TABLE 3.

Cox Regression Models for the Association Between Serum Bicarbonate Groups and Clinical Outcomes Accounting for Complex Survey Design^a,b

	Serum Bicarbonate (mEq/L)
	<22	[22–26]	>26
All-cause mortality
Model 1	1.63 (1.42–1.88); <.001	Ref	1.02 (0.96–1.07); .51
Model 2	1.62 (1.37–1.92); <.001	Ref	1.03 (0.97–1.10); .31
Model 3	1.54 (1.30–1.83); <.001	Ref	1.04 (0.97–1.11); .26
CVD mortality
Model 1	Ref	1.26 (0.89–1.77); .19	1.06 (0.96–1.17); .23
Model 2	1.26 (0.89–1.79); .20	Ref	1.04 (0.93–1.16); .54
Model 3	1.12 (0.77–1.62); .56	Ref	1.06 (0.94–1.19); .33
Cancer mortality
Model 1	Ref	1.57 (1.16–2.11); .003	1.01 (0.89–1.14); .88
Model 2	1.47 (1.01–2.15); .05	Ref	1.07 (0.93–1.22); .37
Model 3	1.46 (1.00–2.13); .05	Ref	1.07 (0.93–1.23); .34

^aCVD = cardiovascular disease; HR = hazard ratio; Ref = reference.

^bValues shown are HR (95% CI); P value.

Model 1 is adjusted for age, sex, race (n=31,195).

Model 2 is adjusted for variables in Model 1+ tobacco use, coronary artery disease, heart failure, cholesterol, systolic blood pressure, chronic obstructive pulmonary disease, liver disease, body mass index, high-density lipoprotein, malignancy, diuretics, angiotensin converting enzyme inhibitors, or angiotensin receptor blockers (n=26,652).

Model 3 is adjusted for variables in Model 2 + estimated glomerular filtration rate, and log transformed spot urine albumin/creatinine (n=26,404).