Issues Related to Time Averaging of Exposure in Modeling Risks Associated with Intermittent Exposures to Lead

Typical exposures to lead often involve a mix of long-term exposures to relatively constant exposure levels (e.g., residential yard soil and indoor dust) and highly intermittent exposures at other locations (e.g., seasonal recreational visits to a park). These types of exposures can be expected to result in blood lead concentrations that vary on a temporal scale with the intermittent exposure pattern. Prediction of short-term (or seasonal) blood lead concentrations arising from highly variable intermittent exposures requires a model that can reliably simulate lead exposures and biokinetics on a temporal scale that matches that of the exposure events of interest. If exposure model averaging times (EMATs) of the model exceed the shortest exposure duration that characterizes the intermittent exposure, uncertainties will be introduced into risk estimates because the exposure concentration used as input to the model must be time averaged to account for the intermittent nature of the exposure. We have used simulation as a means of determining the potential magnitude of these uncertainties. Simulations using models having various EMATs have allowed exploration of the strengths and weaknesses of various approaches to time averaging of exposures and impact on risk estimates associated with intermittent exposures to lead in soil. The International Commission of Radiological Protection (ICRP) model of lead pharmacokinetics in humans simulates lead intakes that can vary in intensity over time spans as small as one day, allowing for the simulation of intermittent exposures to lead as a series of discrete daily exposure events. The ICRP model was used to compare the outcomes (blood lead concentration) of various time-averaging adjustments for approximating the time-averaged intake of lead associated with various intermittent exposure patterns. Results of these analyses suggest that standard approaches to time averaging (e.g., U.S. EPA) that estimate the long-term daily exposure concentration can, in some cases, result in substantial underprediction of short-term variations in blood lead concentrations when used in models that operate with EMATs exceeding the shortest exposure duration that characterizes the intermittent exposure. Alternative time-averaging approaches recommended for use in lead risk assessment more reliably predict short-term periodic (e.g., seasonal) elevations in blood lead concentration that might result from intermittent exposures. In general, risk estimates will be improved by simulation on shorter time scales that more closely approximate the actual temporal dynamics of the exposure.     

'But she didn't say no': an exploration of sibling sexual abuse

Sibling sexual abuse often causes polarities of view in professional and client groups alike. These views range from seeing it as benign to damaging. For professionals new to the field this paper gives an overview of the discussion that sibling sexual abuse is as traumatic as parental sexual abuse, and has lasting impact on its victims. Recognising the particular dynamics of sibling sexual abuse and effect on victims raises the challenge of case management in families where it occurs. This paper will explore this challenge within the New South Wales context.     

Nonparametric Bayesian analysis for multi-site hidden Markov model

The hidden Markov model (HMM) provides an attractive framework for modeling long-term persistence in a variety of applications including pattern recognition. Unlike typical mixture models, hidden Markov states can represent the heterogeneity in data and it can be extended to a multivariate case using a hierarchical Bayesian approach. This article provides a nonparametric Bayesian modeling approach to the multi-site HMM by considering stick-breaking priors for each row of an infinite state transition matrix. This extension has many advantages over a parametric HMM. For example, it can provide more flexible information for identifying the structure of the HMM than parametric HMM analysis, such as the number of states in HMM. We exploit a simulation example and a real dataset to evaluate the proposed approach.     

Face Preferences for Infant‐ and Adult‐Directed Speakers in Infants of Depressed and Nondepressed Mothers: Association with Infant Cognitive Development

Face preferences for speakers of infant‐directed and adult‐directed speech (IDS and ADS) were investigated in 4‐ to 13.5‐month‐old infants of depressed and nondepressed mothers. Following 1 min of exposure to an ID or AD speaker (order counterbalanced), infants had an immediate paired‐comparison test with a still, silent image of the familiarized versus a novel face. In the test phase, ID face preference ratios were significantly lower in infants of depressed than nondepressed mothers. Infants' ID face preference ratios, but not AD face preference ratios, correlated with their percentile scores on the cognitive (Cog) scale of the Bayley Scales of Infant & Toddler Development (3rd Edition; BSID‐III), assessed concurrently. Regression analyses revealed that infant ID face preferences significantly predicted infant Cog percentiles even after demographic risk factors and maternal depression had been controlled. Infants may use IDS to select social partners who are likely to support and facilitate cognitive development.     

A New Model for Multivariate Markov Chains

We propose a new model for multivariate Markov chains of order one or higher on the basis of the mixture transition distribution (MTD) model. We call it the MTD‐Probit. The proposed model presents two attractive features: it is completely free of constraints, thereby facilitating the estimation procedure, and it is more precise at estimating the transition probabilities of a multivariate or higher‐order Markov chain than the standard MTD model.     

Nano Risk Analysis: Advancing the Science for Nanomaterials Risk Management

Scientists, activists, industry, and governments have raised concerns about health and environmental risks of nanoscale materials. The Society for Risk Analysis convened experts in September 2008 in Washington, DC to deliberate on issues relating to the unique attributes of nanoscale materials that raise novel concerns about health risks. This article reports on the overall themes and findings of the workshop, uncovering the underlying issues for each of these topics that become recurring themes. The attributes of nanoscale particles and other nanomaterials that present novel issues for risk analysis are evaluated in a risk analysis framework, identifying challenges and opportunities for risk analysts and others seeking to assess and manage the risks from emerging nanoscale materials and nanotechnologies. Workshop deliberations and recommendations for advancing the risk analysis and management of nanotechnologies are presented.     

Regulation as Country‐Specific (Dis‐)Advantage: Smoking Bans and the Location of Foreign Direct Investment in the Tobacco Industry

This paper seeks to examine the relationship between smoking bans and the propensity of tobacco firms to engage in foreign direct investment (FDI). Using international business theory based on the firm‐specific advantage/country‐specific advantage (FSA/CSA) matrix, the authors show that, contrary to what one may expect, smoking bans at home are an important institutional intervention, reducing the propensity for firms to engage in FDI, even to countries without a ban themselves.