Skip to main content

Perceived health competence and health education experience predict health promotion behaviors among rural older adults: A cross-sectional study

Abstract

Background

Health promotion behaviors are key determinant of health and well-being, and also play an important role in promoting successful aging. This study investigated levels of engagement in health promotion behaviors among Chinese rural older adults, and explored effects of perceived health competence, health education activities experience and sociodemographic variables on health promotion behavior in this population.

Methods

A multicenter cross-sectional survey was performed. Participants were recruited by a multistage, stratified, cluster-sampling procedure from Nanbu County, Sichuan Province, China. All participants completed four paper questionnaires: sociodemographic characteristics and health care status survey, the Chinese version of the health promoting lifestyle profile-II (HPLP-II), perceived health competence scale and Lubben social network scale. Data were collected from July to August 2021. Stepwise multiple linear regression analysis was performed to analyze the effects of different factors on health promotion behaviors.

Results

A total of 425 rural older adults with an average age of 72.7 years were included in analysis. The overall average score of HPLP-II was 101.6. The stepwise multiple linear regression analysis results showed that those who had higher perceived health competence (β = 0.66, P < 0.001), experienced health education activities (β = 0.254, P < 0.001), had physical examination (β = 0.107, P < 0.001), was married (β = 0.189, P < 0.001), had primary school education or above (β = 0.189, P < 0.001), and had a per capita monthly household income of more than 1000¥ (β = 0.085, P = 0.007), have higher levels of engagement in health promotion behaviors; while the level of health promotion behaviors of the older adults living alone was lower than that of living with their spouse or others (β = -0.192, P < 0.001). Combination of the above variables accounted for a total of 69.1% of the variance in health promotion behaviors. Conclusions: The level of health promotion behaviors among Chinese rural older adults is low. Perceived health competence and health education activities experience are two strong determinants of health promotion behaviors. Comprehensive health promotion programs aimed at improving perceived health competences and health literacy through health education activities may be an important part of optimizing the level of health promotion behaviors among rural older adults.

Peer Review reports

Background

China is one of the fastest ageing countries in the world, with the largest absolute number of older adults. It is reported that the number of people aged 60 and over in China has reached 264 million in 2020, accounting for 18.29% of the total population [1]. Previous studies have shown that 61.36% of Chinese older adults live in rural areas where the economic situation is poor [2]. The aging of the population triggers a series of problems, such as declining physical function, and increasing prevalence of chronic diseases and psychological problems [3, 4]. Therefore, finding effective ways to guarantee and improve the health level of rural older adults has become an important challenge to be addressed urgently. Health promotion behaviors have been identified as a key determinant of health and well-being, and also play an important role in promoting successful aging [5, 6]. Identifying the level of health promotion behaviors among older adults and exploring its key predictors are prerequisites for developing effective health promotion behaviors interventions among older adults.

Many previous studies have been conducted to investigate the level of health promotion behaviors among older adults [5, 7,8,9,10]. However, most of them focused on urban older adults [7, 8], or analyzed urban and rural residents as a group, without taking into account differences in where they lived [5, 9, 10]. Several studies have shown that the level of health promotion behaviors among older adults is affected by the living area [5, 9, 10]. Therefore, separate studies should be conducted to investigate the level and key predictors of health promotion behaviors in rural or urban older adults, thus providing references for the development of targeted interventions.

In previous studies, several factors have been explored as potential predictors of health promotion behavior. The main factors involved included gender [5, 10, 11], age [10, 12], living area [5, 9, 10], education status [5, 10, 12, 13], income [13], marital status [5, 10], regular physical examination [12, 13], social network [12, 14] and general self-efficacy [7, 12, 15, 16]. The relationships between most of the above factors and health promotion behavior in different studies are inconsistent, and further studies are needed.

Perceived health competence is the degree to which an individual feels capable of effectively managing his or her health behaviors and health outcomes [17]. According to the knowledge, attitude, belief and practice model, knowledge and attitudes/beliefs are key variables for behavior change [18]. Based on this model, older adults with health education experience are likely to have higher levels of health promotion knowledge and perceived health competence, and thus have higher levels of health promotion behaviors. However, few studies have focused on the relationship between perceived health competence, health education experience, and health promotion behaviors among rural older adults.

This study was conducted to investigate the levels of health promotion behavior among Chinese rural older adults, and to explore effects of perceived health competence, health education activities experience and sociodemographic variables on health promotion behaviors.

Methods

Study design and participants

This study was a multicenter cross-sectional survey conducted in Nanbu County, Sichuan Province, China. Rural community-dwelling residents who: were aged 60 years or older; resided in selected villages; had lived there for at least 1 year preceding the survey date; were able to understand and respond to the questions on the questionnaire were invited to participate in the study. Those who lived in selected villages but were housed in nursing homes or were unwilling to participant in the study were excluded.

Sampling

We used a multistage, stratified, cluster-sampling procedure, which considered geographical region and economic development status. In stage 1, Nanbu County, Sichuan Province, China was selected. Sichuan province can be classified as economically developed area in western China and plays an important role in the overall development of the country. Nanbu County, located in the northeast of Sichuan Province, is a typical area with serious aging of the older population, higher than the national and Sichuan average (Table 1), and the aging phenomenon of rural population in Nanbu Country is more prominent than that of urban population. Therefore, Nanbu Country, Sichuan Province was selected as the sample region. The social-economic characteristics of the sample region are shown in Table 1. Nanbu County has 38 townships and 363 administrative villages, each village has nearly 10 village groups and about 200 households. In stage 2, five townships were randomly selected from 38 townships. In stage 3, one administrative village was randomly selected from each selected township. In sage 4, three village groups were randomly selected from each selected administrative village. Finally, we screened all eligible individuals in the 15 village groups as the sample population for this study.

Table 1 Social-economic characteristics of sample region in 2020

Measures

All participants completed four paper questionnaires: sociodemographic characteristics and health care status survey, the Chinese version of the health promoting lifestyle profile-II (HPLP-II), perceived health competence scale (PHC) and Lubben social network scale.

Sociodemographic characteristics and health care status survey

Sociodemographic characteristics including gender, age, education status, marital status, per capita monthly household income, proportion of living with alone, smoking and drinking, were investigated. The questionnaire also addressed the following: regular physical examination and health education activities experience. These indicators were measured by the following questions: Have you had a regular physical examination during the past year? Have you participated in any health education activities before this survey? For each question, the response options included “yes” and “no”.

The Chinese version of the health promoting lifestyle profile-II (C-HPLP-II)

The health promoting lifestyle profile-II developed by Walker [19], translated and validated by Cao [20], was used to assess health promotion behaviors. The C-HPLP-II consists of 6 dimensions with a total of 40 items: interpersonal relationship (5 items), responsibility for health (11 items), stress management (5 items), diet (6 items), physical activity (8 items), spiritual growth (5 items). Each item is rated on a four-point Likert scale with a range of 1 (not at all) to 4 (always). The mean score was calculated with a higher score indicating higher levels of engagement in health promotion behaviors. The original scale had a Cronbach’s α coefficient of 0.94 at the time of its development. The Cronbach’s α coefficient of the scale in this study was 0.907.

The Chinese version of the perceived health competence scale (C-PHC)

The perceived health competence scale (PHC) by Smith [17], translated and validated by Liang [12], was used to assess perceived health competence. The C-PHC consists of 8 items on a five-point Likert scale. Respondents were asked how much they agreed with each item with a range of 1 (do not agree at all) to 5 (absolutely agree). The mean score was calculated with a higher score indicating higher perceived health competence. The original scale had a Cronbach’s α coefficient of 0.90 at the time of its development. The Cronbach’s α coefficient of the scale in this study was 0.893.

The Chinese version of the Lubben social network scale (C-LSNS)

The Lubben social network scale (LSNS) by Lubben [21], translated and validated by Qi [22], was used to assess the credible relationships among older adults with family/relatives and friends and the support they can get from them. The C-LSNS consists of 12 items. The score for each item ranges from 0 to 5, with a total score of 0–60. The higher the score, the richer the respondent's social network. The Cronbach’s α coefficient of the scale in this study was 0.792.

Data collection procedures

For data collection, the researchers informed the heads of selected village groups of the purpose of this study and obtained permission to conduct research in these places. In this study, 3 researchers and 9 research assistants formed three survey teams. Each team, including a researcher and three assistants, was in charge of the collection of data from a village group. All research assistants were senior nursing students. For inter-rater reliability, the survey teams were trained by the primary investigator on the contents of the questionnaire and survey techniques. The investigators then visited selected village groups and identify potential participants who were interested in participation by conducting household visits. They were screened for eligibility to participate, and if they were eligible to participate, the purpose and procedures of the study were explained to them. After written consent was obtained, a face-to-face interview was conducted using structured questionnaires. Participants completed the questionnaire themselves with a pen if they were able to do so. The completed questionnaires were then reviewed and collected by surveyors. For participants with literacy difficulties, mobility problems, or poor vision, a surveyor read the questions aloud and recorded the participants' responses to the questions. Data were collected from July to August 2021. A total of about 700 older adults were visited, of whom 273 were excluded from the study because of severe cognitive or communication disabilities (n = 81), unwillingness to participate in this study (n = 186), or local residence of less than one year (n = 6). The remaining 427 older adults who met the inclusion criteria were investigated. During the survey, two older adults dropped out and failed to complete the questionnaire. Therefore, data from the remaining 425 older adults were included in the final analysis.

Data analysis

Descriptive statistics, including number, percentage, mean and standard deviation, were used to summarize the characteristics of participants and the levels of health promotion behaviors. Differences in health promotion behaviors according to sociodemographic characteristics and health care status were analyzed using t-tests. Pearson’s correlation coefficients were calculated to determine associations of health promotion behaviors with age, perceive health competence and social network. Stepwise multiple linear regression analysis was performed to analyze the effects of different factors on health promotion behaviors. All statistical analyses were performed using IBM SPSS version 25, and a P-value less than 0.05 was considered statistically significant.

Results

Characteristics of the participants

Table 2 shows the characteristics of participants. The mean age of participants was 72.7 ± 7.0 years and most of them were women (71.8%). Less than half of participants were single (40%) and lived alone (37.6%), while the others lived with a spouse, adult/child or both. The majority of participants reported a low education level with 64.7% having no education. Most participants (78.8%) had a per capita monthly household income < 1000¥, but more than four-fifths of them had a regular physical examination during the past year. A total of 68.2% participants had no any experience of health education activities. The mean PHC and LSNS scores was 26.4 and 23.6, respectively, indicating poor perceived health competence and social network of this group of population.

Table 2 Characteristics of participants (N = 425)

Level of health promotion behaviors of participants

The overall average score of HPLP-II was 101.6 ± 12.9. The average item score for each of the six dimensions of health promotion behaviors were 2.85 in interpersonal relationship, 2.71 for nutrition, 2.70 for stress management, 2.65 for spiritual growth, 2.57 for physical activity, and 2.16 for responsibility for health.

Differences in health promotion behaviors according to sociodemographic characteristics and health care status

As shown in Table 3, significant differences in participants’ levels of engagement in health promotion behaviors were found according to most of the sociodemographic and health care variables, excluding smoking.

Table 3 Differences in health promotion behaviors according to sociodemographic characteristics and health care status (N = 425)

Correlations of health promotion behaviors with age, perceive health competence and social network

Perceived health competence (r = 0.724, P < 0.001) and social network (r = 0.184, P < 0.001) was significantly positively correlated, age (r = 0.184, P < 0.001) was significantly negatively correlated with health promotion behaviors.

Results of stepwise multiple linear regression analysis

The stepwise multiple linear regression analysis results showed that those who had higher perceived health competence, experienced health education activities, had physical examination, was married, had primary school education or above, and had a per capita monthly household income of more than 1000¥, had higher levels of engagement in health promotion behaviors; while the levels of health promotion behaviors of the older adults living alone was lower than that of living with their spouse or others (Table 4). Combination of the above variables accounted for a total of 69.1% of the variance in health promotion behaviors, F (417) = 133.245, P < 0.001, with an adjusted R2 of 0.686.

Table 4 Results of stepwise multiple linear regression analysis (N = 425)

Discussion

In this study, C-HPLP-II was used to investigate levels of engagement in health promotion behaviors among rural older adults in Nanbu County, Sichuan Province, China. The result showed that the overall average score of HPLP-II was 101.6, accounting for only 63.1% of the total score of the scale. It indicates that the overall levels of health promotion behaviors of this group of population was relatively low. It is necessary to develop and implement programs that encourage the rural older persons to engage in health promotion behaviors.

The average item score for each of the six dimensions of the C-HPLP-II was also calculated in this study. The dimensions that scored highest were interpersonal relationship and nutrition, and lowest were responsibility for health. The results are similar to those of studies in other countries or regions [10, 13]. This phenomenon may be explained by the fact that Chinese people have always attached importance to the maintenance of interpersonal relationships [23], and with the development of rural economy, rural older adults gradually pay attention to dietary ingredients and nutritional management [24]. The lowest score on health responsibility dimension may be related to the fact that few rural older adults are aware of their responsibility to be proactive in maintaining their health. Previous studies have provided evidence that older adults are not free from age-related stereotypes when they are faced with health problems [25]. For example, older adults tend to believe that the decline in their physical and cognitive functions is a natural aging process, so health care is unnecessary [26]. Additionally, they often express negative beliefs about the curability and controllability of health problems [27]. This low expectation of ageing may also be related to the inactive involvement of older adults in taking responsibility for their own health [28]. Therefore, interventions focused on promoting active ageing is recommended.

Stepwise multiple linear regression analysis was performed to examine the amount of variance in health promotion behaviors explained by the independent variables (Table 4). The results showed the combination of perceived health competence, health education activities experience, education status, per capita monthly household income, regular physical examination, living with alone and marital status accounted for a total of 69.1% of the variance in health promotion behaviors. Of them, perceived health competence (β = 0.66, P < 0.001) and health education activities experience (β = 0.254, P < 0.001) had the greatest effect on the health promotion behaviors of older adults.

In the study, participants with higher levels of perceived health competence were found to have higher levels of engagement in health promotion behaviors. Perceived health competence is the individual's perception or efficacy of health [17]. Empirical evidence has shown that self-efficacy is associated with many positive outcomes, particularly in the area of health behavior [7, 12, 15, 16]. The study supports this connection by demonstrating that perceived health competence positively predict health promotion behaviors. In other words, this study further confirmed the potentially powerful role of health self-efficacy in improving health promotion behaviors among rural older adults. This is a reminder that health care providers may be able to improve the level of health promotion behaviors of rural older adults by making efforts to enhance the perceived health competence.

Another key finding of the study was that older adults who participated in health education activities had higher levels of health promotion behaviors than those who did not. The finding provide evidence that the levels of health promotion behaviors may be improved through health education campaigns. One possible explanation for the finding is that older adults who experienced health education activities have higher health literacy [29, 30]. Previous studies have confirmed that individuals with higher health literacy have higher levels of health behaviors [31, 32]. Given the high proportion (68.2%) of rural older adults who did not participant any health education activities in this study, it is urgent to carry out health education activities in this population to improve their levels of health promotion behaviors.

In addition, this study confirmed that education level, per capita monthly household income, regular physical examination and marriage positively predicted health promotion behaviors, while living alone was a negative predictor of health promotion behaviors. These findings are consistent with previous empirical evidence [5, 10, 12, 13]. It is suggested that these five sociodemographic and health care variables should be taken into account when formulating policies and prevention plans for health promotion behavior of rural older adults.

Notably, although several studies have shown associations of social networks, smoking, drinking and health promotion behavior in different groups [33,34,35], this association has not been confirmed in this study. One possible explanation is that the social networks of rural Chinese older people are mainly composed of local rural relatives and neighbors [36]. Rural people generally have lower levels of education and health promotion behaviors, as confirmed by this study. Another explanation is that the prevalence of smoking and drinking among rural women in China is very low [37, 38], and the majority of the study population in this study were women. Further studies on relationships between these variables and health promotion behaviors of rural older adults are warranted in other countries or regions.

The study has several limitations. First, the cross-sectional design of the study allows only for correlation, not causation. To solve this problem, longitudinal studies will be necessary in the future. Second, participants were recruited from only one county, which limited the generalizability of the study findings. However, given the similarities between the participants in the study and the census demographic statistics of older adults in Sichuan and China, the study is likely to be representative of older adults in other geographic regions of China. Moreover, environmental factors that hinder the maintenance of positive health promotion behaviors in rural settings are prevalent in many villages around the world, which may enhance the generalizability of this study in other regions of China as well as in rural areas of the world.

Despite these limitations, the study has several strengths. First, the study investigated levels of health promotion behaviors of a large number of Chinese rural older adults. Second, the effects of sociodemographic and health care characteristics, perceived health competence and social network on the health promotion behaviors of rural older adults were analyzed in this study. Perceived health competence and health education activities experience were found to have the greatest effect on health promotion behaviors. The results of the study may be used as basic data for the development of health promotion programs for Chinese rural older adults. At the same time, these findings have implications for the development of preventive policies and programs to promote health behaviors in other countries with a similar socioeconomic structures and cultural expectations for health behaviors.

Conclusions

In conclusion, the level of health promotion behaviors among Chinese rural older adults is low. Perceived health competence and health education activities experience are the main predictors of health promotion behaviors in this group of population. It indicates comprehensive health promotion programs aimed at improving perceived health competences and health literacy through health education activities may be an important part of optimizing the level of health promotion behaviors among rural older adults. These findings have important implications for improving health promotion behaviors among older adults, thereby improving their health and promoting successful ageing in China and other countries or regions around the world that are experiencing demographic transition.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

HPLP-II:

Health promoting lifestyle profile-II

PHC:

Perceived health competence scale

LSNS:

Lubben social network scale

M:

Mean

SD:

Standard deviation

CI:

Confidence interval

References

  1. National bureau of statistics of the people's Republic of China. bulletin of the seventh national population census of the people's Republic of China (N0.5)——age composition of the population. 2021. Accessed at: http://www.stats.gov.cn/tjsj/tjgb/rkpcgb/qgrkpcgb/202106/t20210628_1818824.html.

  2. Gong F, Zhao D, Zhao Y, Lu S, Qian Z, Sun Y. The factors associated with geriatric depression in rural China: stratified by household structure. Psychol Health Med. 2018;23(5):593–603.

    PubMed  Article  Google Scholar 

  3. Ren J. The problem of population aging: challenges and countermeasures. Theor Exploration. 2009;1:98–100.

    Google Scholar 

  4. Guo Y, Zhang C, Huang H, Zheng X, Pan X. Mental health and related influencing factors among the empty-nest elderly and the non-empty-nest elderly in Taiyuan, China: a cross-sectional study. Pub Health. 2016;141:210–7.

    Article  Google Scholar 

  5. Harooni J, Hassanzadeh A, Mostafavi F. Influencing factors on health promoting behavior among the elderly living in the community. J Educ Health Promot. 2014;3:40.

    PubMed  PubMed Central  Google Scholar 

  6. Lee TW, Ko IS, Lee KJ. Health promotion behaviors and quality of life among community-dwelling elderly in Korea: A cross-sectional survey. Int J Nurs Stud. 2006;43(3):293–300.

    PubMed  Article  Google Scholar 

  7. Hepburn M. The variables associated with health promotion behaviors among urban black women. J Nurs Sch. 2018;50(4):353–66.

    Article  Google Scholar 

  8. Hepburn M, Bautista C, Feinn R. Health promotion behaviors among urban black women. Western J Nurs Res. 2021;43(11):1001–9.

    Article  Google Scholar 

  9. Zheng X. The study on influencing factors and mechanisms for elderly of health promoting lifestyles based on structural equation model. Shanxi: Shanxi Medical Univ; 2018.

  10. Zhao J, Tang W, Lan M, Zhang Y. Study on health-promoting lifestyle and influential factors of the aged in Chengdu. Modern Prev Med. 2018;45(4):663–5 (699).

    Google Scholar 

  11. Abad S. Optimization of health promotion model and evaluation of applying with adult health education theory in the elderly promoting behaviors change in city of Yazd. Tehran: Tarbiat Modarres Univ; 2006.

  12. Liang S, Du P. Health promotion lifestyle and its influencing factors among the elderly in Macao. Chin J Gerontol. 2018;38(23):5851–4.

    Google Scholar 

  13. Xiao X, Chen C, Hu L, Xie J, Wang Z. Health-promoting lifestyle and influencing factors of wrinkly and elderly residents. Sichuan Modern Prev Med. 2019;46(19):3575–9.

    Google Scholar 

  14. Watt RG, Heilmann A, Sabbah W, Newton T, Chandola T, Aida J, Sheiham A, Marmot M, Kawachi I, Tsakos G. Social relationships and health related behaviors among older US adults. BMC Public Health. 2014;14:533.

    PubMed  PubMed Central  Article  Google Scholar 

  15. Yeom HE. Association among ageing-related stereotypic beliefs, self-efficacy and health-promoting behaviors in elderly Korean adults. J Clin Nurs. 2014;23(9–10):1365–73.

    PubMed  Article  Google Scholar 

  16. Kim AS, Jang MH, Park KH, Min JY. Effects of self-efficacy, depression, and anger on health-promoting behaviors of Korean elderly women with hypertension. Int J Environ Res Public Health. 2020;17(17):6296.

    PubMed Central  Article  Google Scholar 

  17. Smith SM, Wallston KA, Smith CA. The development and validation of the perceived health competence scale. Health Edu Res. 1995;10(1):51–64.

    CAS  Article  Google Scholar 

  18. Yang K. knowledge, attitude, belief and practice model. Shanghai Med Pharm J. 2013;10:42.

    CAS  Google Scholar 

  19. Walker S, Sechrist K, Pender N. The Health-Promoting Lifestyle Profile II. 1995.

  20. Cao W, Guo Y, Ping W, Zheng J. Development and psychometric tests of a Chinese version of the HPLP-II scales. Chin J Dis Control Prev. 2016;20(3):286–9.

    Google Scholar 

  21. Lubben J, Gironda M, Lee A. Refinements to the Lubben social network scale: The LSNS-R. Behav Meas Lett. 2002;7(2):2–11.

    Google Scholar 

  22. Qi Y. Study on the living conditions and quality of life of the elderly in mainland China and Hong Kong. Beijing: Peking University Press; 1998.

  23. Jia Z, Li X, Chang Z. Why do Chinese people attach importance to interpersonal relationship? Sci Soc Psychol. 2012;11:48–53.

    Google Scholar 

  24. Li X. The association of fruit and vegetable intake with the changes of serum lipid levels and incidence of elevated TC and LDL-Cin middle-aged and older Chinese population. Beijing: Peking Union Medical College; 2018.

  25. Yeom HE, Heidrich SM. Effect of perceived barriers to symptom management on quality of life in older breast cancer survivors. Cancer Nurs. 2009;32(4):309–16.

    PubMed  PubMed Central  Article  Google Scholar 

  26. Levy BR, Ashman O, Slade MD. Age attributions and aging health: contrast between the United States and Japan. J Gerontol B Psychol Sci Soc Sci. 2009;64(3):335–8.

    PubMed  Article  Google Scholar 

  27. Heidrich SM, Egan JJ, Hengudomsub P, Randolph SM. Symptoms, symptom beliefs, and quality of life of older breast cancer survivors: a comparative study. Oncol Nurs Forum. 2006;33(2):315–22.

    PubMed  Article  Google Scholar 

  28. Kim SH. The association between expectations regarding aging and health-promoting behaviors among Korean older adults. Taehan Kanho Hakhoe Chi. 2007;37(6):932–40.

    PubMed  Google Scholar 

  29. Osborn CY, Paasche-Orlow MK, Bailey BC, Wolf MS. The mechanisms linking health literacy to behavior and health status. Am J Health Behav. 2011;35(1):118–28.

    PubMed  PubMed Central  Article  Google Scholar 

  30. Mao T, Qu C, He C, Wang X, Ji L, Xu X, Yang G, Li X. Analysis on the influence of health literacy on daily healthy behaviors among residents in Jiangsu Province. Chin J of Health Educ. 2020;36(1):20–3.

    Google Scholar 

  31. Cubero J, Sánchez S, Calderón M, Vallejo JR, Franco-Reynolds L. Health Education & e_Health Literacy. In: Ribeiro J, Lima E, editors. Atas do II Encontro Nacional de Novos Investigadores em Saúde & II International Meeting of New Health Researchers. Leiria: Politécnico de Leiria; 2017. p. 6.

  32. Wen X. Affection of health education on health literacy and health. Beijing: Peking University; 2014.

  33. Lolokote S. Effects of socio-cultural factors on college students’ self-rated health status and health-promoting lifestyles in Dalian. China: A Cross-sectional study. Dalian Medical University; 2017.

    Google Scholar 

  34. Liu F. Health behavior status and its influencing factors in patients with migraine. Henan Med Res. 2020;29(34):6408–10.

    Google Scholar 

  35. Zou M. Health-promoting lifestyle and the influence factors among medical staff of health-promoting hospitals in Chongqing. Chongqing: ChongQing Medical University; 2020.

  36. Zhang Z. A review of research on social support networks for rural older adults. Labor Secur World. 2020;2:76–7.

    Google Scholar 

  37. Xu Q, Chen L, Zhang X, Zhou J, Ge S. A survey on smoking, drinking and sleep status of rural older adults a case study of rural older people in Bijie, Guizhou Province. Cardiovasc Dis J Integr Tradit Chin Western Med (Electron). 2019;7(2):196–7.

    Google Scholar 

  38. Xia C, Shi Y, Huang H. Drinking behavior and influencing factors of rural older adults in Suqian City. Chin J Gerontol. 2018;38(17):4282–4.

    Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This study was supported by Nanchong Federation of Social Science Associations (Grant no. NC2020C061). The funding body played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

XX conceived the study and wrote the paper. XX, JD and JH conducted the analysis of the data. XX, JD, JH, YL and ZL contributed to the study design and methodology. All authors contributed to the interpretation of the findings, commented on drafts of the paper and approved the final version.

Corresponding author

Correspondence to Xia Xie.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Biomedical Ethics Committee of Affiliated Hospital of North Sichuan Medical College (Approval number: 2021ER068-1). Standard procedures for the protection of human rights were carefully followed before data collection, including explanation of the purpose of the study, patient rights and confidentiality, and obtaining written informed consent. The authors declare that all methods were carried out in accordance with relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, 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 changes were made. 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/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Xie, X., Du, J., He, J. et al. Perceived health competence and health education experience predict health promotion behaviors among rural older adults: A cross-sectional study. BMC Public Health 22, 1679 (2022). https://doi.org/10.1186/s12889-022-14080-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-022-14080-1

Keywords

  • Health behaviors
  • Health promotion
  • Perceived health competence
  • Health education activities experience