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|Year : 2013 | Volume
| Issue : 63 | Page : 148--150
Letter to Editor: Are the findings of "Effects of industrial wind turbine noise on sleep and health" supported?
Christopher A Ollson, Loren D Knopper, Lindsay C McCallum, Melissa L Whitfield-Aslund
Intrinsik Environmental Sciences, 6605 Hurontario St., Mississauga, ON L5T 0A3, Canada
Christopher A Ollson
Intrinsik Environmental Sciences Inc, 6605 Hurontario Street, Suite 500, Mississauga, ON L5T 0A3
|How to cite this article:|
Ollson CA, Knopper LD, McCallum LC, Whitfield-Aslund ML. Letter to Editor: Are the findings of "Effects of industrial wind turbine noise on sleep and health" supported?.Noise Health 2013;15:148-150
|How to cite this URL:|
Ollson CA, Knopper LD, McCallum LC, Whitfield-Aslund ML. Letter to Editor: Are the findings of "Effects of industrial wind turbine noise on sleep and health" supported?. Noise Health [serial online] 2013 [cited 2021 Jan 26 ];15:148-150
Available from: https://www.noiseandhealth.org/text.asp?2013/15/63/148/110302
With great interest we read the paper "effects of industrial wind turbine noise on sleep and health"  published in the September-October edition of Noise and Health. The stated purpose of the Nissenbaum et al., work was to undertake an epidemiology study to investigate the relationship between reported adverse health effects and wind turbines among residents of two rural communities: Mars Hill and Vinalhaven, Maine, USA. Participants living 375-1400 m and 3.3-6.6 km were given questionnaires to obtain data about sleep quality (using the Pittsburgh Sleep Quality Index [PSQI]), day-time sleepiness (using the Epworth Sleepiness Score (ESS)) and general physical and mental-health (using the (SF36 v2 health survey). Overall the authors reported that when compared to people living further away than 1.4 km from wind turbines, those people living within 1.4 km of wind turbines had worse sleep, were sleepier during the day and had worse mental-health scores.
While this publication is recent, earlier works by Nissenbaum et al., about this investigation have been publically available on the internet since 2009. They also appear in a publically available conference proceeding from 2011.  We note that the publication in Noise and Health in large part remains consistent with earlier works.
We have previously detailed concerns related to study design, methodology, sample size, and administration of questionnaires to participants during previous legal proceedings (McKinnon v. Martin;  Erickson v. MOE  ). These concerns are not repeated fully herein. Notwithstanding these previous criticisms, the purpose of this letter is to ask the question: Are the findings of "Effects of industrial wind turbine noise on sleep and health" supported?
Post hoc Introduction of Sound Levels
For the first time in publishing this work, the authors included sound levels with distance from the turbines. The authors indicate that "Simultaneous collection of sound levels during the data collection at the participants' residences was not possible, but measured industrial wind turbine (IWT) sound levels at various distances, at both sites, were obtained from publically available sources." 
For Mars Hill the sound levels were reportedly extracted from the "Sound Level Study, Compilation of Ambient and Quarterly Operations Sound Testing, and the Maine Department of Environmental Protection Order No. L -2 1635-26-A-N." However, Nissenbaum et al.,  do not provide the figures from which the data were obtained and simply state in the notes of [Table 1] that: "Values read or derived from report figures; accuracy ± 50 m and ± 1 Db." For Vinalhaven no reference other than "R and R, personal communication, 2011,"  which was not listed as a reference in the published article, was provided for the sound measurements that were apparently collected as 2-min measurements over a single day in February 2011.
Given that the relationship between noise from wind turbines and health concerns is the fundamental premise of the study by Nissenbaum et al., it is surprising that the authors gave such little consideration to collection of actual sound data measurements at the study participant homes. The use of post-hoc sound data, visually obtained from figures in reports, is not scientifically defensible and should not have been used to draw conclusions about the findings of the questionnaires with distance from turbine locations.
Given the nature of these data we believe that any results or conclusions related to sound levels at these facilities are not supported and the finding that "… it is apparent that this value will be less than an average hourly LA eq of 40 dBA, which is the typical night time value permitted under the current guidance in most jurisdictions"  is simply not defensible.
We also believe that the title of the paper "Effects of industrial wind turbine noise on sleep and health" is not supported given the nature of the data presented. No evidence with respect to sound level (noise) and its effect on sleep and health has been statistically presented in this paper and the authors could have more appropriately focused the title with respect to the distance, which is the variable that they actually investigated.
Statistical Finding of Sleep Outcomes
The study team administered two questionnaires related to sleep: The PSQI and the ESS.
The PSQI is a self-rated questionnaire meant to assess sleep quality and disturbances over a 1 month period. A global PSQI score > 5 can be used to distinguish "good sleepers" from "poor sleepers." This is acknowledged within the Nissenbaum et al., (2012) paper in the Questionnaire Development section. Although, there was a statistically significant difference between the mean PSQI scores in the near (7.8) and far group (6.0), it is important to remember that both of these average scores are greater than 5, which would qualify both groups as "poor sleepers." When one examines the reported "% of PSQI score >5" no statistical difference between the near and far groups was found (P = 0.0745).
Moreover, the authors attempt to illustrate the relationship between PSQI and distance to the nearest wind turbine in [Figure 1] (and ESS scores in [Figure 2] and SF36 mental component summary (MCS) scores in [Figure 3]).  In all cases, the regression lines had P values < 0.05. Nissenbaum et al., appear to mistake these significant P values in the regression lines as being related to the relationship of the scores with distance. As with all regressions, the P values in these tests refer to the significance of the slope of the lines being greater than 0, rather than a relationship between variables on the x and y axis. In fact, in these types of regressions, as important, if not more important, is the r2 value (co-efficient of determination/goodness of fit). This value provides one with the ability to ascertain how well a regression line fits the scatter of data that it attempts to predict. The closer r2 is to 1.0, the better the fit of the data and the ability of a regression line to predict a future outcome.
The authors did not provide the r2 values for any of the three figures nor did they present the slope equations for these lines. If one examines the figures it is revealed that there is considerable scatter of the values, especially, in the 375-1400 m near group. For example, the scatter of the resulting PSQI scores in the near group is between 1 and 18 and in the far group the range is 1-16. Through our visual examination of these figures we do not believe that one can predict the PSQI values from the slope of this line at any given distance. For example, between 600 m and 900 m one could just as easily have a score of 19 as they would 1. Based on our experience it is unlikely that the r2 for any of the three figures would provide reasonable fit to make these regression lines of any use in future predictions or even in predicting scores with distance in this study.
The ESS is also a widely used self-administered questionnaire that can provide information about a person's general level of day-time sleepiness or average daily sleep propensity. According to the University of Maryland Medical Centre, Sleep Disorders Centre, an ESS score of 10 or more is considered sleepy and a score of 18 or more is considered very sleepy ( http://www.umm.edu/sleep/epworth_sleep.htm ).
Similar to the PSQI test, when completing the ESS test those living near turbines had significantly different scores than those in the far group (7.8 vs. 5.7); however, given that the threshold of sleepiness is a value of 10, on average neither group should be considered sleepy. Moreover, the "% with ESS score > 10" was not statistically different between the two groups (P = 0.1313). While some individuals from both groups reported scores greater than 10 it needs to be high-lighted that 10-20% of the general population report having ESS scores greater than 10 ( http://epworthsleepinessscale.com/about-epworth-sleepiness/ ), similar to those found in the near and far groups in this study.
In their paper Nissenbaum et al., state that noise emitted by IWTs can affect sleep. However, their results do not support this statement. In fact, the authors state that "The data on measured and estimated noise levels were not adequate to construct a dose-response curve…" and no statistical analyses were conducted to assess this supposed relationship. Therefore, we do not believe that Nissenbaum et al.,  show any statistical difference in overall "poor" sleep quality or sleepiness between the groups. Thus, any conclusions on distance from wind turbines and effect on sleep outcomes is not supported by the authors' statistical findings.
Physical and Mental-Health Outcomes
The SF36 test has been widely used within the quality of life scientific investigation field. The SF36 is a multi-purpose, short-form health survey made up of 36 questions that yields an 8-scale profile of functional health and well-being scores as well as psychometrically-based physical and mental-health summary measures and a preference-based health utility index ( http://www.sf-36.org/tools/sf36.shtml ).
Nissenbaum et al.,  did show significantly decreased SF36 MCS scores between the near (42.0) and far (52.9) groups (P = 0.0021). However, the conclusion that the reduced MCS score in some residents living near wind turbines is related to noise emissions is hypothetical and not support by the data. In the paper, neither sleep nor physical effects were related to noise levels, and no attempt was made to relate MCS score to sleep. Moreover, there was no significant difference (P = 0.06) between the number of respondents that required psychotropic medications since the start of turbine operations for the two groups. Simply put Nissenbaum et al., show that some people in the vicinity of turbines reported lesser MCS scores than those living further away, but no underlying reason for this was conclusively established.
Nissenbaum et al.,  pointed out that visual cue and attitude towards wind turbines "are known to affect the psychological response to environmental noise." While this may be true, visual cue and attitude by themselves have been shown to be stronger drivers of psychological responses than a wind-turbine specific variable like sound itself.  Therefore, a conclusion that can be drawn from this study is that the self-reported MCS scores of people living near wind turbines can be likely attributable to physical manifestations from an annoyed state, rather than a wind-turbine specific factor like noise. Indeed, the weight of evidence in the wind turbine and human health literature points to a causal relationship between self-reported health effects and annoyance, which is to say annoyance brought on by the change in the local environment (i.e., a decrease in amenity) that wind turbines represent. 
It is important to note that the authors acknowledge that "There was no statistically significant difference in [physical component score] PCS (P = 0.9881)."  This means that respondents reported no difference in their physical component summary score or physical well-being between the two groups. The findings of the PCS score appear to support the premise that there is nothing physically emitted from the turbines that affected health in this small population sample size. It also appears that negative MCS scores in the near group were not affecting the physical health of individuals.
Are the Authors Conclusions Supported?
Based on their findings the author's concluded that:
"…the noise emissions of IWTs disturbed the sleep and caused day-time sleepiness and impaired mental-health in residents living within 1.4 km of the two IWT installations studied." 
Overall, in our opinion the authors extend their conclusions and discussion beyond the statistical findings of their study. We believe that they have not demonstrated a statistical link between wind turbines - distance - sleep quality - sleepiness and health. In fact, their own statistical findings suggest that although, scores may be statistically different between near and far groups for sleep quality and sleepiness, they are no different than those reported in the general population. The claims of causation by the authors (i.e., wind turbine noise) for negative MCS scores are not supported by their data. This work is exploratory in nature and should not be used to set definitive setback guidelines for wind-turbine installations.
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|2||Nissenbaum MA, Aramini JJ, Hanning CD. Adverse health effects of industrial wind turbines: A preliminary report. 10 th International Congress on Noise as a Public Health Problem (ICBEN) 2011, London UK: Conference Proceedings; 2011. p. 650-5.|
|3||McKinnon v. Martin, 2010 SKQB 374, Queen′s Bench of Saskatchewan, 2010.|
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