Knowledge, attitudes and practices regarding respirable silica exposure and personal protective equipment use among brick kiln workers in Nepal.

OBJECTIVES: Brick kiln workers in Nepal are a neglected population who are exposed to high respirable silica concentrations, and few use interventions to reduce exposure. We aimed to characterise the prevalence of respiratory personal protective equipment (PPE) use, understand knowledge and attitudes towards kiln dust and respiratory PPE and identify factors associated with respiratory PPE use. METHODS: We conducted a cross-sectional study in Bhaktapur, Nepal. We used simple random selection to identify 10 out of 64 total kilns and stratified random sampling of 30 households to enrol workers aged ≥14 years within selected kilns. Field workers surveyed participants using structured questionnaires. Our primary outcome was to characterise the prevalence of current respiratory PPE use and secondary outcomes were summaries of knowledge, attitudes and practice of PPE use. RESULTS: We surveyed 83 workers (mean age 30.8 years, 77.1% male). Of these, 28.9% reported current respiratory PPE use at work, 3.6% heard of silicosis prior to the survey and 24.1% correctly identified the best respiratory PPE (N95, compared with surgical masks and barrier face coverings) for reducing dust exposure. Respiratory PPE users had higher income (mean monthly household income US$206 vs US$145; p=0.04) and education levels (25% vs 5.1% completed more than primary school; p=0.02) compared with non-users. CONCLUSIONS: Respiratory PPE use was low. Workers had poor knowledge of kiln dust health effects and proper respiratory PPE. We highlight important barriers to PPE use, particularly knowledge gaps, which can guide future investigations to reduce the silicosis burden among brick kiln workers.

Brick kiln pollution and its impact on health: A systematic review and meta-analysis.

Brick kiln emissions adversely affect air pollution and the health of workers and individuals living near the kilns; however, evidence of their impacts remains limited. We conducted a systematic review of brick kiln pollution (emissions, source contributions and personal exposures) and its effects on health. We extracted articles from electronic databases and through manual citation searching. We estimated pooled, sample-size-weighted means and standard deviations for personal exposures by job type; computed mean emission factors and pollutant concentrations by brick kiln design; and meta-analyzed differences in means or proportions for health outcomes between brick kiln workers and controls or for participants living near or far away from kilns. We identified 104 studies; 74 were conducted in South Asia. The most evaluated pollutants were particulate matter (PM; n = 48), sulfur dioxide (SO2; n = 24) and carbon monoxide (CO; n = 22), and the most evaluated health outcomes were respiratory health (n = 34) and musculoskeletal disorders (n = 9). PM and CO emissions were higher among traditional than improved brick kilns. Mean respirable silica exposures were only measured in 4 (4%) studies and were as high as 620 µg/m3, exceeding the NIOSH recommended exposure limit by a factor of over 12. Brick kiln workers had consistently worse lung function, more respiratory symptoms, more musculoskeletal complaints, and more inflammation when compared to unexposed participants across studies; however, most studies had a small sample size and did not fully describe methods used for sampling or data collection. On average, brick kiln workers had worse health outcomes when compared to unexposed controls but study quality supporting the evidence was low. Few studies reported silica concentrations or personal exposures, but the few that did suggest that exposures are high. Further research is needed to better understand the relationship between brick kiln pollution and health among workers, and to evaluate exposure mitigation strategies.

Bayesian hierarchical modeling and inference for mechanistic systems in industrial hygiene.

A series of experiments in stationary and moving passenger rail cars were conducted to measure removal rates of particles in the size ranges of SARS-CoV-2 viral aerosols and the air changes per hour provided by existing and modified air handling systems. Such methods for exposure assessments are customarily based on mechanistic models derived from physical laws of particle movement that are deterministic and do not account for measurement errors inherent in data collection. The resulting analysis compromises on reliably learning about mechanistic factors such as ventilation rates, aerosol generation rates, and filtration efficiencies from field measurements. This manuscript develops a Bayesian state-space modeling framework that synthesizes information from the mechanistic system as well as the field data. We derive a stochastic model from finite difference approximations of differential equations explaining particle concentrations. Our inferential framework trains the mechanistic system using the field measurements from the chamber experiments and delivers reliable estimates of the underlying physical process with fully model-based uncertainty quantification. Our application falls within the realm of the Bayesian "melding" of mechanistic and statistical models and is of significant relevance to environmental hygienists and public health researchers working on assessing the performance of aerosol removal rates for rail car fleets.

Application and demonstration of meso-activity exposure factors to advance estimates of incidental soil ingestion among agricultural workers.

BACKGROUND: Soil is an understudied and underregulated pathway of chemical exposure, particularly for agricultural workers who cultivate food in soils. Little is known about how agricultural workers spend their time and how they may contact soil while growing food. Exposure factors are behavioral and environmental variables used in exposure estimation. OBJECTIVES: Our study aimed to derive exposure factors describing how growers engage in different tasks and use those factors to advance the use of time-activity data to estimate soil ingestion exposures among agricultural workers. METHODS: We administered a meso-activity-based, season-specific soil contact activity questionnaire to 38 fruit and vegetable growers. We asked growers to estimate the frequency and duration of six meso-activities and describe how they completed them. We used questionnaire data to derive exposure factors and estimate empirical and simulated exposures to a hypothetical contaminant in soil via incidental ingestion using daily, hourly, and hourly-task-specific ingestion rates. RESULTS: We generated exposure factors characterizing the frequency and duration of six meso-activities by season, and self-reported soil contact, glove use, and handwashing practices by meso-activity and season. Seasonal average daily doses (ADDs) were similar across all three forms of ingestion rates. No consistent patterns regarding task-specific contributions to seasonal or annual ADDs were observed.