The current environmental situation has resulted in an expansion of renewable energy, including industrial wind turbines (IWTs). IWTs represent an emissions-free alternative that can help reduce air pollution and illness related to air quality (Clark et al., 2010). Maximizing the electricity production from IWTs has resulted in development that encroaches on residential land, and this practice has led to an increase in environmental noise (Pedersen & Waye, 2007). Environmental noise is a growing concern for public health, given the association between noise exposure and cardiovascular disease (Stansfeld & Crombie, 2011), annoyance (World Health Organization Regional Office for Europe, 2011), cognitive performance (Passchier-Vermeer & Passchier, 2000), and sleep disturbance (Basner, Muller, & Elmenhorst, 2011).
Expansion of IWT developments, particularly in rural Ontario communities, has prompted residents living in the vicinity to urge local health authorities to respond to the high number of complaints concerning sleep disturbance due to IWT noise. While IWT noise has been associated with annoyance (Pedersen & Waye, 2004) and decreased health-related quality of life (Shepherd, McBride, Welch, Dirks, & Hill, 2011), there is a lack of scientific evidence to support health-related claims from IWTs (Chief Medical Officer of Health, 2010). Presently, IWT facilities continue to be installed in Ontario, despite growing concerns over the potential impacts on sleep and health that have led to active social movements that oppose further expansion of wind power resources. To begin to address the lack of empirical research on the impact of IWT noise on sleep, we used actigraphy and sleep diaries in a preliminary study examining the sleep quality of individuals who reside in the vicinity of IWTs compared with a community without IWTs.
Two rural Ontario communities were purposefully selected as study sites: one community with IWTs and one without. The unexposed community was selected in an area that was similar in terrain and demographic characteristics and also housed a renewable energy facility: a grid-connected anaerobic digestion plant. The study protocol was reviewed and received ethics clearance through the Office of Research Ethics at the University of Waterloo.
A random sample of 50 residences in the exposed community and 56 residences in the unexposed community were selected for door-to-door recruitment. This process made contact with 54 individuals, 29 of whom were from the exposed group and 25 of whom were from the unexposed group. Of these, 15 individuals from the exposed group and 12 from the unexposed group agreed to participate, giving a response rate of 52% and 48%, respectively, and 50% overall. These 27 individuals were given a brief health assessment to check for exclusion criteria such as diagnosed or self-reported sleep disorders, symptoms suggestive of a sleep disorder (e.g., heavy snoring, leg jerk, gasping for breath), psychiatric disorders, cognitive impairment, use of medication known to alter sleep, and medical conditions that alter an individual's daily independence. Of the 27 participants, two were excluded from the exposed group (both due to use of sleep medication) and two were excluded from the unexposed group (one due to a diagnosis of sleep apnea, and one who was not of legal age for participation).
The remaining 23 participants (13 exposed, 10 unexposed; final participation rate 43%) were asked to give their written consent and were invited to participate in the full study. One participant from the exposed group was lost due to noncompliance and another completed only the sleep diary.
Actigraphy, using ActiGraph GT3X+ devices to detect body movements during sleep, was used to measure sleep parameters. The actigraphs were worn on the wrist of the nondominant arm and all procedures recommended by the manufacturer were followed. Actigraphy data were analysed using the Cole-Kripke scoring algorithm for actigraphy (Cole, Kripke, Gruen, Mullaney, & Gillin, 1992) available with ActiLife software version 5.11.
Sleep measures included sleep onset latency (SOL), wake after sleep onset (WASO), total sleep time (TST), time in bed (TIB), number of awakenings, and sleep efficiency (SE). SOL was defined according to the Cole-Kripke algorithm as the time to the start of the first complete minute scored as sleep (Cole et al., 1992). Number of awakenings was defined as the number of blocks of adjoining wake episodes. WASO was defined as the number of wake minutes after sleep onset. TST was defined as the total amount of time scored as sleep. TIB was defined as the time between first attempting sleep to the final...