Table 3.

Contributions of Various Biomarkers to the Sex Difference in Mortality^a (n = 933), Social Environment and Biomarkers of Aging Study, Taiwan, 2000–2006

	Odds Ratio for Male Sex	95% Confidence Interval	Change From Base Model, %
Base modelb	2.28*	1.46, 3.57
Any smoking in past 6 months	1.58	0.96, 2.59	−54.8
Standard risk factors
Hypertension and use of antihypertensive agents	2.31*	1.47, 3.62	2.1
Total cholesterol	2.26*	1.43, 3.56	−1.7
High density lipoprotein cholesterol	2.21*	1.40, 3.47	−5.8
Body mass indexc	2.20*	1.40, 3.46	−6.5
High waist circumference	2.32*	1.45, 3.69	2.6
Glycoslyated hemoglobin and use of hypoglycemic agents	2.51*	1.59, 3.97	17.8
All biomarkers in this cluster	2.51*	1.52, 4.14	17.6
Markers of disease progression
Creatinine clearance and its quadratic term	2.33*	1.47, 3.67	3.3
Albumin	2.12*	1.35, 3.34	−12.4
White blood cell count and its quadratic term	2.33*	1.48, 3.66	3.6
Neutrophils	2.14*	1.36, 3.36	−11.4
All biomarkers in this cluster	2.09*	1.31, 3.34	−15.0
Nonclinical markers
Epinephrine and its quadratic term	2.80*	1.75, 4.48	40.5
Norepinephrine	2.40*	1.53, 3.79	9.4
Cortisol	2.34*	1.49, 3.68	4.8
Dehydroepiandrosterone sulfate	2.34*	1.48, 3.69	4.5
Interleukin-6 and its quadratic term	2.12*	1.34, 3.36	−12.7
Insulin-like growth factor 1	2.30*	1.47, 3.60	1.5
All biomarkers in this cluster	2.69*	1.64, 4.43	32.0

* P < 0.01 (2-sided).

^aEach row represents the effect of adding the specified biomarker or cluster of biomarkers to the base model. A negative percent change implies that inclusion of the selected biomarker accounts for some of the excess male mortality, whereas a positive percent change indicates that inclusion of the biomarker exaggerates the sex difference.

^bThe base model excluded smoking from model 1 (Table 2).

^cWeight (kg)/height (m)².