ArticleNoise & health
Relationship Between Workplace Noise Exposure and Sleep in Tanzania.
Article in Noise & health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
backgroundHigh noise levels during daytime work may cause sleep disturbances amongst workers, but research findings are inconclusive so far.
objectiveThis study aims to compare sleep amongst workers exposed to high and low daytime noise during work in a developing country, where workplaces often have high noise levels.
methodsA cross-sectional study was conducted amongst 181 metal industrial workers (high-noise-exposed workers) and 72 office cleaners (low-noise-exposed workers) in Tanzania. The average noise levels were 97.9 and 76.6 dBA for the high- and low-noise-exposed workers, respectively. An interview-based questionnaire was used to collect data on sociodemographic characteristics, sleep variables, the Epworth sleepiness scale (ESS) and the Bergen insomnia scale (BIS). Data were analysed using descriptive statistics, t-tests, Kruskal-Wallis tests, Pearson chi-square tests and logistic regression analysis.
resultsThe mean BIS score for high-noise-exposed workers was 13.2, with 40.3% reporting insomnia and 39.8% reporting excessive daytime sleepiness (ESS ≥ 11). The low-noise-exposed workers had a mean BIS score of 15.4, with 51.4% reporting insomnia and 41.7% reporting excessive daytime sleepiness. The crude odds ratio (OR) of insomnia when exposed to high noise was 1.56 (95% CI = 0.90-2.718, P = 0.111), and the crude OR for excessive daytime sleepiness was 1.08 (95% CI = 0.62-1.88, P = 0.782). Insomnia and daytime sleepiness were not different between groups when adjusting for age, marital status, education, smoking, alcohol, coffee consumption and daytime rest periods.
conclusionNo differences were found between daytime high- and low-noise-exposed workers in relation to self-reported sleep variables. The results must be interpreted with caution due to the use of self-reports and possible unmeasured confounders.
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