socioeconomic differentials in mortality among the oldest old in china

Socioeconomic Differentials Socioeconomic Differentials in Mortality among the in Mortality among the

Oldest Old in ChinaOldest Old in China

Haiyan ZhuHaiyan Zhu

Yu XieYu Xie

University of MichiganUniversity of Michigan

BackgroundBackground

Well documented inverse relationship: Well documented inverse relationship:

Higher SES Lower mortalityHigher SES Lower mortality

However, magnitude varies by ageHowever, magnitude varies by age

Yu Xie (1994). “Log-multipliticative Models for Discrete Time, Discrete Covariate Event-History Data”

SES differentials in mortality diminish SES differentials in mortality diminish with age (Convergence hypothesis)?with age (Convergence hypothesis)?– The oldest old are detached from The oldest old are detached from

economic activities and thus immune from economic activities and thus immune from some causal mechanisms (e.g., job some causal mechanisms (e.g., job hazards, work stress)hazards, work stress)

– Biological determinants, rather than social Biological determinants, rather than social determinants, play a predominant roledeterminants, play a predominant role

– The oldest old are a select group with The oldest old are a select group with respect to unobserved health traitsrespect to unobserved health traits

Research Questions:Research Questions:

Does SES still affect mortality Does SES still affect mortality among the oldest old Chinese?among the oldest old Chinese?

Do SES differentials in mortality Do SES differentials in mortality disappear beyond an old age disappear beyond an old age (e.g., 80, 90, or 100)?(e.g., 80, 90, or 100)?

ImportanceImportance

Previous studies have not Previous studies have not specifically studied these specifically studied these questions questions

This study focuses on these This study focuses on these questions using a sample of questions using a sample of oldest old in China oldest old in China

Data and MeasuresData and Measures

The Chinese Healthy Longevity The Chinese Healthy Longevity Survey:1998 and 2000 cohort dataSurvey:1998 and 2000 cohort data

SES: composite of education and urbanitySES: composite of education and urbanity– Illiterate, ruralIlliterate, rural– Illiterate, urbanIlliterate, urban– Literate, ruralLiterate, rural– Literate, urbanLiterate, urban

Covariates: age, sex, ethnicity, region, Covariates: age, sex, ethnicity, region, self-rated health, ADL, and “time-interval”self-rated health, ADL, and “time-interval”– ““time-interval”: time since the first interviewtime-interval”: time since the first interview

AnalysesAnalyses

Three alternative target Three alternative target populationspopulations80 and older, 90 and older, and 100 80 and older, 90 and older, and 100

and olderand older Logit, discrete time analysisLogit, discrete time analysis

Descriptive StatisticsDescriptive Statistics

FemaleFemale NumberNumber PercentagePercentage Death (%)Death (%)

80+80+

1. Illiterate, rural1. Illiterate, rural 31143114 59.059.0 21.421.4

2. Illiterate, urban2. Illiterate, urban 14861486 22.322.3 21.521.5

3. Literate, rural3. Literate, rural 236236 8.78.7 11.911.9

4. Literate, urban4. Literate, urban 426426 10.010.0 15.015.0

90+90+





100+100+





Table 1 Distribution of SES and Mortality by SES, female

Note: numbers are unweighted; percentages are

weighted.

Descriptive StatisticsDescriptive Statistics (Continued)(Continued)

MaleMale NumberNumber PercentagePercentage Death (%)Death (%)

80+80+





90+90+





100+100+





Table 2. Distribution of SES and Mortality by SES, male

Note: numbers are unweighted; percentages are

weighted.

Results Results

VariableVariable 80+80+Mortality Mortality

90+90+ 100+100+

FemaleFemale .657*** .657*** .762** .762** .789** .789**

Age (time-varying)Age (time-varying) 1.092*** 1.092*** 1.055***1.055*** 1.035 1.035

IntervalInterval 1.014** 1.014** 1.017*** 1.017*** 1.030*** 1.030***

SESSES

Illiterate, urbanIlliterate, urban .997.997 .937 .937 .981 .981

Literate, ruralLiterate, rural .773* .773* .912 .912 .932 .932

Literate, urbanLiterate, urban .708** .708** .731* .731* .657** .657**

Table 3. Effects of SES on Mortality (controlling ethnicity and region)

* p<.05; ** p<.01; *** p<.001

Results Results (Continued)(Continued)

VariableVariable 80+80+Mortality Mortality

90+90+ 100+100+

FemaleFemale .622*** .622*** .690*** .690*** .716***.716***

Age (time-varying)Age (time-varying) 1.080***1.080*** 1.041** 1.041** 1.023 1.023

IntervalInterval 1.017** 1.017** 1.022***1.022*** 1.036*** 1.036***

SESSES

Illiterate, urbanIlliterate, urban 1.0221.022 .930 .930 .939 .939

Literate, ruralLiterate, rural .795.795 .936 .936 1.029 1.029

Literate, urbanLiterate, urban .711** .711** .717* .717* .601** .601**

Self-rated HealthSelf-rated Health 1.649*** 1.649*** 1.612*** 1.612*** 1.473*** 1.473***

ADLADL 1.690*** 1.690*** 1.824*** 1.824*** 1.906***1.906***

Table 4. Effects of SES on Mortality (controlling health, ethnicity and region)

P<0.1; * p<.05; ** p<.01; *** p<.001

1st cohort 80 81 82

2nd cohort 81 82 83

3rd cohort 82 83 84

time1 time2 time3

SummarySummary

SES differentials in mortality SES differentials in mortality persist, using all three persist, using all three operationalizations of “old age”operationalizations of “old age”

Convergence was not supportedConvergence was not supported Future studiesFuture studies

socioeconomic differentials in mortality among the oldest old in china

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