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A Study on DETERMINANTS OF HEALTHY LONGEVITY IN CHINA A. Introduction of Chinese longitudinal survey on Healthy Longevity; B. Some Results of the Data Analysis. Zeng Yi. A. A BRIEF INTRODUCTION to Chinese Longitudinal Survey on Healthy Longevity.

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zeng yi

A Study onDETERMINANTS OF HEALTHY LONGEVITY IN CHINAA.Introduction of Chinese longitudinal survey on Healthy Longevity;B.Some Results of the Data Analysis

Zeng Yi

slide2

A. A BRIEF INTRODUCTION to Chinese Longitudinal Survey on Healthy Longevity

  • This is a Duke-PKU collaborative large project, aiming at
  • To better understand determinants of healthy longevity, such as social, economical, behavioral, environmental and biological factors.
  • To provide data information for academic research, health and aging policy analysis.
slide3

Progress of longitudinal surveys in 1998, 2000, and 2002

(1) Achieved sample size distributions.

-- Extensive questionnaire data were gathered from 8,959, 11,161, and 11,163 oldest-old aged 80+ in 1998, 2000, and 2002, respectively.

-- Among them, 8,170, 10,457, and 12,656 interviews were conducted with centenarians, nonagenarians, and octogenarians, respectively;

-- Data on date/cause of death, health status, socioeconomic status, and degree/length of disability and suffering before dying, etc., were collected from 2,783, 2,406 and 1,449 deceased interviewees aged 100+, 90-99, and 80-89, respectively.

slide4

(2) Significant Extension of CLHLS study since 2002

-- Thanks to NIA, UNFPA, China Social Science Foundation, Peking University, Taiwan Academia Sinica and Mainland China Academy of Social Science, we added 4,894 younger elderly aged 65-79 and 4,478 elderly interviewees’ adult children aged 35-65 into our sample in 2002 wave.

-- The total sample size is now over 20,000 interviewees including oldest-old (focus), younger elderly (as a comparison group) and elders’ adult children (intergenerational relations and healthy longevity).

slide5

Age

Survival interviewees

deceased (proxy interview)

follow-up

newly interview

Total

M

F

T

M

F

T

M

F

T

M

F

T

1998 baseline survey

80-89

NA

NA

NA

1787

1741

3528

1787

1741

3528

NA

NA

NA

90-99

NA

NA

NA

1299

1714

3013

1299

1714

3013

NA

NA

NA

100+

NA

NA

NA

481

1937

2418

481

1937

2418

NA

NA

NA

Total

NA

NA

NA

3567

5392

8959

3567

5392

8959

NA

NA

NA

2000 follow-up survey

80-89

996

1048

2044

1471

1403

2874

2467

2451

4918

339

262

601

90-99

720

907

1627

925

1260

2185

1645

2167

3812

574

612

1186

100+

262

891

1153

256

1022

1278

518

1913

2431

348

1213

1561

Total

1978

2846

4824

2652

3685

6337

4630

6531

11161

1261

2087

3348

2002 follow-up survey

35-65

NA

NA

NA

3132

1346

4478

3132

1346

4478

NA

NA

NA

65-79

NA

NA

NA

2456

2438

4894

2456

2438

4894

NA

NA

NA

80-89

1454

1411

2865

673

672

1345

2127

2083

4210

483

377

860

90-99

948

1236

2184

590

858

1448

1538

2094

3632

547

679

1226

100+

277

917

1194

442

1685

2127

719

2602

3321

295

941

1236

Total

2679

3564

6243

7293

6999

14292

9972

10563

20535

1325

1997

3322

Sample Distribution, 1998-2002

NA -- Not applicable

slide6

(3) Sampling areas

-- The survey was conducted in the randomly selected half of the counties and cities of 22 provinces out of the total of 31 provinces where Han are majority.

-- The population in the survey areas constitutes about 85 percent of the total population in China.

slide7

PERSPECTIVE

General plan of our 2005 and 2008 follow-up surveys

2. Further in-depth data analysis to better understand the determinants of healthy longevity

Data Availability:

The 1998 baseline and 2000 follow-up healthy longevity survey data is now being distributed internationally by the Peking University Center for Healthy Aging and Family Studies (http://www.pku.edu.cn/academic/population/center/index.htm) and the program project at Duke University (http://www.pubpol.duke.edu/centers/ppa/). The data processing and preliminary analysis of the 2002 follow-up survey are underway and the data sets of 2002 wave will be distributed internationally in October 2004.

Contacts:

Prof. Liu Yuzhi, Peking University; E-mail: chafs@pku.edu.cn or yuzhil@pku.edu.cn

Dr. Danan Gu, Duke University;E-mail: danan@aas.duke.edu

slide8

B.Some Results of the Data Analysis

(a) CORRECTING THE UNDERESTIMATION OF DISABLED LIFE EXPECTANCY:

The CLHLS new data collection has led to a New Method & Application to the Oldest Old In China(Zeng, Gu, and Land, 2004)

slide9

Previous research has indicated that the underestimation of disability is one of the major problems in research on population aging (Gill et al. 2002; Guralnik and Ferrucci 2002)

We found that extant studies of active/disabled life expectancy based on multi-state life table implicitly assume that persons who die between ages x and x+1 (or ages x and x+n) do not change their functional status between age x and time of death.

 Such unreasonable assumption has resulted in that the widely used disabled life expectancies based on conventional methods are significantly underestimated.

Based on the unique CLHLS data on ADL before dying, we propose a new method to correct the underestimation of disabled life expectancy inherent in the MSLT method.

slide10

Results and Discussion

1. Underestimation of disabled life expectancy by classic MSLT method

①    Proportion of underestimated disabled life expectancy by conventional MSLT method at age 80 are 10% and 6% for males and females respectively. With advancing of age, such underestimation declines ----the underestimation of disabled life expectancy is statistical significant.

②    The underestimation of disabled life expectancy is larger for males than for females.

  • The underestimation of disabled life expectancy is around 12% and 6% for males and females at age 65 respectively based on the extrapolation.
slide12

Gill et al. (2002) demonstrated that prevalence ratesof disability at different waves with longer intervals between waves (e.g. 1-5 years) are substantially underestimated.

Gill and colleagues proposed to substantially reduce the length of the observation intervals between interviews or using monthly telephone interviews

---- but largely increase the costs.

slide13

Age and gender differentials in status-based ALEafter correcting the underestimation of disabled life expectancy

slide14

Life table proportions of the extent of morbidity before dying

among the oldest old who are active or disabled at initial ages

The slight morbidity profile: refers to those who were ADL active & bedridden for <5 days (including not bedridden).

  • The moderate morbidity profile: refers to those who were ADL active & bedridden for ≥5 days or ADL disabled & bedridden for <5 days.
  • Severe morbidity profile: refers to those who were ADL disabled & bedridden for 5-59 days.
  • The long-term severe morbidity profile: refers to those who were ADL disabled & bedridden for ≥60 days.
slide16

(1)ADL disability at Survey is strongly associated with the extent of morbidity before dying.

(2) As compared to their male counterparts, Chinese oldest old women not only survive in a more likely disabled status, but also suffer more before dying

(3)Our empirical results show that the life table proportions of slight morbidity death over initial age y generally do not decline with the increase of age y

----This is generally consistent with previous similar studies and provides additional evidence concerning debates on the hypothesis about compression of morbidity (Fries 1980), or Morbidity dynamic equilibrium (Manton 1982).

---- reject the hypothesis of a pandemic of disability(Gruenberg 1977)

---- healthy longevity (i.e., achieving longevity while relatively compressing morbidity) is not impossible (Hubert et al. 2002)

slide17

(b) Positive Life Satisfaction & Healthy LongevityAge differentials of physical performance, activity of daily living, good cognitive function, self-reported good health and life satisfaction of the oldest old

slide18
We find that life value in terms of positive personality, optimistic attitudes and positive view of current life has beneficial effects on health and longevity. Such positive value should be advocated.

Our unique data from the oldest-old aged 80-105 with largest survey sample size ever conducted have shown that life satisfaction and happiness is one of the secrets of healthy longevity.