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. Author manuscript; available in PMC: 2015 Apr 1.
Published in final edited form as: Metabolism. 2013 Nov 27;63(4):475–483. doi: 10.1016/j.metabol.2013.11.017

Table 2.

Unadjusted linear regression coefficients between NT-proBNP and lipid and metabolic variables at levels above and below NT-proBNP inflection point. MESA baseline.

Dependent Variables NT-proBNP IP
(pg/mL)		 R2 b<IP p value
at <IP 		b>IP p value
at >IP
BMI, kg/m2 95 0.007 −0.01 (0.002) <.0001 −0.0003 (0.0003) 0.4
Total Cholesterol, mg/dL 50 0.03 −0.21 (0.03) <.0001 −0.001 (0.002) 0.6
LDL-C, mg/dL 90 0.01 −0.11 (0.02) <.0001 0.0008 (0.002) 0.7
HDL-C, mg/dL 120 0.17 0.04 (0.005) <.0001 −0.00002 (0.0008) 1.0
Triglycerides, mg/dL 60 0.01 −0.39 (0.07) <.0001 0.0005 (0.005) 0.9
Glucose, mg/dL 65 0.05 −0.14 (0.02) <.0001 0.002 (0.002) 0.4
HOMA-IR 65 0.01 −0.02 (0.005) <.0001 0.0003 (0.0004) 0.5

BMI = body mass index. IP = inflection point. The unadjusted b values are slopes for each dependent variable regressed on baseline NT-proBNP < and > the IP value. Each row represents a single linear spline model, that is, the regression equation is dependent variables = a + b<IP*(NT-proBNP − IP) + b>IP*(NT-proBNP − IP) * INT-proBNP >IP. Where a = intercept. The IP was chosen as the NT-proBNP value between 20 – 300 pg/mL with the highest R2.