key: cord-0816251-9p1vxv9z
authors: Shkembi, Abas; Neitzel, Richard L.
title: Noise as a risk factor for COVID‐19 transmission: Comment on Zhang: “Estimation of differential occupational risk of COVID‐19 by comparing risk factors with case data by occupational group”
date: 2022-03-22
journal: Am J Ind Med
DOI: 10.1002/ajim.23349
sha: e161b46c944c210ed019a5a9194b88aab10c5780
doc_id: 816251
cord_uid: 9p1vxv9z

nan

Noise as a risk factor for COVID-19 transmission: Comment on Zhang: "Estimation of differential occupational risk of COVID-19 by comparing risk factors with case data by occupational group"

Zhang published an important article examining occupational risk factors for COVID-19 transmission in the state of Washington during the early months of the pandemic using O*NET data on major occupational groups. 1 Zhang found exposure to diseases at work as a risk factor, as would be intuitively expected, as well as physical proximity between workers. We wish to comment on the consideration of another exposure-occupational noise-as a potential risk factor for COVID-19 transmission. been shown to impair middle-to high-voice frequencies, resulting in substantial reductions in speech intelligibility. 2 As such, adherence to social distancing and mask requirements may be lower in highnoise work environments due to the need to communicate with fellow workers, which could, in turn, increase the risk of COVID-19 transmission among workers. To test this hypothesis, we performed a small, simple analysis based in part on the same data used by Zhang.

We merged the data reported in table 1 by Zhang (total employment, COVID-19 case counts, and incidence rate per so that the effect estimates of the regression were normalized per 100,000 employees and could be interpreted as incidence rate ratios (IRRs). Since Zhang's analysis did not include farming, fishing, and forestry occupations (major SOC group "45-0000") after deeming the reported COVID-19 incidence rate to be statistically influential (rate of 3330 cases per 100,000 employees), we ran this regression twice: once with the farming, fishing, and forestry occupations included (Model 1), and once without (Model 2). Table 1 displays the results of these two regression models. The full regression model (Model 1) indicates that a 1 dB increase in occupational noise exposure is significantly associated with a 16% (95% confidence interval: 15%, 18%) increase in the incidence of COVID-19, while a doubling of exposure (3 dB increase) is significantly associated with a 57% (52%, 62%) increase in COVID-19 incidence. Excluding farming, fishing, and forestry occupations from the model (Model 2) did not substantially alter the effect estimate of the model, with a still significant 10%-and 33% higher incidence rate of COVID-19 associated with a 1 dB increase in, and 3 dB doubling of, occupational noise exposure, respectively. Abbreviations: T CI , confidence interval; IRR, incidence rate ratio;TWA OSHA , time-weighted average noise level measured according to the occupational safety and health administration noise regulation.

Estimation of differential occupational risk of COVID-19 by comparing risk factors with case data by occupational group

Short report on the effects of SARS-CoV-2 face protective equipment on verbal communication

Imputation of missing values in a large job exposure matrix using hierarchical information