Socioeconomic Differentials in Mortality among the Oldest Old in China Haiyan Zhu Yu Xie University of Michigan

Background Well documented inverse relationship: Higher SES Lower mortality However, magnitude varies by age

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

SES differentials in mortality diminish with age (Convergence hypothesis)? The oldest old are detached from economic activities and thus immune from some causal mechanisms (e.g., job hazards, work stress) Biological determinants, rather than social determinants, play a predominant role The oldest old are a select group with respect to unobserved health traits

Research Questions: Does SES still affect mortality among the oldest old Chinese? Do SES differentials in mortality disappear beyond an old age (e.g., 80, 90, or 100)?

Importance Previous studies have not specifically studied these questions This study focuses on these questions using a sample of oldest old in China

Data and Measures The Chinese Healthy Longevity Survey:1998 and 2000 cohort data SES: composite of education and urbanity Illiterate, rural Illiterate, urban Literate, rural Literate, urban Covariates: age, sex, ethnicity, region, self-rated health, ADL, and “time-interval” “time-interval”: time since the first interview

Analyses Three alternative target populations 80 and older, 90 and older, and 100 and older Logit, discrete time analysis

Descriptive Statistics Table 1 Distribution of SES and Mortality by SES, female Female Number Percentage Death (%) 80+   1. Illiterate, rural 3114 59.0 21.4 2. Illiterate, urban 1486 22.3 21.5 3. Literate, rural 236 8.7 11.9 4. Literate, urban 426 10.0 15.0 90+ 2279 60.2 40.8 946 27.9 38.5 115 4.9 41.8 181 6.9 40.6 100+ 1264 61.0 60.4 424 31.4 60.9 50 2.5 52.2 68 5.1 Note: numbers are unweighted; percentages are weighted.

Descriptive Statistics (Continued) Table 2. Distribution of SES and Mortality by SES, male Male Number Percentage Death (%) 80+   1. Illiterate, rural  958 26.7 27.1 2. Illiterate, urban 356 6.4 30.0 3. Literate, rural 1167 41.2 23.5 4. Literate, urban 1062 25.8 21.1 90+ 554 29.4 51.3 197 9.2 53.5 586 36.4 45.4 419 25.0 34.8 100+ 164 33.6 69.3 63 15.3 72.0 153 31.5 65.3 78 19.6 53.4 Note: numbers are unweighted; percentages are weighted.

Results Table 3. Effects of SES on Mortality (controlling ethnicity and region) Variable 80+ Mortality 90+ 100+ Female .657*** .762** .789** Age (time-varying) 1.092*** 1.055*** 1.035 Interval 1.014** 1.017*** 1.030*** SES Illiterate, urban .997 .937 .981 Literate, rural .773* .912 .932 Literate, urban .708** .731* .657** * p<.05; ** p<.01; *** p<.001

Results (Continued) Table 4. Effects of SES on Mortality (controlling health, ethnicity and region) Variable 80+ Mortality 90+ 100+ Female .622*** .690*** .716*** Age (time-varying) 1.080*** 1.041** 1.023 Interval 1.017** 1.022*** 1.036*** SES Illiterate, urban 1.022 .930 .939 Literate, rural .795 .936 1.029 Literate, urban .711** .717* .601** Self-rated Health 1.649*** 1.612*** 1.473*** ADL 1.690*** 1.824*** 1.906***  P<0.1; * p<.05; ** p<.01; *** p<.001

time1 time2 time3 1st cohort 80 81 82 2nd cohort 81 82 83 3rd cohort 82 83 84

Summary SES differentials in mortality persist, using all three operationalizations of “old age” Convergence was not supported Future studies