Table 3.
Results of multiple linear regression analysis of associations between different quartiles of PCB congeners and various lipid fractions and BMI (n = 181).
| Variable in Model | TGa |
LDa |
HDb |
BMIc |
||||
|---|---|---|---|---|---|---|---|---|
| B | P value | B | P value | B | P value | B | P value | |
| PCB 138 quartiles | 44.98 | 0.001∗ | 3.21 | 0.50 | -2.01 | 0.17 | 0.64 | 0.27 |
| PCB 153 quartiles | 30.14 | 0.04∗ | 1.98 | 0.71 | -1.27 | 0.43 | -0.41 | 0.53 |
| PCB 180 quartiles | 20.64 | 0.09 | 0.02 | 0.10 | 0.12 | 0.93 | 0.04 | 0.94 |
| PCB Sum quartiles | 65.82 | 0.006∗ | 1.78 | 0.84 | 3.32 | 0.22 | -0.02 | 0.99 |
| PCB 118 quartiles | 20.10 | 0.005∗ | 2.45 | 0.36 | -1.22 | 0.14 | 0.62 | 0.053 |
| Model R square | 0.31 | 0.06 | 0.25 | 0.13 | ||||
∗Statistically significant relationship (p < 0.05).
a
TG & LDL adjusted for Age, Gender, BMI, Fat rich diet, Working Type (Active or Sedentary).
b
HDL adjusted for Age, Gender, BMI, Fat rich diet, Working Type (Active or Sedentary) and Seafood diet.
c
BMI adjusted for Age, Gender, Fat rich diet, Working Type (Active or Sedentary).