Objectives Occupational exposure to disinfectants is associated with work-related asthma, especially in healthcare workers. However, little is known about the specific products involved. To evaluate disinfectant exposures, we designed job-exposure (JEM) and job-task-exposure (JTEM) matrices, which are thought to be less prone to differential misclassification bias than self-reported exposure. We then compared the three assessment methods: self-reported exposure, JEM and JTEM.
Methods Disinfectant use was assessed by an occupational questionnaire in 9073 US female registered nurses without asthma, aged 49–68 years, drawn from the Nurses' Health Study II. A JEM was created based on self-reported frequency of use (1–3, 4–7 days/week) of 7 disinfectants and sprays in 8 nursing jobs. We then created a JTEM combining jobs and disinfection tasks to further reduce misclassification. Exposure was evaluated in 3 classes (low, medium, high) using product-specific cut-offs (eg, <30%, 30–49.9%, ≥50%, respectively, for alcohol); the cut-offs were defined from the distribution of self-reported exposure per job/task.
Results The most frequently reported disinfectants were alcohol (weekly use: 39%), bleach (22%) and sprays (20%). More nurses were classified as highly exposed by JTEM (alcohol 41%, sprays 41%, bleach 34%) than by JEM (21%, 30%, 26%, respectively). Agreement between JEM and JTEM was fair-to-moderate (κ 0.3–0.5) for most disinfectants. JEM and JTEM exposure estimates were heterogeneous in most nursing jobs, except in emergency room and education/administration.
Conclusions The JTEM may provide more accurate estimates than the JEM, especially for nursing jobs with heterogeneous tasks. Use of the JTEM is likely to reduce exposure misclassification.
- Job-Exposure Matrix
- Job-Task-Exposure Matrix
- occupational exposure
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Contributors CQ contributed to the statistical programming and data analysis, data interpretation and primary manuscript preparation. OD contributed to the study conception, participation in the acquisition of the data, assistance with data analysis, data interpretation, primary manuscript preparation and critical revision of the manuscript. PKH, RV and JPZ contributed to the conceptualisation and design of the nested case–control study in NHSII, data interpretation and critical revision of the manuscript. ASW participated in the acquisition of the data, data management, data interpretation and critical revision of the manuscript. FES contributed to the conceptualisation and design of NHSII and the nested case–control study, participation in the acquisition of the data, data interpretation and critical revision of the manuscript. MG contributed to the data interpretation and critical revision of the manuscript. CAC participated in the conceptualisation and design of NHSII, conceptualisation and design of the nested case–control study, participation in the acquisition of the data, study conception, data interpretation and critical revision of the manuscript. NLM contributed to the conceptualisation and design of the nested case–control study in NHSII, study conception, assistance with data analysis, data interpretation, primary manuscript preparation and critical revision of the manuscript.
Funding Centers for Disease Control and Prevention R01 OH-10359; National Institutes of Health UM1 CA176726; Hubert Curien Partnerships for French–Dutch cooperation, French Ministry of Higher Education and Research and OCW Dutch Ministry (Ministerie van Onderwijs, Cultuur en Wetenschap) PHC Van Gogh 33653RF; University of Versailles Saint-Quentin-en-Yvelines EDSP doctoral grant.
Disclaimer The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health.
Competing interests None declared.
Patient consent Obtained.
Ethics approval Institutional Review Board at the Brigham and Women's Hospital.
Provenance and peer review Not commissioned; externally peer reviewed.
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