Abstract
The growth of the aging population has been accompanied throughout a rapid increase in the number of disabled people and the demand for long-term care (LTC) services. Shandong Province has the largest number of older adults in China. It is necessary to explore their preferences in LTC models and the related factors. In a cross-sectional study conducted in August 2017, 6997 older adults aged 60 years and older were interviewed. Descriptive analysis, independent sample t tests, χ2 tests, and multinomial logistic regression were used to show preferences and the related factors in LTC models (family care, home- and community-based care (HCBS), and institutional care) based on the Andersen Behavior Model. Family care (89.1%) was the first preference for older adults and 8.2% chose institutional care, but only 2.7% chose HCBS. The logistic regression results indicated that older people aged 60–64 years and those with a higher education level tended to choose HCBS or institutional care (P < 0.05); in the eastern region of Shandong Province, they tended to choose HCBS and institutional care over family care (P < 0.05). Older people with self-care limitations were more likely to choose HCBS (P < 0.05). Older adults with a stronger sense of loneliness were more likely to choose HCBS and institutional care (P < 0.05). The results can enable us to make tentative recommendations for older people, relevant decision-makers, and administrative bodies. Additionally, a more rigorous longitudinal design is necessary to investigate causality in regard to related factors and preference in LTC models.
Keywords: Older adults, Long-term care models, Andersen behavior model, Influencing factors
Introduction
While the aging population poses serious challenges for health care and long-term care (LTC) systems in many countries around the world, the problem is especially acute in China. In 2018, the number and proportion of people aged 60 and above in China were 249 million and 17.9%, respectively (China 2019). It is estimated that by 2050, the Chinese population aged 60 and above will reach 440 million, accounting for 31% of the total population (Peng et al. 2010). This rapid growth and the increase in chronic degenerative diseases have increased the demand for LTC services, particularly for disabled older adults and those with dementia. To ease the caregiving and economic burden, many developed nations and almost all Organization for Economic Co-operation and Development (OECD) countries have established relatively advanced and comprehensive LTC systems and supported legislation to ensure the quality of its implementation over the past two or three decades, for example, social insurance programs in Germany (Colombo et al. 2011a, b) and Japan (Nanako Tamiya and Campbell 2011) as well as the private market for long-term care insurance (LTCI) in the United States (Brown and Finkelstein 2011).
However, China still lacks a comprehensive, systematic LTC system. Currently, there are three mainstream LTC models in China (Li et al. 2017), namely, family care, home- and community-based care (HCBS), and institutional care. Family care is a traditional, informal care model where family members (including spouses, children, friends, or neighbors) provide service for older adults. Currently, family care is the preferred model in China. HCBS is provided mostly by family members and other informal (i.e., unpaid) caregivers, supplemented by formal (i.e., paid) services and supports where they are available and affordable (Glinskaya and Feng 2018). Institutional care refers to nursing home, where older adults are serviced by formal caregivers (health and social care services) (Xiaoying et al. 2018). Additionally, the “13th Five-Year Plan” (Jing 2016) put forward improvements to the multi-socialized LTC service system, which is based on family care, supplemented by HCBS, and supported by institutional care for the aged by 2020. As a new type of LTC model, it is not well known to older adults in China. Therefore, it is important to investigate the preferences for HCBS and institutional care compared with traditional family care as well as the related factors for older adults in China.
Shandong Province has the second largest population in China (China 2019). However, the number and proportion of older adults are the largest. In 2018, the number of people aged 60 and above in Shandong Province was 22.39 million, accounting for 22.29% of the total population (100.448 million). Therefore, the responsibility to support older adults is higher than the national average. At present, most studies on the LTC model in Shandong Province are only based on cities, communities, or rural/urban areas, which can’t reflect the overall LTC model preference of older people. Moreover, although the potential related factors are analyzed based on people’s social characteristics, there is no systematic theoretical framework. Andersen Behavior model classifies factors associated with people’s health into predisposing factors (i.e., demographic characteristics such as age and sex; social factors such as education, occupation, ethnicity; social relationships; and mental factors such as health beliefs), enabling factors (i.e., finance factors and organizational factors), and need factors (perceived need for health services) (Babitsch et al. 2012), and is widely used in the field of social medicine and public health services, for example, health care costs (Heider et al. 2014), drug use (Andersen et al. 2000; Spark et al. 2013), and nursing care (Stone 2014; Tiwari et al. 2010).
Consequently, the aim of this study was to describe LTC model preferences and examine factors related to those preferences among older adults in Shandong Province based on the Andersen Behavior model. Understanding older adults’ preferences and providing flexible options for services and supports are critical for person-centered care, which is essential to effectively deliver high-quality LTC.
Participants and methods
Participants
The present study utilized data taken from the Shandong Elderly Family Health Service Survey conducted in August 2017. The detailed sampling and quality assurance measures have been described in a previously published paper (Yu et al. 2019) In brief, a three-stage, stratified, random sampling scheme was used to ensure that samples are representative of the whole population of Shandong Province. In the first stage, Shandong Province was divided into three strata based on geographic regions: east, central, and west. Within each stratum, one urban district and one rural county were randomly selected to serve as the primary sampling units (PSUs). In the second stage, 18 villages in rural counties and 18 communities in rural districts were randomly selected from each PSU to serve as the secondary sampling units (SSUs). In the third stage, three towns and three sub-districts were selected randomly from each county and district separately. Then, from each town and sub-district, six villages and six committees were selected separately. Lastly, an average of 50 households were randomly selected and making up the total sample. Eligible participants were those aged 60 years or older with local household registrations. Finally, a total of 5643 households consisting of 7088 were selected and interviewed. Of these, 91 were excluded due to incomplete data or incorrect response on the questionnaires. Finally, data from 6997 older adults were used for analysis. For functionally disabled older people with language dysfunction, we adopt the method of face-to-face interview in the house and family members involve in answering the questions. All data collection was performed by trained master students in the participant’s home using a study questionnaire by face-to-face interviews.
Measures
Dependent variables
In this study, the dependent variables were LTC model preferences, which were measured by a single question: “If you are unable to care for yourself in the future, which type of long-term care would you choose?” (possible responses: code 1 = family care, code 2 = home- and community-based care [HCBS], code 3 = institutional care).
Independent variables
Predisposing factors included: gender (male, female), age (60–64, 65–69, 70–74, 75 or above), education (primary or below, junior, senior or above), occupational status (employed, retired, unemployed), marital status (married, others), and living arrangement (empty nest, living alone, empty nest and living alone, others).
Enabling factors included: personal income (≤ 3000 RMB, 3001–6000 RMB, 6001–18,000 RMB, 5700–16,800 RMB, > 16,800 RMB), health insurance (urban employee basic medical insurance [UEBMI]), urban and rural residents’ basic medical insurance [URRBMI], others or no insurance), type of residential registration (rural, urban), and regions of Shandong Province (East, Central, West). All variables are categorical variables.
Need factors were classified as psychological or physiological need factors.
Psychological needs included: (1) Self-rated health (good, fair, bad). Self-rated health can reflect the residents’ general health status. (2) Loneliness was measured using the University of California Los Angeles Loneliness Scale, ULS-6. The Chinese version of the ULS-6 has achieved satisfactory validity and reliability in Chinese rural community-dwelling older adults (Liang et al. 2012). The scale contains six items. Sample items include: “I lack companionship,” “There is no one I can turn to,” “I feel left out” and so on. Each item is rated on a 4-point Likert scale, ranging from 1 (“never”) to 4 (“always”). Higher scores indicate a greater sense of loneliness. Cronbach’s α of the questionnaire was 0.905 in this study.
Physiological needs included: (1) Physical function. This was measured using Activities of Daily Living (ADL), including the Physical Self-maintenance Scale (PSMS) (Katz 1963) and the Instrumental Activities of Daily Living Scale (IADL) (Lawton and Brody 1969). The PSMS assesses six functions: feeding, dressing, bathing, toileting, grooming, and ambulation. The IADL subscale evaluates the ability to perform eight more complex activities such as using a telephone, using transportation, and shopping. Each function was evaluated from 1 (“can do completely”) to 4 (“can’t do at all”). A higher total ADL score indicates poorer physical function. The ADL score can be divided into three levels: independent (≤ 14), functional decline (15–21), and obvious dysfunction (≥ 22). The reliability and validity of the ADL were good (Lawton and Brody 1969). The Cronbach’α value was 0.931 in this study. (2) Number of chronic diseases (0,1, and ≥ 2).
Data analysis
The Statistical Package for Social Sciences (SPSS) version 21.0 (Chicago, IL, USA) was used for data analysis; P < 0.05 was considered statistically significant. Descriptive analysis was used to describe the LTC preferences and participates’ characteristics using frequency and percentage for categorical variables and means and standard deviations for continuous variables. Chi square tests and ANOVA were conducted to explore factors related to the older adults’ LTC models. Finally, multinomial logistic regression was used to identify factors related to the LTC model preferences, taking family care as reference. Results were indicated by odds ratio (OR) and a 95% confidence interval (CI).
Results
Descriptive analyses
Among the 6997 participants, 89.1% (n = 6237) chose family care, 8.2% (n = 573) chose institutional care, and 2.7% (n = 187) chose HCBS. Most participants were female, aged from 65 to 69, junior high school level of education, unemployed, married, had a rural residential registration, from east region, having URRBMI, with one type of chronic disease, living independently, and good self-rated health status. The average loneliness score was 8.05 ± 3.65. Details of the sample characteristics are described in Table 1.
Table 1.
Differences in characteristics among participants choosing family care, HCBS and institutional care (n = 6997)
| Factors | Total (n = 6997) | Family care n = 6237 | HCBS n = 187 | Institution care n = 573 | χ2 | P value | P | P | P |
|---|---|---|---|---|---|---|---|---|---|
| Family care versus HCBS | Family care versus Institution care | HCBS versus Institution care | |||||||
| Predisposing factors | |||||||||
| Gender | |||||||||
| Male | 2824 (40.4%) | 2548 (40.9%) | 59 (31.6%) | 217 (37.9%) | 8.133 | 0.017 | 0.011 | 0.164 | 0.119 |
| Female | 4173 (59.6%) | 3689 (59.1%) | 128 (68.4%) | 356 (62.1%) | |||||
| Age (years) | |||||||||
| 60–64 | 1556 (22.2%) | 1344 (21.5%) | 52 (27.8%) | 160 (27.9%) | 42.362 | < 0.001 | 0.016 | < 0.001 | 0.950 |
| 65–69 | 2101 (30.0%) | 1843 (29.5%) | 61 (32.6%) | 197 (43.4%) | |||||
| 70–74 | 1763 (25.2%) | 1583 (25.4%) | 47 (25.1%) | 133 (23.2%) | |||||
| 75 or above | 1577 (22.5%) | 1467 (23.5%) | 27 (14.4%) | 83 (14.5%) | |||||
| Education | |||||||||
| Primary or below | 2255 (32.2%) | 2112 (33.9%) | 30 (16.0%) | 113 (19.7%) | 154.268 | < 0.001 | < 0.001 | < 0.001 | 0.128 |
| Junior | 2889 (41.3%) | 2606 (41.8%) | 63 (33.7%) | 220 (38.4%) | |||||
| Senior or above | 1853 (26.5%) | 1519 (24.8%) | 94 (50.3%) | 240 (41.9%) | |||||
| Occupational situation | |||||||||
| Employed | 2158 (30.8%) | 1968 (31.6%) | 29 (15.5%) | 161 (28.1%) | 399.296 | < 0.001 | < 0.001 | < 0.001 | 0.002 |
| Retirement | 1437 (20.5%) | 1077 (17.3%) | 102 (54.5%) | 258 (45.0%) | |||||
| Unemployed | 3402 (48.6%) | 3192 (51.2%) | 56 (29.9%) | 154 (26.9%) | |||||
| Marital status | |||||||||
| Married | 5674 (81.1%) | 5042 (80.8%) | 163 (87.2%) | 469 (81.8%) | 4.972 | 0.083 | |||
| Others | 1323 (18.9%) | 1195 (19.2%) | 24 (12.8%) | 104 (18.2%) | |||||
| Living arrangement | |||||||||
| Empty nest | 1627 (23.3%) | 1454 (23.3%) | 48 (25.7%) | 125 (21.8%) | 5.972 | 0.426 | |||
| Live alone | 737 (10.5%) | 652 (10.5%) | 13 (7.0%) | 72 (12.6%) | |||||
| Empty nest and living alone | 278 (4.0%) | 250 (4.0%) | 8 (4.3%) | 20 (3.5%) | |||||
| Others | 4355 (62.2%) | 3881 (62.2%) | 118 (63.0%) | 356 (62.1%) | |||||
| Enabling factors | |||||||||
| Personal income | |||||||||
| ≤3000 | 1932 (27.6%) | 1809 (29.0%) | 24 (12.8%) | 99 (17.3%) | 308.287 | < 0.001 | < 0.001 | < 0.001 | 0.122 |
| 3001–6000 | 1669 (23.9%) | 1571 (25.2%) | 22 (11.8%) | 76 (13.3%) | |||||
| 6001–18,000 | 1739 (24.9%) | 1566 (25.1%) | 37 (19.8%) | 136 (23.7%) | |||||
| >18,000 | 1657 (23.7%) | 1291 (20.7%) | 104 (55.6%) | 262 (45.7%) | |||||
| Health insurance | |||||||||
| UEBMIa | 1248 (17.8%) | 931 (14.9%) | 96 (51.3%) | 221 (38.6%) | 350.386 | < 0.001 | < 0.001 | < 0.001 | 0.002 |
| URRBMIb | 5553 (79.4%) | 5129 (82.2%) | 84 (44.9%) | 340 (59.3%) | |||||
| Others/No | 196 (2.8%) | 177 (2.8%) | 7 (3.7%) | 12 (2.1%) | |||||
| Residence | |||||||||
| Rural | 4959 (70.9%) | 4594 (73.7%) | 71 (38.0%) | 294 (51.3%) | 227.747 | < 0.001 | < 0.001 | < 0.001 | 0.002 |
| Urban | 2038 (29.1%) | 1643 (26.3%) | 116 (62.0%) | 279 (48.7%) | |||||
| Region | |||||||||
| Eastern | 2374 (33.9%) | 1932 (31.0%) | 125 (66.8%) | 317 (55.3%) | 235.690 | < 0.001 | < 0.001 | < 0.001 | 0.002 |
| Central | 2321 (33.2%) | 2148 (34.4%) | 42 (22.5%) | 131 (22.9%) | |||||
| Western | 2302 (32.9%) | 2157 (34.6%) | 20 (10.7%) | 125 (21.8%) | |||||
| Need factors | |||||||||
| Chronic diseases | |||||||||
| 0 | 2497 (35.7%) | 2229 (35.7%) | 73 (39.0%) | 195 (34.0%) | 2.274 | 0.685 | |||
| 1 | 2859 (40.9%) | 2554 (40.9%) | 72 (38.5%) | 233 (40.7%) | |||||
| ≥2 | 1641 (23.5%) | 1454 (23.3%) | 42 (22.5%) | 145 (25.3%) | |||||
| ADL | |||||||||
| Independently | 5405 (77.2%) | 4793 (76.8%) | 157 (84.0%) | 455 (79.4%) | 9.603 | 0.048 | 0.022 | 0.318 | 0.191 |
| Functional decline | 1272 (18.2%) | 1160 (18.6%) | 20 (10.7%) | 92 (16.1%) | |||||
| Dysfunction | 320 (4.6%) | 284 (4.6%) | 10 (5.3%) | 26 (4.5%) | |||||
| Self-rated health | |||||||||
| Good | 3736 (53.4%) | 3312 (53.1%) | 111 (59.4%) | 313 (54.6%) | 3.800 | 0.434 | |||
| Fair | 1969 (28.1%) | 1761 (28.2%) | 49 (26.2%) | 159 (27.7%) | |||||
| Bad | 1292 (18.5%) | 1164 (18.7%) | 27 (14.4%) | 101 (17.6%) | |||||
| Loneliness | 8.05 ± 3.65 | 7.96 ± 3.53 | 8.50 ± 4.31 | 8.94 ± 4.45 | 23.360 | < 0.001 | 0.519 | < 0.001 | 0.054 |
aUEBMI: Urban Employee Basic Medical Insurance
bURRBMI: Urban and Rural Residents Basic Medical Insurance
Factors related to LTC model preferences
Chi square tests showed that LTC preferences differed by participant gender (P = 0.017), age (P < 0.001), education (P < 0.001), employment situation (P < 0.001), personal income (P < 0.001), health insurance (P < 0.001), residence (P < 0.001), regional distribution (P < 0.001), and physical function (P = 0.048). Participants who preferred institutional care reported a greater sense of loneliness (P < 0.001) by ANOVA. Living arrangement, marital status, self-rated health, and chronic diseases did not show a statistically significant relationship with LTC model preferences (Table 1).
Multinomial logistic regression analyses
Table 2 shows the ORs (95% CIs) and P-values from the multinomial logistic regression of the three LTC models. Taking family care as reference, female older adults were more likely to choose HCBS (OR = 0.686, P = 0.032). Lower age groups were more likely to choose HCBS (60 ~ 64: OR = 2.029, P = 0.007; 65 ~ 69: OR = 1.882, P = 0.010) or institutional care (60 ~ 64: OR = 1.885, P < 0.001; 65 ~ 69: OR = 1.807, P < 0.001; 70 ~ 74: OR = 1.395, P = 0.028). Compared with older adults whose education level was junior, those with senior or above or primary or below tended to choose HCBS (OR = 0.670, P = 0.029) or institutional care (OR = 0.718, P = 0.033). Those who were unemployed were more likely to choose family care over institutional care (employed: OR = 1.633, P < 0.001; retired: OR = 2.443, P < 0.001). The respondents with high personal income (> 18,000) were more likely to choose institutional care (≤ 3000: OR = 0.698, P = 0.042; 3001–6000: OR = 0.598, P = 0.006). Urban older adults were more likely to choose institutional care (OR = 0.695, P = 0.010). Compared with those in western region, participants from the eastern region were more likely to choose HCBS (OR = 2.791, P = 0.001) or institutional care (OR = 1.355, P = 0.037). Those who had stronger feelings of loneliness were more likely to select HCBS (OR = 1.049, P = 0.004) or institutional care (OR = 1.075, P < 0.001). Older adults who were dysfunctional were more likely to choose HCBS (independent: OR = 0.467, P = 0.036; functional decline: OR = 0.378, P = 0.017). In general, gender, age, education, employment situation, residence, regional distribution, ADLs, and loneliness showed significant differences.
Table 2.
Multinomial logistic regression of older people’s LTC preference (n = 6997)
| Factors | HCBSa | Institution carea | |||
|---|---|---|---|---|---|
| OR (95% CI) | P | OR (95% CI) | P | ||
| Predisposing factors | Gender (female) | ||||
| Male | 0.686 (0.486, 0.969) | 0.032 | 0.821 (0.671, 1.003) | 0.054 | |
| Age (75 or above) | |||||
| 60–64 | 2.029 (1.218, 3.390) | 0.007 | 1.885 (1.390, 2.556) | < 0.001 | |
| 65–69 | 1.882 (1.162, 3.049) | 0.010 | 1.807 (1.359, 2.401) | < 0.001 | |
| 70–74 | 1.608 (0.979, 2.641) | 0.061 | 1.395 (1.037, 1.878) | 0.028 | |
| Education (Senior or above) | |||||
| Primary or below | 0.771 (0.451, 1.317) | 0.341 | 0.718 (0.529, 0.974) | 0.033 | |
| Junior | 0.670 (0.468, 0.959) | 0.029 | 0.836 (0.673, 1.038) | 0.098 | |
| Employment situation (Unemployed) | |||||
| Employed | 0.958 (0.582, 1.576) | 0.866 | 1.633 (1.264, 2.109) | < 0.001 | |
| Retired | 1.482 (0.862, 2.551) | 0.155 | 2.443 (1.748, 3.413) | < 0.001 | |
| Enabling factors | Personal income (> 18,000) | ||||
| ≤ 3000 | 0.682 (0.366, 1.273) | 0.230 | 0.698 (0.493, 0.987) | 0.042 | |
| 3001–6000 | 0.777 (0.412, 1.465) | 0.436 | 0.598 (0.416, 0.860) | 0.006 | |
| 6001–18,000 | 0.933 (0.563, 1.548) | 0.789 | 0.899 (0.667, 1.213) | 0.448 | |
| Medical insurance (Other) | |||||
| UEBMIb | 1.484 (0.645, 3.413) | 0.353 | 1.726 (0.918, 3.245) | 0.090 | |
| URRBMIc | 0.735 (0.323, 1.673) | 0.463 | 1.464 (0.786, 2.728) | 0.230 | |
| Residence (Urban) | |||||
| Rural | 0.668 (0.420, 1.063) | 0.088 | 0.695 (0.526, 0.917) | 0.010 | |
| Region (Western) | |||||
| Eastern | 2.791 (1.547, 5.033) | 0.001 | 1.355 (1.018, 1.804) | 0.037 | |
| Central | 1.323 (0.723, 2.421) | 0.364 | 0.799 (0.594, 1.074) | 0.138 | |
| Need factors | ADL (Dysfunction) | ||||
| Independently | 0.467 (0.229, 0.950) | 0.036 | 0.639 (0.408, 1.001) | 0.051 | |
| Functional decline | 0.378 (0.171, 0.838) | 0.017 | 0.722 (0.449, 1.161) | 0.178 | |
| Loneliness | 1.049 (1.015, 1.085) | 0.004 | 1.075 (1.056, 1.095) | < 0.001 | |
aTaking family care as reference
bUEBMI: Urban Employee Basic Medical Insurance
cURRBMI: Urban and Rural Residents Basic Medical Insurance
Discussion
In terms of LTC model preferences, 89.1% were willing to live at home and 8.2% chose institutional care, while only 2.7% chose HCBS services. This finding is consistent with previous reports. For example, Zhang and colleagues (2017) found that 86.37% of the older adults in Xiamen selected family care, 10.77% selected HCBS, and only 2.86% chose to live in institutions. In a study using older adults from four cities (Fu et al. 2017), 75.3% of the older people chose family care, 16.7% chose HCBS, and 8.0% chose institutional care. Taken together, it can be seen that family care is preferred by Chinese older adults. However, the percentage of family care is higher than in other studies for the aged in China. Shandong Province is the birthplace of the Confucian norm of filial piety (Zhang et al. 2012). Under this cultural mandate, which is also codified in current Chinese law, adult children are required to care for older parents physically, financially, and emotionally. Currently, healthcare policies need to emphasize improvements in the quality of family care.
Moreover, in contrast to the mix of aged service targets in the “9073” plan of the official policy and other studies, the present study showed that older people were less accepting of HCBS. One possible reason is that HCBS has generally been a more recent development. When we conducted this study, most of the participants knew nothing about HCBS. The study did not cover the regions where long-term care insurance (LTCI) system was piloted. Before it was explained, participants were skeptical about the unimplemented HCBS and had little awareness of it. Therefore, policymakers should strengthen promotion and establish health reforms to gradually increase older adults’ awareness of HCBS. Future studies can focus on older adults in the pilot cities of Shandong Province and summarize experiences to expand the scope for implementing the LTCI system. Meanwhile, we can learn from similar policies that have been adopted in OECD countries, Japan, and the US to support care provision in home or community settings. (Colombo et al. 2011; Feng et al. 2011; Ikegami et al. 2003) However, the policies must be based on the socioeconomic, cultural, and political contexts as well as the market environment in China.
In terms of predisposing characteristics, the findings that age and education have a significant effect are supported by many studies (Wu et al. 2014a; Xiaolong and Yan 2013). Older adults of lower age and senior or above education tended to choose HCBS or institutional care. Due to intergenerational differences, those born in the 1950s (60-70 years old), unlike their predecessors, experienced the Cultural Revolution, the restoration of the College Entrance Examination, and the Reforming and Opening Up. As a result, this generation showed new features in cultural education, awareness of rights and interests, and subjective initiative. Meanwhile, older adults with lower age and senior or above higher education have high ideologies and acceptance of new things with the rise of new concepts and ways of providing for the aged, and are more likely to accept HCBS or institutions. With the shift of generation and the improvement of the education level, older adults’ pension concept may have high recognition and acceptance of HCBS or institution, whose demand will also be increased, accordingly. In general, as in many other countries around the world, population aging and the weakening of traditional family care for older people are increasing the need for formal LTC services.
With respect to enabling factors, economic factors show obvious differences in the choice of the “family vs. Institutional” LTC model. Older people with lower incomes and those who were unemployed tended to choose family care, which is consistent with Zhang Qilin’s study (2018). This result reflects that the affordability and financing limit the choice of formal LTC, and partly explains the high vacancy rates in many private sector senior care facilities. China should consider developing a universal public long-term care financing system similar to the universal social insurance models adopted in Japan (Campbell et al. 2010), and in Korea (Mor et al. 2014). However, there was no difference in the choice of the “family vs. HCBS” LTC model. The probable reason is that there is no pilot project in this survey area, and older adults have no accurate concept of the payment standard. Rural older adults were more likely to choose family care compared with institutional care, but there was no difference in the choice of the “family vs. HCBS” LTC model. The result indicated that the needs unmet by informal care are more acute in rural areas, pointing to the need to develop formal and informal care delivery for rural elderly (the day care arrangements and support for family care). The results of this study also showed that older adults in the eastern region tend to choose HCBS or institutional care compared to those in the central and western regions, which is in line with other studies (Fu et al. 2017; Lou et al. 2011; Zhan et al. 2006). The reasons for this regional disparity may be due to differences in geographical location, city size, and level of economic development among the three regions. More specifically, the eastern region is coastal with flat terrain, convenient for external communication, and has a higher level of economic development than the central and western regions do. This difference reminds us that each area should adopt its own specific means and methods for pension planning.
In regard to need factors, the subjective and objective needs of older adults were included in the regression analysis simultaneously. ADLs were significant in the choice of the “family care vs. HCBS” LTC model, which is consistent with previous studies (Zhang et al. 2017; Fu et al. 2017; Wu et al. 2014b). Older people with more physical impairments are more likely to choose HCBS to obtain formal and informal care from family members and community service personnel. As a consequence of increased longevity, a higher share of the elderly may suffer from noncommunicable diseases (NCDs) toward the end of their lives. The population cohorts entering their 70 s and 80 s in the next two decades may have been more exposed to NCD-related risks in middle age than previous cohorts, making them more vulnerable to disabilities in old age (Giles et al. 2018). A higher incidence of diabetes and high blood pressure, in particular, may increase long-term care (LTC) needs. However, self-rated health had no significance, which is contrary to many other conclusions (Zhang et al. 2017; Xizhe et al. 2017). This shows that older adults in this study pay more attention to their physical health when choosing an LTC models. The absence of an association between chronic disease and LTC models in the present study was contrary to the results of other studies (Wenjuan and Meng 2014; Li et al. 2017; Liu et al. 2013; Slobbe et al. 2017). The differing results might be that the surveyed chronic diseases, such as hypertension, diabetes, coronary heart disease, have little effect on their daily activities and self-care ability. Further research is needed to examine the relationship between the different types and severities of chronic diseases and LTC model preference in cross-cultural contexts, which will help the formulation of relevant policies to be more targeted.
This study found that loneliness had a strong influence on older adults’ LTC model preference. Similar to previous studies (Liangwen et al. 2017; Du Peng et al. 2016), older adults with a stronger sense of loneliness were more inclined to choose HCBS or institutional care. A recent study in China indicated that about 28% of older Chinese adults reported feeling lonely (Luo and Waite 2014), which was a public health problem in need of attention. Empty nest, living alone and retirement among older adults lead to a less stimulating daily environment, and weaken social networks. Hence, older people who felt lonely may be more willing to engage in society or the collective activities and to have more preference to enhance social communication and participation Therefore, in addition to attaching importance to physical health, healthcare policies should pay more attention to enabling lonely older people to get more social support.
In summary, although family care is still the preferred LTC model for older adults in Shandong Province, the change from family care to HCBS or institutional has become the consensus of most relevant scholars. In this study, we found that age, education level, economic status, regional distribution, ability of daily life, and loneliness were the main factors affecting older adults’ preferences when choosing an LTC models in Shandong Province. We propose different strategies to alleviate the burden of pension in Shandong Province from different angles.
This study has several limitations. First, the study was cross-sectional, and it was impossible to draw any causal conclusions. Second, the participants were older adults living at home in different areas of Shandong Province. Although the sample size was large, it was not necessarily a representative sample of the Chinese aged population. Similar studies in communities or institutions have been suggested. Third, the survey data were self-reported; therefore, they were subject to report bias. Preferences for LTC options include both settings (where care is rendered) and care providers (individuals or organizations that provide care). It is necessary to comprehensively evaluate the health status of older adults combined with subjective and objective indicators.
Conclusions
Our findings revealed that family care is still the predominant choice of older adults in Shandong Province. Age, education level, economic status, regional distribution, ADLs, and loneliness were found to have a significant association with older adults’ preferences when choosing an LTC models in Shandong Province. The results of this study suggested that we should consider developing a universal public long-term care financing system similar to the universal social insurance models adopted in the Netherlands, Germany, Japan, and more recently in Korea, and pilot cities in China. We also can improve the quality of HCBS or institutions and raising older adults’ awareness. As for regional distribution, regional planning for the aged in construction of socialized LTC services can be carried out. Finally, policymakers should also pay attention to the older adults’ physical and psychological needs.
Acknowledgements
We would like to thank the center for health economics experiment and public policy, School of Public Health, Shandong University. This work was supported by two grants of National Natural Science Foundation of China (Grant Numbers: 71673169 and 71673170). The author is also grateful for the assistance in data collection processes of the master students from School of Public Health, Shandong University.
Author Contributions
LX conceived the idea. HY participated in the interpretation of the results and also polished it. YZ provided suggestions for the statistical analysis of the manuscript; XL gave many valuable comments on the draft and also polished it. HL drafted the manuscript and statistical analysis. All authors read and approved the final manuscript.
Compliance with ethical standards
Conflict of interest
The authors declare no conflict of interest.
Footnotes
Responsible Editor: Susanne Iwarsson.
Publisher's Note
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