The COVID-19 pandemic has created substantial and dynamic disruptions in society, personal behavior, and potentially chronic sound exposures, which are associated with hearing loss, cardiovascular disease, and other health impacts. Leveraging preliminary data from our unique nationwide Apple Hearing Study, we explored changes in personal sound exposures resulting from COVID-19-related social distancing. Volunteer participants opted to share environmental sound data from their Apple Watch and headphone sound data from their iPhone. Participants for this analysis were chosen from four states which exhibited diverse responses to COVID-19. Equivalent continuous average sound exposures (in A-weighted decibels, dBA) were computed per person-day and normalized to 8 hour L_EX8h exposures. Daily mean L_EX8h exposures across two time periods, a baseline period (before the first known US COVID-19 death at the time of analysis) and an intervention period (starting with each state’s first COVID-related public health social distancing announcement and ending on April 22, 2020) were defined to assess changes in sound exposure. We modeled sound levels across 5,894 participants and 516,729 monitored days using a linear mixed-effects model with random effects for participant. The overall reduction in LEX8h between baseline and intervention was 2.6 ± 0.05 dBA (mean ± SE). There was a significant day-of-week effect during the baseline period, with the lowest exposures on Monday and the highest on Saturday. This effect was not noted during the intervention period. COVID-19 social distancing measures were associated with an approximately 3 dBA reduction in personal environmental sound exposures; this represents a substantial and meaningful reduction in this harmful exposure. Our analysis demonstrates the utility of everyday use devices in detecting behavior and exposure changes associated with the COVID-19 pandemic, and the usefulness of longitudinal, large-scale characterization of personal exposures and health impacts using wearable technology.

Little research has been done to evaluate the occupational health of electronic waste (e-waste) recycling workers in Latin America. The objective of this study was to complete comprehensive health evaluations on e-waste recycling workers in Chile and to compare those that work in informal (i.e., independent) to those that work in formal (i.e., established company) settings. A cross-sectional study in the summer of 2017 recruited 78 informal recycling workers from two cities and 15 formal e-waste recycling workers from a single recycling facility to assess exposures and health outcomes. Participants completed a health questionnaire and underwent a full health assessment. Herein, only health questionnaire data are reported. Participants were primarily male, middle-aged, married with children, and had worked in e-waste recycling for an average of 12 years. Participants generally reported good health status, and their prevalence of chronic diseases was comparable to national rates. Workers frequently reported exposures to several occupational stressors, including noise and insufficient income, as well as other mental health stressors. Occupational injuries were commonly reported and use of safety equipment was low. Only a few significant differences, generally of a rather small magnitude, were found between informal and formal workers. In conclusion, from survey data, we did not identify major risks to health among e-waste workers, and only minor differences between workers in informal and formal settings.

Introduction The contribution of hazardous noise—a ubiquitous exposure in workplaces—to occupational injury risk is often overlooked. In this ecological study, the fraction of US workplace acute injuries resulting in days away from work in 2019 attributable to hazardous occupational noise exposure was estimated. Methods Using the NoiseJEM, a job exposure matrix of occupational noise, and 2019 Occupational Employment and Wage Statistics data, the proportion of workers experiencing hazardous occupational noise (≥85 dBA) was estimated for every major US Standard Occupational Classification (SOC) group. Population attributable fractions (PAFs) were calculated for each major SOC group using the relative risk (RR) taken from a published 2017 meta-analysis on this relationship. Results About 20.3 million workers (13.8%) are exposed to hazardous levels of occupational noise. Nearly 3.4% of acute injuries resulting in days away from work in 2019 (95% CI 2.4% to 4.4%) were attributable to hazardous occupational noise, accounting for roughly 14 794 injuries (95% CI 10 367 to 18 994). The occupations with the highest and the lowest PAFs were production (11.9%) and office and administrative support (0.0%), respectively. Discussion Hazardous noise exposure at work is an important and modifiable factor associated with a substantial acute occupational injury burden.

Objectives: This study: (i) assessed the relationship between noise exposure and injury risk, comprehensively adjusting for individual factors, psychosocial stressors, and organizational influences; (ii) determined the relative importance of noise on injuries; (iii) estimated the lowest observed adverse effect level (LOAEL) of noise on injury risk to determine the threshold of noise considered hazardous to injuries; and (iv) quantified the fraction of injuries that could be attributed to hazardous noise exposure. Methods: In this cross-sectional study at 10 US surface mine sites, traditional mixed effects, Poisson regression, and boosted regression tree (BRT) models were run on the number of reported work-related injuries in the last year. The LOAEL of noise on injuries was identified by estimating the percent increase in work-related injuries at different thresholds of noise exposure using a counterfactual estimator through the BRT model. A population attributable fraction (PAF) was quantified with this counterfactual estimator to predict reductions in injuries at the LOAEL. Results: Among 18 predictors of work-related injuries, mine site, perceived job safety, age, and sleepiness were the most important predictors. Occupational noise exposure was the seventh most important predictor. The LOAEL of noise for work-related injuries was a full-shift exposure of 88 dBA. Exposure ≥88 dBA was attributed to 20.3% (95% CI: 11.2%, 29.3%) of reported work-related injuries in the last year among the participants. Conclusions: This study further supports hypotheses of a dose–response relationship between occupational noise exposure and work-related injuries, and suggests that exposures ≥88 dBA may increase injury risk in mining.