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LIVING ARRANGEMENTS AND PSYCHOLOGICAL

WELL-BEING AMONG THE OLDEST OLD IN CHINA

Zheng WuChristoph M. SchimmeleDepartment of Sociology

University of VictoriaVictoria, BC V8W 3P5

zhengwu@uvic.ca

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Introduction

Population is aging not only in the industrial societies but also in the developing world.

In China, e.g., life expectancies at birth have rapidly increased since the 1950s.

The average life expectancy at birth was only 41 years of age in the early 1950s.

This figure steadily advanced in the following decades, reaching 71 years at the end of the 20th century, and is expected to continue to rise.

In China, the oldest old numbered over 11 millions of the national population in 1999. This number is expected to rise to 17 millions in 2010, 24 millions in 2020, and 92 millions in 2050.

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Figure 1

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1950 1975 2000 2025 2050

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Figure 1. Total Population Aged 65 and Over: P. R. China, 1950-2050

Source: United Nation. (2002). World Population Ageing 1950-2050. New York: United Nations, p. 178.

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Figure 2

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Figure 2. Total Population Aged 80 and Over: P. R. China, 1950-2050

Source: United Nation. (2002). World Population Ageing 1950-2050. New York: United Nations, p. 178.

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Figure 3

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Figure 3. Proportion of the Total Population Aged 65+: P. R. China, 1950-2050

Source: United Nation. (2002). World Population Ageing 1950-2050. New York: United Nations, p. 178.

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Figure 4

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Figure 4. Proportion of the Total Population Aged 80+: P. R. China, 1950-2050

Source: United Nation. (2002). World Population Ageing 1950-2050. New York: United Nations, p. 178.

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Introduction (cont’d)

It is not surprising to find that, within the next five decades, or less than a generation, the Chinese oldest old population will expand more than eight-fold.

With the “greying” of the world population, healthy aging has become an increasingly relevant topic for health scientists, policy-makers, health care professionals, and the public.

The trend toward a growing elderly population, particularly the oldest old, raises urgent policy and social concerns.

Of particular interest are questions about health care provision and quality of life for the recent and coming entries to the elderly population, especially the oldest old.

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Objectives

In this study, we use data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) to examine psychological well-being within the oldest old population.

Our main objective is to determine whether living arrangements (as a form of social support) affect psychological well-being among this population.

We also examine if having at least one child living in close proximity fosters good psychological well-being.

Finally, we examine if living arrangements (and other relevant variables) have differential effects on psychological well-being across selected oldest old age groups.

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Theory and Hypotheses

Recent economic development and rural-to-urban migration in China have left many elderly parents geographically separated from their adult children.

These trends have negative implications for the availability of social support among the oldest old.

Given this context, we have good reasons to believe that living arrangements may affect mental health among this population.

First, co-residence, especially with adult children or grandchildren, is likely a good indicator of available instrumental support.

Given the Chinese culture, this suggests that people living alone are likely to be childless or live in far proximity from family members.

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Theory and Hypotheses (cont’d)

Second, co-residential and close proximity living arrangements are likely to give elderly individuals a relatively strong perception of projected security.

Projected security refers to the sense of having someone who will provide long-term care and assistance, which is important for mental health because it reduces the perceived threat of future problems.

Finally, co-residence may promote good mental health for normative reasons.

While not a component of social support, normative expectations for culturally desirable family interactions are a potential determinant of psychological well-being among the oldest old.

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Theory and Hypotheses (cont’d)

Our main hypothesis is that oldest old individuals living in co-residential households will have superior psychological well-being compared with those living alone.

Our secondary hypotheses examine how change in living arrangements, having children living in close proximity, and age group affect the psychological well-being of the oldest old.

We expect that moving out of co-residence will be a health risk because it represents an undesirable change and a loss of social support.

We expect that having a child living in close proximity will foster good psychological well-being for the oldest old in general, because this situation increases the potential supply of social support.

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Theory and Hypotheses (cont’d)

We expect that the effects of living arrangement (and other variables) will be different across selected oldest old age groups, given that the overall need for social support progressively increases with age.

In addition, our multivariate analysis includes controls for demographic and other mental health risk factors.

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Data and Methods

Our analysis used data from the first two waves of the health and longevity survey.

Our sample is restricted to those who participated in both waves of data collection.

We exclude respondents who did not provide information on the key variables.

With these restrictions, our final study sample includes 2,514 women and 1,857 men.

Our dependent variable is psychological well-being.

To measure psychological well-being, each respondent was prompted with the following statement:

“People have their own disposition. Here are some statements of people’s description of their disposition. How similar are you to these people?”

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Data and Methods (cont’d)

The statements are as follows: I always look on the bright side of things; I like to keep my belongings neat and clean; I often feel fearful or anxious; I often feel lonely and isolated; I can make my own decisions concerning my

personal affairs; The older I get, the more useless I feel; I am as happy now as when I was younger.

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Data and Methods (cont’d)

There were five possible responses to each statement, including very similar, similar, so-so, not similar, and not similar at all.

An overall assessment of psychological well-being was derived from the total score of the responses to these statements (Cronbach’s alpha = .63).

Our primary independent variable is living arrangements.

We measure living arrangement with a five-level categorical variable: with a spouse only; with children and/or grandchildren; with siblings, parents, and/or others; in a nursing home; and living alone (reference group).

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Data and Methods (cont’d)

We use a three-level categorical variable identify respondents who experienced a change in living arrangement between T1 and T2: moving into co-residence, moving out of co-residence, and other or no changes in living arrangements.

We used random effects models in the analysis to adjust for the cluster (county/city) effects in the CLHLS and obtain valid parameter estimates and SEs.

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Data and Methods (cont’d)

In this study, we propose the following simplified random effects model:

m

k ijikijkNijxy

1 , i = 1, 2, …, c, j = 1, 2, …, ni (1)

where ijy is the observed value of the dependent variable for the

jth respondent in the ith county/city; N

is the intercept (the overall mean of the response measure);

ijkx represents the kth

explanatory variable; k

is the corresponding unknown fixed-effects parameter;

i ~ iid N(0, 2

N ), and

ij ~ iid N(0, 2

).

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Data and Methods (cont’d)

The first two terms on the right-hand side of equation (1) comprise the fixed effects part of the model, whereas (

iji ) forms the

random effects part of the model. The variance components 2

N and 2

measure the variations of

counties/cities and respondents in terms of the response measure, respectively. Equation (1) can also be seen as the two-level hierarchical linear model because the respondents are nested within each city or country in the target population.

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Table 1

TABLE 1. Living of Arrangement of Oldest Old Chinese, 1998-2000

Living arrangement Time 1 Time 2

Spouse only 13.5 12.5 Children/great/grandchildren 64.0 63.4 Siblings/parents/others 2.4 1.8 Nursing home 6.9 7.4 Living alone 13.3 14.9

Total 100% 100%

Note : Weighted percentages. N = 3,625.

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Table 2

TABLE 2. Random Effects Models of Psychological Well-being (T2) on Living of Arrangement (T1): China, 1998-2000

Independent Variable Model 1 Model 2 Model 3 Model 4Living Arrangement (T1) Spouse only 0.628 * 0.689 * Children/great/grandchildren 0.682 *** 0.719 ** Siblings/parents/others 1.015 * 1.114 * Nursing home 0.115 0.385 Living alonea

Change in living arrangement (T1, T2) Moving into co-residence -0.848 ** -0.377 Moving out of co-residence -0.855 ** -0.973 *** Other/no changea

Proximity (1 = yes) -0.029 -0.005

Psychological well-being (T1) 0.253 *** 0.252 *** 0.254 *** 0.187 ***

Socioeconomic Status (T1)Education 0.090 ***Occupation at 60 (agriculture/fishery = 1) -0.225Source of financial support Own income 0.640 *** Government assistance 0.201 Familya

Fruit 0.280 ***

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Table 2 (Cont’d)

Health Status (T1)Self-reported health status 0.318 ***Chronic condition (yes = 1) -0.228 †ADLs -0.174 ** Demographic Variables (T1)Female (yes = 1) -0.587 *** -0.582 *** -0.585 *** -0.188Age -0.321 -0.291 -0.291 -0.228Age square × 100 0.173 0.158 0.159 0.127Marital status Widowed -0.476 * -0.522 ** -0.589 *** -0.308 Separated/divorced/never married -0.170 -0.276 -0.393 -0.077 Marrieda

Number of living children 0.045 0.049 † 0.045 0.045Number of living siblings 0.115 † 0.122 * 0.117 † 0.095Ethnicity (minority = 1) -0.134 -0.126 -0.127 -0.108Rural residence (yes = 1) -1.234 *** -1.185 *** -1.205 *** -0.826 ***

Intercept 35.254 *** 34.423 *** 34.379 *** 29.960 **Covariance Parameter Estimate

2.725 *** 2.675 *** 2.711 *** 2.413 ***11.599 *** 11.604 *** 11.649 *** 11.321 ***

- 2 REML Log Likelihood 19638 19635 19653 19540a Reference category.* p < .05 ** p < .01 *** p < .001 (two-tailed test).† p < .05 (one-tailed test).

2ˆ N2ˆ e

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Table 3

TABLE 3. Random Effects Models of Psychological Well-being (T2) on Living of Arrangement (T1) by Selected Age Groups: China, 1988-2000 AgeIndependent Variable 80-89 90+Living Arrangement (T1) Spouse only 0.725 † 0.609 Children/great/grandchildren 0.657 * 0.730 † Siblings/parents/others 1.360 * 0.583 Nursing home 0.616 -0.069 Living alonea

Change in living arrangement (T1, T2) Moving into co-residence -0.144 -0.707 Moving out of co-residence -1.215 *** -0.516 Other/no changea

Proximity (1 = yes) 0.214 -0.355

Psychological well-being (T1) 0.147 *** 0.220 ***

Socioeconomic Status (T1)Education 0.124 *** 0.036Occupation at 60 (agriculture/fishery = 1) -0.157 -0.269Source of financial support Own income 0.851 *** 0.194 Government assistance 0.286 0.139 Familya

Fruit 0.261 ** 0.374 ***

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Table 3 (Cont’d)

Health Status (T1)Self-reported health status 0.362 *** 0.270 †Chronic condition (yes = 1) -0.238 -0.304ADLs -0.307 ** -0.077 Demographic Variables (T1)Female (yes = 1) -0.175 -0.371Marital status Widowed -0.214 -0.202 Separated/divorced/never married -0.062 0.042 Marrieda

Number of living children 0.063 0.014Number of living siblings 0.111 0.089Ethnicity (minority = 1) 0.504 -0.682Rural residence (yes = 1) -1.032 *** -0.669 **

Intercept 20.368 *** 19.407 ***Covariance Parameter Estimates

1.740 *** 3.054 ***11.491 *** 11.147 ***

- 2 REML Log Likelihood 11426 8165

a Reference category.* p < .05 ** p < .01 *** p < .001 (two-tailed test).† p < .05 (one-tailed test).

2ˆ N2ˆ e

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Discussion and Conclusions

The oldest old population is rapidly growing in China.

This growth may have serious implications related to other demographic and economic changes.

The results confirmed our hypothesis that individuals living in family co-residential households have better psychological well-being than those living alone.

These results are consistent with the notion that elderly individuals benefit from social support provided by adult children, particularly when the demand for assistance is greatest, such as in older ages.

Having children living in close proximity also has a non-significant effect.

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Discussion and Conclusions (cont’d)

To conclude, this study confirms the health benefits of coresidence for elderly individuals.

Family co-residence remains the “core of support” for elderly people.

Current demographic projections and social policies suggest that an increasing number of elderly individuals will have to live alone.

This means that these individuals may experience unmet instrumental and emotional needs.

Further, primary eldercare givers will face an increasingly heavy burden of domestic work.

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Discussion and Conclusions (cont’d)

Since women are the main providers of eldercare, this burden may reduce women’s mental health through prolonged and acute role strain, or even suppress equality by restricting women’s capacity to enter the labour force full-time.

In these respects, government intervention is required to foster healthy aging and ensure that the burden of eldercare does not become a persistent source of gender inequality.

Thank you.