active life expectancy among chinese oldest-old: are there any differences by gender, place of...

Active life expectancy among Chinese oldest-old: Are there any differences

by gender, place of residence, ethnicity, and SES

Yasuhiko Saito, Nihon UniversityGu Danan, Duke University

Presented at the workshop on"Determinants of Health Longevity in China"

Max Planck Institute for Demographic Research Rostock, Germany, August 2-4, 2004

Purpose of the study

• Try to understand the factors affecting healthy longevity by computing active life expectancy by gender, place of residence, ethnicity, and SES

• Try to present methodological issues in computing active life expectancy based on multistate life table methods

• We have seen many studies to evaluate effects of factors on mortality and health status of oldest-old Chinese. One way of making these transition rates/ probabilities more tangible or intuitive is to compute active life expectancy.

Data

• Chinese Longitudinal Healthy Longevity Survey (CLHLS)

• 1998, 2000, and 2002

Definition of Active/Disabled

• Measures used: 6 ADL items– Eating, Bathing, Transferring, Toileting,

Dressing, Continence• Response categories:

– can do it– can do it but need assistance– con not do it

• Disabled: At least one ADL limitation

Method--step 1

• Create new variable which indicates health status at each wave – active, disabled and dead

• Create interval observation data from 3 waves of CLHLS and pooled– health status at wave 1 as initial health status

and at wave 2 as end– health status at wave 2 as initial health status

and at wave 3 as end

Pooled Data

ID Wave 1 Wave 2 Wave 31 active disabled dead2 active active

Interval Observation

Beginning of Interval

End of Interval

ID=1 active disabledID=1 disabled deadID=2 active active

Original Data

Method--step 2

• Applied Discrete Time Hazard Model to estimate transition rates (not transition probability from multinomial logistic regression model)– SAS: PROC LIFEREG– weights are applied wherever applicable

Estimating 4 transition schedules

Active Disabled

Dead

Method--step 3• Construct multistate life tables (transition r

ates as input) as age and gender covariates– Population-based – Status-based

• Construct multistate life tables by introducing other factors which may associate with each transitions– Status-based

Distribution of Sample Persons by Health Status (pooled data)

end of interval

beginning of interval active disabled dead lost-to-

follow-up

active3,028

(38.2%)1,350

(17.0%)1,608

(20.3%)1,932

(24.4%)

disabled478

(8.2%)1,428

(24.6%)2,362

(40.7%)1,536

(26.5%)

Possible factors affecting healthy longevity analyzed in this study

• age: computed based on dates 　 (no 106+years)

• gender: females (0) / males (1) • ethnicity: Han (0) / minority (1)• education: no education (0) / 1+ education (1)• place of residence: rural (0) / urban (1)• economic independence: no (0) / yes (1)• marital status: other (0) / currently married (1)

Distribution of Sample Persons by Health Status and Ethnicity

end of interval

beginning of interval ethnicity active disabled dead

activeHan 5,437 2,050 2,825

minority 500 121 262

disabledHan 694 1910 3272

minority 62 87 178

Distribution of Sample Persons by Health Status and Education

end of interval

beginning of interval education active disabled dead

activeno 3,463 1,459 2,056

1+ 535 1,399 2,588

disabledno 2,474 712 1,031

1+ 221 598 862

Model Specificationsindependent vars 1 2 3 4 5 6 7

age O O O O O O O

male O O O O O O O

minority O O

1+ education O O

urban O O

econ independent O

currently married O

Results: Transition rates estimation for

Model 1 (Gender as a covariate)

from active disabled

to disabled dead active dead

age -*** -*** +*** -***

male +*** -*** - -***

***: significant at 0.01 level; **: 0.05 level; *: 0.10 level

data workshop (label='healthy longevity data: for males');* data workshop (label='healthy longevity data: for females');

male=1;* male=0;

do b_age=80 to 100; e_age=b_age; tr_1_1=0; tr_1_2=exp(-(5.3118 -0.0374*b_age +0.3129*male)); tr_1_3=exp(-(8.1075 -0.0691*b_age -0.2222*male)); tr_2_1=exp(-(-4.0470 +0.0685*b_age -0.0668*male)); tr_2_2=0; tr_2_3=exp(-(4.9473 -0.0424*b_age -0.2257*male)); output;end;run;

proc print;run;

Population-basedActive Life Expectancy

age total active disabled % active

males80 6.02 4.96 1.06 82.4

100 2.13 1.30 0.82 61.0

females80 6.72 5.05 1.75 75.1

100 2.46 1.12 1.34 45.5

Status-based Active Life ExpectancyInitial Health Status: Active


males 80 6.24 5.38 0.87 86.2

100 2.38 1.94 0.43 81.5

females 80 6.97 5.52 1.45 79.2

100 2.82 2.05 0.77 72.7

Status-based Active Life ExpectancyInitial Health Status: Disabled


males 80 4.54 2.22 2.31 48.9

100 1.69 0.18 1.51 10.7

females 80 5.33 2.41 2.92 45.2

100 2.12 0.22 1.89 10.4


Model 2 (Ethnicity is added)



age -*** -*** +*** -***

male +*** -*** - -***

minority +*** + -*** -

Estimated Transition Rates by Gender and Ethnicity:from Active to Disabled

0

0.05

0.1

0.15

0.2

0.25

80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100

Age

Rat

e

M-HanM-Non-HanF-HanF-Non-Han

Estimated Transition Rates by Gender and Ethnicity:from Active to Dead

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100

Age

Rat

e


No statistically significantdifferences in transitionrates by ethnicity

Estimated Transition Rates by Gender and Ethnicity:from Disabled to Active

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100

Age

Rat

e


No statistically significantdifferences in transitionrates by gender

Estimated Transition Rates by Gender and Ethnicity:from Disabled to Dead

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100

Age

Rat

e


No statistically significantdifferences in transitionrates by ethnicity

Active/Disabled Life Expectancy by Gender and Ethnicity at Age 80

Initial health sex ethnicity total

LEactive

LEdisabled

LE

active

M Han 6.72 6.19 0.53M non-Han 6.19 5.31 0.88F Han 7.59 6.66 0.94F non-Han 6.91 5.43 1.48

disabled

M Han 5.13 3.33 1.85M non-Han 4.50 2.16 2.34F Han 6.01 3.71 2.30F non-Han 5.27 2.31 2.97

Active/ Disabled LE at Age 80by Initial Health Status, Gender and Ethnicity

012345678

Non-Han

Han Non-Han

Han Non-Han

Han Non-Han

Han

Males Females Males FemalesInitial: Active Initial: Disabled

Years Disabled LE

Active LE

Proportion of Active/ Disabled LE at Age 80by Initial Health Status, Gender and Ethnicity

0%20%40%60%80%

100%

Non-Han

Han Non-Han

Han Non-Han

Han Non-Han

Han

Males Females Males FemalesInitial: Active Initial: Disabled

Disabled LEActive LE

Results: Transition rates estimation for Model 3 (Education is added)



age -*** -*** +*** -***

male +*** -*** -* -***

1+ edu - +*** -** +**

Active/Disabled Life Expectancy by Gender and Education at Age 80Initial health sex edu total

LEactive

LEdisabled

LE

active

M 1+ 6.50 5.56 0.94M Non 5.71 5.00 0.71F 1+ 7.61 5.85 1.76F Non 6.82 5.45 1.38

disabled

M 1+ 4.68 2.25 2.43M Non 4.24 2.17 2.07F 1+ 5.72 2.40 3.32F Non 5.24 2.41 2.83


Model 4 (urban is added)



age -*** -*** +*** -***

male +*** -*** - -***

urban -*** + +*** +***

Active/Disabled Life Expectancy by Gender and Residence at Age 80Initial health sex urban/

ruraltotal LE

active LE

disabled LE

active

M urban 6.36 5.31 1.04M rural 6.24 5.49 0.75F urban 7.08 5.41 1.67F rural 6.96 5.73 1.23

disabled


Transition rates estimation for Model 5

(economically independent is added)



age -*** -*** +*** -***

male +*** -*** -* -***

eco ind - +*** +** +***


Model 6 (Married is added)



age -*** -*** +*** -***

male +*** -*** - -***

married - +*** - +***


Model 7

from active disabledto disabled dead active dead

age -*** -*** +*** -***male +*** -*** -* -***minority +*** + -*** +1+ edu + +*** +* +**urban -*** + +*** +***

Active/Disabled Life Expectancy by Gender and Residence at Age 80, ceteris paribus

Initial health sex urban/

ruraltotal LE

active LE

disabled LE

active


disabled


Active/ Disabled LE by Initial Health Status, Gender,current residence, and controll of other variables

012345678

not

cont

rolle

dno

tco

ntro

lled

not

cont

rolle

dno

tco

ntro

lled

not

cont

rolle

dno

tco

ntro

lled

not

cont

rolle

dno

tco

ntro

lled

urban rural urban rural urban rural urban ruralMales Females Males Females


Initial Health: Active Initial Health: Disabled

Proportion of Active/ Disabled LE by Initial Health Status,Gender, current residence, and controll of other variables

0%20%40%60%80%

100%no

tco

ntrol

led not

cont

rolled no

tco

ntrol

led not

cont

rolled no

tco

ntrol

led not

cont

rolled no

tco

ntrol

led not

cont

rolled

urban rural urban rural urban rural urbanruralMales Females Males Females


Initial Health: Active Initial Health: Disabled

Status-based ALE at Age 80Initial Health Status: Active

w/ & w/o Controlled for other variables

control total active disabled % active

Mw/o 6.24 5.38 0.87 86.2

w/ 6.11 5.28 0.83 86.4

Fw/o 6.97 5.52 1.45 79.2

w/ 7.15 5.66 1.49 79.2

Status-based ALE at Age 80Initial Health Status: Disable

w/ & w/o Controlled for other variables

control total active disabled % active

Mw/o 4.54 2.22 2.31 48.9

w/ 4.54 2.32 2.22 51.1

Fw/o 5.33 2.41 2.92 45.2

w/ 5.47 2.49 2.98 45.5

Conclusions• In general, those who are active at the

beginning of the interval have a significantly longer life expectancy, longer active life expectancy, shorter disabled life expectancy and higher proportion of active life over the total life expectancy.

• In contrast, those with disability have shorter life expectancy, shorter active life expectancy, longer disabled life expectancy.

Conclusions-con't

• Females tend to have longer total life expectancy and active life expectancy but smaller proportion of active life expectancy to total life expectancy tend to smaller.

• Minority seems to have shorter total life expectancy, active life expectancy and higher proportion of active life but we may need to hold this conclusion because of the smaller sample size of minorities.

Conclusions--con't

• Education, place of residence, economic independence, marital status, all have statistically significant effect on, at least some of the transition schedules. However, the effects of these factors on active/disabled life expectancy are mainly evaluated independently.

Possible Improvements

• Need to estimate up to 105• Need to consider some more covariates

available in the survey• Need to test statistical significance of

differences in active life expectancies• Need to look at interactions among

covariates more carefully

In Addition

Introduction to The Nihon University

Longitudinal Study of Aging (NUJLSOA)

Purpose of the Study

• Investigate levels of and changes in health status of Japanese elderly

• Investigate factors affecting health status and changes in health status over time

• Observe effect of long-term care insurance program on attitute toward long-term care

• Collect comparable data to other longitudinal data for cross-national comparisons

• Help advancing research on Japanese elderly by releasing the data

Overview of the Survey• Wave 1 – November 1999

– Follow-up March 2000

• Wave 2 – November 2001– Follow-up December 2001

• Wave 3 – November 2003– Follow-up December 2003

Survey Design• Nationally representative sample of 65 and over• Initial sample of 6,700 persons selected by Multi-stage strat

ified sampling• oversampled those aged 75 and over by factor of 2• In-person interview survey using structured survey question

naire (proxy allowed)• Sample refreshing - New sample persons for those age 65

and 66 were added at each wave.• Approximately 2 years interval

Sample Size

1999 2001Panel

200165-66

2003Panel

200365-66

SampleSize 6700 900 3992+α 900

Responded4997

（74.6%）3992

（79.9%）631

（70.1%）

Deceased327

（6.5%）Did notRespond

1703（25.4%）

678（13.6%）

269（29.9%）

Interview

• 2 pre-tests for Wave1 (50 subjects each)– convenient sample – site: Tokyo metropolitan area– additional 2 hospitalized subjects

• 1 pre-test for Waves 1 & 2• Mean interview time

– Wave 1: 70 min– Wave 2: 60 min

Question Items in Wave 1

• Demographic attributes• Family Structure• Socioeconomic status• Intergenerational exchange• Information on Surviving

Children’s family• Health behaviors• Chronic conditions

• Physical functioning (ADL, IADL, NAGI)

• Mental Health• Vision & Hearing• Dental Health• Health Care Utilization• Housing• Information Technology

Question Items in Wave 2Additional Feature Decedent Interview• Date of death• Cause of death• Place of death• Medical expenses in the

last 6 months prior to death

• Relationship of main caregiver

Additional Questions• Long-term care insurance

system• CIDI

Question Items in Wave 3Additional Feature• Sleeping disorders• Restless Leg Syndrome• Pain• Stress

Additional Questions• survey of survival status of

those who did not respond at Wave 1

Data Release• Wave 1: Release by the end of August• Wave 2: Sometime in 2005

Support for Preparation and Distribution of the NUJLSOA: NIA AG021609

[email protected]

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