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  Table of Contents    
Year : 2015  |  Volume : 17  |  Issue : 77  |  Page : 175-181
Wind turbines and health: An examination of a proposed case definition

1 Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge; Staff Physician, Brigham and Women's Hospital, Pulmonary Division, Boston, Germany
2 Institute for Occupational Epidemiology and Risk Assessment of Evonik Industries, AG, Essen; Institute and Policlinic for Occupational Medicine, Environmental Medicine and Preventive Research, University of Cologne, Cologne, Germany
3 Schulich School of Medicine and Dentistry, Western University, London, Ontario; Chatham-Kent Public Health Unit, Chatham, Canada
4 ENVIRON International Corporation, Massachusetts, USA

Click here for correspondence address and email
Date of Web Publication13-Jul-2015

Renewable energy demands have increased the need for new wind farms. In turn, concerns have been raised about potential adverse health effects on nearby residents. A case definition has been proposed to diagnose "Adverse Health Effects in the Environs of Industrial Wind Turbines" (AHE/IWT); initially in 2011 and then with an update in 2014. The authors invited commentary and in turn, we assessed its scientific merits by quantitatively evaluating its proposed application. We used binomial coefficients to quantitatively assess the potential of obtaining a diagnosis of AHE/IWT. We also reviewed the methodology and process of the development of the case definition by contrasting it with guidelines on case definition criteria of the USA Institute of Medicine. The case definition allows at least 3,264 and up to 400,000 possibilities for meeting second- and third-order criteria, once the limited first-order criteria are met. IOM guidelines for clinical case definitions were not followed. The case definition has virtually no specificity and lacks scientific support from peer-reviewed literature. If applied as proposed, its application will lead to substantial potential for false-positive assessments and missed diagnoses. Virtually any new illness that develops or any prevalent illness that worsens after the installation of wind turbines within 10 km of a residence could be considered AHE/IWT if the patient feels better away from home. The use of this case definition in the absence of a thorough medical evaluation with appropriate diagnostic studies poses risks to patients in that treatable disorders would be overlooked. The case definition has significant potential to mislead patients and its use cannot be recommended for application in any health-care or decision-making setting

Keywords: Case definitions, epidemiology, infrasound, low-frequency sound, wind turbines

How to cite this article:
McCunney RJ, Morfeld P, Colby W D, Mundt KA. Wind turbines and health: An examination of a proposed case definition. Noise Health 2015;17:175-81

How to cite this URL:
McCunney RJ, Morfeld P, Colby W D, Mundt KA. Wind turbines and health: An examination of a proposed case definition. Noise Health [serial online] 2015 [cited 2023 Dec 1];17:175-81. Available from: https://www.noiseandhealth.org/text.asp?2015/17/77/175/160678

  Introduction Top

Some people living near wind turbines have raised concerns about a multitude of nonspecific symptoms that they attribute to the turbines. In turn, a case definition has been published that sets out criteria for a probable diagnosis of "Adverse Health Effects in the Environs of Industrial Wind Turbines" (AHE/IWT), the cumbersome term introduced in the article [1],[2] [[Table 1] for the criteria]. This proposed case definition concludes, despite the absence of credible scientific literature to support the assertion, that numerous self-reported symptoms can be causally linked to living in proximity to wind turbines. The case definition has been used in public policy deliberations in Ontario during Environmental Review Tribunal hearings as a basis for diagnosing adverse health effects from living in the vicinity of wind turbines. The case definition also has been referenced in an editorial in the Canadian Family Physician: "It will be important to identify the possibility of exposure to industrial wind turbines in patients presenting with appropriate clinical symptoms," a comment that was followed by a citation of McMurtry 2011, [3] in which the AHE/IWT case definition was proposed.
Table 1: Criteria of the proposed case definition for AHE/IWT*

Click here to view

A major use of case definitions in health care is for forming diagnoses, conducting research, and identifying "cases" of disease for epidemiologic analysis. Epidemiology studies need reliable criteria for forming an accurate diagnosis of a "case." Information about cases, including their use in generating reports of disease incidence and prevalence, is often used as the basis for public health interventions, and for decision-making in insurance and legal matters. Case definitions have been used in the diagnosis of diseases with variable presentations, such as fibromyalgia, chronic fatigue syndrome, rheumatoid arthritis, and collagen vascular diseases, among other ailments. [4] As a result of the importance of case definitions in medical care and public policy, it is essential that the case diagnostic criteria accurately reflect the diagnosis of the disease or symptoms under review - whether for diagnostic, treatment, research, or policy purposes.

In light of how the AHE/IWT case definition already has been used in public policy, cited in the medical literature, and in consideration of the author's call for commentary ("The author invites critical commentary"), [1] this report examines the scientific basis of the development and appropriateness of the application of the case definition to residents living near wind turbines. We further illustrate its poor specificity through a mathematical demonstration.

This report is not intended to critically review the literature on wind turbines and health, as such reviews are available. [3],[4],[5],[6],[7],[8],[9],[10] The purpose of this report is to quantitatively assess the potential for possible diagnoses through the application of the proposed criteria. The case definition was initially proposed in 2011. In 2014, the case definition was published with minor changes not noted by the authors, but including the addition of headache to third order criteria and the expansion of the exposure metric to living within 10 km of a wind turbine. We will focus our mathematical assessment on the 2011 criteria, i.e., we will apply a conservative approach. Clearly, the potential of a person being diagnosed with "AHE/IWT "with the expanded exposure metric will increase.

  Methods Top

A quantitative assessment of proposed case definition

We followed the proposed case definition through its first-, second-, and third-order diagnostic criteria to analyze by using binomial coefficients the potential of a positive-screening test. This approach allowed a quantitative assessment of the application of the case definition to diagnose illness from living in the vicinity of wind turbines.

In light of the importance of precision in a case definition, and its ability to differentiate among different etiological and nosological entities, the AHE/IWT criteria were evaluated to determine the number of different ways in which the criteria for a "probable diagnosis" could be met. With this approach, it is possible to gain a quantified perspective on the case definition by assessing how specific the criteria are for reaching a diagnosis and, thus, how likely they are to be associated with false-positive assessments.

To calculate the number of possible combinations that may lead to a diagnosis according to the case definition, we translate the problem into terms of combinatorics. [11],[12] The task is equivalent to calculating the number of subsets with k elements that can be formed from a set S of n distinct objects. Note that the term "subset" implies that no object is used more than once and that the order of the objects is disregarded. Binomial coefficients nCk are the appropriate mathematical tools to count the number of subsets of prescribed size k from a given set S with n elements, called "from n choose k":

nCk = [n × (n-1) × … × (n-k)]/ [1 × 2 × 3 ×…× k]

where n is the overall number of objects in S and k is number of objects per subset that are selected.

According to McMurtry 2011 [1] and McMurtry and Krogh 2014, [2] the set S with n elements is always of the form:

S = {o 1 , w 1 , o 2 , w 2 , …, o n/2 , w n/2}

with o i denoting "occurrence of symptom I after installation of a wind turbine " and w i denoting "worsening of symptom I after the installation of a wind turbine."

There is some vagueness in the definition related to the terms "occurrence" and "worsening" of a symptom as presented in the proposed case definition. [1],[2] We apply three interpretations to perform quantitative assessments:

Scenario A

A symptom will be counted twice in the same person if it occurs after installation of a wind turbine and if it worsens later.

Scenario B

A symptom will never be counted more than once in one person, but it could be a first occurrence of the symptom after installation of a wind turbine or a worsening of the prevalent symptom after installation of a wind turbine.

Scenario C

A symptom is only counted if it occurs for the first time after installation of a wind turbine. Worsening of symptoms will be disregarded.

Note that calculations in the scenarios A and C can readily be done with the help of binomial coefficients:

Scenario A: The number of subsets is nCk = (from n chose k), k ≤ n.

Scenario C: The number of subsets are (n/2)Ck = (from n/2 choose k), k ≤ n/2.

Scenario B means that we have to consider all subsets with k element of S under the constraint that we never draw two elements of the same index i = 1, 2, …, n/2. We focus on occurrences first. This is scenario C and we calculate (n/2)Ck (from n/2 choose k) subsets of the form {o i(1), o i(2), …, o i(k)}, with i as an injective mapping from {1, 2, …k} into {1, 2, …, n/2}, k ≤ n/2. Next we take into account that each o i(j), 1 ≤ j ≤ k can be substituted by w i(j), 1 ≤ j ≤ k. This leads to 2 k additional variations. In summary we yield

Scenario B: The number of subsets are (n/2)Ck × 2 k .

Qualitative assessment based on guidelines of the Institute of Medicine (IOM)

In 2011, the IOM of the USA issued standards for clinical practice guidelines that are intended to enhance transparency and objectivity, and to standardize the format for their development. [13] The American Cancer Society subsequently adopted these recommendations for use in the development of their cancer-screening guidelines. [14] The proposed case definition for AHE/IWT was qualitatively evaluated in light of the IOM guidelines.

  Result Top

Quantitative assessment of proposed case definition

The proposed first-, second-, and third-order criteria are reviewed below from a mathematical perspective to determine how many independent combinations of symptoms would lead to a diagnosis of probable AHE/IWT. In the proposed case definition [Table 1].

  • All four first-order criteria must be met, then
  • Any three of four second-order criteria must be met, then
  • Any three of 18 third-order criteria must be met

In this evaluation, we have focused on the definition given in McMurtry 2011. [1] We note that McMurtry and Krogh 2014 [2] relaxed the criteria. They now refer to a 10-km radius instead of 5 km to define the relevant environment of IWT. They also added "headache" as a 19 th third-order criterion [[Table 1] for a detailed comparison]. In addition, they stated: "If the symptoms described in second-order criteria (b and c) are present, no further symptoms or complaints are required for the probable diagnosis." Thus, in this case the first- and second-order criteria are already sufficient, it follows that our quantitative evaluation of the case definition as published in McMurtry 2011 [1] yields lower bounds for the possible number of ways a diagnosis can be reached according to McMurtry and Krogh 2014. [2]

First-order criteria

First-order criteria include any change in health status in people living within 5 km of a wind turbine, in which the symptoms improve when away from the home and recur upon return to the home. The exposure metric for assessing noise from wind turbines is "Living within 5 km of a wind turbine." No scientific support is provided for the selection of this distance or for exposure to any noise emissions from the turbine actually occurring at residences at this distance. Scientific justification for this distance and why the value of noise levels, the most objective and widely used metric, was ignored is lacking in the article. An exposure estimate as arbitrary as "living within 5 km of a wind turbine" sets a broad stage for false-positive assessments, as most individuals living within 5 km of a wind turbine may not be able to see it and may not be exposed to any emissions from it. In summary, one can meet the first-order criteria if they live within 5 km of a turbine, have a change in health status, and feel better when away from the home near the wind turbines, even if they are not exposed to any noise emissions from the turbine (i.e., absent what might be considered actual "exposure"). We note that McMurtry and Krogh 2014 [2] relaxed the exposure metric to 10 km! Once a person meets the first-order criteria, the next step is to determine if they meet second-order criteria.

Second-order criteria

Given that the first-order criteria are met, there are the following numbers of different ways that three of four second-order criteria can be met:

Scenario A: (from 8 choose 3) = (8 × 7 × 6)/(1 × 2× 3) = 56

Scenario B: (from 4 choose 3) × 2 3 = (4 × 3 × 2)/(1 × 2 × 3) × 8 = 32

Scenario C: (from 4 choose 3) = (4 × 3 × 2)/(1 × 2 × 3) = 4

Now that we have determined the minimum (four) and maximum (56) ways in which the second-order criteria can be met, the next step is to determine for each of these options noted in the three scenarios above (4, 32, 56) the number of ways that third-order criteria can be met.

Third-order criteria

The case definition requires meeting three of 18 third-order criteria. The numbers of combinations are:

Scenario A: (from 36 choose 3) = (36 × 35 × 34)/(1 × 2 × 3) = 7140

Scenario B: (from 18 choose 3) × 2 3 = 816 × 8 = 6528

Scenario C: (from 18 choose 3) = 816

We note that these numbers increase if we refer to the 19 third-order criteria listed in McMurtry and Krogh 2014. [2]

Summary of the quantitative assessment

Combining the three order criteria, we get the following number of possible ways to fulfill the diagnostic criteria:

Scenario A: 56 × 7140 = 399,840

Scenario B: 32 × 6528 = 208,896

Scenario C: 4 × 816 = 3,264

In summary, once the first-order criteria are met, there are a minimum of 3,264 and a maximum of 399,840 ways of reaching a diagnosis. Note that the numbers of combinations calculated under Scenario C are strict lower bounds of the true numbers, as worsening is considered by McMurtry 2011 [1]

Because McMurtry and Krogh 2014 [2] listed 19 third-order criteria, the numbers calculated for Scenarios A, B, and C are strict lower bounds for the possible ways of reaching a diagnosis according to the 2014 publication. [2]

Qualitative assessment based on guidelines of the IOM

[Table 2] notes some of the limitations of the symptoms chosen by the author to be part of the case definition. The case definition overlooks recall bias in completing questionnaires and their corresponding limitations in assessing work-related disease, among other conditions, such as environmental illness. [13]
Table 2: Medical assessment of case definition

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In 2011, the Institute of Medicine (IOM) in the USA issued guidelines for the development of clinical guidelines. [13] Major IOM criteria are noted in [Table 2] and [Table 3], against which the AHE/IWT criteria are contrasted. This report was not designed to conduct a comprehensive comparison of the case definition with the IOM guidelines, but only to highlight key points. The case definition does not meet essential criteria for clinical guidelines, most notably by lack of committee involvement in the development of the guidelines, as the AHE/IWT reflects two authors perspective; the lack of indication of potential conflicts of interest; and lack of transparency in how evidence was selected for review. Not one peer-reviewed paper was cited in the article in which the case definition first appeared. [1]
Table 3: A selection of IOM criteria for clinical guidelines

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Customarily, position papers on diagnosis, treatment, and other aspects of medical care, such as "case definitions," are based on a thorough process that involves expert reviews of the peer-reviewed literature, followed by the development of a consensus document prepared by expert committees or national/international medical societies. For example, the American College of Occupational and Environmental Medicine (ACOEM) has developed position papers on a variety of topics (acoem.org). The steps toward the development of a position paper or consensus statement, such as a case definition, are as follows: First, a separate committee, such as a "Committee on Scientific Affairs," will critically review peer-reviewed literature on a specific topic and then prepare a consensus report. A "Council of Scientific Affairs" then reviews this report and as with any peer-reviewed paper submitted for publication, a decision is made to request revisions or additions. When the Council approves the document, it is submitted to the Board of Directors for final approval. Similar approaches in the development of position papers are followed by medical specialty societies worldwide.

This type of process ensures some scientific rigor in the review and interpretation of scientific literature to reach a consensus for the subsequent use of the position paper in policy. In stark contrast to these internationally accepted procedures, the wind turbine syndrome case definition represents the opinion of one individual initially, supplemented by a second author in 2014; it is not a consensus perspective or a policy statement of any medical or health organization.

  Discussion Top

Scientific validity

As noted by its authors, the proposed definition has not been validated. [1]

The mathematical exercise we carried out highlights the inability of the proposed case definition to differentiate among numerous combinations of largely common symptoms, regardless of the actual exposure sustained by a patient. Moreover, our analysis does not address the merits and scientific justification (or lack thereof) of the symptoms chosen for the case definition [Table 1]. The minimum of 3,264 and maximum of 399,840 ways in which a diagnosis of AHE/IWT can be reached, once the first-order criteria are met, do not reflect the additional uncertainty in the reliability of the first-order criteria (i.e., proximity to a wind turbine as "exposure" and the consideration of any new symptom that improves away from wind turbines) or the limited reliability of self-reports in assessing exposure-related symptoms. [15]

Exposure metric

In the evaluation of potential exposure-related illness, it is critical to define the exposure and specify how it was measured or estimated. This principle is fundamental in occupational and environmental medicine and is an essential factor in conducting a causality assessment. In fact, a member of the editorial board of Occupational and Environmental Medicine emphasized in a recent editorial the importance of a proper exposure assessment. [16] In the case of wind turbines, sound is one exposure variable of importance. Thus, how wind turbine sounds are measured will have a critical bearing on the assessment of exposure-related effects and on the scientific validity of any case definition. Using "living within 5 km - and now 10 km - of a wind turbine" as an exposure metric is inappropriate, especially in light of the wide availability of noise-monitoring devices against which results could be compared to previous studies and environmental regulations, among other sources. An extension to 10 km, as proposed in McMurtry and Krogh 2014, [2] decreases further the low specificity of the suggested case definition.


There are a number of unsubstantiated scientific comments in the case definition articles, [1],[2] some of which are described below.

In the proposed case definition, it is stated: "While adherence to the criteria has resulted in no false-positive diagnosis to date further validation is required." There are no studies cited in which false positives were assessed, so this conclusion is unwarranted. In fact, no citations are provided for the categorical generalization that "no false-positive diagnosis [with the proposed case definition] has occurred." This statement cannot be supported in the absence of a published survey and, moreover, seems profoundly implausible in light of our analysis that indicates that there are over 3,000 and up to 400,000 ways to reach the diagnosis, once the first-order criteria are met. Moreover, we are unaware of any blood or diagnostic test used in medical practice today for which no "false positives" occur. On the contrary, false-positive test results are very common in medical practice and represent approximately 5% of the results of routine clinical chemistry tests and for some parameters a higher value (see http://www.ahrq.gov/clinic/uspstfix.htm).

The author of the proposed case definition claimed: "The definition endeavors to be specific and sensitive." [1] Despite such laudable goals, the methodology failed to reflect the extensive experience of screening tests and their corresponding false-positive and false-negative results as described by the US Preventive Services Task Force (http://www.ahrq.gov/clinic/uspstfix.htm). Sensitivity refers to the percentage of people with a disease (true positives) who have a positive test. A false positive is a test result that is "positive" in someone without the disease (a true negative). Specificity refers to the percentage of people without the disease who have a negative test. False negatives are negative results in someone who actually has the disease being screened.

The article states: "There are few, if any, alternative explanations for the first and second order criteria than AHE/IWT." [1] This statement is incorrect, as the case definition for second-order criteria includes sleep disruption, altered quality of life, and annoyance - symptoms that can be associated with numerous medical conditions, including cancer, diabetes, coronary artery disease, sleep apnea, asthma, and many others. Moreover, there are numerous reasons why one particular home could be perceived as less desirable than another including the following: Amenities or lack thereof, structural issues (insulation, including urea-formaldehyde foam and asbestos in older homes); weather factors (mold growth after flooding); dirty ventilation systems (hypersensitivity pneumonitis, asthma); maintenance activities (use of certain cleaning agents); environmental factors (allergens from to plants, animals, etc.); and local industrial and transportation (rail, highway) activities. Social factors (i.e., neighbors, etc.) may also play a role in some people preferring their time away from their residence, whether or not they live near a wind turbine. Finally, when people are away from their home, they are likely on vacation or in some new/different location (family/friend's house, etc.), and it is not surprising that they forget about the stresses of home, school, and work, among other responsibilities. This assessment would be true regardless of a nearby IWT.

To demonstrate the lack of precision of the case definition, consider a new diagnosis of breast cancer that is made after the installation of a wind turbine within 5 km of the person's residence. According to the case definition, if the person's symptoms improve when away from the turbines and recur upon return, they only need to show:

1. Second-order criteria:

  1. Compromise of quality of life,
  2. Sleep disruption, and
  3. Annoyance producing increased levels of stress, and

2. Third-order criteria:

  1. Fatigue,
  2. Sleepiness, and
  3. Frustration in order to be diagnosed with AHE/IWT

All of the above symptoms are associated with cancer and many other medical conditions that have nothing to do with living in the vicinity of a wind turbine. Other examples where the case definition would fall short of being valid include asthma, rheumatoid arthritis, and sleep apnea, all of which, among others, could meet the criteria of the case definition.

This "diagnosis" of probable AHE/IWT in light of newly diagnosed breast cancer demonstrates the imprecision and low specificity (i.e., high false-positive rate) with the case definition criteria. Suggesting that living in the vicinity of a wind turbine could be a cause of breast cancer seems profoundly beyond the realm of medical probability, but such a conclusion could be drawn by using the case definition criteria. Moreover, the proposed case definition goes beyond defining a "case" of any illness or condition, and assigns a specific cause, an exercise not customary for case definitions other than those such as "lead poisoning" or "silicosis" in which the causal agent is specific and known.

  Conclusions Top

The point of this exercise was to quantitatively evaluate the scientific validity of the proposed case definition if it were to be used as intended. There are at least 3,264 and up to 399,840 ways for meeting a diagnosis of AHE/IWT once the nonspecific first-order criteria are met. The numbers are even larger when the updated case definition is used, as proposed by McMurtry and Krogh 2014. [2] These numerous combinations indicate a lack of precision and specificity in the case definition that would lead to a considerable number of false-positive results. We note that such an imprecise and unspecific case definition probably adds to the problem of overdiagnosis. This is described as a severe challenge to modern medicine in Hofmann 2014 [17] : "Overdiagnosis is a fundamental challenge to modern health care." [18] It is claimed to be "the biggest problem posed by modern medicine," [19] leading to unnecessary suffering and significant costs. [18] In the USA, it is estimated that this results in more than $200bn wasted on unnecessary treatment every year, [20] and that 30% of the health-care spending is on ineffective measures." [21],[22]

The proposed case definition has several fundamental shortcomings, most notably the lack of specificity and the absence of a suitable exposure metric. The case definition remains unvalidated four years after initially being published, and there are no case series of clinical studies in which its reliability has been documented. In addition and of major importance, no cohort or case-control epidemiological study showed that the proposed case definition is related to any kind of exposure that may be linked to wind turbines. Its use is not appropriate for diagnosing symptoms or for evaluating potential causal links between living in the vicinity of wind turbines and adverse health effects. Reliance on this case definition in the absence of a traditional medical evaluation that includes a thorough history, review of medical records, and the conduct and interpretation of appropriate diagnostic studies poses risks to patients in that potentially serious and treatable conditions would be overlooked.

  References Top

McMurtry RY. Toward a case definition of adverse health effects in the environs of industrial wind turbines: Facilitating a clinical diagnosis. Bull Sci Technol Soc 2011;31:316.   Back to cited text no. 1
McMurtry RY, Krogh CM. Diagnostic criteria for adverse health effects in the environs of wind turbines. JRSM Open 2014;5: 2054270414554048.  Back to cited text no. 2
Jeffery RD, Krogh C, Horner B. Adverse Health Effects of industrial wind turbines. Can Fam Physician 2013;59:473-5.  Back to cited text no. 3
Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A. The chronic fatigue syndrome: A comprehensive approach to its definition and study. International Chronic Fatigue Syndrome Study Group. Ann Intern Med 1994;121:953-9.  Back to cited text no. 4
Knopper LD, Ollson CA. Health effects and wind turbines: A review of the literature. Environ Health 2011;10:78.  Back to cited text no. 5
Jeffery RD, Krogh CM, Horner B. Industrial wind turbines and adverse health effects. Can J Rural Med 2014;19:21-6.   Back to cited text no. 6
Kurpas D, Mroczek B, Karakiewicz B, Kassolik K, Andrzejewski W. Health impact of wind farms. Ann Agric Environ Med 2013;20:595-604.  Back to cited text no. 7
MDPH 2012: Massachusetts Department of Environmental Protection. Independent Expert Science Panel Releases Report on Potential Health Effects of Wind Turbines http://www.mass.gov/dep/public/press/0112wind.htm. [Last accessed on 2015 May 05].  Back to cited text no. 8
McCunney RJ, Mundt K, Colby WD, Dobie R, Kaliski K, Blais M. Wind turbines and health: A critical review of the scientific literature. J Occup Environ Med 2014;56:e108-30.   Back to cited text no. 9
Pedersen E. Health aspects associated with wind turbine noise - Results from three field studies. Noise Contr Eng J 2011;59;47-53.  Back to cited text no. 10
Kreyszig E. Advanced Engineering Mathematics Hardcover-Sega. Boston: John Wiley & Sons; 2011. p. 1-1283.  Back to cited text no. 11
Brualdi RA. Introductory Combinatorics. 5 th ed. Prentice-Hall: Pearson; 2010. p. 1-618.  Back to cited text no. 12
Institute of Medicine. Clinical Practice Guidelines we can trust. Washington, DC: National Academies Press; 2011. p. 1-290.  Back to cited text no. 13
Brawley O, Byers T, Chen A, Pignone M, Ransohoff D, Schenk M, et al. New American cancer society process for creating trustworthy cancer screening guidelines. JAMA 2011;306:2495-9.  Back to cited text no. 14
Lenderink AF, Zoer I, van der Molen HF, Spreeuwers D, Frings-Dresen MH, van Dijk FJ. Review on the validity of self-report to assess work-related diseases. Int Arch Occup Environ Health 2012;85:229-51.  Back to cited text no. 15
Loomis D. On the importance of quantification. Occup Environ Med 2012;69:609.   Back to cited text no. 16
Hofmann B. Diagnosing overdiagnosis: Conceptual challenges and suggested solutions. Eur J Epidemiol 2014;29:599-604.  Back to cited text no. 17
Moynihan R, Doust J, Henry D. Preventing overdiagnosis: how to stop harming the healthy. BMJ. 2012;344:e3502. doi:10.1136/bmj.e3502.  Back to cited text no. 18
Welch HG, Schwartz L, Woloshin S. Overdiagnosed : making people sick in the pursuit of health. Boston: Beacon Press; 2011.  Back to cited text no. 19
Berwick DM, Hackbarth AD. Eliminating waste in US health care. JAMA 2012;307:1513-6.  Back to cited text no. 20
Bloche MG. Beyond the ′′R word′′? Medicine′s new frugality. N Engl J Med 2012;366:1951-3.  Back to cited text no. 21
Fisher ES, Wennberg DE, Stukel TA, Gottlieb DJ, Lucas FL, Pinder EL. The implications of regional variations in medicare spending. Part 2: health outcomes and satisfaction with care. Ann Intern Med 2003;138:288-98.  Back to cited text no. 22

Correspondence Address:
Robert J McCunney
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge - 02139, 77 Massachusetts Avenue Bldg. 16; Brigham and Women's Hospital, Pulmonary Division, Boston, Massachusetts, USA

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Source of Support: None, Conflict of Interest: Drs. McCunney, Colby and Mundt have served as experts in several litigation matters (including Environmental Tribunal Reviews in Ontario) on behalf of wind farm developers and wind turbine manufacturers, typically co-defendants with the Ontario Ministry of the Environment (MOE). Dr Morfeld is head of the Institute for Occupational Epidemiology and Risk Assessment of Evonik Industries AG.

DOI: 10.4103/1463-1741.160678

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