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Article

Changes of Health Status and Institutionalization Among Older Adults in China

Rong Peng, PhD1 and Bei Wu, PhD2

AbstractObjective: To examine rates of institutionalization of Chinese older adults aged 65+ and the impact of changes in health status on the likelihood of institutionalization. Method: Using data from the 2002, 2005, 2008, and 2011 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), admission rates for each 3-year interval between waves were calculated. Logistic regression models were used to assess the changes of five health status variables as risk factors. Results: Between the first (2002-2005) and third (2008-2011) intervals, the institutionalization rate increased from 0.5% to 0.8%. Risk of institutionalization increased 70% for respondents with declining ability to perform activities of daily living, 53% for those with declining cognitive function, and 44% for those with increasing number of chronic diseases. Discussion: Development of policies and programs to improve older adults’ health status is essential to delay institutionalization. Quality of workforce is also critical in meeting the care needs.

Keywordsactivities of daily living, cognitive function, health status changes, institutionalization, long-term care

1National Economics Research Center and School of Economics, Guangdong University of Finance and Economics, Guangzhou, China2Duke University, Durham, NC, USA

Corresponding Author:Bei Wu, Professor, School of Nursing, Global Health Institute, and Center for the Study of Aging and Human Development, Duke University, 307 Trent Drive, DUMC 3322, Durham, NC 27701, USA. Email: [email protected]

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Introduction

The rate of institutionalization of Chinese older adults in long-term care (LTC) facilities is increasing rapidly. The number of Chinese adults aged ≥65 years living in such facilities increased from 0.86% to 1.51% between 2005 and 2012, and the number of LTC residents in this age group (1.25 million in 2005, 2.93 million in 2012) more than doubled (Ministry of Civil Affairs of the People’s Republic of China, 2013). Frail elders have traditionally been cared for at home by family members as an expression of the traditional Chinese cultural value of “filial piety” (Chou, 2010; Chu & Chi, 2008; Zhan, Feng, Chen, & Feng, 2011). However, this system of family care is being eroded by rapid demographic and socioeconomic change (Cheung & Kwan, 2009; Z. Feng et al., 2011; H. Zhang, 2007).

The Chinese population is aging rapidly; three decades of the one-child family policy have drastically reduced fertility and family size, whereas lon-gevity has increased (Flaherty et al., 2007; C. Liu, Feng, & Mor, 2014; Zhan et al., 2011). Adults aged 65 and above comprised 5.5% of the population in 1990, 6.8% in 2000, 8.6% in 2010, and 9.1% in 2012, and this percentage is projected to increase to 12.4% in 2020, 17.2% in 2030, and 24.1% in 2040 (U.S. Census Bureau, 2014). As this population of older adults continues to expand, the number of children and grandchildren available to provide support is diminishing. Particularly in urban areas, large multigenerational households are giving way to family structures with less potential for providing care to dependent elders, such as the four-two-one family (four grandparents; two parents, each without a sibling; and one grandchild), the small nuclear family, and the “empty nest.” In addition, older adults are living alone in increasing numbers (Z. Feng et al., 2011; Korinek, Zimmer, & Gu, 2011; C. Liu et al., 2014; Y. Zhang & Goza, 2006). Availability of family support is also contract-ing for rural older adults as increasing numbers of adult children seeking employment migrate to cities, leaving their parents behind (Wu, Mao, & Zhong, 2009). Despite these changes in family structure and living arrange-ments, most Chinese older adults still rely primarily on family support, par-ticularly after they become functionally dependent (Wang, Zheng, Kurosawa, Inaba, & Kato, 2009). The majority of adult children continue to adhere to the traditional values of filial piety, acknowledge their responsibility to care for elderly parents who can no longer care for themselves, and wish to fulfill that responsibility by personal providing care (Zhan et al., 2011). However, many of those who are employed cannot afford to give up their jobs to serve as full-time caregivers for disabled parents (Zhan, Liu, & Guan, 2006).

In response to the increasing demand for LTC facilities driven by these factors, the elder care industry is emerging in China, especially in urban areas



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(Chu & Chi, 2008; Z. Feng et al., 2011; Zhan, Liu, Guan, & Bai, 2006). The number of beds in LTC facilities almost quintupled (from 735,000 to 4.2 mil-lion) between 1990 and 2012 (Ministry of Civil Affairs of the People’s Republic of China, 2013). With increased availability of LTC facilities and continuing erosion of traditional family care systems, institutional care has become a more common option for Chinese older adults and their families in recent years (Z. Feng et al., 2011; Zhan, Feng, & Luo, 2008). However, China’s LTC system is still in a preliminary stage of development (Wu et al., 2009), largely due to the lack of standardized health assessments for admis-sion, limited government funding, and workforce quality issues (Wu & Caro, 2009; Wu, Carter, Goins, & Cheng, 2005). Frontline staff in LTC institutions are typically migrants from rural villages or laid-off industrial workers with little or no previous training in geriatric care; the quality of care is generally low, and staff turnover is high (Chu & Chi, 2008).

Risk Factors for Institutionalization

In developed countries, many researchers have investigated risk factors for institutionalization (Gaugler, Duval, Anderson, & Kane, 2007; Luppa, Luck, Brahler, König, & Riedel-Heller, 2008; Luppa, Luck, Weyerer, et al., 2010). Factors that consistently predict nursing home admission include advanced age, disability in activities of daily living (ADLs), disability in instrumental activities of daily living (IADLs), lower self-rated health, and cognitive impairment (Gaugler, Kane, Kane, Clay, & Newcomer, 2003; Gnijdic et al., 2012; Luppa, Luck, Weyerer, et al., 2010; von Bonsdorff, Rantanen, Laukkanen, Suutama, & Heikkinen, 2006). Additional predictors of institu-tionalization that have been reported include gender, unmarried status (E. Nihtila & Martikainen, 2008), living alone (Greene & Ondrich, 1990), use of community-based services (Y.-M. Chen & Berkowitz, 2014) or a domestic/family helper (Freedman, 1996; Gaugler et al., 2000), chronic medical condi-tions (Koller et al., 2014; E. K. Nihtila et al., 2008), depression (Luppa, Luck, Matschinger, König, & Riedel-Heller, 2010), as well as caregiver character-istics such as poor health and perceived caregiver burden (Buhr, Kuchibhatla, & Clipp, 2006; Gaugler et al., 2003).

Limited evidence from longitudinal studies in developed countries sug-gest that changes in health status are important factors for institutionalization. Gaugler et al. (2003); Wattmo, Wallin, Londos, and Minthon (2011); and Wolinsky, Callahan, Fitzgerald, and Johnson (1993) identified declines in ability to perform ADLs and/or IADLs as predictors of institutionalization. Wattmo et al. also investigated the effect of declining cognitive function on institutionalization of older adults with Alzheimer’s disease but found no




significant association. However, Wilson et al. (2007) reported that declining cognitive function in Alzheimer’s patients was associated with nursing home placement. Cognitive function and physical function are strongly correlated, but they have their unique domains. To examine predictors of decline of health status on institutionalization among older adults, it is critical to exam-ine the impact of changes of health status in multiple domains older adults over a period of time.

Relatively few studies have examined risk factors related to institutionaliza-tion of older adults in China, a country with a very different cultural background, health care system, and level of economic development than most developed countries. In a study based on national survey data, Gu, Dupre, and Liu (2007) identified poor health status at baseline (ADL disability, cognitive impairment, and having one or more chronic diseases), as risk factors for institutionalization. Further research using longitudinal data is needed to evaluate changes of health status as predictors of institutionalization (Gaugler et al., 2003).

The objective of this study was to examine rates of institutionalization and to explore changes in health status (i.e., ability to perform ADLs and IADLs, cognitive function, self-rated health, and number of chronic diseases) as potential risk factors for institutionalization of Chinese community-dwelling older adults. In view of evidence linking changes in the ability to perform ADLs and IADLs in developed countries (Gaugler et al., 2003; Wattmo et al., 2011; Wolinsky et al., 1993), we hypothesized that declining ability to per-form ADLs and/or IADLs would also be significant predictors of institution-alization in Chinese older adults.

Cognitive impairment and functional disability have similar age-related trajectories and are strongly interrelated (Barberger-Gateau & Fabrigoule, 1997), and older adults with lower levels of cognitive function are more likely to become physically disabled than those with higher levels of cognitive func-tion (Comijs, Dik, Aartsen, Deeg, & Jonker, 2005). In Western samples, decline of cognitive function is also predictive of declining ability to perform IADL tasks such as preparing meals, shopping for groceries, managing money, light housework, and medication management (McGuire, Ford, & Ajani, 2006). In addition, many behavior symptoms related to cognitive impairment, such as memory loss, agitation, aggression, and wandering, significantly increase caregiving burden for family members (Comas-Herrera, Wittenberg, Pickard, & Knapp, 2007; Comijs et al., 2005; Jönsson, Lindgren, Wimo, Jönsson, & Winblad, 1999; Luppa, Heinrich, et al., 2008; Luppa, Luck, et al., 2008; Rice et al., 2001), which can increase the risk of institutionalization.

The relationship between declining cognitive function and entry into LTC facilities has not previously been explored for Chinese older adults, although Gu et al. (2007) reported a significant association between baseline cognitive



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impairment and institutionalization in this population. It should be noted, however, that exclusion of individuals with cognitive impairment (dementia in particular) occurs in most Chinese LTC facilities (Dong & Wu, 2010; Wu et al., 2009). Thus, although Wilson et al. (2007) identified deteriorating cog-nitive function as a risk factor for institutionalization of older adults in the United States, we hypothesized that cognitive decline would affect the risk of institutionalization among Chinese older adults, but we did not specify the direction of the association.

Chronic medical conditions have been identified by E. K. Nihtila et al. (2008) as risk factors for institutionalization of Finnish older adults, and Gu et al. (2007) have identified having one or more chronic diseases as a risk factor for institutionalization of Chinese older adults. Some effects of chronic diseases on institutionalization may be indirect, because many chronic dis-eases increase the risk of functional impairment (E. K. Nihtila et al., 2008). For example, in a longitudinal study of Swedish community-dwelling older adults, the number of chronic diseases at baseline was a significant predictor of declines in ability to perform ADLs (Marengoni, von Strauss, Rizzuto, Winblad, & Fratiglioni, 2008). Changes in the number of chronic diseases have not yet been linked directly with institutionalization. However, longitu-dinal research in the United States has clearly established the onset of new chronic conditions as a predictor of functional decline (Wolff, Boult, Boyd, & Anderson, 2005). We therefore hypothesized that an increase in the num-ber of chronic diseases would increase the risk of institutionalization in LTC facilities among Chinese older adults. Based on research that identified low self-rated health as a predictor of institutionalization in several samples of Western older adults (Gaugler et al., 2003; Gnijdic et al., 2012; Luppa, Luck, Weyerer, et al., 2010), we also hypothesized that declining self-rated health would increase the risk of institutionalization in their Chinese counterparts.

Method

Data Source

This study used Chinese Longitudinal Healthy Longevity Survey (CLHLS) data collected in 2002, 2005, 2008, and 2011. The CLHLS, an ongoing national survey in China, randomly selects participants from half of the counties and cities in 22 provinces, representing 85% of the total population of the country. The study population was community-dwelling older adults in this sample whose age ranged from 65 to 105 years. Participants older than 105 were not included in the study because of unreliability in age reporting (Zeng & Gu, 2008). The first and second waves of CLHLS, conducted in 1998 and 2000,




respectively, were limited to persons aged 80 and above, but participants aged 65 to 79 were added to the survey in 2002 and have been included in all subse-quent waves. At each follow-up wave of the CLHLS, surviving participants were re-interviewed, and new participants were enrolled to make up for attri-tion from loss to follow-up and death. For participants who died during the inter-survey period, a short post-mortality follow-up interview was conducted with proxies to collect information about the deceased participants in the year prior to their death, which included their living arrangements and functional status. Detailed descriptions of CLHLS sampling design and data quality have been reported elsewhere (Gu, 2007; Gu & Zeng, 2004). Participants living in a private home either alone or with household members at the time of interview were classified as living in the community (Gu et al., 2007). All participants provided written informed consent. Each wave of the CLHLS was approved by the research ethics committees of Duke University and Peking University.

Study Sample

Our study used a stacked sample of the participants at baseline. We treated each segment of time between CLHLS survey waves as an observation period and stacked data that covered each wave and subsequent follow-up, as described by Korinek et al. (2011). The waves of 2002, 2005, and 2008 were designated as baselines, and the 2005, 2008, and 2011 waves were treated as their respective follow-ups. All eligible participants interviewed from the 2002, 2005, 2008, and 2011 waves were included in our sample. The number of observations for each eligible participant ranged from two to four. This stacking process produced a total of 45,812 participants at baseline, of which 23,107 survived and were re-interviewed in the follow-up wave, 15,535 died before the follow-up interview, and 7,170 were lost to follow-up. The 7,170 participants lost to follow-up were excluded from the analysis due to lack of information on their living arrangements.

Outcome Variable

Institutionalization was defined as living in a LTC facility at the time of the follow-up interview. We coded institutionalization as 1 and non-institutional-ization as 0.

Independent Variables

Data for five measures of health status were included in this study: ability to perform ADLs and IADLs, cognitive impairment scores, self-rated health, and



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number of chronic diseases. Older adults who needed help to perform any of the six daily tasks of bathing, dressing, toileting, transferring, continence, and eating were classified as ADL disabled (coded as 1); otherwise, they were classified as non-disabled (coded as 0). IADL tasks consisted of eight activi-ties (visiting neighbors, shopping, cooking, laundry, walking 1 km, lifting or carrying something as heavy as a 5-kg bag, crouching and squatting, or taking public transportation). Older adults who had difficulty performing at least one of these IADLs were classified as “IADL disabled” (coded as 1); otherwise, they were classified as “IADL non-disabled” (coded as 0).

Participants were screened for cognitive impairment using the Chinese version of the Mini-Mental State Examination (MMSE); scores range from 0 to 30, and lower scores represent more severe impairment (Katzman et al., 1988). Consistent with previous studies, “unable to answer” responses were frequent for some questions on the MMSE; these were classified as incorrect answers and coded as “0” based on recommendations (Herzog & Wallace, 1997; Z. Zhang, 2006; Z. Zhang, Gu, & Hayward, 2008). Self-rated health was operationalized as a five-level variable: very poor (coded as 1), poor, fair, good, and very good (coded as 5). The number of chronic diseases was determined by assigning a score (1 = present, 0 = absent) to each of 15 dis-eases (including hypertension, stroke, heart diseases, cerebrovascular dis-ease, pneumonia, and arthritis) for which data had been continuously collected in the 2002, 2005, 2008, and 2011 waves of the CLHLS, and then summing the 15 scores.

We then constructed five health status change variables: declining ability to perform ADLs (ADL decline), declining ability to perform IADLs (IADL decline), decline of cognitive function, decline of self-rated health, and increase in number of chronic diseases. Each health status change variable was coded as a dummy variable, in which 1 indicated a decline during the period between two waves and 0 indicated no decline. For example, ADL decline was coded as 1 if a non-disabled participant changed to disabled in ADLs. Decline in cognitive function was coded as 1 if participants scored lower on the MMSE than they had in the previous wave; otherwise, this vari-able was coded as 0. Increase in number of chronic diseases was coded as 1, if a participant had a higher number of chronic diseases than in the previous wave; otherwise, it was coded as 0. Comparable coding algorithms were applied to the other health outcomes.

Covariates

Covariates in this analysis included demographic characteristics, socioeco-nomic status, family support, health behavior, and time period variables.




Demographic variables include age (continuous variable), gender (male = 1), place of residence (urban = 1), and marital status (married = 1). Socioeconomic factors included years of education (continuous variable) and financial inde-pendence (yes = 1). Family support measures included living arrangements (living alone = 1), received assistance from others when having problems (yes = 1), and number of children (continuous variable). Health behaviors included current smoker (yes = 1), current drinker (yes = 1), and exercised regularly (yes = 1). A time period variable was constructed to identify the 2002 to 2005, 2005 to 2008, and 2008 to 2011 time periods, which were coded as 0, 1, and 2, respectively.

Analysis

The total number of participants institutionalized was calculated by combining data from both surviving and deceased sample participants. Weighted rate of institutionalization was calculated by adjusting for baseline weight variables. No information on admission to institutions was available for deceased partici-pants in the 2005 and 2008 waves. Participants who survived at the follow-up wave were therefore used to study risk factors for institutionalization.

Univariate statistics (mean and standard deviation for continuous vari-ables, n and % for categorical variables) were calculated for health status variables and covariates at baseline, and for health change variables between successive waves. Differences between institutionalized and non-institution-alized participants were compared using two-sided t tests for continuous vari-ables and Pearson’s χ2 test for categorical variables. Logistic regression were used to examine the associations between institutionalization and predictor variables. Considering that one participant may be represented by up to three observations in the stacked data set, robust stand error estimation was used in the multiple logistic regression models to account for clustering at the indi-vidual level (Cameron & Miller, 2011). All baseline variables and change of health status variables described above were included in the analysis. Variables with a significance level of p < .10 were included in the final model. Adjusted odds ratios (ORs) and confidence intervals (CIs) were reported in the study.

We also fitted separate stepwise logistic regression models for participants in each time period (2002-2005, 2005-2008, and 2008-2011). Several factors were consistently found as significant predictors of institutionalization in all three time periods, whereas others were significant in some but not all mod-els. However, results of these analyses are not reported, because the small number of participants transferred from community to LTC institutions within any one time period (e.g., only 47 participants were institutionalized



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there between 2005 and 2008) limited the reliability and stability of the results.

All analyses were performed using SAS Version 9.3. Missing values for variables except self-rated health did not exceed 3% in this study. Multiple imputations of missing values were used to reduce the potential for inferen-tial bias (Royston, 2005).

Results

Table 1 shows the sample selection and the rate of institutionalization among Chinese older adults aged 65 to 105. Between the wave of 2002 and 2005, 7,828 (75.1%) of participants survived; for the two other survey intervals (2005-2008 and 2008-2011), there were 7,274 (70.1%) and 8,005 (74.7%) survivors, respectively. The rate of institutionalization among survivors increased from 0.4% in the first interval (2002-2005) to 0.6% in the third interval (2008-2011), and the rate of institutionalization among the deceased increased from 1.1% to 2.2% during the same period. The total rate of insti-tutionalization between the 2002 and 2005 waves was 0.5%, compared with a rate of 0.8% between the 2008 and 2011 waves.

Table 2 compares sample characteristics for participants who were institu-tionalized and those who were not institutionalized. At baseline, institutional-ized participants were older, had a higher level of education, had more children, and had higher levels of functional (ADL and IADL) and cognitive impairment. They were also more likely to be urban residents and to live alone at baseline. Difference of institutionalized and non-institutionalized characteristics among three time periods was significant. Percentages of

Table 1. Rate of Institutionalization Between Two Waves of the CLHLS Among Chinese Elders.

Follow-up wave Institutionalization

Baseline

totalLost to

follow-up Survivors DeceasedAmong

survivorsAmong the deceased Total

Survey periods n n (%) n (%) n (%) n (%) n (%) n (%)

2002-2005 15,069 1,857 (13.0) 7,828 (75.1) 5,384 (11.9) 57 (0.4) 30 (1.1) 87 (0.5)2005-2008 14,935 2,808 (19.2) 7,274 (70.1) 4,853 (10.8) 47 (0.3) — —2008-2011 15,808 2,505 (14.5) 8,005 (74.7) 5,298 (10.8) 86 (0.6) 48 (2.2) 134 (0.8)

Note. Numbers are from unweighted data. Percentages are weighted to reflect population. CLHLS = Chinese Longitudinal Healthy Longevity Survey.




Table 2. Characteristics of the Study Population According to Institutionalization Status.

VariablesTotal

(N = 23,107)Institutionalized

(n = 190)

Not institutionalized

(n = 22,917) p value

Independent variables Baseline health status Having at least one

ADL disability, n (%)

2,991 (12.9) 44 (23.2) 2,947 (12.9) <.001

Having at least one IADL disability, n (%)

12,667 (54.8) 126 (66.3) 12,541 (54.7) .002

Cognitive function score (MMSE), M (SD)

24.5 (7.4) 22.3 (9.1) 24.5 (7.4) <.001

Self-rated health, n (%)

.951

Very good 2,466 (11.5) 21 (10.8) 2,445 (11.5) Good 8,124 (35.4) 68 (28.1) 8,056 (35.5) Fair 8,244 (34.8) 66 (41.7) 8,178 (34.8) Poor 3,833 (16.6) 30 (18.1) 3,803 (16.6) Very poor 440 (1.6) 5 (1.2) 435 (1.6) Number of chronic

diseases, M (SD)0.9 (1.1) 1.0 (1.1) 0.9 (1.1) .655

Health change variables ADL decline = 1,

n (%)3,483 (15.1) 51 (26.8) 3,432 (15.0) <.001

IADL decline = 1, n (%)

4,316 (18.7) 39 (20.5) 4,277 (18.7) .517

Decline of cognitive function = 1, n (%)

11,517 (43.0) 115 (62.8) 11,402 (42.9) .003

Decline of self-rated health = 1, n (%)

8,307 (35.5) 63 (35.0) 8,244 (35.5) .421

Increased number of chronic diseases = 1, n (%)

7,829 (33.9) 80 (42.1) 7,749 (33.8) .020

Covariates Demographic characteristics Age, M (SD) 81.8 (10.7) 87.0 (10.1) 81.8 (10.7) .022 Male, n (%) 10,476 (47.6) 92 (61.8) 10,384 (47.6) .421

(continued)



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Table 2. (continued)

VariablesTotal

(N = 23,107)Institutionalized

(n = 190)

Not institutionalized

(n = 22,917) p value

Urban residents, n (%)

9,364 (37.0) 119 (51.6) 9,245 (37) <.001

Currently married, n (%)

9,500 (61.8) 39 (35.0) 9,461 (61.9) <.001

Socioeconomic status Years of school, M

(SD)2.3 (3.6) 2.7 (4.2) 2.3 (3.6) .002

Financial independence, n (%)

18,111 (77.9) 145 (68.2) 17,966 (77.9) .483

Family support Living alone, n (%) 3,515 (13.2) 65 (47.0) 3,450 (13) <.001 Receiving assistance

from others, n (%)22,563 (97.5) 179 (92.6) 22,384 (97.5) .002

Number of children, M (SD)

3.7 (1.9) 2.7 (2.1) 3.7 (1.9) .001

Health behavior Current drinker,

n (%)5,039 (23.8) 35 (17.8) 5,004 (23.8) .290

Current smoker, n (%)

4,940 (26.3) 26 (19.7) 4,914 (26.3) .009

Current exerciser, n (%)

8,093 (38.2) 64 (37.2) 8,029 (38.2) .757

Time period .007 2002-2005 7,828 (33.9) 57 (30.0) 7,771 (33.9) 2005-2008 7,274 (31.5) 47 (24.7) 7,227 (31.5) 2008-2011 8,005 (34.6) 86 (45.3) 7,919 (34.6)

Note. Numbers are from unweighted data. Percentages are weighted to reflect population. ADL = activities of daily living; IADL = instrumental activities of daily living; MMSE = Mini-Mental State Examination.

participants with ADL decline, declining cognitive function, and increased number of chronic diseases were significantly higher for institutionalized participants than for those who remained in the community. ADL decline occurred in 26.8% of institutionalized and 15.0% of non-institutionalized participants; cognitive decline occurred in 62.8% of institutionalized and 42.9% of non-institutionalized participants; and number of chronic diseases




Table 3. Multiple Logistic Regression Model for Predictors of Institutionalization in Chinese Elders.

95% CI

Predictors OR Lower Upper p value

Health change variables Decline of ADLs (1 vs. 0) 1.701 1.186 2.440 .004 Decline of cognitive function (1 vs. 0) 1.526 1.094 2.129 .013 Increased number of chronic diseases

(1 vs. 0)1.444 1.055 1.976 .022

Baseline variables Age 1.019 0.998 1.041 .080 Male 1.706 1.193 2.439 .004 Urban residents 2.363 1.721 3.246 <.001 Currently married 0.685 0.441 1.065 .093 Years of school 1.040 0.993 1.089 .097 Living alone 2.781 1.987 3.892 <.001 Number of children 0.788 0.717 0.866 <.001 Currently smoker 0.637 0.406 0.986 .050 Having at least one ADL limitation 1.677 1.092 2.577 .018 Cognitive function score 0.978 0.956 0.999 .050Time period 2008-2011 1.617 1.145 2.283 .006−2 log likelihood 1,976.1AIC 2,026.1

Note. This table only includes the variables with p < .1. OR = odds ratio; CI = confidence interval; ADL = activities of daily living; AIC = Akaike information criterion.

increased for 42.1% of institutionalized and 33.8% of non-institutionalized participants.

Table 3 shows results of the multiple logistic regression model. Three health change variables were found to be predictors of institutionalization. Risk of institutionalization increased 70% (OR = 1.70; 95% CI = [1.18, 2.44]) for the participants who had ADL decline, increased by 53% (OR = 1.53; 95% CI = [1.09, 2.13]) for participants with declining cognitive function, and increased by 44% (OR = 1.44; 95% CI = [1.06, 1.98]) for participants with an increasing number of chronic diseases between baseline and follow-up waves. IADL decline and decline in self-rated health were not significantly associated with institutionalization. The following baseline variables also showed correlation with institutionalization: advanced age, male, urban



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residence, unmarried status, higher level of education, living alone, having a smaller number of children, non-smoker, ADL impairment, and lower level of cognitive function. Compared with the time period of 2002 to 2005, par-ticipants in the 2008 to 2011 period were more likely to be institutionalized (OR = 1.671; 95% CI = [1.145, 2.283]).

Discussion

Institutionalization Rates

This study is the first to use national longitudinal survey data to examine rates of institutionalization and the impact of changes in health status on institu-tionalization among Chinese community-dwelling older adults. Rates of institutionalization for older adults in the CLHLS sample increased from 0.5% to 0.8% between the first interval (2002-2005) and the third interval (2008-2011).

Several factors may have contributed to this increase. First, older adults comprise an increasing proportion of the Chinese population. Although there is evidence for reductions in the prevalence of ADL disability among Chinese older adults between 1992 and 2008 (Q. Feng et al., 2013; Gu, Zhang, & Zeng, 2009), rapid growth in all subgroups of this population (particularly persons aged 80 and above, who have the highest levels of disability) is increasing the total number of older adults with impaired physical or cogni-tive function and chronic diseases who need high levels of supportive and medical care. The rising numbers and increased longevity of these older adults are increasing the burden on the traditional system of family care at the same time that socioeconomic changes (reduced family size, reconfiguration of family structures, out-migration of adult children from rural to urban areas, competing work demands) are eroding the capacity of family members to provide that care (Chu & Chi, 2008; Z. Feng et al., 2011; Li et al., 2013; Zhan et al., 2011; Y. Zhang & Goza, 2006). A reason for institutionalization fre-quently given by older adults residing in LTC facilities is that adult children are “too busy” to provide the supportive care they need (Chou, 2010). Additional contributing factors to increased institutionalization rates which were not represented in the source data set include increased availability and accessibility of LTC facilities (Ministry of Civil Affairs of the People’s Republic of China, 2013) and changing attitudes toward elder care, such as increasing acceptance of residence in LTC facilities as an appropriate strat-egy for meeting parental care needs and reframing the provision of financial support for maintenance of parents in LTC facilities by adult children who cannot provide personal care as an expression of filial piety (L. Chen & Ye,




2013; Cheng, Rosenberg, Wang, Yang, & Li, 2012; Chou, 2010; Zhan, Liu, Guan, & Bai, 2006; Zhan et al., 2011).

Results of this study indicated that the institutionalization rate was higher for participants who died before the follow-up interview than for survivors. Previous studies have shown that deterioration of health status (e.g., declin-ing physical or cognitive function, increased burden of chronic disease) occurred more frequently in older adults who died between baseline and fol-low-up surveys than in those who survived (Wolinsky et al., 1993).

Risk Factors for Institutionalization

ADL decline. Regression results (Table 3) supported the hypothesis that ADL decline is a risk factor for institutionalization of Chinese older adults, but did not support the hypothesis that IADL increases the risk of institutionalization. Our finding that ADL decline was significantly associated with institutional-ization among Chinese older adults is consistent with results of U.S. studies which have identified declining ability to perform basic ADLs as a risk factor for institutionalization of community-dwelling older adults (Gaugler et al., 2003; Wolinsky et al., 1993). Older adults with declining ability to perform basic ADLs need more supportive and medical care, which may impose physi-cal, financial, and psychological burdens that exceed the capacity of family caregivers, triggering institutionalization. In contrast, reductions in older adults’ ability to perform IADLs such as shopping, shopping, cooking, and laundry may be more manageable for family members who already perform such activities as a routine part of their household chores.

Our findings that ADL decline is a significant risk factor for institutional-ization of older adults is also consistent with a qualitative study of Chinese older adults living in LTC facilities and their families which identified sud-den increases in caregiving burden that upset the balance between the work obligations of adult children and parental needs as a powerful determinant of relocation to an elder care facility (L. Chen & Ye, 2013). One mechanism underlying the significant association between ADL decline and institutional-ization may be the precipitation of a caregiver crisis when illness or injury causes an abrupt decline in an elder’s ability to perform basic ADLs (L. Chen & Ye, 2013). Another reason for institutionalization frequently cited by LTC residents is that impaired physical function made it impossible for them to remain in a previous residence such as an apartment on the sixth or seventh floor of a building with no elevator (Chou, 2010). Additional evidence for the linkage between ADL decline and institutionalization is provided by our find-ing that older adults with advanced age (with which ADL decline is strongly associated) were more likely to enter elder care institutions.



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Declining cognitive function. Our study is the first to examine the effects of declining cognitive function on institutionalization in Chinese older adults. Our findings supported the hypothesis that changes in cognitive function would affect the likelihood of institutionalization for CLHLS participants (Table 3). Our hypothesis did not specify a direction for this association, because it is a common practice among LTC facilities to deny admission to persons with cognitive impairment (Dong & Wu, 2010; Khan & Loo, 2014; Wu et al., 2009). Nevertheless, our study identified that decline in cognitive function is a risk factor for institutionalization. The role of cognitive decline as a risk factor for placement in elder care homes is of particular interest because China has more than nine million people with some form of demen-tia and more cases of Alzheimer’s disease than any other country (Chan et al., 2013), and the growing population of cognitively impaired older adults (especially those with Alzheimer’s and other forms of dementia) is presenting a huge challenge to Chinese health and social care systems (Khan & Loo, 2014; Upson, 2014).

Unlike most developed countries, where the predominant objective of nursing homes is to provide care for persons who are physically or cogni-tively impaired, most elder care institutions in China tend to preferentially accept younger, healthier, or non-disabled older adults (Balfour, 2012; Dong & Wu, 2010; Span, 2011). Z. Feng et al. (2011) reported that almost half of the older adults residing in a sample of 140 elder care homes in Nanjing were capable of living independently, whereas Gu et al. (2007) reported that only 24.2% of older adults in a CLHLS survey sample of 770 institutionalized persons aged 80 and above were ADL disabled and only 12.7% had cognitive disabilities. In contrast, 96% of residents in U.S. LTC facilities need assis-tance with at least 1 ADL, and 48.5% are diagnosed with dementia (Harris-Kojetin, Sengupta, Park-Lee, & Valverde, 2013).

Most residential elder care facilities in China deny admission to dementia patients because their frontline staff lack the skills to provide adequate medi-cal and supportive care to this population (Khan & Loo, 2014; Wu & Caro, 2009; H. Zhang, 2007). Government-owned LTC facilities, many of which were established to house older adults with no financial resources or family support (Gu et al., 2007), usually deny entry to cognitively impaired older adults; however, less disabled individuals with declining cognitive function who can afford to pay higher rates for provision of care may be accepted as residents to balance the bottom line. Privately owned facilities, in which the cost of residence is borne almost completely by residents and their families, are more willing than government facilities to provide LTC for older adults with functional impairments and dementia (Z. Feng et al., 2011; C. Liu et al., 2014). However, even in these institutions, individuals with diagnosed




dementia comprise only a quarter of the resident population (Z. Feng et al., 2011). The percentage of residents who need ADL assistance is higher than the percentage of residents diagnosed with dementia in both government and private institutions (Z. Feng et al., 2011; C. Liu et al., 2014) because provid-ing assistance for older adults with significant cognitive impairment requires higher levels of skill than caring for those who are only ADL disabled. In extreme cases, elder care institutions may force out residents when they become too needy (Balfour, 2012). Older adults with severely impaired cog-nitive and/or physical function thus comprise a very small percentage of the population in both types of facilities.

Because community health services also lack the capability to provide dementia care, most dementia sufferers in China are supported by family caregivers with little or no training and minimal assistance from the state, who care for their elderly relatives at considerable physical, psychological, and financial cost to themselves (Fang, 2013). Family caregivers of Chinese older adults with dementia spend more time assisting with ADLs and report higher levels of burden than those providing care to older family members without dementia (Z. Liu et al., 2009). Some dementia caregivers must also cope with challenging behavioral and psychological symptoms such as agita-tion, destructive behavior, and physical aggression (Xiao et al., 2014). As family care systems continue to erode and availability of LTC facilities con-tinues to increase, older adults with declining cognitive and physical func-tions are more likely to be placed in nursing home by their families. Improving skills and reducing turnover of the personnel who provide elder care in LTC institutions are critical if China is to meet the need for LTC for its rapidly increasing population of disabled older adults. Examination of factors that increase the risk of institutionalization—with particular emphasis on changes of health status—can provide insight for planning for future care needs, help develop intervention strategies, and suggest policy implications for LTC development in China.

Increased number of chronic medical conditions. There was no difference in the number of chronic diseases at baseline between institutionalized and non-institutionalized participants in this CLHLS sample of Chinese older adults (Table 2), so baseline number of chronic diseases was not included in the regression. In contrast, an increase in the number of chronic diseases was significantly associated with institutionalization in bivariate analysis (Table 2). Increase in the number of chronic diseases between baseline and follow-up remained significant as a risk factor for institutionalization in a regression adjusted for baseline functional status (ADL, IADL), ADL decline, and IADL decline (Table 3). Increased chronic disease comorbidity is strongly linked to



Peng and Wu 17

ADL decline (E. K. Nihtila et al., 2008; Wolff et al., 2005); however, in this study, increases in the number of chronic diseases also appear to increase the risk of institutionalization in ways unrelated to ADL decline. Assessment of chronic disease comorbidity through a simple count of medical conditions is an oversimplification, as some chronic diseases are much more powerful pre-dictors of disability and institutionalization than others (Gu et al., 2007; Marengoni et al., 2008; E. K. Nihtila et al., 2008; Wolff et al., 2005). The mechanisms through which increased chronic disease burden might increase the risk of institutionalization for older Chinese adults merit further study.

Self-rated health. Neither baseline levels of self-rated health nor decline in self-rated health were significantly associated with institutionalization in this population of Chinese older adults. Thus, the findings of this study did not support the hypothesis that declining self-rated health would also predict increased risk of institutionalization. This hypothesis was based on evidence from Western studies (Luppa, Luck, Weyerer, et al., 2010) that identified low baseline self-rated health as a strong predictor of institutionalization. How-ever, the generalizability of this relationship to populations of Chinese older adults may be limited by cultural and linguistic differences in responses to queries about self-rated health. For example, Peng, Ling, and He (2010) observed that CLHLS participants aged 80+ tended to overrate their own health.

Effects of baseline characteristics. In this sample of Chinese older adults, urban residents were more likely than their rural counterparts to live in residential care institutions. This finding is consistent with research indicating that LTC facilities are more readily available in urban than in rural areas of China, and that urban residents and their families, who have higher incomes, are better able to afford the cost of residence in such facilities (Cheng, Rosenberg, Wang, Yang, & Li, 2012; Gu et al., 2007; Li et al., 2013). Demand for high-quality LTC is also higher in urban than in rural areas (Z. Feng et al., 2011). Urban older adults have more favorable perceptions of LTC facilities and are more willing than their rural counterparts to regard living in an LTC as an acceptable residential option (Chou, 2010).

Our study illustrates the importance of living arrangements and family support in the provision of care to Chinese older adults. Older adults living alone had nearly twice the odds of admission to an elder care home (OR = 3.1) than those who lived with others. Living alone also increases the odds of nursing home entry for U.S. older adults, but the effect is smaller (OR = 1.9; Gaugler et al., 2007). For older adults in some other developed countries, liv-ing alone has little or no effect on the risk of admission to an LTC facility




(Luppa, Luck, Weyerer, et al., 2010). Having more children was protective in this sample of Chinese older adults, a finding consistent with research on older adults in developed countries (Gaugler et al., 2007; Greene & Ondrich, 1990; Luppa, Luck, Weyerer, et al., 2010). However, the reduction in risk of institutionalization associated with having more children observed in this sample is likely to be less salient for Chinese older adults in the future, because one-child families are now the norm for most Chinese adults now transitioning into old age, as they were required to comply with the one-child family policy. The proportion of older Chinese adults who live alone is steadily increasing (Zeng & Wang, 2003), and meeting the needs of this seg-ment of the population for LTC will be particularly challenging.

Limitations

Some limitations of this study are inherent in the structure of the CLHLS data set. We were not able to include time to institutionalization as a covariate in our analysis due to the structure of the data. Because CLHLS interviews were conducted every 3 years starting from the year 2002, we were not able to observe short-term events (such as transitions from community to institu-tional residence and then back to the community) that occurred within the 3-year intervals between waves. However, such events are not common. Other limitations of the survey data (mentioned earlier) include lack of infor-mation about factors which were not included in the survey, including migra-tion history of adult children and attitudes of participants and their families toward institutionalization. Furthermore, the survey did not include measures of participants’ proximity to LTC facilities or items assessing participants’ perceptions about the availability, accessibility, and affordability of LTC facilities. Accordingly, it was not possible for us to determine whether there was any association between availability of such facilities and the likelihood of institutionalization.

Conclusion

Our study shows the rate of institutionalization of Chinese older adults increased between 2002 and 2011, and identifies changes of health status as significant risk factors for the transition to residence in LTC facilities. Among community-dwelling CLHLS participants, those who experienced declines in the ability to perform ADLs or cognitive function were more likely to be institutionalized. The study findings suggest clinical and policy implications for the development of the LTC system in China. China’s LTC infrastructure is still in the preliminary stage of development, especially in rural areas, and



Peng and Wu 19

rapid increases in the number of older adults who can no longer care for themselves will inevitably increase the pressure on the current system for provision of elder care, which relies heavily on informal support from family members. Policies and programs need to be developed to improve or main-tain physical and cognitive functions of older adults, thus increasing their active life expectancy, delaying their entry into LTC facilities, and alleviating some of the burden of elder care. Initiatives to provide better support for fam-ily caregivers of older adults with physical and cognitive impairment could also allow older adults to continue living with family for longer periods of time before moving to LTC facilities. Finally, it is essential to improve the skills of care providers in LTC facilities, so this workforce can better serve the increasing number of older adults who will need their assistance.

Acknowledgment

We thank Dr. Elizabeth Flint for her insight and editorial assistance.

Authors’ Note

Data derived from the Chinese Longitudinal Healthy Longevity Survey were pro-vided by the Research Group of Chinese Healthy Longevity in China.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Statistical Scientific Research Projects of China (Grant 2014LY110), the Humanity and Social Science Foundation of the Ministry of Education of China (Grant 12YJCZH164) and the special fund of Theoretical Issues Research of Guangdong Province of China (Grant LLYJ1302).

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