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In the United Kingdom the Health and Safety Executive for some years has stored chemical exposure data in their National Exposure Database. However, it has been difficult to persuade industry and other organizations to contribute to this resource. The aim of this project was to devise a cost-effective method of obtaining occupational exposure data on chemicals from U.K. industry and other sources. Five strategies were used to identify data for three different substances: toluene, acrylonitrile, and ethylene oxide. In total, 810 organizations were contacted and over 45 percent responded. However, only 40 had relevant exposure data. Almost equal numbers of acceptable measurements were identified for toluene and acrylonitrile (2,770 and 2,000 respectively) with lesser ethylene oxide data (800). These measurements were drawn from a wide range of industries and are probably representative of measurements made by U.K. industry, although most of the data were from companies employing more than 100 people. During the second phase of the project, more than 3,000 measurements and associated contextual information were collected (499 for toluene, 1,516 for acrylonitrile, and 17 for ethylene oxide, with a further 1,004 measurements for 1 of 27 substances collected simultaneously with one of the above). The costs of identifying and collecting exposure data ranged from ł7 to ł380 per valid measurement, depending on the source of the data. We suggest that, rather than trying to retrospectively collect data, it is likely to be more cost-effective to enlist a number of occupational hygiene consults and industrial organizations to prospectively provide anonymized exposure measurements for inclusion in the Health and Safety Executives National Exposure Database.

This study contributes to homicide research by parsing out the Hispanic Effect and applying an intersectional approach to examining U.S. homicide victimization trends by race, ethnicity, and gender, jointly. Drawing on mortality data, we document and describe total, firearm, and non-firearm homicide victimization rates from 1990 to 2016 for six subgroups: Black women, Black men, Hispanic women, Hispanic men, White women, and White men. The analysis of within- and between-group homicide trends reveals important subgroup-specific patterns that prior studies using aggregate or confounded data have masked. The findings have important research, theory, and policy implications and advocate for an intersectional approach to studying homicide.

Introduction Studies consistently demonstrate a link between subjective sleep disturbances and the continuum of suicidality, although this evidence primarily comes from retrospective, cross-sectional studies using limited items to assess sleep. Longitudinal assessment of well-defined and measured sleep/wake behaviors with high-risk individuals are needed to enhance the specificity of near-term suicide risk detection and render concrete targets for suicide prevention. Methods Participants (N=46) included ultra-high-risk adolescents (N=29 ages 12-18) and college students (N=17 ages 18-24). For up to 12 weeks, participants wore an actigraph to yield objective data on sleep/wake, and concurrently completed daily cellphone-based ratings of subjective sleep and suicidality. Generalized estimating equations were used to examine the association between sleep parameters (subjective and objective) and the odds of next-day suicidal outcomes (i.e., passive death wish [PDW], suicidal ideation, suicidal intent) controlling for age, gender, and depression severity. Results Significant quadratic relationships were observed between actigraphy-derived total sleep time (TST) and probability of next-day PDW (Z=3.7, p=0.0002), suicidal ideation (Z=2.1, p=0.04), and suicidal intent (Z=2.78, p=0.006), with increasing suicidality at low and high values of TST. Low sleep efficiency (<75%) was associated with increased odds of next-day PDW (OR=1.24, Z=2.07, p=0.038). Subjectively (sleep diary measures), low sleep quality (<50 on 100-point scale) was associated with increased odds of next-day suicidal ideation (OR=1.57, Z=3.42, p<0.001), and longer sleep onset latency (>20 minutes) with next-day suicidal intent (OR=3.00, Z=2.37, p=0.018). Conclusion Poor sleep health may signal increasing suicide risk, and are modifiable risk factors. We document a significant temporal association whereby objectively-derived short and long TST and low sleep efficiency, as well as subjective sleep quality and sleep onset latency, predicts next day’s suicidality. Further understanding of the temporal association between sleep and suicidality may hold promise to inform real-time monitoring and preventive strategies. Interventions targeting these factors may therefore help reduce suicidality in high-risk youth. Support American Foundation for Suicide Prevention; University of Pittsburgh Clinical and Translational Science Institute