Association between residential noise exposure and burnout among healthcare workers in Taiwan: a cross-sectional study

Few studies have explored the association between residential noise exposure and burnout. In this study, we investigated the association between residential noise exposure and burnout prevalence among 5416 health-care workers in Taiwan from 2012 to 2017. Burnout was evaluated using the Mandarin version of the Copenhagen Burnout Inventory by considering both continuous and binary measures. We applied ordinary Kriging models to calculate the annual average residential noise exposure at an individual level. Multivariable linear regression models and logistic regression models were employed. Restricted cubic splines were used to explore dose-response relationships. The median age of the health-care workers was 31.5 years. In the multivariable linear regression models, exposure to residential noise (per 1 dBA) was associated with increases in personal burnout and work-related burnout scores by 1.59 ± 0.25 and 1.38 ± 0.20, respectively. In the multivariable logistic regression models, the adjusted odds ratios were 1.24 (95% confidence interval [CI]: 1.16, 1.32) for personal burnout and 1.19 (95% CI: 1.13, 1.26) for work-related burnout per 1-dBA increase in residential noise exposure. Linear dose-response associations of burnout with residential noise level were detected. Our findings suggest that exposure to residential noise may increase the risk of burnout among health-care workers.

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Publication Details

Journal
Scientific Reports
Published
2024-10-12
DOI
https://doi.org/10.1038/s41598-024-73649-5
Citations
5
Primary Topic
Noise Effects and Management
Type
article
Field-Weighted Citation Impact
4.36

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article

Association between residential noise exposure and burnout among healthcare workers in Taiwan: a cross-sectional study

Chin‐Chi Kuo, Ta‐Chien Chan, Ro‐Ting Lin, Hsiu‐Yin Chiang et al.
5 citations
Scientific Reports
Noise Effects and Management
4.36
article

Association between residential noise exposure and burnout among healthcare workers in Taiwan: a cross-sectional study

Chin‐Chi Kuo, Ta‐Chien Chan, Ro‐Ting Lin, Hsiu‐Yin Chiang, Yu-Ting Lin, Wei-Cheng Chen, Shinn‐Jye Liang
article en
5 citations

Abstract

Few studies have explored the association between residential noise exposure and burnout. In this study, we investigated the association between residential noise exposure and burnout prevalence among 5416 health-care workers in Taiwan from 2012 to 2017. Burnout was evaluated using the Mandarin version of the Copenhagen Burnout Inventory by considering both continuous and binary measures. We applied ordinary Kriging models to calculate the annual average residential noise exposure at an individual level. Multivariable linear regression models and logistic regression models were employed. Restricted cubic splines were used to explore dose-response relationships. The median age of the health-care workers was 31.5 years. In the multivariable linear regression models, exposure to residential noise (per 1 dBA) was associated with increases in personal burnout and work-related burnout scores by 1.59 ± 0.25 and 1.38 ± 0.20, respectively. In the multivariable logistic regression models, the adjusted odds ratios were 1.24 (95% confidence interval [CI]: 1.16, 1.32) for personal burnout and 1.19 (95% CI: 1.13, 1.26) for work-related burnout per 1-dBA increase in residential noise exposure. Linear dose-response associations of burnout with residential noise level were detected. Our findings suggest that exposure to residential noise may increase the risk of burnout among health-care workers.

Scientific ReportsVol. 14(1)
National Yang Ming Chiao Tung University (TW), China Medical University (TW), China Medical University Hospital (TW), Research Center for Humanities and Social Sciences, Academia Sinica (TW)
Academia Sinica, China Medical University Hospital, China Medical University, Health and Welfare Data Science Center, National Science and Technology Council, Division of Materials Research
Openalex Percentile: Top 6%
Noise Effects and Management
4.36
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