“The Effects of Sociodemographic Factors on the Hazard of Dying Among Aged Chinese Males and Females” Dudley L. Poston,

1. “The Effects of Sociodemographic Factors on the Hazard of Dying Among Aged Chinese Males and Females” Dudley L. Poston, Jr. and Hosik Min Department of Sociology Texas A&M University College Station, Texas 77843 dudleyposton@yahoo.com

2. Introduction Prior Studies Data and Methods Results Kaplan-Meier Survival Curves Cox Proportional Hazard Regression Adjusted Cox Survival Curves Conclusion

3. The Kaplan-Meier estimator of surviving beyond time t (i.e., not dying): S(t) =

4. Cox Proportional Hazard Regression: log h(t) = log h0(t) + b1x1 + ... + bkxk where: h0(t) is an unspecified function of time t, x1to xk are sociodemographic co-variates (independent variables), and b1to bk are the Cox parameters to be estimated.

5. Figure 1. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month: 8,131 Oldest Old Persons, China, 1998-2000

6. Figure 2. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month, Males and Females: 8,131 Oldest Old Persons, China, 1998-2000 Male Female Χ2 = 7.27, P = .007

7. Figure 3. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month, Han and non-Han: 8,131 Oldest Old Persons, China, 1998-2000 Non-Han Han Χ2 = 1.40, P= .237

8. Figure 4. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month, Rural and non-Rural Residents: 8,131 Oldest Old Persons, China, 1998-2000 Non-Rural Rural Χ2 = 35.96, P = .000

9. Figure 5. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month, Rural Birth and non-Rural Birth: 8,131 Oldest Old Persons, China, 1998-2000 Non-Rural Birth Rural Birth Χ2 = 37.89, P = .000

10. Figure 6. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month, Four Age Groups: 8,131 Oldest Old Persons, China, 1998-2000 77-79 80-89 90-99 100+ Χ2 = 896.00, P = .000

11. Table 1. Cox Proportional Hazard Model Estimates of the Effects of Sociodemographic Co-variates, on the Hazard of Dying: 8,131 Oldest Old Persons, China, 1998-2000 Hazard Hazard Semi-Standardized Variable Coefficient Ratio Hazard Ratio Female -0.27* 0.76 0.88 Han 0.13* 1.13 1.03 Rural Residence 0.04 1.04 1.02 Rural Birth 0.13* 1.14 1.05 Education (years) 0.00 1.00 1.00 Never Married 0.08 1.08 1.01 Separated/Divorced 0.20 1.22 1.03 Widowed 0.43* 1.53 1.18 Age group 0.60* 1.83 1.65 Final Log Likelihood = -28468.04 Likelihood Ratio 2 = 947.88, P = .000 *significant at p<0.05, one-tailed test

12. Cox proportional hazard model survival curve that adjusts for the co-variates in the Cox model: where the predicted survival function at time t is given by a baseline survival function raised to a power equal to the exponential of the sum of the predicted Cox parameters times the mean values of the co-variates.

13. Figure 7. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month: 8,131 Oldest Old Persons, China, 1998-2000

14. Figure 8. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month, Males and Females: 8,131 Oldest Old Persons, China, 1998-2000 Female Male

15. Figure 9. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month, Han and non-Han: 8,131 Oldest Old Persons, China, 1998-2000 Non-Han Han

16. Figure 10. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month, Rural and non-Rural Residents: 8,131 Oldest Old Persons, China, 1998-2000 Non-Rural Rural

17. Figure 11. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month, Rural Birth and non-Rural Birth: 8,131 Oldest Old Persons, China, 1998-2000 Non-Rural Birth Rural Birth

18. Figure 12. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month, Four Age Groups: 8,131 Oldest Old Persons, China, 1998-2000 77-79 80-89 90-99 100+

19. End of Presentation