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

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

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

4 Cox Proportional Hazard Regression: log h(t) = log h 0 (t) + b 1 x b k x k where: h 0 (t) is an unspecified function of time t, x 1 to x k are sociodemographic co-variates (independent variables), and b 1 to b k 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,

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

7 Χ 2 = 1.40, P=.237 Figure 3. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month, Han and non-Han: 8,131 Oldest Old Persons, China, Non-Han Han

8 Χ 2 = 35.96, P =.000 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, Non-Rural Rural

9 Χ 2 = 37.89, P =.000 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, Non-Rural Birth Rural Birth

10 Figure 6. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month, Four Age Groups: 8,131 Oldest Old Persons, China, Χ 2 = , P =

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, Hazard Hazard Semi-Standardized VariableCoefficient Ratio Hazard Ratio Female -0.27* Han 0.13* Rural Residence Rural Birth 0.13* Education (years) Never Married Separated/Divorced Widowed 0.43* Age group 0.60* Final Log Likelihood = Likelihood Ratio  2 = , P =.000 *significant at p<0.05, one-tailed test

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,

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, 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, 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, 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, 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,

19 End of Presentation