TABLE III.

Linear regression models^a of associations between lead dose and systolic blood pressure among 652 Korean lead workers

Independent variable	β coefficient	SE β	p-value	Model r2
Model 1
Patella lead, μg/g	0.0059	0.0071	0.41	0.19
Model 2
Blood lead, μg/dL	0.1007	0.0404	0.01	0.20
Model 3
Patella lead, μg/g	−0.0017	0.0078	0.82	0.20
Blood lead, μg/dL	0.1048	0.0444	0.02
Model 4b
Intercept	121.63	0.6034	<0.01	0.19
Age, years	0.4448	0.1043	<0.01
Patella lead, μg/g	0.0043	0.0078	0.59
Patella lead, μg/g × age cat1	0.0066	0.0139	0.64
Model 5b
Intercept	121.15	1.6001	<0.01	0.20
Age, years	0.4529	0.1021	<0.01
Blood lead, μg/dL	0.1196	0.0603	0.05
Blood lead, μg/dL × age cat1	−0.0301	0.0714	0.67

^aThe models also controlled for age (linear and quadratic terms), gender, body mass index, lead job duration, antihypertensive medication use, and cumulative lifetime drinks in current alcohol users (divided into quartiles).

^bThe oldest tertile of workers is the reference group (italized); the beta coefficient for this term is therefore the slope for the association between the lead variable and systolic blood pressure in the older workers. The slope in the younger age category (age cat¹ which is the youngest 67th percent) is obtained by adding the beta coefficient of the cross-product term (below the reference category) to the beta coefficient of the reference category (i.e., the slope for the association between patella lead and systolic blood pressure in the younger age group is 0.0109 [0.0043 + 0.0066]). P-values for the cross-product terms of age and lead dose reflect the statistical significance of the difference between the slopes of the regression lines in the younger age category and in the oldest age group.