Health effects of wind turbines: a review of the literature between 2010-2020

Figures & data

Figure 1. The Flow Diagram of the Reviewed Articles (PRISMA Flow Diagram).

Table 1. Main characteristics of reviewed articles.

No	Author	Country/ Year	Study Design	Number of Participants/ Response Rate	Data Collection Strategy	Variables and Tools used to measure	Evidence of Competing Interest	Evidence of Bias/ Limitation	Funding of the Research
1	Jalali et al.	Canada/ 2016a	Cohort	16/ Not indicated	Not clear	Noise: Measurement Sleep: EEG^a, PSG^b, diaries noise sensitivity, attitude to WTs	No	Potential limitation from lack of control group	Municipality and industry
2	Jalali et al.	Canada/ 2016b	Cohort	64/ 30%	Mailbox and door-to-door	Noise: Measurement Sleep: PSQI^c, ESS^d, ISI^e, economic benefit	No	Recall and non-response bias	Industry
3	Michaud et al.	Canada/ 2016a	Cross-sectional	1238/ 78.9%	Interview (face-to-face and telephone)	Noise: Measurement Noise annoyance Sleep: PSQI, Actigraphy, Perceived stress, Lifestyle behaviours, Chronic disease	No	Confounding bias lack of appropriate study design	Public
4	Michaud et al.	Canada/ 2016b	Cross-sectional	1238/ 78.9%	Interview (face-to-face at home)	Noise: measurement Sleep: PSQI Annoyance	No	Sample size homogeneity distribution and noise exposure problems	No
5	Kageyama et al.	Japan/ 2016	Cross-sectional	1079/ Participants 49%, Control 45%	Interview (mail and face-to-face)	Noise: Measurement, Noise sensitivity Sleep: Questionnaire Physical/mental health Environmental Problems	No	Confounding bias	Public
6	Nissenbaum et al.	USA/ 2012	Cross-sectional	79/ Not indicated	Not clear	Noise: Recordings (obtained from publicly available sources) Sleep: PSQI, ESS, mental and physical health: SF-36v2 Attitude toward IWTs, psychiatric disorders	No	Reposting and selection bias	Not indicated
7	Shepherd et al.	NewZealand/ 2011	Experimental	306/ 32–34%	Self-administered (postal)	QOL: WHO-QOL BREF ^f, Annoyance: NPS^g, Environmental amenity, Noise sensitivity	No	Lack of sample size of turbine group and coincident noise measurements were not obtained	Not indicated
8	Mroczek et al.	Poland/ 2015	Cross-sectional	1277/ 85%	Interview (door to door)	QOL^h: SF-36v2 Smoking: Fagerstrom questionnaire Health problems, Risky drinking, Reaction to WT	No	Not indicated	Not indicated
9	Pawlaczyk-Łuszczyńska et al.	Poland/ 2014a	Cross-sectional	156/ 71%	91.7% self-administered (mail) and 8.3% interviewed (some elderly people)	Attitude towards WT, Environmental satisfaction, Chronic illnesses, General wellbeing, Sleep Quality Mental health status: GHQ-12^i Noise: measurement	No	Not indicated	Public
10	Pedersen et al.	Holland/ 2009	Cross-sectional	725/ 33%	Postal questionnaire	Response to wind turbine noise, Economical Benefit Noise: measurement	Not indicated	Not indicated	European union and industry
11	Maffei et al.	Italy/ 2013	Experimental	34/ No sampling	Self-reported	Noise: 3D Virtual Scenarios Visual and acoustic aspects	No	Not indicated	Not indicated
12	Klæboe et al.	Norway/ 2016	Cross-sectional	90/ 38%	Interview (web-based tool)	Living environment, health, annoyances, noise sensitivity Noise: measurement	No	Not indicated	None
13	Magari et al.	USA/ 2014	Cross-sectional	62/ No sampling	Interview (door to door)	response to WT, annoyance, Noise: measurement	No	Not indicated	Not indicated
14	Crichton et al.	New Zealand/ 2014a	Experimental	54/ No sampling	Self-reported	Physical symptoms, blood pressure and heart rate measurement	Not indicated	Not indicated	Not indicated
15	Blanes -Vidal et al.	Denmark/ 2016	Cross-sectional	454/ 40.5%	Self-administered (mail)	Concerning symptoms, perceived environment, personal characteristics, physical symptoms, annoyance, distance to closest WT	No	Confounding selection and non-response bias	Not indicated
16	Crichton et al.	New Zealand/ 2014b	Experimental	60/ No sampling	Self-reported	Symptoms and mood	No	A limitation for noise exposure simulation was indicated	Not indicated
17	Clark et al.	Australia/ 2016	Qualitative	16/ No random sampling (snowballing approach)	Face-to-face in-depth interview	Health complaints	No	Limitations about sampling	Public
18	Walker et al.	Canada/ 2011	Qualitative	178/ No sampling	Face-to-face in-depth interview	Physical Health Complaints about WT	Not indicated	Selection bias	University
19	Chapman et al.	Australia/ 2013	Ecological	129/ 30%	Recorded data	Complaints about noise or health	No	Study design limitations	None
20	Smith et al.	Sweden/ 2020	Experimental	50/ No sampling	Postal, mailings, telephone contact, and public advertising	Sleep: EEG ^j, PSG, EOG ^k Salivary cortisol measurement. Tiredness, tension, irritation, sleep quality, Sleep disturbance by WTN	Yes (one of the author has clients from WT industry)	Self -selection bias, limitations about confounding factors and non-comparability bias	Public
21	Barry et al.	Canada/ 2018	Cross-sectional	1,238 / 78.9%	Secondary data	Distance QOL: WHO-QOL	Yes (three out two authors)	Study design limitations, volunteer bias, ‘survivor bias’	Industry and public
22	Poulsen et al.	Denmark/ 2019	Cohort	711,249/Sample population was determined by noise levels.	Register-based data	Noise: modelling MI ^l or Stroke Cases: ICD 10 code records	No	Limitations about confounding, potential bias from missing data	Public

^a:EEG (electroencephalogram), ^b:PSG (polysomnography), ^c: PSQI: Pittsburgh Sleep Quality Index, ^d: ESS (Epworth daytime Sleepiness Scale), ^e: ISI (Insomnia Severity Index), ^f:WHO-QOL BREF (World Health Organization- Quality of Life short version), ^g:NPS (Neighbourhood Problem Scale), ^h:QOL(Quality of Life), ⁱ:GHQ-12 (Goldberg General Health Questionnaire), ^j:EKG (electrocardiography), ^k:EOG (electro-oculogram), ^l:MI (myocardial infarction)

Table 2. Summary outcomes of the reviewed studies.

No	Author	Summary of Outcomes
1	Jalali et al. (a)	There was no significant difference in noise measurements before and after installation, but a significant decrease was detected in sleep quality.
2	Jalali et al. (b)	Negative attitude, visual effects, and concern about property value were associated with poor sleep quality.
3	Michaud et al. (a)	Outdoor WTN up to 46 dB(A) was not associated with subjective sleep disturbance or objectively measured sleep outputs such as sleep latency, sleep efficiency, total sleep time, rate of awakening bouts, and wake duration after sleep.
4	Michaud et al. (b)	Annoyance due to all investigated effects about WTs (noise, vibration, shadow, warning lights, visual effect) increased as the WTN increased.
5	Kageyama et al.	Those who were concerned about environmental issues and expressed auditory and visual annoyance related to WT reported more complaints about insomnia and symptoms. Regardless of the actual noise level, noise sensitivity and visual annoyance were associated with poor health.
6	Nissenbaum et al.	WTN can cause sleep disturbances and mental problems at a distance of 1.4 km.
7	Shepherd et al.	General health of the case group living within 2 km of a turbine was not affected but they did report lower quality of life. Sleep quality deteriorated in correlation with dose and distance.
8	Mroczek et al.	Residents of places where wind-farm developments were either at planning stage or under construction had the lowest overall QoL and general health scores. It has been explained by environmental stress and its adverse health effects.
9	Pawlaczyk-Łuszczyńska et al.	Subjective factors such as noise, general attitude towards WTs and sensitivity to landscape littering might explain 63% of the WT-related annoyance.
10	Pedersen et al.	WTN was found to be more annoying than the other noise sources like transportation and industry because of its high visibility, temporal variability, and lack of night-time abatement characteristics.
11	Maffei et al.	Distance is found to be the strongest factor in determining personal responses. More positive attitude towards green and white turbines has been reported.
12	Klæboe et al.	WTs have been defined as visually poor and non-aesthetic. Non-acoustic factors play an essential role in general perception against WT.
13	Magari et al.	Noise levels have not been associated with annoyance or satisfaction with the living environment.
14	Crichton et al.(a)	Concerns about the health effects of WTN could be explained by psychological expectations.
15	Blanes -Vidal et al.	When checked against the confounders (environmental sensitivity, personal reactions etc.), any significant association between WT and health symptoms disappeared.
16	Crichton et al. (b)	Individual perspectives, negative information and attitudes towards WT could determine physical symptoms.
17	Clark et al.	Participants’ stake, interest and legitimacy characteristics may be relevant with reported WT related health effects.
18	Walker et al.	No significant associations between WT and daily life were observed. During the planning process, a healthy community relationship and appropriate information techniques reduced the psychological outcomes
19	Chapman et al.	The prevalence of the complainants residing around wind farms is 0.4%. When the historical and geographical variations in complaints are investigated, it is seen that nocebo effects play an important role in the aetiology of complaints.
20	Smith et al.	WTN have caused longer rapid eye movement (REM) sleep latency and lower amount of REM sleep. Self-reported sleep was consistently rated as worse following WTN exposure nights.
21	Barry et al.	Residential proximity to WT is correlated with annoyance and health-related quality of life measures.
22	Poulsen et al.	No evidence was found of any association between WTN and MI or stroke.

Data availability statement

The datasets used during the current study are available from the corresponding author on request.