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Precise age‐specific average body weight estimates are necessary for deterministic risk assessments, and an accurate body weight distribution is equally important in probabilistic risk assessments. Age‐specific body weight distributions for U.S. residents are estimated using NHANES (National Health and Nutrition Examination Survey) data collected in four surveys over the last 24 years. The weighted mean and standard deviation of natural log‐transformed body weights are computed for single‐year age groups and population age‐specific weight patterns further described using piece‐wise polynomial spline functions and nonparametric age‐smoothed trend lines. These functions are used to compare distributional changes in age‐specific body weight in the United States from the first NHANES survey in 1976–1980 to the most recent in 1999–2002. Analysis demonstrates that age‐ and sex‐specific average body weight changes over this time period are not uniform. Use of these functions to compute body weight distributions for selected child‐age categories is demonstrated.

AbstractThis article presents the findings from a numerical simulation study that was conducted to evaluate the performance of alternative statistical analysis methods for background screening assessments when data sets are generated with incremental sampling methods (ISMs). A wide range of background and site conditions are represented in order to test different ISM sampling designs. Both hypothesis tests and upper tolerance limit (UTL) screening methods were implemented following U.S. Environmental Protection Agency (USEPA) guidance for specifying error rates. The simulations show that hypothesis testing using two‐sample t‐tests can meet standard performance criteria under a wide range of conditions, even with relatively small sample sizes. Key factors that affect the performance include unequal population variances and small absolute differences in population means. UTL methods are generally not recommended due to conceptual limitations in the technique when applied to ISM data sets from single decision units and due to insufficient power given standard statistical sample sizes from ISM.

The Deepwater Horizon oil spill (April 20, 2010) caused concern regarding Gulf seafood safety. Communities were skeptical of governmental risk assessments because they did not take into account the higher consumption of seafood along coastal areas. The objective of this study was to perform a probabilistic risk assessment based on the consumption rates of high-end consumers of Gulf seafood. We utilized seafood consumption data from five communities across the northeastern Gulf of Mexico. This study collected finfish, shrimp, blue crab, and oysters from these communities and analyzed their tissues for polynuclear aromatic hydrocarbons (PAHs). A probabilistic risk assessment was performed using population-specific seafood consumption rates and body weights for commercial fishers, recreational fishers, and a Filipino-American community. For non-cancer effects, 95(th) percentile hazard quotients for these targeted populations ranged between 1.84E-04 to 5.39E-03 for individual seafood types. The 95(th) percentile hazard indices for total seafood consumption ranged from 3.45E-03 to 8.41E-03. Based on total seafood consumption, highest hazard indices were modeled for the Filipino-American community followed by commercial and recreational fishers. Despite higher consumption rates, hazard indices for the high-end consumers targeted in this study were two to three orders of magnitude below the regulatory limit of 1.