Dust Exposure, Fractional Exhaled Nitric Oxide and Respiratory Symptoms among Volcanic Rock Miners in Kilimanjaro, Tanzania

Physiology and Biomarkers for Surveillance of Occupational Lung Disease

Respiratory surveillance is the process whereby a group of exposed workers are regularly tested (or screened) for those lung diseases which occur as a result of a specific work exposure. Surveillance is performed by assessing various measures of biological or pathological processes (or biomarkers) for change over time. These traditionally include questionnaires, lung physiological assessments (especially spirometry), and imaging. Early detection of pathological processes or disease can enable removal of a worker from a potentially harmful exposure at an early stage. In this article, we summarize the physiological biomarkers currently used for respiratory surveillance, while commenting on differences in interpretative strategies between different professional groups. We also briefly review the many new techniques which are currently being assessed for respiratory surveillance in prospective research studies and which are likely to significantly broaden and enhance this field in the near future.

Association between exposure to a mixture of metals, parabens, and phthalates and fractional exhaled nitric oxide: A population-based study in US adults

The effects of environmental endocrine-disrupting chemicals (EDCs) (e.g., phthalates) on fractional exhaled nitric oxide (FeNO) in children have received much attention. However, few studies evaluated this relationship in adults, and the previous studies have considered only a unitary exposure or a set of similar exposures instead of mixed exposures, which contain complicated interactions. We aimed to evaluate simultaneously the relationship between three types of EDCs (six phthalate metabolites and two parabens in urine, two heavy metals in blood) and FeNO (as a continuous variable) in adults. Data of adults aged ≥20 years from the National Health and Nutrition Examination Survey (NHANES, 2007-2012) were collected and analyzed. The generalized linear (GLM) regression model was used to explore the association of chemicals with FeNO. The combined effect of 10 chemicals on the overall association with FeNO was evaluated by the weighted quantile sum regression (WQS) model. In addition, The Bayesian kernel machine regression (BKMR) model was explored to investigate the interaction and joint effects of multiple chemicals with FeNO. Of the 3296 study participants ultimately included, among the GLMs, we found that mercury (Hg) (β = 0.84, 95%CI:0.32-1.36, FDR = 0.01) and methyl paraben (MPB) (β = 0.47, 95%CI:0.16-0.78, FDR = 0.015) were positively correlated with FeNO. In the WQS model, the combined effect of chemicals almost had a significantly positive association with FeNO and the top three contributors to the WQS index were Hg (40.2%), MECPP (22.1%), and MPB (19.3%). BKMR analysis showed that there may be interactions between MPB and Hg, Mono (carboxyoctyl) phthalate (MCOP) and Hg and the overall effect of the mixture showed a positive correlation with FeNO. In conclusion, our study strengthens the credibility of the view that EDCs can affect respiratory health. In the future, we should be particularly careful with products containing Hg, MECPP, MPB, and MEHP for the prevention of respiratory diseases.