Active health behaviors and their influencing factors among community-dwelling elderly hypertensive patients: a cross-sectional study in Zhengzhou, China.

Active health behaviors and their influencing factors among community-dwelling elderly hypertensive patients: a cross-sectional study in Zhengzhou, China - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice BMC Public Health . 2026 Apr 20;26:1770. doi: 10.1186/s12889-026-27465-3 Active health behaviors and their influencing factors among community-dwelling elderly hypertensive patients: a cross-sectional study in Zhengzhou, China XinWen 1 , Yan Zhang 1, ✉ , Shiwei Ma 1 , Qi Li 1 , Xinqi Wu 1 Author information Article notes Copyright and License information 1 School of Nursing and Health, Zhengzhou University, Zhengzhou, Henan China ✉ Corresponding author. Received 2024 Sep 22; Accepted 2026 Apr 15; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13227720  PMID: 42010579 Abstract Background Hypertension is a common chronic disease among older adults, and active health behaviors are important for disease management and health promotion in this population. However, evidence on the current status of active health behaviors and their influencing factors among community-dwelling older adults with hypertension remains limited. This study aimed to investigate the current status of active health behaviors among community-dwelling older adults with hypertension and explore the factors influencing these behaviors, thereby providing a basis for improving active health behaviors in this population.To investigate the current status of active health behaviors among elderly hypertensive patients in the community and explore the factors influencing these behaviors, providing a basis for improving the active health behaviors of this population. Methods In this community-based cross-sectional study, convenience sampling was used to recruit 401 community-dwelling elderly hypertensive patients in Zhengzhou, Henan Province, China, from November 2023 to December 2023. Data were collected using a general information questionnaire, the Active Health Behavior Scale, the Digital Health Literacy Assessment Scale for Community Elderly, and the Brief Illness Perception Questionnaire. Descriptive statistics, univariate analyses, Pearson correlation analysis, and multiple linear regression were used to analyze the data. Results The average score of active health behaviors among elderly hypertensive patients in the community was 109.86(21.64). Multiple linear regression showed that age, per capita monthly household income, health status, form of medical payment, digital health literacy, and illness perception were factors influencing active health behaviors in elderly hypertensive patients in the community (P<0.05), explaining 60.6% of the total variance. Conclusion The level of active health behaviors among elderly hypertensive patients in the community needs improvement. Higher levels of active health behaviors were associated with older age, higher per capita monthly household income, better self-assessed health status, and having medical insurance as the form of payment. Positive illness perception and digital health literacy also had a favorable impact on the active health behaviors of elderly hypertensive patients in the community. Trial registration Not applicable. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-026-27465-3. Keywords: Elderly, Hypertension, Active health behaviors, Digital health literacy, Illness perception Background Hypertension is the leading risk factor for cardiovascular diseases and mortality, making it a significant public health issue [ 1 ]. More than half of the elderly population in China suffer from hypertension, with over 90% of those aged 80 and above affected [ 2 ]. China continues to face challenges such as high hypertension prevalence, low control rates, and high mortality rates [ 3 ]. One of the barriers to effectively managing hypertension and other chronic diseases is the lack of active health management by patients [ 4 ]. The “Healthy China 2030” plan introduces the concept of active health [ 5 ], emphasizing the importance of improving health literacy [ 6 ], guiding active health behaviors, and creating a healthy environment, which are crucial for the prevention and control of hypertension and other chronic diseases. Active health behavior in hypertensive patients refers to the individual’s active engagement in health management and disease coping, taking personal responsibility for health, utilizing available health resources, and actively managing external risk factors such as work, rest, diet, exercise, and emotions [ 7 ]. While existing studies have often explored the role of active health perspectives in chronic disease management and community health management [ 4 – 10 ], research specifically focusing on the factors influencing active health behaviors in hypertensive and other chronic disease populations is limited. Previous studies have found that factors such as digital health literacy and illness perception positively impact active health behaviors [ 11 , 12 ]. Individuals with higher digital health literacy are better at finding, understanding, and evaluating health-related information through digital devices and using this knowledge to address health issues, thereby making better health decisions [ 13 ]. Patients with better illness perception are able to use their knowledge and experience to analyze their current condition [ 14 ], which aids in their coping behaviors and psychological responses [ 15 ]. As community medical institutions are the “main battlefield” for chronic disease prevention and control in China [ 16 ], this study aims to investigate the current status of active health behaviors among elderly hypertensive patients in a community in Zhengzhou, Henan Province, and to explore the influence of digital health literacy and illness perception on these behaviors. The goal is to provide valuable reference data for the subsequent development of targeted smart active health interventions for elderly hypertensive patients and to lay the foundation for actively addressing the challenges of an aging society. Methods Study design, setting, and participants This community-based cross-sectional study was conducted in an urban community in Zhengzhou, Henan Province, China, from November 2023 to December 2023. Zhengzhou is the capital city of Henan Province, and local community health service institutions routinely provide chronic disease follow-up, blood pressure monitoring, and health education for older adults with hypertension. Using convenience sampling, community-dwelling elderly patients with hypertension were recruited for the survey. Sample size determination The minimum sample size was estimated using Cochran’s formula for estimating a single population proportion: n = [Z² α/2 p(1-p)]/d², which is commonly used for prevalence studies. Based on a pilot survey conducted before the formal investigation, the anticipated proportion of participants with a moderate-to-high level of active health behaviors was set at p = 0.75. With a 95% confidence level (Z = 1.96) and an allowable error of d = 0.05 [ 17 ], the estimated sample size was 288.12, which was rounded up to 289. After allowing for a 20% invalid-response rate, the minimum required sample size was 347. Inclusive criteria (1) age ≥ 60 years; (2) diagnosis of primary hypertension according to ICD-10 code I10 [ 18 ];.(3) residence in the community for at least 6 months in the previous year; and (4) clear consciousness and basic communication ability to complete the questionnaire. Exclusive criteria (1) patients with comorbidities such as diabetes or other chronic diseases; (2) unavailable key community health records or invalid/incomplete questionnaire data. Questionnaire General information questionnaire The general information questionnaire was developed by the researchers based on a comprehensive synthesis of established demographic and clinical factors identified in previous large-scale epidemiological studies and hypertension management guidelines [ 19 , 20 ]. The questionnaire includes 12 items: gender, age, ethnicity, education level, occupation, monthly per capita household income, number of children, self-assessed health status, marital status, form of medical payment, whether children are nearby, and frequency of participation in hypertension health education seminars. Active health behavior scale, AHBS Developed by Wei Yilin [ 7 ], the scale is used to measure an individual’s active acquisition of health information and selection of healthy behaviors [ 21 ].It includes five dimensions: health responsibility, labor and emotion management, diet management, exercise management, and disease management, with a total of 30 items. Each item is rated on a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree), with total scores ranging from 30 to 150; higher scores indicate better active health behaviors. Following the original scale study [ 7 ], the scoring index (actual score / total possible score × 100%) was used to classify the level of active health behaviors as low (< 60%), moderate (60%-80%), or high (> 80%). In this study, Cronbach’s α for the scale was 0.897. Digital health literacy assessment scale Developed by Liu Siqi [ 22 ], this scale is used to assess the ability of older adults to search for, understand, and evaluate health information on digital media, actively engage in health information exchange and interaction, manage their health, and solve health-related problems [ 23 ]. It includes three dimensions: digital health information acquisition and evaluation ability, digital health information interaction ability, and digital health information application ability, with a total of 15 items. The scale uses a 5-point Likert scoring system, ranging from “strongly disagree” to “strongly agree,” with scores assigned from 1 to 5. Higher scores indicate a higher level of digital health literacy. In this study, the Cronbach’s α coefficient for the scale was 0.959. Brief illness perception questionnaire, BIPQ Developed by Broadbent et al. [ 24 ] and translated into Chinese by Sun Weiming et al. [ 14 ], this scale is used to assess patients’ cognitive representations, emotional representations, and understanding of their illness [ 25 ]. The scale comprises nine items covering three dimensions: Cognition (Items 1, 2, 3, 4, and 5), Emotion (Items 6 and 8), and Understanding Ability (Item 7). The ninth item is an open-ended question regarding causal attribution. Each item is scored on a scale of 0 to 10, with Items 3, 4, and 7 being reverse-scored. The total score ranges from 0 to 80, where higher scores signify a more negative Illness Perception and a greater perceived severity of disease symptoms. The Cronbach’s α coefficient for the scale is 0.831, indicating good reliability and validity. Data collection Before data collection, the investigators received standardized training on the study purpose, eligibility criteria, communication skills, and the meaning of each questionnaire item. During the formal survey, face-toface, one-to-one interviews were conducted offline in the target community. After written informed consent had been obtained, participants completed the questionnaires with assistance from trained investigators when needed. A total of 423 questionnaires were collected. After exclusion of 22 invalid questionnaires (for example, questionnaires with obvious response patterns or missing key information), 401 valid questionnaires were included in the final analysis, yielding a valid response rate of 94.8%. Data analysis Statistical analysis was conducted using SPSS 29.0 software. Continuous variables, including age and the scores of active health behaviors, digital health literacy, and illness perception, were described using mean(standard deviation). Categorical data, such as gender and educational level, were described using frequencies and percentages. A univariate analysis was performed on the active health behavior scores, with non-normally distributed variables analyzed using the Wilcoxon rank-sum test and normally distributed variables analyzed using t-tests or ANOVA. Pearson correlation analysis was used to test the correlation between active health behaviors and digital health literacy, as well as illness perception. Multiple linear regression analysis was employed to identify the influencing factors of active health behaviors. A P-value of less than 0.05 was considered statistically significant. Results Participant characteristics In this study, the majority of the surveyed elderly hypertensive patients were female (52.62%). Regarding educational background, the largest proportion had received a high school/technical secondary school education (39.40%). Among the respondents, the highest percentage (40.65%) reported their occupation as retired cadres/intellectuals and office workers. The highest proportion of respondents (39.65%) had a monthly income of 3000 yuan or more. Additionally, 81.50% of the respondents rated their health as good, and 39.90% indicated that their medical expenses were covered by urban employee medical insurance. Furthermore, the study results indicated that there were statistically significant differences ( P < 0.05) in the scores for active health behaviors among community-dwelling elderly hypertensive patients across different categories of age, educational level, occupation, monthly per capita household income, health status, marital status, medical payment methods, whether their children lived nearby, and the frequency of participation in hypertension health education lectures (see Table 1 ). Table 1. Socio-demographics of study participants ( N = 401) Variable Category Frequency ( n = 401)| Percentage (%) Gender Male 190 47.38 Female 211 52.62 Age (years) 60~ 130 32.42 70~ 198 49.38 80~ 73 18.20 Ethnicity Han 380 94.76 Hui 18 4.49 Other 3 0.75 Education Level Primary school or below 75 18.68 Middle school 93 23.19 High school/Technical school 158 39.40 Junior college 62 15.49 University or above 13 3.24 Occupation Farmer 108 26.93 Worker 63 15.71 Retired cadres/Intellectuals/Staff 163 40.65 Self-employed/Others 28 6.98 Unemployed 39 9.73 Monthly Household Income per Capita (Yuan) <1000 31 7.73 1000~ 118 29.43 2000~ 93 23.19 3000~ 159 39.65 Number of Children None 6 1.50 1 child 69 17.21 2 children 167 41.65 3 or more children 159 39.64 Self-Rated Health Status Good 325 81.05 Poor 76 18.95 Marital Status Unmarried 5 1.25 Married 343 85.54 Divorced 13 3.24 Widowed 40 9.97 Medical Payment Method Urban employee medical insurance 160 39.90 Urban resident medical insurance 110 27.43 New rural cooperative medical insurance 126 31.42 Self-funded 5 1.25 Whether Children Live Nearby Yes 281 70.07 No 120 29.93 Frequency of Participation in Hypertension Health Education Lectures Never 135 33.67 Occasionally (at least once every six months) 227 56.61 Frequently (at least once a month) 39 9.72 Open in a new tab 1) t-value 2) F-value 3) z-value 4) H-value Descriptive statistics of the study variables The results of this study indicate that the active health behavior score among elderly community-dwelling patients with hypertension was 109.86(21.635) points. The digital health literacy score was 40.39(15.85) points, and the illness perception score was 37.87(7.55) points. See Table 2 . Table 2. Descriptive statistics of active health behaviors, digital health literacy, and illness perception Variable Score Range Mean (SD) Average Item Score Active Health Behavior 30 ~ 150 109.86(21.64) 3.66(0.72) Labor and Emotion Management 7 ~ 35 27.68(5.96) 3.95(0.85) Dietary Management 8 ~ 40 31.14(6.64) 3.89(0.83) illness Management 2 ~ 10 7.32(1.83) 3.66(0.92) Exercise Management 3 ~ 15 10.78(3.18) 3.59(1.06) Health Responsibility 10 ~ 50 32.94(8.20) 3.29(0.82) Digital Health Literacy 15 ~ 75 40.39(15.85) 2.69(1.06) Acquisition and Evaluation Ability 9 ~ 45 25.10(10.04) 2.79(1.12) Application Ability 3 ~ 15 8.12(3.32) 2.71(1.11) Interaction Ability 3 ~ 15 7.17(3.61) 2.39(1.20) Illness Perception 0 ~ 80 37.87(7.55) 4.73(0.94) Emotion 0 ~ 20 11.68(3.52) 5.84(1.76) Cognition 0 ~ 50 22.72(6.19) 4.54(1.24) Understanding Ability 0 ~ 10 3.47(2.04) 3.47(2.04) Open in a new tab Correlations This study analyzed the relationship between active health behaviors, digital health literacy, and illness perception among community-dwelling elderly hypertensive patients. The results showed that active health behaviors were positively correlated with digital health literacy ( r = 0.463) and negatively correlated with illness perception ( r =-0.253). See Table 3 . Table 3. Correlation of active health behavior, digital health literacy and illness perception Variable Active Health Behavior Digital Health Literacy Illness Perception Active Health Behavior 1 Digital Health Literacy 0.46* 1 Illness Perception -0.25* -0.10* 1 Open in a new tab * p < 0.01 Regression analyses Using the active health behavior scores of community-dwelling elderly hypertensive patients as the dependent variable, multiple linear regression analysis was conducted with the variables that showed statistical significance ( P < 0.05) in univariate and correlation analyses as independent variables. The results indicated that age, monthly per capita household income, self-rated health status, marital status, medical payment method, frequency of blood pressure measurement per week, digital health literacy, and illness perception were influencing factors, explaining 60.6% of the total variance (see Table 4 ). Table 4. Regression analysis result Variable β SE β’ t 95%CI P value Age (years) 3.12 1.02 0.10 3.05 [1.11, 5.12] 0.002 Education Level -1.28 0.86 -0.06 -1.49 [-2.96, 0.41] 0.138 Occupation 1.14 0.64 0.07 1.79 [-0.11, 2.39] 0.074 Monthly Household Income per Capita (Yuan) 2.22 0.94 0.10 2.37 [0.38, 4.05] 0.018 Self-Rated Health Status 6.19 1.99 0.11 3.11 [2.29, 10.09] 0.002 Marital Status 0.71 1.22 0.02 0.58 [-1.69, 3.10] 0.564 Medical Payment Method -2.52 1.08 -0.10 -2.34 [-4.63, -0.41] 0.020 Whether Children Live Nearby 2.87 1.65 0.06 1.74 [-0.36, 6.09] 0.083 Frequency of Participation in Hypertension Health Education Lectures 2.12 1.37 0.06 1.54 [-0.57, 4.81] 0.124 Digital Health Literacy 0.46 0.05 0.33 8.87 [0.36, 0.56] < 0.001 Illness Perception -2.51 0.56 -0.16 -4.48 [-3.62, -1.41] < 0.001 Open in a new tab Discussions The level of active health behaviors among elderly patients with hypertension in the community needs to be improved The results of this study show that the patients’ active health behavior score was 109.86(21.64), indicating a moderate level. This suggests that patients are somewhat attentive to their health status, have a certain degree of willingness to manage their health, and exhibit relatively high levels of health belief-seeking behavior [ 26 ]. However, health literacy still needs to be strengthened [ 27 ]. The score is slightly higher than the results reported by Li Huan et al. [ 28 ] in a study on rural patients, which may be attributed to the fact that urban community patients have more comprehensive social medical services and access to health resources [ 29 ], leading to a higher level of active health behavior. In this study, the highest scores were observed in the dimensions of work and emotion management, indicating that patients are capable of reasonably balancing work and rest and effectively managing their emotions. This may be due to the patients’ accumulated self-management experience and health assessment abilities [ 30 ], as well as the positive role of family support [ 31 – 33 ]. In contrast, the lowest scores were found in the health responsibility dimension, reflecting a lack of awareness among patients regarding their responsibility for illness progression and health maintenance. This may be related to unclear identification of health responsibilities and insufficient implementation of health behaviors [ 6 ]. Based on the “knowledge-attitude-practice” (KAP) theory, healthcare workers should focus on fostering active health concepts, acquiring scientific knowledge, and implementing health behaviors [ 6 ]. They should advocate the idea that “everyone is the primary person responsible for their own health,“ [ 34 ] help patients utilize health resources, enhance their ability to make autonomous decisions, and promote active and healthy aging. Patients should be encouraged to participate in health activities, such as reducing sodium and increasing potassium intake, adopting a light diet, and developing health plans [ 35 , 36 ], in order to improve the willingness and capacity of elderly patients with hypertension to engage in health behaviors, thereby contributing to the “Healthy China” initiative. An analysis of factors influencing active health behaviors among elderly hypertensive patients in the community Age This study shows that among elderly hypertensive patients in the community, age is positively correlated with active health behaviors, consistent with previous research [ 37 ]. This may be because, as age increases, patients place greater importance on health and longevity [ 37 , 38 ], leading them to engage more actively in health management. It is recommended that younger patients use information technology and wearable devices to assist in health monitoring, coupled with personalized guidance. Additionally, family involvement in health management should be encouraged to help patients gradually develop healthy behavioral habits and enhance their active health awareness. Average monthly household income per capita This study indicates that there is a positive correlation between the per capita monthly household income of elderly hypertensive patients in the community and the level of active health behaviors, consistent with previous research [ 39 ]. Patients with higher incomes, due to their stronger economic capabilities, are better able to manage their health and treatment, thereby enhancing their health awareness. To improve the health status and quality of life of low-income patients, it is recommended that the government and relevant departments increase the reimbursement rate of medical insurance, promote affordable treatment products, and provide free health and psychological counseling services through community family doctors as “health gatekeepers” [ 40 ], thereby increasing the level of active health behaviors. The form of medical payment is medical insurance This study indicates that elderly hypertensive patients in the community covered by health insurance exhibit better active health behaviors than those who pay out-of-pocket, consistent with previous research [ 41 ]. Health insurance reduces financial burdens, increases willingness to provide economic support [ 42 ], promotes patient-doctor communication [ 43 ], and improves adherence to medical advice [ 37 ], thereby enhancing patients’ active health behaviors. It is recommended that the government and relevant departments focus on uninsured elderly patients, integrate resources within medical alliances [ 44 ], provide social security, including pension and medical care, and establish community-based hypertension self-management platforms to enhance patient participation in medical decision-making and health management, thereby improving active health behaviors. Self-assessed health status The results of this study indicate that elderly hypertensive patients in the community who have better self-assessed health status exhibit higher levels of active health behavior, consistent with previous research findings [ 45 ]. This may be related to the fact that individuals with better self-assessed health status tend to have stronger health awareness and health concepts [ 46 ]. Ghazi et al. [ 47 ] found that good health status enables the elderly to effectively utilize resources to promote their health, with a strong awareness of seeking health information, which in turn fosters active health behavior. It is recommended that health-related professionals encourage patients to participate in health activities, disseminate knowledge about the causes, risks, prevention, and control of hypertension, guide scientific health self-assessment, and that healthcare workers should encourage patients to actively practice regular follow-ups based on health guidance, adjusting treatment plans and health strategies in a timely manner. Digital health literacy The results of this study indicate that the overall digital health literacy score among elderly hypertensive patients in the community is low 37.87(7.548), consistent with previous research [ 48 ]. One reason for this may be the inclusion of non-internet users among the survey participants, who have lower rates of technological engagement and acceptance [ 49 ]. Additionally, this study shows that digital health literacy is an independent positive influencing factor for active health behaviors among elderly hypertensive patients in the community, aligning with previous findings [ 50 ]. High levels of digital health literacy help patients effectively acquire and process health knowledge, participate in and practice healthy behaviors [ 12 ], which in turn assists the elderly in developing correct and reasonable lifestyles, further reinforcing their active health behaviors. It is recommended that primary healthcare institutions provide digital skills training for the elderly [ 51 ], organize digital health lectures, workshops, and other activities, and build active health management platforms with smart digital healthcare [ 51 ] to offer patients functions such as health knowledge, blood pressure monitoring, and online consultations, thereby enhancing patients’ active health awareness and improving health outcomes. Illness perception The results of this study indicate that the overall illness perception score among elderly hypertensive patients in the community is 37.87(7.548), reflecting a moderate level. This suggests that elderly hypertensive patients in the community have a certain awareness of illness risk. The analysis suggests that patients with good self-rated health (81.5%) are more likely to actively acquire illness-related knowledge, thereby increasing their understanding of the illness [ 38 ]. According to the health behavior theory [ 52 ], an increase in patients’ knowledge of the illness can enhance their risk perception. Furthermore, illness perception is an independent negative influencing factor on active health behaviors among elderly hypertensive patients in the community, consistent with the findings of Chen Zhuo [ 53 ]. This may be partly due to the fact that the educational level and cultural background of patients in urban areas are important factors in illnesse perception [ 54 ]. It is recommended that health workers provide appropriate health education based on patients’ cultural and educational levels, and that the government strengthens primary healthcare infrastructure and promotes interdisciplinary collaboration to optimize health services. Strengths and limitations Strengths This study has several strengths that enhance the interpretability and public health relevance of the findings. First, we targeted **community-dwelling older adults wition central to community-based chronic disease prevention and control, thereby improving the practical applicability of the results to primary care and community health services. Second, key constructs were measured using validated and context-appropriate instruments, including the Hypertension Patient Active Health Behavior Scale (AHBS), the Digital Health Literacy Assessment Scale for Community Elderly, and the Brief Illness Perception Questionnaire (BIPQ), which supports construct validity and facilitates comparison with related research. Third, data collection procedures were implemented rigorously (trained investigators, face-to-face administration, and on-site completeness checks), which is particularly important when surveying older adults and helps to reduce missing data and measurement error. Finally, by modelling digital health literacy and illness perception simultaneously alongside sociodemographic and health-related variables, our analysis provides a more integrated understanding of factors associated with active health behaviors and identifies potentially modifiable targets for future community interventions. In line with the role of cross-sectional studies in describing associations and supporting hypothesis generation, these findings can inform the design and prioritization of subsequent longitudinal and intervention research. Limitations Several limitations should be noted. First, participants were recruited using convenience sampling from a single community/city in Henan Province, which may limit the generalizability of the findings to other regions or, the cross-sectional design restricts causal inference; therefore, the observed associations should be interpreted as correlational rather than causal. Third, the use of self-reported questionnaires may introduce recall bias and social desirability bias. Future studies should consider multi-site sampling strategies with probability-based recruitment, incorporate objective behavioral or clinical indicators (e.g., blood pressure control, healthcare utilization), and apply longitudinal or intervention designs to examine causal pathways and evaluate targeted strategies to improve active health behaviors. Conclusion This study found that the level of active health behaviors among elderly hypertensive patients in the community is slightly above average and is influenced by factors such as age, household income, health status, method of medical payment, digital health literacy, and illness perception. Healthcare providers should pay attention to these factors to enhance patients’ active health behaviors, support the development of smart elderly care and nursing services, and promote active aging. Supplementary information Supplementary Material 1. (30.7KB, docx) Acknowledgements We would like to acknowledge the contributions of all the individuals who have contributed to this study. We thank the study staff and participants. Abbreviations AHBS Active Health Behavior Scale BIPQ Brief Illness Perception Questionnaire ICD-10 International Statistical Classification of Diseases and Related Health Problems, Tenth Revision SD Standard deviation Authors' contributions Study Design: XW，YZ. Data collection: XW，SWM，QL. Data analysis: XW，XQW and QL. Manuscript preparation: XW，YZ，SWM，QL and XQW. All authors have agreed on the final version of the manuscript. Funding This study was supported by the 2024 Research Project of the Chinese Nursing Association (Grant No. ZHKY202414). Data availability No datasets were generated or analysed during the current study. Declarations Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki and was approved by the Zhengzhou University Life Sciences Ethics Review Committee (Approval No. ZZUIRB2024-49). Written informed consent was obtained from all participants prior to data collection. 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. References 1. Jiang XJ, Jiang KW, Jia N, et al. Current perspectives on catheter-based renal denervation for hypertension: clinical research results and existing issues. Chin Circulation J. 2023;38(10):999–1004. [in Chinese]. [ Google Scholar ] 2. Yang C, Yang C. Target organ damage and related research progress in elderly patients with hypertension and orthostatic hypotension. J Geriatric Med Health Care. 2023;29(6):1395–8. [in Chinese]. [ Google Scholar ] 3. Zhao L, Li Y, Niu X. Reflections on hypertension prevention and control strategies in China. Chin J Hypertens. 2024;32(1):2–5. [in Chinese]. [ Google Scholar ] 4. Gao X, Li X, Zhou L, et al. Thoughts and explorations on digital chronic disease prevention and control based on active health index. J Shanghai Jiao Tong Univ (Medical Science). 2023;43(2):137–42. [in Chinese]. [ Google Scholar ] 5. Central Committee of the Communist Party of China, State Council. Healthy China 2030 planning outline. https://www.gov.cn/zhengce/2016-10/25/content_5124174.htm . Accessed 25 Feb 2023. [in Chinese]. 6. Lei X, Zhou Y, Wu L. Passive treatment or active health? Behavioral choices of asymptomatic populations from the perspective of the Healthy China strategy. Med Controversies. 2019;10(04):75–8. [in Chinese]. 7. Wei Y, Zhang L, Chen F, et al. Development of an active health behavior scale for hypertension patients. Chin J Public Health. 2023;39(3):370–4. [in Chinese]. [ Google Scholar ] 8. Zhou L, Li X, Gao X, et al. Exploration of a precision management model for chronic diseases based on active health index. Chin J Chronic Disease Prev Control. 2023;31(4):294–9. [in Chinese]. [ Google Scholar ] 9. Jiang G, Wang X, Zhao Y, et al. Issues and reflections on community health management from the perspective of big health. J Nanjing Med Univ (Social Sci Edition). 2022;22(1):31–5. [in Chinese]. [ Google Scholar ] 10. Lu W, Zhang W, Huang Z. Research on optimizing the health promotion system integrating sports and medicine in China from the perspective of active health. J Tianjin Univ Sport. 2023;38(6):703–11. [in Chinese]. [ Google Scholar ] 11. Zhang M, Lu Y, Gao S, et al. Study on awareness and willingness to seek medical treatment for mild cognitive impairment among people aged 55 and above in Shanghai from the perspective of active health. Chin Gen Pract Med. 2024;27(10):1208–14. [in Chinese]. [ Google Scholar ] 12. Wu L, Zhao L. Digital health literacy and the alleviation of anxiety in the elderly. J South China Normal Univ (Social Sci Edition). 2022;(04):72–83+206. [in Chinese]. 13. Tang H, Yuan D, Wang M, et al. Mediating effects of digital integration and healthy lifestyle on the relationship between socioeconomic status and depression in the elderly. J Peking Univ (Medical Edition). 2024;56(2):230–8. [in Chinese]. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 14. Sun W, Lou Q, Yuan Y, et al. Application of a simplified Chinese version of the disease cognition questionnaire in patients with somatoform disorders. J Chongqing Med Univ. 2015;40(8):1138–42. [in Chinese]. [ Google Scholar ] 15. Wu Y, Xu J, Zhao Q, et al. Study on the relationship between illness perception and anxiety/depression symptoms in elderly hypertensive patients. Chin J Chronic Disease Prev Control. 2024;32(3):188–192197. [in Chinese]. [ Google Scholar ] 16. Tong X, Huang Y. Current status and development strategies of traditional Chinese medicine in the prevention and treatment of diabetic kidney disease. J Beijing Univ Traditional Chin Med. 2022;45(12):1189–95. [in Chinese]. [ Google Scholar ] 17. Charan J, Biswas T. How to calculate sample size for different study designs in medical research? Indian J Psychol Med. 2013;35(2):121–6. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 18. World Health Organization. ICD-10: international statistical classification of diseases and related health problems. 10th revision. 2nd ed. Geneva: World Health Organization. 2004. Available from: https://iris.who.int/handle/10665/42980 . 19. Mills KT, Stefanescu A, He J. The global epidemiology of hypertension. Nat Rev Nephrol. 2020;16(4):223–37. 10.1038/s41581-019-0244-2. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 20. Unger T, Borghi C, Charchar F, et al. 2020 International society of hypertension global hypertension practice guidelines. Hypertension. 2020;75(6):1334–57. 10.1161/HYPERTENSIONAHA.120.15026. [ DOI ] [ PubMed ] [ Google Scholar ] 21. Zhou P, Peng X, Chen T, et al. A review of the scientific management of health assets in the new era from the perspective of active health. Chin Health Econ. 2020;39(8):62–4. [in Chinese]. [ Google Scholar ] 22. Liu S. Development and empirical research of a digital health literacy assessment scale for community elderly under the background of active aging [master’s thesis]. Chongqing: Army Medical University; 2023. [in Chinese]. 23. Liu S, Luo Y, Fu J, et al. Current status and countermeasures of digital health literacy among the elderly under the background of active aging. Nurs Res. 2021;35(2):250–4. [in Chinese]. [ Google Scholar ] 24. Broadbent E, Petrie KJ, Main J, et al. The brief illness perception questionnaire. J Psychosom Res. 2006;60(6):631–7. [ DOI ] [ PubMed ] [ Google Scholar ] 25. Jia X, Sun J, Chen J, et al. Research progress on assessment tools for illness perception in chronic disease patients. Chin J Nurs. 2023;58(11):1397–402. [in Chinese]. [ Google Scholar ] 26. Wang X, Zhang C, Xing Y, et al. Study on health self-care behaviors and influencing factors of community elderly patients with type 2 diabetes in Shanghai from the perspective of active health. Chin J Chronic Disease Prev Control. 2024;32(2):100–5. [in Chinese]. [ Google Scholar ] 27. Ma G, Shen Z, Duan Y, et al. Current status of health literacy assessment tools for hypertension patients. Chin J Hypertens. 2020;28(1):30–6. [in Chinese]. [ Google Scholar ] 28. Li H, Zhang J, Ma Y, et al. Perception of cardiovascular disease risk and its impact on self-management in elderly hypertensive patients in rural areas. J Nurs. 2023;38(19):12–1533. [in Chinese]. [ Google Scholar ] 29. Xie X. A Study on the Current Situation of Self-management Behaviors and Factors Influencing the Self-management Behaviors of Elderly Empty-nesters with Hypertension and Diabetes in Lanzhou Communit [master’s thesis]. Lanzhou: Gansu University of Chinese Medicine; 2023. 30. Chen P, Gong L, Sun X. Self-management types of hypertension patients and their impact on blood pressure based on latent profile analysis. Chin J Disease Control. 2023;27(6):668–72. [in Chinese]. [ Google Scholar ] 31. Wang Z, Zhang X, Ding Y, et al. Concept analysis of family resilience in adult cancer patients. J Nurs. 2021;36(19):12–5. [in Chinese]. [ Google Scholar ] 32. Liu L, Zhang Y, Tian Y, et al. Research progress on self-management in elderly sarcopenic patients. Chin J Chronic Disease Prev Control. 2023;31(12):948–51. [in Chinese]. [ Google Scholar ] 33. Zang X, Wang X. Study on the relationship between social support, self-efficacy, and self-management in hypertensive patients. Gen Pract Nurs. 2021;19(28):3901–5. [in Chinese]. [ Google Scholar ] 34. Fu S, Wei B. Research on factors influencing medical behavior in the elderly from the perspective of whole-cycle health management. Health Econ Res. 2024;41(2):56–60. [in Chinese]. [ Google Scholar ] 35. Chen X, Guo J. Construction of a service framework for integrating sports and medicine in China under the background of active health. J Capital Univ Phys Educ Sports. 2021;33(5):474–80. [in Chinese]. [ Google Scholar ] 36. Research Group on Development of Precision Exercise Prescription and Construction of Exercise Prescription Database, Ren H, Zhao Y. Development of precision exercise prescriptions for the Chinese population under the concept of active health. J Beijing Sport Univ. 2023;46(11):102–17. [in Chinese]. [ Google Scholar ] 37. Deng J. Study on the relationship between self-perceived aging, self-management motivation, and self-management in elderly hypertensive patients [master’s thesis]. Yanji: Yanbian University; 2021. [in Chinese]. 38. Zhang Y. Study on the status quo and influencing factors of health-promoting lifestyle in patients with knee osteoarthritis [master’s thesis]. Jinan: Shandong University; 2021. [in Chinese]. 39. Xie Q. Study on the impact of social resource utilization and proactivity on medication safety behaviors in hypertensive patients [master’s thesis]. Yanji: Yanbian University; 2021. [in Chinese]. 40. Chen K, Jiang Q, Wang J, et al. Development and validation of management norms for high-risk populations with hypertension complications in the community. Chin Health Resour. 2023;26(5):539–47. [in Chinese]. [ Google Scholar ] 41. Tang X, Luo Q, Yao K, et al. Analysis of health literacy status and influencing factors among elderly hypertensive patients in the community. Occup Health. 2023;39(20):2843–28462855. [in Chinese]. [ Google Scholar ] 42. Liu Q, Wang J, Wang L. Analysis of the current status and influencing factors of chronic disease prevalence among elderly people in rural Jiangxi Province. Chin J Rural Health Manage. 2021;41(7):510–4. [in Chinese]. [ Google Scholar ] 43. Wang X, Liu Y. The impact of internet usage behavior on doctor-patient trust: an analysis based on CFPS 2016 data. J Northwest Normal Univ (Social Sci Edition). 2019;56(2):119–26. [in Chinese]. [ Google Scholar ] 44. Duan H, Zhang Y, Hou Y et al. The impact of medical consortium policies on the service capacity of grassroots community health institutions: a quasi-experimental study from the perspective of organizational alliance theory. J Gansu Administrative Coll. 2020;(04):4–16+124. [in Chinese]. 45. Hu X, Li G, Li J, et al. Influencing factors on health self-management ability among adults aged 45 and above in rural areas. Chin J Disease Control. 2020;24(9):1057–62. [in Chinese]. [ Google Scholar ] 46. Jin S, Li X. Research progress on electronic health literacy among the elderly. Nurs Res. 2024;38(4):620–3. [in Chinese]. [ Google Scholar ] 47. Ghazi SN, Albage A, Martinsson J, et al. The prevalence of eHealth literacy and its relationship with perceived health status and psychological distress during COVID-19: a cross-sectional study of older adults in Blekinge, Sweden. BMC Geriatr. 2023;23(1):5. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 48. Liu Z, Zhang H, Zhang Y, et al. Analysis of the status quo and influencing factors of electronic health literacy among elderly people in rural Zhengzhou. Mod Prev Med. 2020;47(2):283–286309. [in Chinese]. [ Google Scholar ] 49. Peng Y, Gao Y, Yong J, et al. Analysis of the status of anxiety towards digital health technology among elderly community members and nursing countermeasures. Chin J Nurs. 2023;58(11):1345–51. [in Chinese]. [ Google Scholar ] 50. Li Z, Wang Y, Li X, et al. Study on the relationship between digital health literacy and physical health among middle-aged and elderly people: mediating effect of physical exercise behavior. China Sport Sci Technol. 2023;59(12):44–51. [in Chinese]. [ Google Scholar ] 51. Jiao Z, Zhang J, Wang Y, et al. Tianxia120: a multimodal medical data collection bioinformatic system for proactive health management in Internet of Medical Things. J Healthc Eng. 2020;2020:8828738. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 52. Hu Z, Lei D, Zhao Y, et al. The impact of nursing interventions based on the integrated theory of health behavior change on patients with diabetic retinopathy. Chin J Nurs. 2024;59(3):300–7. [in Chinese]. [ Google Scholar ] 53. Chen Z. The impact of illness perception and psychological coherence on treatment adherence in hypertension patients [master’s thesis]. Yanji: Yanbian University; 2020. [in Chinese]. 54. Li J, Long T, Liu Y, et al. Relationship between illness perception and depressive symptoms among type 2 diabetes mellitus patients in China: a mediating role of coping style. J Diabetes Res. 2020;2020:3142495. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials Supplementary Material 1. (30.7KB, docx) Data Availability Statement No datasets were generated or analysed during the current study. Articles from BMC Public Health are provided here courtesy of BMC ACTIONS View on publisher site PDF (1.0 MB) Cite Collections Permalink RESOURCES Similar articles Cited by other articles Links to NCBI Databases Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top

Related documents

• Research on the utilization of community health services and its determinants among older adults: a cross-sectional study in Liuzhou City.#1053982
• The Influence of Tai Chi Practice on Blood Pressure and Brain Health Among Older Adults With Hypertension (ACTION)#432773
• Predictors of Illness Acceptance Among Hypertensive Patients in Freetown: A Multivariate Analysis of Sociodemographic, Religiosity, and Quality of Life Factors.#461482
• Hubungan Aktivitas Fisik dan Konsumsi Kopi dengan Tekanan Darah pada Pasien Hipertensi di Wilayah Kerja Puskesmas Pahandut: The Correlation Between Physical Activity and Coffee Consumption and Blood Pressure in Hypertensive Patients in Working Area of Pahandut Health Center#268956
• Hubungan Aktivitas Fisik dan Konsumsi Kopi dengan Tekanan Darah pada Pasien Hipertensi di Wilayah Kerja Puskesmas Pahandut: The Correlation Between Physical Activity and Coffee Consumption and Blood Pressure in Hypertensive Patients in Working Area of Pahandut Health Center#268850