home edit2 whole TSD November 2002 PDF format - OEHHA

A risk assessment was also conducted using an adjustment for the strong interaction between arsenic
and smoking observed in several occupational cohorts. The prevalence of smoking was independent of
the level of arsenic exposure in the Anaconda cohort (Welch et al., 1982), but may have been higher
than in the general population. Also, there appeared to be no reason for smokers to be distributed
differently among the exposure levels in the Tacoma cohort, hence smoking was assumed to be
independent of arsenic exposure in this cohort as well.
Each dose-specific crude SMR was adjusted taking the low-dose SMR in each study as the baseline.
Next, a nonsmokers’ SMR and a smokers’ SMR were derived. From the nonsmokers’ SMR,
observed and expected deaths among nonsmokers were inferred. Finally, a regression model was fitted
to the inferred nonsmokers’ data to find the slope of the line relating cumulative arsenic dose to excess
relative risk. This procedure was applied to the data of Enterline et al. (1987a) under the assumption
that the interaction between smoking and arsenic varies as a function of dose, and that the joint effects at
low doses are multiplicative.
The MLE for β was 2.30 × 10 -4 using the data on nonsmokers from the study by Enterline et al.
(1987a). An 95% UCL was estimated and used in evaluating unit risks.
Risks were evaluated separately by sex and for four smoking categories: never, former, light (< 1
pack/day) and heavy smokers. Unit risks for these categories range from 400 to 8,400 per million
persons, with upper bounds ranging from 630 to 13,000 per million.
The staff of DHS recommended that the range of risk for ambient exposures to arsenic be based on the
95% UCL predicted from fitting a linear model to the human data adjusted for interaction with smoking.
The staff of DHS further recommended that the overall unit risk, 3.3 × 10 -3 per µg/m 3 , be considered
the best estimate of the upper bound of risk.
Oral
A generalized multistage procedure with both linear and quadratic dose assumptions was used to
predict the prevalence of skin cancer as a function of arsenic concentration in drinking water (d) and age
(t), assuming exposure to a constant dose rate since birth. F(t,d) represents the probability of
developing skin cancer by age t after lifetime exposure to arsenic concentration d. The procedure used
is expressed as follows: F(t,d) = 1 - exp[-g(d) H(t)], where g(d) is a polynomial in dose with nonnegative
coefficients, and H(t) is (t-w) k , where k is any positive real number, and t > w for induction
time w. The cancer potency calculation was based on skin cancer incidence data for Taiwanese males
(Tseng et al., 1968) because their skin cancer prevalence rates were higher than the females studied.
The calculation was also based on several assumptions listed below.
1. The mortality rate was equal for both diseased (skin cancer) and nondiseased persons.
2. The population composition (with respect to skin cancer risk factors) remained constant over time,
implying that there was no cohort effect.
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