Using Biomarkers to Inform Cumulative Risk Assessment

BACKGROUND: Biomarkers are considered the method of choice for determining exposure to environmental contaminants and relating such exposures to health outcomes. However, the association between many biomarkers and outcome is not direct because of variability in sensitivity and susceptibility in the individual. OBJECTIVES: We explore the relationship between environmental exposures and health outcomes as mitigated by differential susceptibility in individuals or populations and address the question “Can biomarkers enable us to understand and quantify better the population burden of disease and health effects attributable to environmental exposures?” METHODS: We use a case–study approach to develop the thesis that biomarkers offer a pathway to disaggregation of health effects into specific, if multiple, risk factors. We offer the point of view that a series or array of biomarkers, including biomarkers of exposure, biomarkers of susceptibility, and biomarkers of effect, used in concert offer the best means by which to effect this disaggregation. We commence our discussion by developing the characteristics of an ideal biomarker, then give some examples of commonly used biomarkers to show the strengths and weaknesses of current usage. We follow this by more detailed case-study assessment outlining the state-of-the-science in specific cases. We complete our work with recommendations regarding the future use of biomarkers and areas for continued development. CONCLUSIONS: The case studies provide examples of when and how biomarkers can be used to infer the source and magnitude of exposure among a set of competing sources and pathways. The answer to this question is chemical specific and relates to how well the biomarker matches the characteristics of an “ideal” biomarker–in particular ease of collection and persistence. The use of biomarkers in combination provides a better opportunity to disaggregate both source and pathway contributions

The utility of screening for perinatal depression in the second trimester among Chinese: a three-wave prospective longitudinal study

This paper aims to study the pattern of perinatal depressive symptomatology and determine the predictive power of second trimester perinatal depressive symptoms for future perinatal periods. A population-based sample of 2,178 women completed the Edinburgh Postnatal Depression Scale (EPDS) in the second and third trimesters and at 6 weeks postpartum. Repeated measures ANOVAs were used to determine the EPDS scores across three stages. The predictive power of the second trimester EPDS score in identifying women with an elevated EPDS score in the third trimester and at 6 weeks postpartum were determined. The predictive power of the second trimester EPDS score was further assessed using stepwise logistic regression and receiver operator characteristic curves. EPDS scores differed significantly across three stages. The rates were 9.9%, 7.8%, and 8.7% for an EPDS score of >14 in the second and third trimesters and at 6 weeks postpartum, respectively. Using a cut-off of 14/15, the second trimester EPDS score accurately classified 89.6% of women in the third trimester and 87.2% of those at 6 weeks postpartum with or without perinatal depressive symptomatology. Women with a second trimester EPDS score >14 were 11.78 times more likely in the third trimester and 7.15 times more likely at 6 weeks postpartum to exhibit perinatal depressive symptomatology after adjustment of sociodemographic variables. The area under the curve for perinatal depressive symptomatology was 0.85 in the third trimester and 0.77 at 6 weeks postpartum. To identify women at high risk for postpartum depression, healthcare professionals could consider screening all pregnant women in the second trimester so that secondary preventive intervention may be implemented

The Impact of Religiosity on Audit Pricing

Prior literature has demonstrated that religiosity is associated with a reduced acceptance of unethical business practices and financial reporting irregularities. On this premise, we examine whether religiosity, conceptualized as the degree of adherence to religious norms in the geographical area where a firm’s headquarters is located, has an impact on audit firms’ pricing decisions in the US. We measure the intensity of religiosity by the number of adherents relative to the total population in a county and demonstrate that increased religious adherence operates as an institutionalized monitoring mechanism that decreases audit risk and audit costs, which is, in turn, reflected in reduced audit pricing. Additional tests suggest that the impact of religiosity on auditors’ pricing decisions is not differentiated by levels of auditor expertise but that audit fees are determined by an auditor’s relative location in a market sector and religious adherence. We conclude that religious adherence reduces the need for shareholders to bear the costs of monitoring agents, a finding which could be of importance for market participants and regulators