Using a smartphone application to capture daily work activities: a longitudinal pilot study in a farming population.

Objectives: Smartphones are increasingly used to collect real-time information on time-varying exposures. We developed and deployed an application (app) to evaluate the feasibility of using smartphones to collect real-time information on intermittent agricultural activities and to characterize agricultural task variability in a longitudinal study of farmers.

Methods: We recruited 19 male farmers, aged 50-60 years, to report their farming activities on 24 randomly selected days over 6 months using the Life in a Day app.

An algorithm for quantitatively estimating occupational endotoxin exposure in the Biomarkers of Exposure and Effect in Agriculture (BEEA) study: I. Development of task-specific exposure levels from published data.

Background/objective: Farmers conduct numerous tasks with potential for endotoxin exposure. As a first step to characterize endotoxin exposure for farmers in the Biomarkers of Exposure and Effect in Agriculture (BEEA) Study, we used published data to estimate task-specific endotoxin concentrations.

Methods: We extracted published data on task-specific, personal, inhalable endotoxin concentrations for agricultural tasks queried in the study questionnaire.

An algorithm for quantitatively estimating occupational endotoxin exposure in the biomarkers of exposure and effect in agriculture study: II. Application to the study population.

Background: We developed an algorithm to quantitatively estimate endotoxin exposure for farmers in the Biomarkers of Exposure and Effect in Agriculture (BEEA) Study.

Methods: The algorithm combined task intensity estimates derived from published data with questionnaire responses on activity duration to estimate task-specific cumulative endotoxin exposures for 13 tasks during four time windows, ranging from "past 12 months" to "yesterday/today." We applied the algorithm to 1681 participants in Iowa and North Carolina.

A Task-Specific Algorithm to Estimate Occupational (1→3)-β-D-glucan Exposure for Farmers in the Biomarkers of Exposure and Effect in Agriculture Study.

Objectives: Farmers may be exposed to glucans (a cell component of molds) through a variety of tasks. The magnitude of exposure depends on each farmer's activities and their duration. We developed a task-specific algorithm to estimate glucan exposure that combines measurements of (1→3)-β-D-glucan with questionnaire responses from farmers in the Biomarkers of Exposure and Effect in Agriculture (BEEA) study.

Application of Pattern Mining Methods to Assess Exposures to Multiple Airborne Chemical Agents in Two Large Occupational Exposure Databases from France.

Surveys of the French working population estimate that approximately 15% of all workers may be exposed to at least three different chemical agents, but the most prevalent coexposure situations and their associated health risks remain relatively understudied. To characterize occupational coexposure situations in France, we extracted personal measurement data from COLCHIC and SCOLA, two large administrative occupation exposure databases. We selected 118 chemical agents that had ≥100 measurements with detected concentrations over the period 2010-2019, including 31 carcinogens (IARC groups 1, 2A, and 2B).

Exposure Determinants in the French Database COLCHIC (1987-2019): Statistical Modeling across 77 Chemicals.

Objectives: The COLCHIC database contains workplace exposure results of chemical samples collected by the French prevention network since 1987. We aimed to investigate potential associations between exposure levels and ancillary variables in COLCHIC across a broad range of chemical agents in order to provide insight into how to best interpret and exploit the information in this national database.

Methods: We selected personal and area measurements in COLCHIC and collected outside respiratory personal protective equipment (PPE), restricted to chemical agents that had at least 1000 samples available.

Diesel Exhaust Exposure during Farming Activities: Statistical Modeling of Continuous Black Carbon Concentrations.

Objectives: Daily driving of diesel-powered tractors has been linked to increased lung cancer risk in farmers, yet few studies have quantified exposure levels to diesel exhaust during tractor driving or during other farm activities. We expanded an earlier task-based descriptive investigation of factors associated with real-time exposure levels to black carbon (BC, a surrogate of diesel exhaust) in Iowa farmers by increasing the sample size, collecting repeated measurements, and applying statistical models adapted to continuous measurements.

Methods: The expanded study added 43 days of sampling, for a total of 63 sample days conducted in 2015 and 2016 on 31 Iowa farmers.

Bayesian Hierarchical Modelling of Individual Expert Assessments in the Development of a General-Population Job-Exposure Matrix.

The CANJEM job-exposure matrix compiles expert evaluations of 31 673 jobs from four population-based case-control studies conducted in Montreal. For each job, experts had derived indices of intensity, frequency, and probability of exposure to 258 agents. CANJEM summarizes the exposures assigned to jobs into cells defined by occupation/industry, agent, and period.

Validity of retrospective occupational exposure estimates of lead and manganese in a case-control study.

Objectives: The validity of surrogate measures of retrospective occupational exposure in population-based epidemiological studies has rarely been evaluated. Using toenail samples as bioindicators of exposure, we assessed whether work tasks and expert assessments of occupational metal exposure obtained from personal interviews were associated with lead and manganese concentrations.

Methods: We selected 609 controls from a case-control study of bladder cancer in New England who had held a job for ≥1 year 8-24 months prior to toenail collection.

Using Decision Rules to Assess Occupational Exposure in Population-Based Studies.

Purpose Of Review: Population-based studies increasingly link task-based occupational questionnaire responses collected from subjects to exposure estimates via transparent, programmable decision rules. We reviewed recent applications and methodological developments of rule-based approaches.

Recent Findings: Agent-specific decision rules require interviews incorporating work-task-based questions.

Characterizing Short-Term Jobs in a Population-Based Study.

Background: Work histories generally cover all jobs held for ≥1 year. However, it may be time and cost prohibitive to conduct a detailed exposure assessment for each such job. While disregarding short-term jobs can reduce the assessment burden, this can be problematic if those jobs contribute important exposure information towards understanding disease aetiology.

A hybrid expert approach for retrospective assessment of occupational exposures in a population-based case-control study of cancer.

Background: While the expert-based occupational exposure assessment approach has been considered the reference method for retrospective population-based studies, its implementation in large study samples has become prohibitive. To facilitate its application and improve upon it we developed, in the context of a Montreal population-based study of prostate cancer (PROtEuS), a hybrid approach combining job-exposure profiles (JEPs) summarizing expert evaluations from previous studies and expert review. We aim to describe the hybrid expert method and its impacts on the exposures assigned in PROtEuS compared to those from a previous study coded using the traditional expert method.

Development of Quantitative Estimates of Wood Dust Exposure in a Canadian General Population Job-Exposure Matrix Based on Past Expert Assessments.

Objectives: The CANJEM general population job-exposure matrix summarizes expert evaluations of 31 673 jobs from four population-based case-control studies of cancer conducted in Montreal, Canada. Intensity in each CANJEM cell is represented as relative distributions of the ordinal (low, medium, high) ratings of jobs assigned by the experts. We aimed to apply quantitative concentrations to CANJEM cells using Canadian historical measurements from the Canadian Workplace Exposure Database (CWED), taking exposure to wood dust as an example.

Occupational exposure to benzene, toluene, xylene and styrene and risk of prostate cancer in a population-based study.

Objectives: While several monocyclic aromatic hydrocarbons are classified as definite or possible carcinogens to humans, little data exist on their role in prostate cancer (PCa). We examined occupational exposure to benzene, toluene, xylene (BTX) and styrene and PCa risk in a population-based case-control study in Montreal, Canada.

Methods: Cases aged ≤75 years diagnosed with PCa in 2005-2009 (n=1920) and population controls frequency-matched on age (n=1989) provided detailed work histories.

Development of and Selected Performance Characteristics of CANJEM, a General Population Job-Exposure Matrix Based on Past Expert Assessments of Exposure.

Objectives: We developed a job-exposure matrix called CANJEM using data generated in population-based case-control studies of cancer. This article describes some of the decisions in developing CANJEM, and some of its performance characteristics.

Methods: CANJEM is built from exposure information from 31673 jobs held by study subjects included in our past case-control studies.

Occupation, industry, and the risk of prostate cancer: a case-control study in Montréal, Canada.

Background: Age, family history and ancestry are the only recognized risk factors for prostate cancer (PCa) but a role for environmental factors is suspected. Due to the lack of knowledge on the etiological factors for PCa, studies that are both hypothesis-generating and confirmatory are still needed. This study explores relationships between employment, by occupation and industry, and PCa risk.

Historical and emerging workplaces affected by silica exposure since the 1930 Johannesburg conference on Silicosis, with special reference to construction.

Introduction: At the time of the 1930 International Labour Office Conference on silicosis in Johannesburg, mining was the main sector affected by silicosis; however, other industries would later emerge as areas of concern.

Methods: A search of the occupational hygiene and epidemiological literature was conducted to retrieve historical and current documents pertaining to silica exposure and associated hazards.

Results: The potential risk of silicosis in construction became evident starting in the 1960s, and the body of literature including case reports, sampling surveys, and medical surveillance continues to grow to this day.

Creatinine and specific gravity normalization in biological monitoring of occupational exposures.

Reference values for the biological monitoring of occupational exposures are generally normalized on the basis of creatinine (CR) concentration or specific gravity (SG) to account for fluctuations in urine dilution. For instance, the American Conference of Governmental Industrial Hygienists (ACGIH(®)) uses a reference value of 1g/L for CR. The comparison of urinary concentrations of biomarkers between studies requires the adjustment of results based on a reference CR and/or SG value, although studies have suggested that age, sex, muscle mass, and time of the day can exert non-negligible influences on CR excretion, while SG appears to be less affected.

Occupational exposure to silica in construction workers: a literature-based exposure database.

We created an exposure database of respirable crystalline silica levels in the construction industry from the literature. We extracted silica and dust exposure levels in publications reporting silica exposure levels or quantitative evaluations of control effectiveness published in or after 1990. The database contains 6118 records (2858 of respirable crystalline silica) extracted from 115 sources, summarizing 11,845 measurements.

Silica exposure during construction activities: statistical modeling of task-based measurements from the literature.

Many construction activities can put workers at risk of breathing silica containing dusts, and there is an important body of literature documenting exposure levels using a task-based strategy. In this study, statistical modeling was used to analyze a data set containing 1466 task-based, personal respirable crystalline silica (RCS) measurements gathered from 46 sources to estimate exposure levels during construction tasks and the effects of determinants of exposure. Monte-Carlo simulation was used to recreate individual exposures from summary parameters, and the statistical modeling involved multimodel inference with Tobit models containing combinations of the following exposure variables: sampling year, sampling duration, construction sector, project type, workspace, ventilation, and controls.

Statistical modeling of crystalline silica exposure by trade in the construction industry using a database compiled from the literature.

A quantitative determinants-of-exposure analysis of respirable crystalline silica (RCS) levels in the construction industry was performed using a database compiled from an extensive literature review. Statistical models were developed to predict work-shift exposure levels by trade. Monte Carlo simulation was used to recreate exposures derived from summarized measurements which were combined with single measurements for analysis.