Skip to main content
. Author manuscript; available in PMC: 2015 Jun 1.
Published in final edited form as: Popul Dev Rev. 2014 Jun 14;40(2):331–360. doi: 10.1111/j.1728-4457.2014.00676.x

Table A-4.

Biomarker summary scores: coefficients from models predicting mortality using social and demographic characteristics, self-reported indicators of health status, and biomarker summary scores

Model 0 Model 2 Model 3 Model 6
Age slopea
  Age 0.11*** 0.09*** 0.09*** 0.06**
  Age × Perceived social support 0.04*** 0.03** 0.03** 0.04***
  Age × Current smoker 0.14** 0.14**
Female −0.46* −0.67** −0.77** −0.82**
Mainlander −0.55* −0.58* −0.57* −0.64*
Urban resident −0.06 −0.18 −0.21 −0.08
Educationb 0.03 0.12 0.16 0.16
Social integrationb −0.14 −0.12 −0.09 −0.09
Perceived social supportb −0.96*** −0.82*** −0.81** −0.98***
Self-assessed health statusb −0.18
Index of mobility limitationsb 0.34*
History of diabetes 0.07
History of cancer 0.11
Number of hospitalizationsb 0.28***
Former smoker −0.02
Current smoker −2.73**
Biomarker risk score in 2006b 0.60*** 0.80*** 0.53***
Change (2006 – 2000) in biomarker riskb −0.35**
Interceptc −5.13*** −4.83*** −4.77*** −4.35***
a

The age slope represents the exponential increase in the mortality rate per year of age.

b

This variable was standardized (Mean=0, SD=1) prior to fitting the model; so, the coefficient represents the effect per SD of the specified variable.

c

Time was measured in terms of years after age 60. Thus, the intercept represents the mortality rate at age 60.