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Table 2 Evaluation of the impact of CMI on eGFR value with the use of piecewise linear regressiona

From: Value of reduced glomerular filtration rate assessment with cardiometabolic index: insights from a population-based Chinese cohort

  

Unadjusted

MV adjusted

Males

 Linear model

β Value (95% CI) P value

−1.850 (−2.259, −1.440) < 0.001

−2.214 (−2.561, −1.866) < 0.001

 Non-linear model

Breakpoint (K)

1.024

1.113

β 1 (<K) (95% CI) P value

−3.324 (−3.863, − 2.786) < 0.001

−3.150 (−3.589, − 2.712) < 0.001

β 2 (>K) (95% CI) P value

3.777 (2.371, 5.182) < 0.001

1.906 (0.675, 3.138) 0.002

Logarithmic likelihood ratio test P value

< 0.001

< 0.001

Females

 Linear model

β Value (95% CI) P value

−4.046 (−4.438, −3.654) < 0.001

−1.914 (−2.262, − 1.566) < 0.001

 Non-linear model

Breakpoint (K)

1.34

1.472

β 1 (<K) (95% CI) P value

−5.001 (−5.472, −4.530) < 0.001

−2.411 (− 2.813, − 2.010) < 0.001

β 2 (>K) (95% CI) P value

2.478 (0.636, 4.320) 0.008

2.268 (0.547, 3.988) 0.010

Logarithmic likelihood ratio test P value

< 0.001

< 0.001

  1. Abbreviations: CMI cardiometabolic index, OR odds ratio, 95% CI 95% confidence interval. Linear model: model that presumes the association between CMI and eGFR is linear. Non-linear model: model that presumes the association between CMI and eGFR is non-linear and has breakpoint. Unadjusted: no adjustment; MV adjusted: multivariable adjusted model, includes age, race, education level, family annual income, physical activity, current smoking, current alcohol intake, hypertension, diabetes, antihypertensive drug, antidiabetic drug, lipid-lowering drug, history of cardiovascular disease and kidney disease. aTwo-step linear regression model was applied to explore the non-linear association between CMI and eGFR