results for factors associated with influenza vaccination
| Factors associated with influenza vaccination |
Wald | P | Adjusted odds ratio (AOR) |
95%CI | ||
|---|---|---|---|---|---|---|
| Lower | Upper | |||||
| CHD: | ||||||
| No | - | 1 | - | - | ||
| Yes | 13.340 | <0.001 | 2.625 | 1.564 | 4.405 | |
| Awareness of influenza: | ||||||
| Low awareness group | - | 1 | - | - | ||
| Moderate Awareness Group | 8.860 | 0.003 | 6.096 | 1.854 | 20.041 | |
| High Awareness Group | 10.763 | 0.001 | 7.179 | 2.211 | 23.305 | |
Adjusted: CHD history, Awareness of influenza
Discussion
This cross-sectional study focused on influenza vaccination and influencing factors among low-income populations in northern China. The study found that, among rural residents aged ≥ 60 years, influenza awareness and vaccine awareness rates were 84.9% and 56.3%, respectively. The influenza vaccination rate was only 7.4%, and according to age group, the highest influenza vaccination rate (8.9%) was for residents aged ≥ 70 years. Among people aged ≥ 60 years, having CHD and high awareness of influenza promoted influenza vaccination.
Global influenza awareness and vaccination rates
Seasonal flu is still an important cause of illness and death. Vaccination is the most cost-effective preventive measure to prevent the disease [1]. It is especially important for people at high risk of severe influenza-related complications, especially the older population and people with serious comorbidities [26]. However, the influenza vaccination rates in many countries is unsatisfactory, and the understanding of influenza is not comprehensive. The results of a cross-sectional study in Italy showed that 64.7% of residents knew that influenza could be prevented with a vaccine [27]. The influenza awareness rate among Saudi Arabian residents was 62.2%, with 88.7% of the participants believing the public needed more science-based knowledge about influenza vaccines and 73.8% believing that influenza vaccines were beneficial [28]. The results of a multicenter study involving 10,045 people of all ages in China showed that the awareness rates for influenza and common cold was 75.3%, and the awareness regarding influenza severity was 82.0% [29]. However, although the population in this study had a high awareness of influenza, its awareness of the influenza vaccine was lower (56.3%). This may be due to the low educational level of the study population and the impaired ability of the older population living in rural areas to receive information. A previous study noted that regular health education among community residents significantly increased their influenza awareness, and the influenza vaccination rate increased by 20% [30]. Therefore, it is possible to increase the frequency of health education to improve influenza-related awareness for the older population with low educational levels.
Global variations in influenza vaccination rates
Influenza vaccination rates for the older population vary globally. Strong vaccination policies in countries like Greece (83%) [31], the United States (75.2%) [32], Brazil (73%) [33], and the UK (>64%) [34] demonstrate high coverage. In Spain and Switzerland, rates are lower (57.4% and 38.5%, respectively) [35, 36], while Japan shows significant regional variation (35–80%) [37, 38]. In contrast, China’s vaccination rates remain low, with only 1.9% overall and 7.4% for those aged ≥ 60 years [17, 39], far below the WHO target of 75%. A recent study in South Korea has shown that socioeconomic status can affect vaccination rates [40]. The population of this study is rural areas in China with low socio-economic status, and the cost of influenza vaccination in this region is borne by participants at their own expense, which may be the reason for the vaccination rate being only 7.3%. Although many cities in China are gradually launching publicly funded influenza programs for the older population, which has significantly increased the rate of influenza vaccination for the older population, the China immunization and vaccination service system is still unable to support a free nationwide influenza vaccination program. With the gradual promotion of free vaccination services in China, the influenza vaccination rate should rapidly increase.
Moreover. in this study, the older population have a low level of awareness of influenza and vaccines due to low education levels and other reasons. However, due to the high prevalence of chronic diseases and other basic diseases in the older population, young family members will actively support the elderly to get vaccinated, in order to reduce the family disease burden. In addition, due to the outbreak of the COVID-19 pandemic, people’s awareness that vaccines will prevent influenza exists. The government’s publicity of vaccination and people’s fear of the epidemic will also increase the vaccination rate of influenza vaccine.
Limitations
Several limitations should be considered when interpreting the findings of this study. First, the study was conducted in a single rural area of Tianjin, which may limit the generalizability of the results to other rural regions in China with different socioeconomic conditions, healthcare infrastructure, and cultural contexts. Future multicenter studies including diverse rural populations are warranted. Second, the cross-sectional design provides only a snapshot of influenza awareness and vaccination behavior and does not allow causal inferences to be made. Longitudinal studies are needed to examine temporal changes in awareness and vaccination uptake and to better understand causal relationships. Third, vaccination history, medical history, and influenza awareness were self-reported, which may be subject to recall bias and social desirability bias. Future studies should incorporate objective data sources, such as vaccination registries and medical records, to validate self-reported information. Fourth, the study included a limited range of sociodemographic variables. Other potentially important factors, such as healthcare accessibility, physician recommendation, and chronic disease management, were not assessed. Including a broader set of variables may provide a more comprehensive understanding of vaccination behavior. Fifth, individuals with severe communication impairments, mental illness, or mobility limitations were excluded, which may have led to an underestimation or overestimation of vaccination coverage and associated factors. Future research should employ inclusive survey methods to capture these vulnerable populations. Finally, the influenza awareness questionnaire was developed by the research team and included closed-ended questions. Although it was informed by previous studies, potential measurement bias cannot be excluded. The development and validation of standardized influenza awareness instruments for the Chinese population are needed.
Conclusion
Influenza cognitive level and chronic medical history are important factors associated with influenza vaccination uptake among older adults in rural China. In order to improve awareness and fill the vaccination gap, community health education should be strengthened, especially in patients with chronic diseases; By simplifying the vaccination process, providing economic subsidies, using community forces to carry out targeted publicity, and actively recommending by doctors, we will promote influenza vaccination among the elderly.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
We thank all participants of the Tianjin Brain Study, and local medical care professionals for their valuable contributions.
Abbreviations
- WHO
World Health Organization
- COVID-19
coronavirus disease 2019
- CHD
Coronary heart disease
- BMI
Body mass index
- SBP
Systolic blood pressure
- DBP
Diastolic blood pressure
- SDs
Standard deviations
- CIs
Confidence intervals
Author contributions
XN, CY, KX were involved in conception and design, and data interpretation for this article. JW was involved in data analysis for this article. YF, JL, XL was involved in manuscript drafting. YF, JL, XL, JH, YL, JT were involved in data collection, case diagnosis and confirmation for this article. XN, CY, KX were involved critical review in for this article.
Funding
This project is funded by the Tianjin Education Commission Research Program Project (2024KJ169).
Data availability
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
This study was approved by the ethics committee at Tianjin Medical University General Hospital and conformed to the Declaration of Helsinki regarding the use of human subjects. Written informed consent was obtained from each patient for this study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Yunhan Fei, Jie Liu, Xiao Li and Juan Hao Contributed equal to this work.
Contributor Information
Keliang Xie, Email: mzk2011@126.com.
Chunsheng Yang, Email: cyang01@tmu.edu.cn.
Xianjia Ning, Email: xning@tmu.edu.cn.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.