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Factors influencing senior care and living preferences among older adults in Jiangsu, China: a cross-sectional survey study



As the population ages, senior care for older adults in China has become increasingly important and has attracted the attention of both government and society. This study aimed to explore preferences and influencing factors related to senior care among older Chinese adults and thus propose effective and targeted strategies for the development of a comprehensive care system for older adults in the aging Chinese population.


Data were obtained from a cross-sectional survey conducted in sixteen communities or villages in Jiangsu Province, China, from July to September 2021. Guided by the Andersen Behavioral Model, multivariate logistic regression was conducted to identify factors associated with preferences for senior care arrangements.


A total of 870 respondents were included in the study, 60.11% of whom preferred receiving care in their own homes, while only 13.68% chose residential care facilities (RCFs). For predisposing factors, rural respondents preferred receiving care in their own homes compared to urban respondents (children’s home: OR = 0.55, P < 0.01; RCF: OR = 0.58, P < 0.01). Concerning enabling factors, respondents who were not employed (OR = 2.30, P < 0.01) and those without financial support (OR = 2.73, P < 0.05) preferred RCFs to their own homes. Respondents receiving life assistance (sometimes: OR = 2.76, P < 0.001; regularly: OR = 2.57, P < 0.01; every day: OR = 3.57, P < 0.001) preferred their children’s homes to their own homes. In terms of need factors, respondents with noncommunicable diseases (NCDs, OR > 1, P < 0.05), those who knew about RCFs (some: OR = 0.53, P < 0.005; no: OR = 0.10, P < 0.001) and those with a good impression of RCFs (fair: OR = 3.72, P < 0.05; good: OR = 11.91, P < 0.001) preferred receiving care in RCFs compared to their counterparts.


Older Chinese adults’ senior care preferences were affected by predisposing factors, enabling factors, and need factors. Policy-makers should consider targeted measures to identify more precise senior care services and thus address aging challenges in China.

Peer Review reports


Population aging is a crucial policy issue worldwide. According to China’s seventh census, the proportion of people aged 65 years and older was approximately 13.8% in 2020 and is predicted to reach approximately 30% by 2050 [1]. The rapidly increasing aging trend has resulted in difficulties for social and economic life in the country. The low fertility rate due to the “one-child” policy [2], changes in fertility perceptions, the irreversibility of aging, and the vulnerability of older adults in terms of physical, psychological, and social factors continue to challenge the senior care service system. Therefore, senior care has become an urgent issue in China [3].

The classification of senior care varies in China. In previous studies, three main categories of senior care have been summarized. First, according to different care responsibilities, senior care can be divided into self-support, family support, and social support [4]. Second, according to where senior care is provided, senior care can be divided into institutional senior care, community senior care, and home-based informal care [5]. Third, the modes of senior care provision can be divided into family care, state-based care, and mixed care [6]. According to previous studies, “aging in place” is the main choice among most older adults [7, 8], which is consistent with the traditional model of senior care in China. However, the mobility of young laborers has increased the number of older adults living independently, and the traditional senior care model that relies on family will not be able to meet the growing demands of older adults [9]. Therefore, preferences and influencing factors related to senior care arrangements must be explored [10] to facilitate the formulation and implementation of government policies.

China is currently undergoing a major social, economic, and demographic transition, and the senior care service sector is facing challenges. The main challenge is determining how to meet the various needs of older adults and reduce the financial burden on families and society, which is why studying the senior care and living preferences of older adults in China is particularly important. Previous studies of senior care choices have mainly focused on demographic characteristics, including gender, education level, number of children, living conditions, physical condition [11,12,13,14,15], and individual resources, and possible influencing factors were directly included in these analyses without a theoretical framework, resulting in limited research on senior care preferences. Senior care is a “demand-oriented” service, and studies from the demand side of living arrangements in relation to senior care can facilitate a better understanding of preferences and attitudes toward residential choices, which can help us respond to the needs of older adults and predict future needs [16, 17].

Conceptual framework

The Andersen Behavioral Model, which guided this study, was designed to explore health service utilization [18] and has recently been extended to examine the relationship between personal choices and health service utilization among Chinese people [19]. It has been used extensively in studies of health services [20,21,22,23], mental health services [24, 25], and quality of life [26, 27], among others. The Andersen Behavioral Model distinguishes variables that contribute to different health service needs into three categories: predisposing factors, enabling factors and patients’ illness level (representing the need factor) [18, 28]. Predisposing factors include demographic and social characteristics [29]. Enabling factors refer to various resources that facilitate individual utilization of available health services [30], such as individual resources, intergenerational relationships, and social support [31, 32]. Need factors correspond to perceived or actual service and health necessities [33, 34].

Previous studies in China have indicated that residence, gender, age, marital status, and education level are predisposing factors for senior care preferences [10, 19, 29, 35]. Economic status and employment status have been defined as important indicators for measuring individual resources [36, 37]. Intergenerational relationships and social support have also been reported to be important indicators for measuring individual resources [38, 39]. Self-rated health was reported to be a subjective measure of internal perceptions and priorities [40] and has been used to evaluate a broad range of factors related to health care [41]. Furthermore, previous studies have shown that the experience of caring for older adults can influence judgments about living arrangements [42, 43]. Planning for old age has been reported to be affected by anchoring bias, which is a cognitive bias that affects decision-making [42, 44, 45]. Based on these previous findings, this study considered RCFs, including whether respondents were knowing about RCFs and their impressions of RCFs, to examine the effects described above on older adults’ senior care choices.

Although some studies have examined senior care preferences in China, most used two categories of senior care models, where cohabitation with children or living in an institution served as the dependent variable [46, 47]. Based on family structure and living arrangements in China, we used three categories (home-based care, children’s homes, and RCFs) of senior care preference as the dependent variable in the present study. The Anderson Behavioral Model was used as the theoretical framework, and potential predisposing variables constituted the baseline model. Then, enabling factors and need factors were added successively to establish Model 2 and Model 3, respectively, to evaluate the influence of predisposing factors, enabling factors and need factors and to compare the interpretation power of the three models. This study design was employed to produce holistic results and allow comparisons of the influence of each category. Based on the findings, targeted strategies were formulated to facilitate the development of a comprehensive care system for older adults in the aging Chinese population.


Sampling and data collection

A cross-sectional survey was conducted in sixteen communities or villages in Jiangsu Province, China, from July to September 2021. These communities/villages were located in Nantong (n = 4751), Nanjing (n = 4276), Xuzhou (n = 4952), Changzhou (n = 4055), and Taizhou (n = 4014), which were selected based on their geographical locations and economic development. In each city, three or four communities/villages were randomly selected, and potentially eligible participants in these communities/villages were identified by rural villages or urban residential committees. Household surveys were conducted under the guidance of pertinent organizational leaders, and approximately 60 elderly people were randomly selected from each community/village. The inclusion criteria were as follows: (1) age ≥ sixty years; (2) able to understand and respond to questions asked by investigators; and (3) willingness to be interviewed. The exclusion criteria were mental disorders and poor adherence (including obviously inaccuracy answer and withdrawal from the survey process).

This study used the Raosoft online sample size calculator to calculate the lowest sample size limit with a response rate of 50%, a confidence interval of 99%, and a margin of error of 5%. The minimum sample size calculated was 645. Face-to-face questionnaire surveys (Annex 1) were conducted to collect information about the participants’ preferences for senior care. A total of 890 questionnaires were collected, and 870 valid questionnaires were ultimately obtained.


Dependent variable

The respondents’ senior care preferences were assessed using the following question: “Where do you plan to stay for your senior care?” Three response options were provided: in my own home, which was coded as 1; in my children’s home, which was coded as 2; and in a residential care facility (RCF), which was coded as 3.

Independent variable

Guided by the Andersen Behavioral Model and previous research, the predisposing variables included residence (urban or rural), age (60–69, 70–79 or ≥ 80), gender (male or female), marital status (married or other), and education level (elementary school and below, middle school, or high school and above).

The enabling variables included employment status (yes or no), retirement pension (yes or no), the number of children (0, 1, 2, or ≥ 3), living arrangement (living alone or not), financial support (yes or no), the frequency of life assistance (rarely or never, sometimes, regularly, or every day), the number of relatives available to meet or contact (≤ 2, 3–4 or ≥ 5), and the number of friends available to meet or contact (≤ 2, 3–4 or ≥ 5).

The need factors included self-rated health (good, fair, or poor), the number of NCDs (0, 1–2, or ≥ 3), and caring for elderly parents (yes or no). To determine participants’ opinions on senior care, they were asked, “Do you know about senior care institutions/nursing homes?” (yes, some, none) and “What is your impression of senior care institutions/nursing homes?” (poor, fair, good).

Statistical analysis

Relationships between predisposing factors, enabling factors, need factors and senior care preferences were first assessed using chi-square tests. Then, three steps of multivariate logistic regressions were run. The dependent variable in each model was senior care preference, and the reference group was “in my own home”. In Model 1, predisposing factors were controlled. Model 2 was further adjusted for enabling factors. Model 3 was subsequently adjusted for need factors. Odds ratio (OR) with 95% confidence intervals (CIs) were used to compare the effects of different variables. The level of significance was defined as a 2-sided P value < 0.05. All analyses were conducted using STATA 18.0.


Description of the sample

A total of 870 respondents aged 60 years and older were included in the study, with a response rate of 97.8%. Among the respondents, 523 (60.11%) preferred their own homes, and 13.68% preferred RCFs. The characteristics of the respondents’ predisposing factors are shown in Table 1. More than half of the respondents were rural residents (54.94%). Males accounted for 51.72% of the sample. A total of 71.15% of the respondents were married, and 28.85% were widowed. For education, 38.97% had completed high school and above. Respondents with different residences, marital statuses, and education levels had different senior care preferences (P < 0.05).

Table 1 Predisposing factors and preferences regarding senior care among the respondents (N = 870)

Table 2 shows the enabling factors of the respondents. Most respondents (71.15%) were not employed, and 58.28% did not have a retirement pension. A total of 1.38%, 250.57%, 41.03%, and 37.01% of the respondents with no children, one child, two children, and more than three, respectively. Furthermore, 14.94% of the respondents lived alone, and 87.28% did not receive financial support from their children. Except for the number of relatives, all other variables differed with respect to preferences for senior care (P < 0.05).

Table 2 Enabling factors and preferences regarding senior care among the respondents (N = 870)

Regarding need factors, approximately 46.78% of the respondents reported good health, and 66.09% had at least one chronic disease. In terms of RCFs, 18.05% of the respondents knew about RCFs, and 14.37% reported a good impression of RCFs. As shown in Table 3, self-rated health, the number of NCDs, knowing about RCFs, and impressions of RCFs were significantly associated with the senior care preferences of the respondents (P < 0.05).

Table 3 Need factors and preferences regarding senior care among the respondents (N = 870)

Factors associated with senior care preferences among older adults

The multinomial logistic regression model is presented in Table 4. Living in one’s own home served as the reference category, which was compared with living in children’s homes and living in RCFs.

Among the predisposing factors, differences in residence, marital status, and education level were found to be statistically significant. Older adults living in rural areas were more inclined to choose their own homes for senior care than those living in urban areas (OR < 1). Preferences for senior care were also affected by education level; older adults at the middle school level were more likely to choose their own homes than RCFs (Model 1: OR = 0.50, P < 0.05; Model 2: OR = 0.48, P < 0.05; Model 3: OR = 0.42, P < 0.05).

For enabling factors, older adults who were not employed were more likely to choose RCFs (Model 2: OR = 2.08, P < 0.01; Model 3: OR = 2.30, P < 0.01) than their own homes. Those without financial support were more likely to choose RCFs than their own homes (Model 2: OR = 2.63, P < 0.05; Model 3: OR = 2.73, P < 0.05). The results also indicated that older adults were more likely to choose their children’s homes when their children more frequently provided life assistance (OR > 1). Compared with those living in children’s homes, older adults with more than five friends were more inclined to choose their own homes for senior care (Model 2: OR = 0.58, P < 0.01; Model 3: OR = 0.54, P < 0.01).

Finally, we observed that older adults with chronic diseases preferred RCFs and their children’s homes. Both knowing about RCFs (some: OR = 0.53, P < 0.005; none: OR = 0.10, P < 0.001) and impressions of RCFs (fair: OR = 3.72, P < 0.05; good: OR = 11.91, P < 0.001) were significant factors influencing senior care preferences. Respondents who knew about RCFs and those with a positive impression of RCFs preferred to RCFs for senior care.

Table 4 Multivariate logistic regression of senior care preferences


Under the analysis framework of the Andersen Behavioral Model, the present study explored preferences for and influencing factors of senior care in Jiangsu Province, China. We found considerable differences in the senior care preferences of older adults, with family care being the predominant choice, which is consistent with previous evidence [48,49,50].

First, older adults in different residential settings preferred their own homes, and the proportion of older adults relying on senior care institutions in rural areas was lower than that in urban areas, primarily because the addresses of senior care institutions were mostly located in cities or towns [51, 52]. We found that older adults with higher education levels were more likely to prefer living in their own homes than in senior care institutions. Studies have shown that education level influences the choice of senior care model through the associated quality of employment and life goals of older adults [29, 53]. We also found that older adults who were currently employed were more likely to prefer living in their own homes than unemployed older adults, possibly because work can provide more social interaction, which is positively associated with mental and physical health, and promote a stronger tendency toward self-care [54].

Second, intergenerational relationships and family are among the most direct sources of support for older adults [55, 56] and have a particular impact on living arrangements in Chinese culture. We found that older adults without financial support were more likely to choose RCFs, which is consistent with other studies [32]. Previous studies have confirmed that financial support can reflect the relationship between older adults and their children [57], which influences their health status and living arrangements [58]. In addition, the frequency of life assistance was also an important factor reflecting the relationship between older adults and their children [59]. Unsurprisingly, older adults were more likely to prefer living in their children’s homes when the frequency of life assistance from family was higher. Moreover, life assistance has been demonstrated to be distinct from financial support [60]; older adults who perceive more actual care and support experience greater familial intimacy and spiritual comfort [61], which can influence living arrangement choices. The results indicated that older adults with more than 3 children preferred to live in their own homes, which may suggest that care responsibilities can be shared by multiple family members in the home, thus reducing the economic burden on the children [62]. This preference was also influenced by Chinese culture [63,64,65], as people prefer to age at home when conditions permit.

Third, older adults with NCDs preferred to live in their children’s homes or in RCFs, suggesting that these older adults need help to maintain their lives and their health [66]. A study demonstrated that formal care services were favored by older adults, especially those with poor mental or physical conditions [67]. Interestingly, having more than 3 NCDs had a significant impact only on the preference for living in children’s homes and not on the preference to remain at home; whether this finding is attributable to the sample size in our study requires further discussion. We also found that the respondents who did not know about RCFs tended to live in their own homes rather than in RCFs. A plausible explanation could be that decision-making is influenced by the degree of information mastery [68], and a more familiar environment provides security and independence [69]. In addition, older adults with a good impression of RCFs were more receptive to institutional care. Favorable exposure to RCFs has been reported to be associated with a positive attitude toward RCFs [70]. According to First Impress [71], older adults’ impressions of RCFs directly affect their choice of senior care, and older adults with positive impressions prefer RCFs [5]. Notably, few respondents preferred RCFs in the present study, and our results indicated that most respondents had little knowledge about RCFs. To develop RCFs, policy-makers should strengthen publicity among older adults.


The strength of this study was our use of the Andersen Behavioral Model to investigate senior care preferences among older adults. We added potential influencing factors to the model, including individual resources, intergenerational relationships, family support and social support, as well as extended need factors, including knowing about and impressions of RCFs, to explore their influence on care choices. Previous research has demonstrated that older adults prefer to live in their own homes for as long as possible [72]. Nevertheless, with the transformation of the Chinese family structure, the perception of traditional senior care has markedly changed, the concept of independent senior care has gradually emerged, and more attention has been directed toward institutional care [46]. Moreover, as shown in the results, having a good impression of RCFs and knowing about RCFs may increase older adults’ willingness to live in such institutions, which needs to be considered. Overall, receiving senior care from professional institutions is desirable for older adults. More specifically, the transition from family care to socialized care will become an inevitable trend in the future.

Our study provides three primary contributions. First, we defined three categories of living arrangements for older adults’ senior care preferences by asking participants where they preferred to live as they continued to age. Expanding the understanding of older adults’ senior care preferences and attitudes is critical for forecasting and responding to demands for senior care [73]. Second, we comprehensively integrated, expanded, and analyzed factors affecting the senior care preferences of older adults based on the Andersen Behavioral Model, including psychosocial factors, individual resources, intergenerational relationships, family and social support, and knowing about and impressions of senior care institutions. Third, we analyzed older adults’ preferences through their choice of living arrangement as they age, which enriched the existing research on the preferences of older adults. Although family care predominated among the senior care preferences of the surveyed older adults, institutional care was gradually accepted by some older adults, which may soon become a better choice for China [6].

Policy implications

According to the findings for senior care preferences among older adults in our study, meeting older adults’ needs required not only a change in people’s conceptions of senior care but also strong support from the government and consideration from society. First, urban and rural senior care systems should be constructed based on the needs of older adults and improved to provide targeted senior care services. Second, different senior care models urgently need to be promoted through the internet, television, newspapers, and other media, and participation from multiple parties and social interactions should be encouraged. Third, laws regarding the senior care service system should be updated considering different senior care models, and high-quality services should be provided under third-party supervision.


This study had several limitations that need to be addressed. First, the respondents were recruited from several cities in Jiangsu Province; therefore, the generalizability of the study findings is limited. Future studies should include larger and more diverse samples to increase representativeness. The classification and inclusion criteria for variables based on the Andersen Behavioral Model may vary in different studies. Additionally, the survey used in this study included some recall questions, and the responses may have been biased due to the aging of the older adults, who may have had poor memories and cognitive impairment. Finally, since our data were collected at one point in time, no temporal changes in participants’ preferences for senior care could be measured. Studies have shown that willingness and preferences for senior care usually change over time [48]. Future studies should further investigate changes in older adults’ senior care preferences over time.


Our study found that preferences for senior care among older adults were affected by predisposing factors, enabling factors, and need factors. China is in a critical initial period of transition with respect to pensions, and the results of this study will provide new perspectives for policy-makers when addressing the challenges faced by older adults in China. This study can serve as a reference for the allocation of senior care resources to meet the growing needs of older adults.

Data availability

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


  1. Office of the Leading Group of the State Council for the Seventh National Population Census. Main data of the seventh national population census 2021. 1st ed. Beijing: China Statistics; 2022. (in Chinese).

    Google Scholar 

  2. Lu J, Zhang L. Research on risk of old age support in the process of comprehensively building a well-off society—In a perspective on transformation of major contradiction of the society in the new era. J Huazhong Univ Sci Technol (Social Sci Edition) 2018(1):8–14. (in Chinese).

  3. Su B, Li Y, Zheng X. Who are to support the aged in rural China? The study of people’s willingness to purchase socialized care service and its influencing factors. J RURAL STUD 2019(prepublish).

  4. Wang Y, Zhang R, Peng S. Cognitive Differences and Influencing Factors of Chinese People’s Old-Age Care Responsibility against the Ageing Background. HEALTHCARE-BASEL 2021, 9(1).

  5. Zhao R, Zhou H, Zhu J. Factors Associated with willingness to choose the way for Old-Age Care: a Population-based cross-sectional study in Chongqing, China. Inquiry: J Med care Organ Provis Financing 2021, 58.

  6. Lu J, Zhang L, Zhang K. Care preferences among Chinese older adults with Daily Care needs: individual and community factors. RES AGING. 2021;43(3–4):166–76.

    Article  PubMed  Google Scholar 

  7. Liu H. Analysis of the intentions of the elderly in Shandong Province and factors influencing them. Shandong: Shandong University; 2019. (in Chinese).

    Google Scholar 

  8. Fänge A, Ivanoff SD, Sahlgrenska A, Institutionen För Neurovetenskap Och, Fysiologi SFAA, Göteborgs U, Gothenburg U, Institute Of Neuroscience And, Physiology DOAL, Sahlgrenska A. The home is the hub of health in very old age: Findings from the ENABLE-AGE Project. ARCH GERONTOL GERIAT 2009, 48(3):340–345.

  9. Wang S, Xiao P, Wu X, Song S. Study on the current state of the use of and demand for on-site medical care for the home-based elderly with chronic diseases in Chaoyang District, Beijing. Chin Nurs Res. 2020;34(6):1070–3. (in Chinese).

    Google Scholar 

  10. Ying L, Zhihong S, Yanli W, Zheng K. An analysis of the elderly’s preference choice and its influencing factors: based on modified Andersen model. Chin J Geriatric Care. 2022;20(03):79–84. (in Chinese).

    Google Scholar 

  11. Wang P, Liu J, Li Y. Research on the Influencing Factors of Social Network on Community Endowment of Elderly in Rural areas of Shaanxi. Humanit Social Sci 2017, 5(5).

  12. Ma Y, He Y, Ren Y, Xin X, Li Z, Liu L. Research on Community Endowment Service Model Combining Medical Treatment with Endowment Based on Intelligent Endowment Service. In: Research on Community Endowment Service Model Combining Medical Treatment with Endowment Based on Intelligent Endowment Service Moscow, Russia; 2019: 567–570.

  13. Li L. Rural Residents’ Endowment Willingness and Its Influencing Factors in Jilin Province. In: Rural Residents’ Endowment Willingness and Its Influencing Factors in Jilin Province:2016; Ji Nan, Shan Dong, China; 2016: 580–585.

  14. Li L, Zhang D, Wang Y, Sun W. Analysis on influencing factors of pension willing and pension mode choice in northern Anhui. J Anhui Tech Coll Water Resour Hydroelectric Power. 2022;22(03):46–9. (in Chinese).

    Google Scholar 

  15. Li X. A study on the willingness and its influencing factors of the Rural Elderly Institutions. Trop Agricultural Eng. 2021;45(3):44–7. (in Chinese).

    Google Scholar 

  16. Zhou Y. Review on the research of Community Home-based pension in China: based on the Domestic Literature Research from 2011 to 2020. J Sociol Ethnology. 2022;7(4):45–53.

    Google Scholar 

  17. Tsuya NO, Martin LG. Living arrangements of elderly Japanese and attitudes toward inheritance. J Gerontol (Kirkwood). 1992;47(2):S45.

    Article  CAS  Google Scholar 

  18. Andersen R, Newman JF. Societal and Individual Determinants of Medical Care Utilization in the United States. Milbank Meml Fund Q Health Soc. 1973;51(1):95.

    Article  CAS  Google Scholar 

  19. Liu T, Hao X, Zhang Z. Identifying community healthcare supports for the elderly and the factors affecting their aging care model preference: evidence from three districts of Beijing. BMC HEALTH SERV RES. 2016;16(Suppl 7):83–92.

    PubMed Central  Google Scholar 

  20. Zhu H. Unmet needs in long-term care and their associated factors among the oldest old in China. BMC GERIATR. 2015;15(1):46.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Heider D, Matschinger H, Müller H, Saum K, Quinzler R, Haefeli WE, Wild B, Lehnert T, Brenner H, König H. Health care costs in the elderly in Germany: an analysis applying Andersen’s behavioral model of health care utilization. BMC HEALTH SERV RES. 2014;14(1):71.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Zeng L, Xu X, Zhang C, Chen L. Factors influencing long-term Care Service needs among the Elderly based on the latest Anderson Model: a Case Study from the Middle and Upper reaches of the Yangtze River. HEALTHCARE-BASEL. 2019;7(4):157.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Aroian KJ, Wu B, Tran TV. Health care and social service use among Chinese immigrant elders. RES NURS HEALTH. 2005;28(2):95–105.

    Article  PubMed  Google Scholar 

  24. Yang H, Hagedorn A, Zhu H, Chen H. Mental health and well-being in older women in China: implications from the Andersen model. BMC GERIATR 2020, 20(1).

  25. Roh S, Burnette CE, Lee KH, Lee Y, Martin JI, Lawler MJ. Predicting Help-Seeking Attitudes toward Mental Health Services among American Indian older adults: is Andersen’s behavioral model a good fit? J APPL GERONTOL. 2017;36(1):94–115.

    Article  PubMed  Google Scholar 

  26. Nazari S, Kamali K, Hajimiri K. Predictive factors of quality of life among the elderly in Iran: application of Andersen’s behavioral model. J EDUC HEALTH PROMOT. 2021;10(1):70.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Baernholdt M, Hinton I, Yan G, Rose K, Mattos M. Factors associated with quality of life in older adults in the United States. QUAL LIFE RES. 2012;21(3):527–34.

    Article  PubMed  Google Scholar 

  28. Andersen R, Rice TH, Kominski GF. Changing the U.S. health care system: key issues in health services policy and management. San Francisco: Jossey-Bass; 2007.

    Google Scholar 

  29. Wei Y, Zhang L. Analysis of the influencing factors on the preferences of the Elderly for the combination of Medical Care and Pension in Long-Term Care facilities based on the Andersen Model. Int J Environ Res Public Health 2020, 17(15).

  30. Garcia-Ramirez J, Nikoloski Z, Mossialos E. Inequality in healthcare use among older people in Colombia. INT J EQUITY HEALTH. 2020;19(1):168.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Zhou J, Walker A. The need for Community Care among older people in China. AGEING SOC. 2016;36(6):1312–32.

    Article  Google Scholar 

  32. Chang Y, Huang J. Impacts of intergenerational care for grandchildren and intergenerational support on the psychological well-being of the elderly in China. Revista Argentina De Clin Psicol. 2020;29(1):57.

    Google Scholar 

  33. Coulton C, Frost AK. Use of Social and Health Services by the Elderly. J HEALTH SOC BEHAV. 1982;23(4):330–9.

    Article  CAS  PubMed  Google Scholar 

  34. Baker SR. Applying Andersen’s behavioural model to oral health: what are the contextual factors shaping perceived oral health outcomes? COMMUNITY DENT ORAL. 2009;37(6):485–94.

    Article  CAS  Google Scholar 

  35. Yang G, Zhang R, Wei HY, Wan L, Dong H, Liang X, He Y. Studying on the willingness of Rural Elderly in Henan Province to choose their pension method and its influencing factors based on Andersen Model. Chin Health Service Manage. 2022;39(05):367–70. 375. (in Chinese).

    Google Scholar 

  36. Reeskens T, Vandecasteele L. Economic hardship and Well-Being: examining the relative role of Individual Resources and Welfare State Effort in Resilience Against Economic Hardship. J HAPPINESS STUD. 2017;18(1):41–62.

    Article  Google Scholar 

  37. Liu Y, Dijst M, Geertman S. The subjective well-being of older adults in Shanghai: the role of residential environment and individual resources. URBAN STUD. 2017;54(7):1692–714.

    Article  Google Scholar 

  38. Multigenerational social support in the face of the COVID-19 pandemic. J FAM THEOR REV 2020, 12(4):431–447.

  39. Chen X, Silverstein M. Intergenerational social support and the Psychological Well-Being of older parents in China. RES AGING. 2000;22(1):43–65.

    Article  CAS  Google Scholar 

  40. Bombak AE. Self-rated health and public health: a critical perspective. FRONT PUBLIC HEALTH. 2013;1:15.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Ocampo JM. Self-rated health: importance of use in elderly adults. Colombia médica (Cali Colombia) 2011, 41(3).

  42. Hayat SZ, Khan S, Sadia R. Resilience, Wisdom, and life satisfaction in Elderly living with families and in Old-Age homes. Pakistan J Psychol Res 2016, 31(2).

  43. Faronbi JO, Faronbi GO, Ayamolowo SJ, Olaogun AA, Institute ONAP, Sahlgrenska A, Göteborgs U, Gothenburg U, Sahlgrenska A, Institutionen FNOF. Caring for the seniors with chronic illness: the lived experience of caregivers of older adults. ARCH GERONTOL GERIAT. 2019;82:8–14.

    Article  Google Scholar 

  44. Bonsang E, Costa-Font J. Behavioral regularities in old age planning. J ECON BEHAV ORGAN. 2020;173:297–300.

    Article  Google Scholar 

  45. Joan C. Institutionalization aversion and the willingness to pay for home health care. J HOUS ECON. 2017;38:62–9.

    Article  Google Scholar 

  46. Wang Y, Zhang R, Peng S. Cognitive differences and Influencing Factors of Chinese People’s Old-Age Care responsibility against the Ageing background. HEALTHCARE-BASEL. 2021;9(1):72.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Fan Y, Fang S, Yang Z. Living arrangements of the elderly: a new perspective from choice constraints in China. CHINA ECON REV. 2018;50:101–16.

    Article  Google Scholar 

  48. Lea D, Torben S, Theodor SJ, Sveja E, Jan Z, Kathrin D. Willingness to provide informal care to older adults in Germany: a discrete choice experiment. Eur J Health Econ 2022.

  49. Tunnard I, Yi D, Ellis-Smith C, Dawkins M, Higginson IJ, Evans CJ. Preferences and priorities to manage clinical uncertainty for older people with frailty and multimorbidity: a discrete choice experiment and stakeholder consultations. BMC GERIATR. 2021;21(1):1–553.

    Article  Google Scholar 

  50. Sudha S. Intergenerational relations and Elder Care Preferences of Asian Indians in North Carolina. J CROSS-CULT GERONTO. 2014;29(1):87–107.

    Article  CAS  Google Scholar 

  51. Zhang Z, Feng L, Hu L, Cao Y. Older residents’ sense of home and homemaking in rural-urban resettlement: a case study of moving-merging community in Shanghai. HABITAT INT. 2022;126:102616.

    Article  Google Scholar 

  52. Usha V, Lalitha K. Quality of life of senior citizens: a rural-urban comparison. Indian J Social Psychiatry 2016, 32(2).

  53. Sanjay K, Anmol G, Salig RM, Deepak S, Ankit C, Shaina C. Assessment of facilities and reasons for settlement in old age homes of Himachal Pradesh, India. Int J Community Med Public Health 2020, 7(7).

  54. Douglas H, Georgiou A, Westbrook J. Social participation as an indicator of successful aging: an overview of concepts and their associations with health. AUST HEALTH REV. 2017;41(4):455.

    Article  PubMed  Google Scholar 

  55. Akinrolie O, Okoh AC, Kalu ME. Intergenerational support between older adults and adult children in Nigeria: the role of reciprocity. J GERONTOL SOC WORK. 2020;63(5):478–98.

    Article  PubMed  Google Scholar 

  56. Bengtson VL, Martin P. Families and intergenerational relationships in aging societies: comparing the United States with German-speaking countries. Zeitschrift für Gerontologie Und Geriatrie. 2001;34(3):207–17.

    Article  CAS  PubMed  Google Scholar 

  57. Tomassini C, Glaser K, Wolf DA, Van Broese MI, Grundy E. Living arrangements among older people: an overview of trends in Europe and the USA. Popul Trends 2004(115):24.

  58. Silverstein M, Cong Z, Li S. Intergenerational transfers and living arrangements of older people in rural China: consequences for psychological well-being. J GERONTOL B-PSYCHOL. 2006;61(5):S256–66.

    Article  Google Scholar 

  59. Choi NG, Wodarski JS. The relationship between social support and health status of elderly people: does social support slow down physical and functional deterioration? SOC WORK RES. 1996;20(1):52–63.

    CAS  PubMed  Google Scholar 

  60. Vaux A, Riedel S, Stewart D. Modes of social support: the social support behaviors (SS-B) scale. AM J COMMUN PSYCHOL. 1987;15(2):209–32.

    Article  Google Scholar 

  61. Coleman D, Iso-Ahola SE. Leisure and health: the role of social support and self-determination. J LEISURE RES. 1993;25(2):111.

    Article  Google Scholar 

  62. Abhishek G, Uday M, Shivendra KS, Manish KM, Sarvada CT, Vijay KS. Home away from home: quality of Life, Assessment of Facilities and reason for settlement in Old Age homes of Lucknow, India. INDAN J COMMUNITY HE 2014, 26(2).

  63. Qian Y, Yang M. Study on select of pension methods of the elderly in community in city and its influencing factors. Nurs Res. 2012;26(1):37–9. (in Chinese).

    Google Scholar 

  64. Gentili E, Masiero G, Mazzonna F. The role of culture in long-term care arrangement decisions. J ECON BEHAV ORGAN. 2017;143:186–200.

    Article  Google Scholar 

  65. Zhang L, Zeng Y, Wang L, Fang Y. Urban–rural differences in long-term Care Service Status and needs among home-based Elderly people in China. Int J Environ Res Public Health. 2020;17(5):1701.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Zhang L, Zeng Y, Fang Y. The effect of health status and living arrangements on long term care models among older Chinese: a cross-sectional study. PLoS ONE 2017, 12(9).

  67. Chen N, Li X, Yuan N, Zhou C, Wang C. Utilization willingness of institutional care between disabled and non-disabled seniors: evidence from Jiangsu, China. BMC HEALTH SERV RES. 2019;19(1):410.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Doherty C, Doherty W. Patients’ preferences for involvement in clinical decision-making within secondary care and the factors that influence their preferences. J NURS MANAGE. 2005;13(2):119–27.

    Article  Google Scholar 

  69. Park S, Han Y, Kim B, Dunkle RE. Aging in place of vulnerable older adults: person–environment fit perspective. J APPL GERONTOL. 2017;36(11):1327–50.

    Article  PubMed  Google Scholar 

  70. Walker N, Dissanayaka NN, Scott T, Manchha A, Pachana NA. Shaping attitudes: the association between prior contact with residential aged care and resistance to enter residential aged care. INT J OLDER PEOPLE N. 2019;14(4):e12268.

    Article  Google Scholar 

  71. Jia JS, Shiv B, Rao S. The product-agnosia effect: how more visual impressions affect product distinctiveness in comparative choice. J Consumer Res. 2014;41(2):342–60.

    Article  Google Scholar 

  72. Cutchin MP. The process of mediated aging-in-place: a theoretically and empirically based model. SOC SCI MED. 2003;57(6):1077–90.

    Article  PubMed  Google Scholar 

  73. Deng T, Fan Y, Wu M, Li M. Older people’ s Long-Term Care preferences in China: the impact of living with Grandchildren on older people’ s willingness and family decisions. Int J Environ Res Public Health. 2022;19(19):12455.

    Article  PubMed  PubMed Central  Google Scholar 

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We are particularly grateful to the support received from all participants in this study.


This work was supported by grants from Humanities and Social Science Foundation of the Ministry of Education in China (Number: 21YJA840018), National Social Science Foundation (Number: 23BSH151), and Funding of Nantong Science and Technology Program (MS2023084). The granting agencies did not have roles in the design, collection, analysis, and interpretation of data or in writing the manuscript.

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Yanan Wang and Yaning Wang carried out the study and holds the main responsibility for writing the manuscript, as well as Yanan Wang and Yaning Wang revised the manuscript. Yitong Liu and Wenkun Xu conducted the statistical analysis. Zhuoya Yang and Zhongying Xu drafted parts of the paper and revised the manuscript. Yanan Wang and Yaqin Zhong contributed equally to this work. All authors provided input during the preparation of the manuscript and approved the final version.

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Correspondence to Yaqin Zhong.

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Wang, Y., Wang, Y., Liu, Y. et al. Factors influencing senior care and living preferences among older adults in Jiangsu, China: a cross-sectional survey study. BMC Health Serv Res 24, 723 (2024).

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