. Author manuscript; available in PMC: 2017 Jan 1.

Published in final edited form as: J Expo Sci Environ Epidemiol. 2015 Sep 2;26(1):78–85. doi: 10.1038/jes.2015.52

Table 5. Predictors of Mercury (Hg) Biomarkers: Hair, Blood, and Urine.

Parameter estimates (SE) and their respective p-values (below, in bold if p<0.05) are reported for the best models predicting natural log-transformed biomarker levels. Urine Hg is specific gravity adjusted. Modeling non-adjusted urine Hg resulted in the same predictors with a worse fit (adjusted r²=0.18).

Dependent	N	Adj. r²	β₀	β₁	β₂	β₃	β₄	β₅
Hair Hg¹	396	0.23	−1.79 (0.23)	0.02 (0.004)	4.70 (0.46)
			<0.0001	0.0002	<0.0001

Blood Hg²	404	0.12	−0.33 (0.49)	0.005 (0.004)	2.79 (0.40)	0.22 (0.09)
			0.50	0.14	<0.0001	0.02

Urine Hg³	318	0.25	−0.46 (0.20)	0.01 (0.004)	−0.24 (0.08)	0.08 (0.01)	0.01 (0.004)	0.005 (0.002)
			0.02	0.0009	0.004	<0.0001	0.05	0.03

Hair Hg model: β₀=intercept, β₁= age (years), β₂= estimated Hg intake from fish consumption (log-transformed, µg Hg/kg body weight/day)

Blood Hg model: β₀=intercept, β₁=age (years), β₂=estimated Hg intake from fish consumption (log-transformed, µg Hg/kg body weight/day), β₃=red blood cell count (X 10⁶/µL)

Urine Hg model: β₀=intercept, β₁= total years in dental practice, β₂=female (vs. male reference), β₃=amalgams in mouth, β₄=hours worked per week, β₅=amalgams handled in the dental office per week (placed + removed)