Development of a Web-Based Tool for Risk Assessment and Exposure Control Planning of Silica-Producing Tasks in the Construction Sector.

We describe the development and implementation of a novel, on-line risk assessment tool for respirable crystalline silica (RCS) exposure for use in the construction sector. It was motivated by the introduction of new OHS regulation in British Columbia that allowed for the substitution of exposure measurement data with "objective air monitoring data" collected at "equivalent work operations." This allowance encouraged the introduction of quantitative risk assessment in a notoriously challenging work environment but it was concluded that without assistance, the typical construction employer would struggle to identify, extract, and interpret validate objective data. The tool described here was based on a continually-updatable RCS exposure database, and a predictive regression model based on the database to generate exposure risk estimates. The model was embedded in an adaptive web-based application that can be run on common platforms. The design followed standard web conventions and features so that no specialized training is required for its use. It was designed to be usable by end-users with varying expertise, including non-OHS experts. Users describe the RCS-dust generating task they will perform, and associated control measures. The tool estimates both uncontrolled and controlled task-based exposure concentrations. Using additional information entered by the user, the on-line tool generates an "exposure control plan" or ECP, a legally regulated document for those undertaking work potentially exposing workers to RCS particulate. The development of the tool was a community-based, tri-partite effort of the local OHS regulator, construction employers, and exposure scientists. In addition to being a practical risk assessment tool, the designers wanted it to function as an educational tool, and that it should explore novel methods for exposure data collection and use. The strengths of this approach include the publicly shared updateable database that encourages continuous improvement and illustrates best practices; and the timely and cost effective collection and sharing of exposure data in a value-added manner. It is however limited to a single task per ECP, and only considers exposure to task operators, and not adjacent workers. Currently in BC, users generate up to 3,900 ECP's per year with the tool.

A scoping review to identify strategies that work to prevent four important occupational diseases.

BACKGROUND: Despite being largely preventable, many occupational diseases continue to be highly prevalent and extremely costly. Effective strategies are required to reduce their human, economic, and social impacts. METHODS: To better understand which approaches are most likely to lead to progress in preventing noise-related hearing loss, occupational contact dermatitis, occupational cancers, and occupational asthma, we undertook a scoping review and consulted with a number of key informants. RESULTS: We examined a total of 404 articles and found that various types of interventions are reported to contribute to occupational disease prevention but each has its limitations and each is often insufficient on its own. Our principal findings included: legislation and regulations can be an effective means of primary prevention, but their impact depends on both the nature of the regulations and the degree of enforcement; measures across the hierarchy of controls can reduce the risk of some of these diseases and reduce exposures; monitoring, surveillance, and screening are effective prevention tools and for evaluating the impact of legislative/policy change; the effect of education and training is context-dependent and influenced by the manner of delivery; and, multifaceted interventions are often more effective than ones consisting of a single activity. CONCLUSIONS: This scoping review identifies occupational disease prevention strategies worthy of further exploration by decisionmakers and stakeholders and of future systematic evaluation by researchers. It also identified important gaps, including a lack of studies of precarious workers and the need for more studies that rigorously evaluate the effectiveness of interventions.

Burden of lung cancer attributable to occupational diesel engine exhaust exposure in Canada.

OBJECTIVE: To estimate the population attributable fraction (PAF) and number of incident and fatal lung cancers in Canada from occupational exposure to diesel engine exhaust (DEE). METHODS: DEE exposure prevalence and level estimates were used with Canadian Census and Labour Force Survey data to model the exposed population across the risk exposure period (REP, 1961-2001). Relative risks of lung cancer were calculated based on a meta-regression selected from the literature. PAFs were calculated using Levin's equation and applied to the 2011 lung cancer statistics obtained from the Canadian Cancer Registry. RESULTS: We estimated that 2.4% (95% CI 1.6% to 6.6%) of lung cancers in Canada are attributable to occupational DEE exposure, corresponding to approximately 560 (95% CI 380 to 1570) incident and 460 (95% CI 310 to 1270) fatal lung cancers in 2011. Overall, 1.6 million individuals alive in 2011 were occupationally exposed to DEE during the REP, 97% of whom were male. Occupations with the highest burden were underground miners, truck drivers and mechanics. Half of the attributable lung cancers occurred among workers with low exposure. CONCLUSIONS: This is the first study to quantify the burden of lung cancer attributable to occupational DEE exposure in Canada. Our results underscore a large potential for prevention, and a large public health impact from occupational exposure to low levels of DEE.

Residential greenness and birth outcomes: evaluating the influence of spatially correlated built-environment factors.

BACKGROUND: Half the world's population lives in urban areas. It is therefore important to identify characteristics of the built environment that are beneficial to human health. Urban greenness has been associated with improvements in a diverse range of health conditions, including birth outcomes; however, few studies have attempted to distinguish potential effects of greenness from those of other spatially correlated exposures related to the built environment. OBJECTIVES: We aimed to investigate associations between residential greenness and birth outcomes and evaluate the influence of spatially correlated built environment factors on these associations. METHODS: We examined associations between residential greenness [measured using satellite-derived Normalized Difference Vegetation Index (NDVI) within 100 m of study participants' homes] and birth outcomes in a cohort of 64,705 singleton births (from 1999-2002) in Vancouver, British Columbia, Canada. We also evaluated associations after adjusting for spatially correlated built environmental factors that may influence birth outcomes, including exposure to air pollution and noise, neighborhood walkability, and distance to the nearest park. RESULTS: An interquartile increase in greenness (0.1 in residential NDVI) was associated with higher term birth weight (20.6 g; 95% CI: 16.5, 24.7) and decreases in the likelihood of small for gestational age, very preterm (< 30 weeks), and moderately preterm (30-36 weeks) birth. Associations were robust to adjustment for air pollution and noise exposures, neighborhood walkability, and park proximity. CONCLUSIONS: Increased residential greenness was associated with beneficial birth outcomes in this population-based cohort. These associations did not change after adjusting for other spatially correlated built environment factors, suggesting that alternative pathways (e.g., psychosocial and psychological mechanisms) may underlie associations between residential greenness and birth outcomes.

Mixed models and empirical bayes estimation for retrospective exposure assessment of dust exposures in Canadian sawmills.

OBJECTIVES: Data on job histories is commonly available from study subjects and worksites, therefore jobs are often used for assigning exposures in historical epidemiological studies. Exposure estimates are often derived by offering jobs as fixed effects in statistical models. An alternative approach would be to offer job as a random effect to obtain empirical Bayes estimates of exposure. This approach is more efficient since it weights exposure estimates according to the within-job and between-job variability and the number of measurements for each job. We assess three models for predicting historical dust exposures of sawmill workers. METHODS: Models were developed using 407 inhalable dust measurements collected from 58 jobs in four sawmills. The first model incorporated all variables as fixed effects; the second added a random term to account for correlation within workers; and the third offered random terms for worker, job and mill (hierarchical model). Empirical Bayes estimates were used to calculate job-specific exposures from the hierarchical model. RESULTS: The fixed effects and random worker mixed models performed nearly identically because there was low within-worker correlation (r = 0.26). The Bayesian exposure predictions from the hierarchical model were slightly more correlated with the observed mill-job arithmetic means than those from the models where jobs were fixed effects (0.74 versus 0.70). CONCLUSIONS: While we observed no large differences in exposure estimates by treating job as a fixed or random effect, treating job as a random effect allowed for job-specific coefficients to be estimated for every job while borrowing strength in the presence of sparse data by assuming that the job means are normally distributed around the group mean. In addition, empirical Bayes job estimates can be used for a posteriori job grouping. The use of this method for retrospective exposure assessment should continue to be examined.