Factors influencing self-help education during public emergencies among older migrants: A cross-sectional study in china's mainland

Abstract

Background：The number of older adult migrants in China continues to grow. As a unique population characterized by both “mobility” and “aging,” they face heightened risks during public emergencies.
Objective:This study investigated the current acceptance rate among these older adult migrants with respect to education for self-help in a public emergency (ESHPE) and analyzed influencing factors.
Study design：A cross-sectional study.
Methods:This study’s data were derived from the 2018 National Migrant Population Dynamic Monitoring Survey, conducted by the National Health Commission of China; overall, 5840 migrants were included in this study. SPSS 25.0 and RStudio 4.3.2 were utilized to analyze the selected sample, while Chi-square tests were conducted to perform univariate analysis on the acceptance rate of ESHPE among older adult migrants. A combination of the Random Forest model and binary logistic regression analysis was employed to assess the importance of statistically significant variables.
Results:Overall, 1162 older adult migrants received ESHPE, representing an acceptance rate of 19.90 %. The acceptance rate was lower among those aged over 75 (Odds Ratio [OR] : 0.637, 95 % Confidence Interval [CI] : 0.454-0.893); residing in rural villages (OR : 0.757, 95 % CI : 0.616-0.931); with a migration duration of 11-15 years (OR : 0.679, 95 % CI : 0.540-0.853), 16-20 years (OR : 0.725, 95 % CI : 0.547-0.961), or over 20 years (OR : 0.708, 95 % CI : 0.531-0.943); who had migrated for family (OR : 0.646, 95 % CI : 0.544-0.768), social (OR : 0.559, 95 % CI : 0.434-0.718), or other reasons (OR : 0.364, 95 % CI : 0.191-0.691); and who had not established resident health records (OR : 0.693, 95 % CI : 0.582-0.825) or were unaware of or unclear about such records (OR : 0.494, 95 % CI : 0.388-0.630).
Conclusions:The acceptance rate of ESHPE in this cohort remains relatively low. Therefore, targeted intervention measures tailored to their specific needs must be developed, and more focused educational resources for public emergencies must be created. Online interactive platforms should be established to enhance the self-help education content and strategies. Such measures should help improve the acceptance rate of ESHPE among older adult migrants.

Keywords

Self-help in a public emergency / Influencing factors / Older adult migrants / Health education

CRediT authorship contribution statement

Junli Chen: Writing -review & editing, Writing -original draft, Software, Methodology, Data curation. Qianqian Gao: Writing -review & editing, Writing -original draft, Data curation. Runguo Gao: Supervision, Writing -review & editing, Methodology. Weiqin Cai: Writing -review & editing, Supervision, Methodology. Haiyan Li: Writing -original draft, Methodology. Qi Jing: Supervision, Resources, Project administration. Hafiz T.A. Khan: Writing -review & editing. All the authors have read and approved the final version of this manuscript.

Ethics approval

The raw data employed herein were authorized by China’s National Population and Family Planning Commission. Each respondent provided informed consent before commencing the interview and completed the questionnaire anonymously. This study utilized de-identified, publicly available survey data from the China Migrants Dynamic Survey for secondary analysis. As the data were pre-existing, anonymized, and did not involve any experimental interventions, no additional ethical approval was required for this study. The study followed the principles of the Declaration of Helsinki as revised in 2013.

Funding

“Youth Innovation Team Plan” Project in Shandong University, China [Grant Number: 2022RW075].

Data availability

Restrictions apply to the availability of these data. Data available upon reasonable request.

Declaration of Competing Interest

All authors of this paper declare that they have no conflicts of interest with the journal, the institutions they are affiliated with, and any organizations, etc.

Acknowledgments

We thank those who helped us throughout the process of creating this article. Additionally, we thank the China Migrant Population Service Center, National Health Commission of the People’s Republic of China, for providing the required data and the training to utilize the same.

References

[1] The CPC Central Committee and the State Council. National Emergency Response Plan for Public Emergencies. Published 25 Feb 2025. Accessed 15 March 2025. https://www.gov.cn/zhengce/202502/content_7005635.htm.

[2] Rajapaksha RMNU, Khatri RB, Abeysena C, et al. Success and challenges of health systems resilience-enhancing strategies for managing Public Health Emergencies of International Concerns (PHEIC): a systematic review protocol. BMJ Open. 2022; 12(11):e067829. https://doi.org/10.1136/bmjopen-2022-067829

[3] Zhang A, Yang H, Wu X, Luo X, Gao J. Development and validation of the coping capacity measurement scale of public health emergencies in China. Int J Environ Res Public Health. 2021; 19(1):94. https://doi.org/10.3390/ijerph19010094

[4] Ochani R, Asad A, Yasmin F, et al. COVID-19 pandemic: from origins to outcomes. A comprehensive review of viral pathogenesis, clinical manifestations, diagnostic evaluation, and management. Infez Med. 2021; 29(1):20-36.

[5] Miller MJ, Loaiza JR, Takyar A, Gilman RH. COVID-19 in Latin America: novel transmission dynamics for a global pandemic? PLoS Negl Trop Dis. 2020; 14(5):e0008265. https://doi.org/10.1371/journal.pntd.0008265

[6] Alshammari MA, Alshammari TK. COVID-19: a new challenge for mental health and policymaking recommendations. J Infect Public Health. 2021; 14(8):1065-1068. https://doi.org/10.1016/j.jiph.2021.05.020

[7] Jafri MR, Zaheer A, Fatima S, Saleem T, Sohail A. Mental health status of COVID-19 survivors: a cross sectional study. Virol J. 2022; 19(1):3. https://doi.org/10.1186/s12985-021-01729-3

[8] González-Garcés Y, Domínguez-Barrios Y, Zayas-Hernández A, et al. Impacts of the COVID-19 pandemic on the mental health and motor deficits in Cuban patients with Cerebellar Ataxias. Cerebellum. 2021; 20(6):896-903. https://doi.org/10.1007/s12311-021-01260-9

[9] Zhang X, Zhang W, Shi H, et al. Acquirement of self-rescue health education on public emergencies and its influencing factors among Chinese migrants. Medicine and Society. 2023; 36(12):59-65,85. https://doi.org/10.13723/j.yxysh.2023.12.010

[10] Wang W, Song J, Fan C, Li Q, Ma D, Yin W. Cross-sectional study of factors affecting the receipt of mental health education in older migrants in China. BMC Public Health. 2023; 23(1):376. https://doi.org/10.1186/s12889-023-15287-6

[11] Cronin A, Hannigan A, Ibrahim N, et al. An updated scoping review of migrant health research in Ireland. BMC Public Health. 2024; 24(1):1425. https://doi.org/10.1186/s12889-024-18920-0

[12] Dong B. A study on the impact and mechanism of action of public health education on the health of the migrant population: evidence from the 2018 China migrants dynamic survey. Front Public Health. 2024;12:1308751. https://doi.org/10.3389/fpubh.2024.1308751

[13] National Health Commission of the People's Republic of China. China Migrant Population Development report 2018. Published 25 Dec 2018. Accessed 24 February 2025. https://www.gov.cn/xinwen/2018-12/25/content_5352079.htm.

[14] National Bureau of Statistics of China. China’s population development presents new features and trends -interpretation of the 7th national population census bulletin. Published 13 May 2021. Accessed 24 February 2025. https://www.stats.gov.cn/sj/sjjd/202302/t20230202_1896485.html.

[15] Zhao J, Kong F, Li S. Association between social integration and medical returns among the migrant elderly following children to Jinan City China. BMC Public Health. 2021; 21(1):1822. https://doi.org/10.1186/s12889-021-11901-7

[16] de Oca VM, García TR, Sáenz R, Guillén J. The linkage of life course, migration, health, and aging. J Aging Health. 2011; 23(7):1116-1140. https://doi.org/10.1177/0898264311422099

[17] Zhang J, Li J, Li C, Wang J. The impact of intergenerational support on older adults’ life satisfaction in China: rural-urban differences. Healthc Rehabil. 2025; 1(1):100011. https://doi.org/10.1016/j.hcr.2024.100011

[18] Bao Y, Tao J, Liu Q. "Embedding" and "pulling back": spatial transformations and urban assimilation of migrant elderlies following their children. Front Public Health. 2022;10:1009274. https://doi.org/10.3389/fpubh.2022.1009274

[19] Xu L, Xiong Y, Li H, et al. Analysis on the status of health literacy and its influencing factors among residents aged 15-69 years old in Haidian District of Beijing City in 2018. Journal of Hygiene Research. 2020; 49(5):738-743. https://doi.org/10.19813/j.cnki.weishengyanjiu.2020.05.007

[20] Li B, Huang Y, Ling C, Jiao F, Fu H, Deng R. The effect of community-based health education programs on health literacy in severely impoverished counties in Southwestern China: results from a quasi-experimental design. Front Public Health. 2023;10:1088934. https://doi.org/10.3389/fpubh.2022.1088934

[21] Zhang H, Zhang Y, Yan Y, Li X, Tian Y. Barriers and facilitators for accepting health education of Chinese rural older adults in Henan Province: a qualitative study. BMC Public Health. 2024; 24(1):2564. https://doi.org/10.1186/s12889-024-19910-y

[22] Sesti F, Minardi V, Baglio G, et al. Social determinants of mental health in Italy: the role of education in the comparison of migrant and Italian residents. Int J Equity Health. 2022; 21(1):116. https://doi.org/10.1186/s12939-022-01720-6

[23] Xu Q, Huang Y, Chen B. Comprehensive assessment of health education and health promotion in five non-communicable disease demonstration districts in China: a cross-sectional study. BMJ Open. 2017; 7(12):e015943. https://doi.org/10.1136/bmjopen-2017-015943

[24] Ritsema TS, Bingenheimer JB, Scholting P, Cawley JF. Differences in the delivery of health education to patients with chronic disease by provider type, 2005-2009. Prev Chronic Dis. 2014;11:130175. https://doi.org/10.5888/pcd11.130175

[25] Lin X, Mao X, Ai F, Yao W. Factors influencing utilization of communicable disease prevention and treatment education among the floating population: a cross-sectional study in China. BMC Public Health. 2023; 23(1):207. https://doi.org/10.1186/s12889-023-15126-8

[26] National Health Commission of the People’s Republic of China. 2018 Report on China’s migrant population development. Beijing: China Population Publishing House; 2019.

[27] He W. Does the immediate reimbursement of medical insurance reduce the socioeconomic inequality in health among the floating population? Evidence from China. Int J Equity Health. 2023; 22(1):96. https://doi.org/10.1186/s12939-023-01913-7

[28] Chiu HT, Tsai HW, Kuo KN, et al. Exploring the influencing factors of health literacy among older adults: a cross-sectional survey. Medicina (Kaunas). 2020; 56(7):330. https://doi.org/10.3390/medicina56070330

[29] Wen W, Dongtu Z, Jing F, Xiaoxiao Z, Yiqun Z, Yanli Y. Analysis of status quo and influencing factors of oral health literacy among the elderly in Hangzhou. BMC Oral Health. 2025; 25(1):235. https://doi.org/10.1186/s12903-024-05165-x

[30] Zhang C, Zhu R, Lu J, et al. Health promoting lifestyles and influencing factors among empty nesters and non-empty nesters in Taiyuan, China: a cross-sectional study. Health Qual Life Outcomes. 2018; 16(1):103. https://doi.org/10.1186/s12955-018-0936-5

[31] The CPC Central Committee and the State Council. Outline of the Tenth Five-Year Plan for National Economic and Social Development of the People's Republic of China. Accessed 2 Mar 2022. https://www.gov.cn/gongbao/content/2001/content_60699.htm.

[32] Zhou J, Sun W, Zhang C, et al. Prevalence of childhood hypertension and associated factors in Zhejiang Province: a cross-sectional analysis based on random forest model and logistic regression. BMC Public Health. 2024; 24(1):2101. https://doi.org/10.1186/s12889-024-19630-3

[33] Islam SMS, Talukder A, Awal MA, et al. Machine learning approaches for predicting hypertension and its associated factors using population-level data from three South Asian countries. Front Cardiovasc Med. 2022;9:839379. https://doi.org/10.3389/fcvm.2022.839379

[34] Pal SC, Ruidas D, Saha A, Towfiqul Islam ARM, Chowdhuri I. Application of novel data-mining technique-based nitrate concentration susceptibility prediction approach for coastal aquifers in India. J Clean Prod. 2022;346:131205. https://doi.org/10.1016/j.jclepro.2022.131205

[35] Toth R, Schiffmann H, Hube-Magg C, et al. Random forest-based modelling to detect biomarkers for prostate cancer progression. Clin Epigenetics. 2019; 11(1):148. https://doi.org/10.1186/s13148-019-0736-8

[36] Qiu X, Wang H, Lan Y, et al. Explore the influencing factors and construct random forest models of post-stroke depression at 3 months in males and females. BMC Psychiatry. 2022; 22(1):811. https://doi.org/10.1186/s12888-022-04467-0

[37] Liu F, Long Q, He H, et al. Combining the fecal immunochemical test with a logistic regression model for screening colorectal neoplasia. Front Pharmacol. 2021;12:635481. https://doi.org/10.3389/fphar.2021.635481

[38] National Health Commission of the People's Republic of China. Notice on the issuance of the "13th Five-Year Plan" for the national health and family planning service management of the migrant population.Accessed 2 October 2022. http://www.nhc. gov.cn/cms-search/xxgk/getManuscriptXxgk.htm?id= 35b213b217254b1fb8eb9a5254cb7506.

[39] Yang Z, Jiang CH. Community education for self-help in public emergency and its influencing factors among migrant population in the Yangtze River Delta. Chinese Journal of Public Health. 2021; 37(2):224-227. https://doi.org/10.11847/zgggws1130557

[40] Liu Y, Duan Y, He Y. The evolutionary trends of health inequality among elderly Chinese people and influencing factors of these trends from 2005 to 2017. Int J Health Plann Manag. 2022; 37(5):2918-2935. https://doi.org/10.1002/hpm.3529

[41] Tang S, Yang T, Ye C, et al. Research on grandchild care and depression of chinese older adults based on CHARLS2018: the mediating role of intergenerational support from children. BMC Public Health. 2022; 22(1):137. https://doi.org/10.1186/s12889-022-12553-x

[42] Hadlaczky G, Hökby S, Mkrtchian A, Carli V, Wasserman D. Mental health first aid is an effective public health intervention for improving knowledge, attitudes, and behaviour: a meta-analysis. Int Rev Psychiatry. 2014; 26(4):467-475. https://doi.org/10.3109/09540261.2014.924910

[43] Balatsoukas P, Kennedy CM, Buchan I, Powell J, Ainsworth J. The role of social network technologies in online health promotion: a narrative review of theoretical and empirical factors influencing intervention effectiveness. J Med Internet Res. 2015; 17(6):e141. https://doi.org/10.2196/jmir.3662

[44] Peng Y, Wu X, Atkins S, et al. Internet-based health education in China: a content analysis of websites. BMC Med Educ. 2014;14:16. https://doi.org/10.1186/1472-6920-14-16

[45] Kim YS, Lee HY, Lee MH, Simms T, Park BH. Mental health literacy in Korean older adults: a cross-sectional survey. J Psychiatr Ment Health Nurs. 2017; 24:523-533. https://doi.org/10.1111/jpm.12395

[46] Belo P, Navarro-Pardo E, Pocinho R, Carrana P, Margarido C. Relationship between mental health and the education level in elderly people: mediation of leisure attitude. Front Psychol. 2020;11:573. https://doi.org/10.3389/fpsyg.2020.00573

[47] Ministry of Finance of the People's Republic of China, National Health Commission of the People's Republic of China, National Healthcare Security Administration of the People's Republic of China, et al. Notice on the issuance of the management measures for subsidy funds for basic public health services and four other items. Published 17 Oct 2019. Accessed 15 October 2022. https://www.gov.cn/xinwen/2019-10/17/content_5440912.htm.

[48] Qian Y, Ge D, Zhang L, Sun L, Li J, Zhou C. Does Hukou origin affect establishment of health records in migrant inflow communities? A nation-wide empirical study in China. BMC Health Serv Res. 2018; 18(1):704. https://doi.org/10.1186/s12913-018-3519-6

[49] Wang J, Zhu J, Wang X, Che Y, Bai Y, Liu J.Sociodemographic disparities in the establishment of health records among 0.5 million migrants from 2014 to 2017 in China: a nationwide cross-sectional study. Int J Equity Health. 2021; 20(1):250. https://doi.org/10.1186/s12939-021-01584-2