A CAUTION FOR MONTE-CARLO RISK ASSESSMENT OF LONG-TERM EXPOSURES BASED ON SHORT-TERM EXPOSURE STUDY DATA

Monte Carlo risk assessments commonly take as input empirical or param etric exposure distributions from specially designed exposure studies. The exposure studies typically have limited duration, since their des ign is based on statistical and practical factors (such as cost and re spondent burden). For these reasons, the exposure period studied rarel y corresponds to the biologic exposure period, which we define as the time at risk that is relevant for quantifying exposure that may result in health effects. Both the exposure period studied and the biologic exposure period will often differ from the exposure interval used in a Monte Carlo analysis. Such time period differences, which are often n ot accounted for, can have dramatic effects on the ultimate risk asses sment. When exposure distributions are right skewed and/ or follow a l ognormal distribution, exposure will usually be overestimated for perc entiles above the median by direct use of exposure study empirical dat a, since biologic exposure periods are generally longer than the expos ure periods in exposure assessment studies. We illustrate the effect t hat biologic exposure time period and response error can have on expos ure distributions, using soil ingestion as an example. Beginning with variance components from lognormally distributed soil ingestion estima tes, we illustrate the effect of different modeling assumptions, and t he sensitivity of the resulting analyses to these assumptions. We deve lop a strategy for determining appropriate exposure input distribution s for soil ingestion, and illustrate this using data on soil ingestion in children.