Adding anthropometric measures of regional adiposity to BMI improves prediction of cardiometabolic, inflammatory and adipokines profiles in youths: a cross-sectional study

Table 2 Relationships between a single anthropometric measurement and biological variables

Variable	BMI Z score	Waist C Z score	WHtR	WHR Z score
Pearson’s R
Fasting glucose	0.235^*	0.176^*	0.193^*	0.057
Fasting insulin^a	0.490^**	0.483^**	0.463^**	0.295^**
HOMA IR^a	0.493^**	0.480^**	0.463^**	0.290^**
QUICKI	−0.475^**	−0.463^**	−0.444^**	−0.283^**
Triglycerides^a	0.205^*	0.270^**	0.250^**	0.249^**
HDL cholesterol^a	−0.205^*	−0.293^**	−0.252^**	−0.273^**
LDL cholesterol	−0.047	−0.013	0.003	0.018
SBP Z score	0.385^**	0.389^**	0.433^**	0.198^*
DBP Z score	0.392^**	0.353^**	0.418^**	0.186^*
CRP^a	0.374^**	0.388^**	0.472^**	0.261^**
Fibrinogen^a	0.341^**	0.316^**	0.375^**	0.193^*
Adiponectin^a	−0.187^*	−0.277^**	−0.201^*	−0.279^**
Leptin^a	0.551^**	0.498^**	0.546^**	0.119
Resistin^a	0.229^*	0.181^*	0.191^*	0.064

Data are Pearson’s R (univariate linear analysis) for single biological variables
^*P-value < 0.05; ^**P-value < 0.001
^aLog-transformed variables

ISSN: 1471-2431