Using In Vitro High‐Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high‐throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline‐based meta‐regression can be used to integrate data across multiple assay replicates to generate a concentration–response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk‐specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta‐regression, may allow risk assessors to identify points of departure and risk‐specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods.     

Housing hardship and energy insecurity among native-born and immigrant low-income families with children in the United States

The costs for rent and utilities account for the largest share of living expenses, yet these two critical dimensions of material hardship have seldom been examined concurrently in population-based studies. This paper employs multivariate statistical analysis using American Community Survey data to demonstrate the relative risk ratio of low-income renter-occupied households with children experiencing ‘rent burden', ‘energy insecurity', or a ‘double burden’ as opposed to no burden. Findings suggest that low-income households are more likely to experience these economic hardships in general but that specific groups are disproportionately burdened in different ways. For instance, whereas immigrants are more likely to experience rental burden, they are less likely to experience energy insecurity and are also spared from the double burden. In contrast, native-born African Americans are more likely than all other groups to experience the double burden. These results may be driven by the housing stock available to certain groups due to racial residential segregation, decisions regarding the quality of housing low-income householders are able to afford, as well as home-country values, such as modest living and energy conservation practices, among immigrant families. This paper also points to important policy gaps in safety net benefits related to housing and energy targeting low-income households.     

Identifying Latent Structures in Panel Data

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized techniques. We consider both linear and nonlinear models where the regression coefficients are heterogeneous across groups but homogeneous within a group and the group membership is unknown. Two approaches are considered—penalized profile likelihood (PPL) estimation for the general nonlinear models without endogenous regressors, and penalized GMM (PGMM) estimation for linear models with endogeneity. In both cases, we develop a new variant of Lasso called classifier‐Lasso (C‐Lasso) that serves to shrink individual coefficients to the unknown group‐specific coefficients. C‐Lasso achieves simultaneous classification and consistent estimation in a single step and the classification exhibits the desirable property of uniform consistency. For PPL estimation, C‐Lasso also achieves the oracle property so that group‐specific parameter estimators are asymptotically equivalent to infeasible estimators that use individual group identity information. For PGMM estimation, the oracle property of C‐Lasso is preserved in some special cases. Simulations demonstrate good finite‐sample performance of the approach in both classification and estimation. Empirical applications to both linear and nonlinear models are presented.     

Effects of a single-lesson tobacco prevention curriculum on knowledge, skill identification and smoking intention

One in five students report experimenting with tobacco before the age of 13 and most prevention efforts take place in the school setting. This study measures the effect of a single-lesson tobacco prevention curriculum, conducted by a health education center, focusing on knowledge of tobacco, ability to identify refusal techniques, and intent not to smoke. Data were collected, via electronic keypads, from students visiting a non-school, health education center in Michigan (n = 704 intervention and 85 comparison). Contingency table Chi-squared tests and t-tests demonstrated that a single lesson can improve general knowledge and ability to identify appropriate refusal techniques. Improvement in intent not to smoke was not significant because both groups had very high intent prior to implementation. Similar to results from other programs, multivariate logistic regression of gender, general knowledge, and skill identification revealed that only the skill variable was associated with intent not to smoke at pretest. Recommendations are given for further research and for designing more effective curricula or programs.     

On the conditions of authority in academic publics

The discourse of some of the most powerful public figures in today’s world is often incoherent and nonsensical. Incoherent yet authoritative discourse shows that authority does not rest in language but results from non‐linguistic and pre‐textual conditions. The non‐linguistic and pre‐textual conditions are exemplified in an Australian case‐study of a media debate between the Immigration Minister and a refugee, drawing on research by Smith‐Khan (2019a, 2019b). Two such conditions are then examined with reference to academic publics. First, I ask which languages do or do not carry authority, before moving on to speaker identity as a condition of authority. The close association between English and academic excellence has resulted in diminishing the authority of academic publications in languages other than English. The same is true of publications by women and people of colour. I close by reflecting on referencing practices as forms of extending authoritativeness to voices in excluded languages and from excluded scholars in academic publics.     

Best practices for online Canadian prenatal health promotion: A public health approach

Background

Prenatal health promotion provides information regarding pregnancy risks, protective behaviours and clinical and community resources. Typically, women obtain prenatal health information from health care providers, prenatal classes, peers/family, media and increasingly, Internet sites and mobile apps. Barriers to prenatal health promotion and related services include language, rural/remote location, citizenship and disability. Online public health platforms represent the capacity to reach underserved women and can be customised to address the needs of a heterogeneous population of pregnant women.

STUDENTS WHO CHOOSE AND THE SCHOOLS THEY LEAVE: Examining Participation in Intradistrict Transfers

Data from one urban school district is analyzed to examine equity‐based arguments about school choice as they pertain to intradistrict transfer policies. We specifically examine which factors influence the propensity for parents to participate in choice, and how choice schools differ from the schools that students are zoned to attend. We find that advantaged and disadvantaged parents make similar choices in that they are both likely to choose more affluent schools with better academic records than the schools they are zoned to attend. However, these choices operate in different spheres, as advantaged parents choose the most affluent schools with the best academic records, and disadvantaged parents choose away from the least affluent schools with the worst academic records to schools that are slightly better.     

The unique effects of environmental strategies in health promotion campaigns: a review

Various strategies are used as tools in health promotion campaigns to increase health-related outcomes among target populations. Evaluations of these campaigns examine effects on changing people's knowledge, attitudes, and/or behaviors. Most evaluations examine the combined impact of multiple strategies. Less is known about the unique effects of particular strategies. To address this gap, we used highly systematic methods to identify and review scientifically rigorous evaluations of 18 campaigns that examined the unique effects of three sets of intervention strategies (entertainment education, law enforcement, and mass media) on changes in knowledge, attitudes, and practice with regard to various health behaviors. Results showed differences in evaluation processes based on the type of strategy used to promote campaign messages. For instance, evaluations of mass-media based campaigns were more likely to examine changes in knowledge, relative to evaluations of campaigns that used law enforcement strategies. In addition, campaign effects varied by particular strategies. Mass media-based campaigns were more likely to affect knowledge, relative to behaviors. Law enforcement and entertainment education-based campaigns showed positive effects on behaviors. The implications for planning and evaluating health promotion campaigns are described.