Association Between Industrial Wind Turbine Noise and Sleep Quality in a Comparison Sample of Rural Ontarians
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Background: Wind turbines (WTs) are an emerging source of renewable energy in Ontario. One concern is that aerodynamic and mechanical noise produced by the WTs results in sleep disturbance in residents living near such facilities. However, evidence to date is primarily self-reported, with no objective measures of the impact on sleep quality currently in the literature. Objective: The objective of this study was to determine if the presence of a grid connected WT is a risk factor for poor sleep quality and if wind turbine noise is associated with sleep parameters. The hypothesis was that individuals residing within fifteen hundred meters of a WT experience poorer sleep, compared to those who do not reside near a WT. Methods: A daily sleep diary and actigraphy-derived measures of sleep quality were obtained from twelve participants from a WT community in rural Ontario and ten participants from a comparison community with no wind power installations. Sound level meters were used to assess the equivalent (LAeq) and maximum (LAmax) sound pressure levels within the bedroom. A variety of statistical analysis were performed to determine co-variation between variables, noise thresholds for sleep disturbance, and risk for poor sleep quality. Results: A total of 110 person-nights and 12,971 sleep epochs were observed. Participants in the exposed group lived at a mean distance of 795 m from the closest WT (range 474 m–1085 m). Although numerous actigraphy-derived sleep parameters were poorer in the exposed group, including lower average sleep efficiency (89% vs. 92%), longer sleep onset latency (6 min vs. 4 min), and longer wake after sleep onset (42 min vs. 29 min), the differences were not statistically significant. When the data was dichotomized by quality of sleep, the prevalence of poor sleep in the exposed group was greater than in the unexposed group (22 vs. 11 per 100 person-nights), although the results of logistic regression modeling indicated that the differences were not statistically significant (after adjustment for age and sex). Findings from the analysis of sleep epochs showed an association between awakenings and LAmax (during the sleep epoch) only for noise events above 55 dBA. No significant differences in sleep parameters derived from the sleep diaries were found between the groups. Conclusion: Both actigraphy and sleep diaries can provide valuable information to understand the impact of industrial WTs on the quality of sleep for residents living in the vicinity. This pilot study had a small sample size which reduced the likelihood of identifying differences in sleep quality between the exposed and unexposed groups. Additionally, measurements were obtained during periods of relatively low wind speeds (nightly power outputs ranged from 1 to 34 MW or 0.5 to 17% capacity) thus, limiting the generalizability of the findings. Findings of poorer mean values of numerous sleep parameters in the exposed group support the need for more extensive research in the area. Low response to noise events up to 45 dBA was an interesting finding that also merits further investigation. Assessment of WT noise is complex and noise exposure measurement requires unique methods than those used for other sources of community noise.
Cite this work
James Lane (2013). Association Between Industrial Wind Turbine Noise and Sleep Quality in a Comparison Sample of Rural Ontarians. UWSpace. http://hdl.handle.net/10012/7533