1. Liu, Guiping Max-Planck-Institute for Demographic Research
Social-economic Differentials of the Dying Risk of the oldest-old Chinese
Liu, Guiping
Max-Planck-Institute for Demographic Research

2. Summary 1. Briefing the existing studies 2. A simple framework
3. Data and method
4. Variables and descriptive statistics
5. Statistical outcomes
6. Main findings
7. Brief discussion

3. 1.Briefing the existing studies
1. Kannisto (1994) reported the differentials of mortality at high ages in developed countries. No social economic factors were involved.
2. Martelin, Koskinen, Valkonen (1998): the dying risk of the oldest-old Finish is significantly associated with income level, educational attainment, occupational experience,marital status, residential place,linguistic attachment.
3. The similar researches in developing countries are rare.

4. 2.A simple framework

5. 3. Data and method
Data: the second wave of Chines Healthy Longevity Survey 2000
Starting time of the observation:1998 base-line survey
Method: Cox Proportional Hazard Model

6. 4.Variables Variables: age group, sex , place of birth,ethnicity;
years of education, number of children ever born; number of biological siblings, birth orders, main occupation before age 60;
marital status, living arrangement, main source of financial support,
self-rated health status.

7. 5. The descriptive statistics
Majority of the oldest-old were born in countryside;
Hans account for major proportion of the interviewees;
A few people received education longer than seven years;
Fifty percent of the interviewees were farm labors before age 60;
Eighty percent of the interviewees were taken care by children, grand-children, or children-in-law when they were ill;
Eighty-four percent of the oldest-old are living with household members;
Sixty-five percent of the oldest-old depended on their children financially.

8. 6. Statistical outcomes (1)
Age group relative risk of dying
80-84(ref.) * * * * *
106 and older *

9. 6. Statistical outcomes (2)
sex relative risk of dying
Male （ref.)
Female *

10. 6. Statistical outcomes (3)
place of birth relative risk of dying
urban areas （ref.)
rural areas *
ethnicity 
Hans (ref.)
minority groups *

11. 6. Statistical outcomes (4)
Marital status relative risk of dying
married, living with spouses（Ref.)
separated or divorced
widowed *
never married

12. 6. Statistical outcomes (5)
Years of education relative risk
0 year (ref.)
1-6 years *
7 years or more

13. 6. Statistical outcomes (6)
Main occupation before age relative risk
professional & technical personnel（ref.)
governments, management
farm labors, forest, husbandry,fishery workers *
manufacture workers *
commercial or services workers *
househusband or housewife *
other *

14. 6. Statistical outcomes (7)
Main source of financial support relative risk
retirement pension（ref
spouse
children
grand-children
other relative
local governments or community
still on work *
others

15. 6. Statistical outcomes (8)
No.of biological siblings relative risk
0 （ref.） *
6 or more *

16. 6. Statistical outcomes (9)
Birth order  relative risk
1st （ref.）
2nd
3rd
4th *
5th
6th or higher

17. 6. Statistical outcomes (10)
Self-rated health status relative risk of dying
very good（ref.）
good *
so-so *
poor or very poor *
not able to answer *

18. 7. Main findings
Social economic statuses are associated with mortality of the oldest-old Chinese;
Lower social status, e.g, born in rural areas; manual workers, expose to higher risk of dying than do professionals and technicians;
The widowed expose to high risk of dying;
Having more siblings indicate a lower risk of dying;

19. 7.Main findings (continued)
Those persons who were in birth order four show lower risk of dying, but we have no solid theory to explain the result;
We did not find living arrangement, residential place, are associated with the dying risk of the oldest-old Chinese.

20. 8. Discussion Our study is based on the following background:
1. The oldest-old is a highly selective groups;
2. The length of the observation is around 24 months;
3. A common statistical method is applied.
Our study suggests that the early events in human life course have impacts on survival probability at age 80 and over.