Table 2.

Associations of KDM-BAacc and PD With All-Cause Mortality in Full Sample

		Model 1			Model 2
		HR/OR (95% CI)	z-Score	p Value	HR/OR (95% CI)	z-Score	p Value
12 biomarkers in CHNS
KDM-BAacc	Per year	1.14 (1.08, 1.19)	4.99	<.001	1.16 (1.10, 1.22)	5.42	<.001
PD	Per SD	1.50 (1.33, 1.69)	6.64	<.001	1.49 (1.31, 1.68)	6.15	<.001
8 biomarkers in CHNS
KDM-BAacc	Per year	1.05 (1.03, 1.08)	3.99	<.001	1.06 (1.03, 1.09)	4.47	<.001
PD	Per SD	1.45 (1.29, 1.64)	6.03	<.001	1.43 (1.25, 1.62)	5.44	<.001
8 biomarkers in CHARLS
KDM-BAacc	Per year	1.05 (1.03, 1.07)	4.44	<.001	1.06 (1.03, 1.08)	5.03	<.001
PD	Per SD	1.44 (1.31, 1.60)	7.20	<.001	1.47 (1.32, 1.63)	7.20	<.001

Notes: CHARLS = China Health and Retirement Longitudinal Study; CHNS = China Health and Nutrition Survey; CI = confidence interval; HR = hazard ratio; KDM-BAacc = Klemera and Doubal method-biological age acceleration; OR = odds ratio; PD = physiological dysregulation; SD = standard deviation. As described in Method section, date of death was available in CHNS. Thus, Cox proportional hazard regression methods were used and HRs (95% CIs) were documented in CHNS. Since date of death was not provided in 2015 wave of CHARLS, we included a binary variable to denote occurrence of death over the 4-year follow-up since baseline in this study, rather than calculating the survival time as done in CHNS. Therefore, we used logistic regression models to examine the associations of KDM-BA and PD with death and documented ORs (95% CIs) in CHARLS. Model 1 adjusted for age and gender. Model 2 additionally adjusted for education, marital status, smoking status, alcohol consumption, and body mass index (BMI) (as categorical variable). The sample size was 8177 in the analysis when using “8 biomarkers in CHNS.”