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Wang AJ, Frishman WH. Literature Review: Effects of Environmental Noise on the Cardiovascular Health. Cardiol Rev 2025:00045415-990000000-00404. [PMID: 39936928 DOI: 10.1097/crd.0000000000000852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/13/2025]
Abstract
The adverse effects of environmental noise on human health have been recognized for more than a century. In particular, during the last decades, the vast majority of studies have focused on the detrimental role of noise in the induction of cardiovascular diseases. In this study, we aim to conduct a literature review on chronic stress responses induced by environmental noise, the risk of cardiovascular disease, and the underlying pathophysiological mechanisms. We retrieved the publications from the PubMed database by searching for "noise AND cardiovascular." By reviewing these publications in this study, we will first describe the epidemiologic research on cardiovascular risk factors and diseases induced by environmental noise, then discuss the mechanism(s) underlying these noise-induced cardiovascular impairments based on clinical and experimental studies, and finally evaluate the strategies to mitigate the effects of noise on cardiovascular health. We also evaluate the studies that describe the effects of noise level and noise intermittency, such as train noise, on cardiovascular health. We discuss whether environmental noise should be part of a risk factor profile for cardiovascular disease and how we should manage it, and assess the strategy that can be used to mitigate the noise-induced physiopathological changes. Furthermore, we briefly describe the effects of air pollution and heavy metals on cardiovascular health and discuss the relevance of these environmental stressors in the noise-induced cardiovascular disease. Our studies suggest that future studies are warranted to investigate new strategies that can mitigate the adverse effects of environmental noise on cardiovascular health.
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Affiliation(s)
- Andrew Jun Wang
- From the Department of Medicine, New York University Grossman School of Medicine, New York, NY
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2
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Li L, Zhang W, Liu S, Wang W, Ji X, Zhao Y, Shima M, Yoda Y, Yang D, Huang J, Guo X, Deng F. Cardiorespiratory effects of indoor ozone exposure during sleep and the influencing factors: A prospective study among adults in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 924:171561. [PMID: 38458472 DOI: 10.1016/j.scitotenv.2024.171561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 02/16/2024] [Accepted: 03/05/2024] [Indexed: 03/10/2024]
Abstract
Ambient ozone (O3) is recognized as a significant air pollutant with implications for cardiorespiratory health, yet the effects of indoor O3 exposure have received less consideration. Furthermore, while sleep occupies one-third of life, research on the health consequences of O3 exposure during this crucial period is scarce. This study aimed to investigate associations of indoor O3 during sleep with cardiorespiratory function and potential predisposing factors. A prospective study among 81 adults was conducted in Beijing, China. Repeated measurements of cardiorespiratory indices reflecting lung function, airway inflammation, cardiac autonomic function, blood pressure, systemic inflammation, platelet and glucose were performed on each subject. Real-time concentrations of indoor O3 during sleep were monitored. Associations of O3 with cardiorespiratory indices were evaluated using linear mixed-effect model. Effect modification by baseline lifestyles (diet, physical activity, sleep-related factors) and psychological status (stress and depression) were investigated through interaction analysis. The average indoor O3 concentration during sleep was 20.3 μg/m3, which was well below current Chinese indoor air quality standard of 160 μg/m3. O3 was associated with most respiratory indicators of decreased airway function except airway inflammation; whereas the cardiovascular effects were only manifested in autonomic dysfunction and not in others. An interquartile range increases in O3 at 6-h average was associated with changes of -3.60 % (95 % CI: -6.19 %, -0.93 %) and -9.60 % (95 % CI: -14.53 %, -4.39 %) in FVC and FEF25-75, respectively. Further, stronger effects were noted among participants with specific dietary patterns, poorer sleep and higher level of depression. This study provides the first general population-based evidence that low-level exposure to indoor O3 during sleep has greater effects on the respiratory system than on the cardiovascular system. Our findings identify the respiratory system as an important target for indoor O3 exposure, and particularly highlight the need for greater awareness of indoor air quality, especially during sleep.
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Affiliation(s)
- Luyi Li
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Wenlou Zhang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Shan Liu
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Wanzhou Wang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Xuezhao Ji
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Yetong Zhao
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Masayuki Shima
- Department of Public Health, School of Medicine, Hyogo Medical University, Nishinomiya, Hyogo 663-8501, Japan
| | - Yoshiko Yoda
- Department of Public Health, School of Medicine, Hyogo Medical University, Nishinomiya, Hyogo 663-8501, Japan
| | - Di Yang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Jing Huang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Xinbiao Guo
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Furong Deng
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China; Center for Environment and Health, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.
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Micic G, Zajamsek B, Lechat B, Hansen K, Scott H, Toson B, Liebich T, Dunbar C, Nguyen DP, Decup F, Vakulin A, Lovato N, Lack L, Hansen C, Bruck D, Chai-Coetzer CL, Mercer J, Doolan C, Catcheside P. Establishing the acute physiological and sleep disruption characteristics of wind farm versus road traffic noise disturbances in sleep: a randomized controlled trial protocol. SLEEP ADVANCES : A JOURNAL OF THE SLEEP RESEARCH SOCIETY 2023; 4:zpad033. [PMID: 37750160 PMCID: PMC10517905 DOI: 10.1093/sleepadvances/zpad033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 05/31/2023] [Indexed: 09/27/2023]
Abstract
Study Objectives Despite the global expansion of wind farms, effects of wind farm noise (WFN) on sleep remain poorly understood. This protocol details a randomized controlled trial designed to compare the sleep disruption characteristics of WFN versus road traffic noise (RTN). Methods This study was a prospective, seven night within-subjects randomized controlled in-laboratory polysomnography-based trial. Four groups of adults were recruited from; <10 km away from a wind farm, including those with, and another group without, noise-related complaints; an urban RTN exposed group; and a group from a quiet rural area. Following an acclimation night, participants were exposed, in random order, to two separate nights with 20-s or 3-min duration WFN and RTN noise samples reproduced at multiple sound pressure levels during established sleep. Four other nights tested for continuous WFN exposure during wake and/or sleep on sleep outcomes. Results The primary analyses will assess changes in electroencephalography (EEG) assessed as micro-arousals (EEG shifts to faster frequencies lasting 3-15 s) and awakenings (>15 s events) from sleep by each noise type with acute (20-s) and more sustained (3-min) noise exposures. Secondary analyses will compare dose-response effects of sound pressure level and noise type on EEG K-complex probabilities and quantitative EEG measures, and cardiovascular activation responses. Group effects, self-reported noise sensitivity, and wake versus sleep noise exposure effects will also be examined. Conclusions This study will help to clarify if wind farm noise has different sleep disruption characteristics compared to road traffic noise.
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Affiliation(s)
- Gorica Micic
- Flinders University, Flinders Health and Medical Research Institute: Sleep Health, College of Medicine and Public Health, Australia
| | - Branko Zajamsek
- Flinders University, Flinders Health and Medical Research Institute: Sleep Health, College of Medicine and Public Health, Australia
| | - Bastien Lechat
- Flinders University, Flinders Health and Medical Research Institute: Sleep Health, College of Medicine and Public Health, Australia
| | - Kristy Hansen
- Flinders University, College of Science and Engineering, Australia
| | - Hannah Scott
- Flinders University, Flinders Health and Medical Research Institute: Sleep Health, College of Medicine and Public Health, Australia
| | - Barbara Toson
- Flinders University, Flinders Health and Medical Research Institute: Sleep Health, College of Medicine and Public Health, Australia
| | - Tessa Liebich
- Flinders University, College of Education, Psychology and Social Work, Australia
| | - Claire Dunbar
- Flinders University, College of Education, Psychology and Social Work, Australia
| | - Duc Phuc Nguyen
- Flinders University, College of Science and Engineering, Australia
| | - Felix Decup
- Flinders University, College of Science and Engineering, Australia
| | - Andrew Vakulin
- Flinders University, Flinders Health and Medical Research Institute: Sleep Health, College of Medicine and Public Health, Australia
- University of Sydney, NEUROSLEEP, Woolcock Institute of Medical Research, Australia
| | - Nicole Lovato
- Flinders University, Flinders Health and Medical Research Institute: Sleep Health, College of Medicine and Public Health, Australia
| | - Leon Lack
- Flinders University, Flinders Health and Medical Research Institute: Sleep Health, College of Medicine and Public Health, Australia
- Flinders University, College of Education, Psychology and Social Work, Australia
| | - Colin Hansen
- The University of Adelaide, School of Mechanical Engineering, Australia
| | - Dorothy Bruck
- Victoria University, Institute for Health and Sport, Australia
| | - Ching Li Chai-Coetzer
- Flinders University, Flinders Health and Medical Research Institute: Sleep Health, College of Medicine and Public Health, Australia
- Department of Respiratory, Sleep Medicine and Ventilation, Southern Adelaide Local Health Network, SA Health, Australia
| | - Jeremy Mercer
- Department of Respiratory, Sleep Medicine and Ventilation, Southern Adelaide Local Health Network, SA Health, Australia
| | - Con Doolan
- University of New South Wales, School of Mechanical and Manufacturing Engineering, Australia
| | - Peter Catcheside
- Flinders University, Flinders Health and Medical Research Institute: Sleep Health, College of Medicine and Public Health, Australia
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Leone MJ, Dashti HS, Coughlin B, Tesh RA, Quadri SA, Bucklin AA, Adra N, Krishnamurthy PV, Ye EM, Hemmige A, Rajan S, Panneerselvam E, Higgins J, Ayub MA, Ganglberger W, Paixao L, Houle TT, Thompson BT, Johnson-Akeju O, Saxena R, Kimchi E, Cash SS, Thomas RJ, Westover MB. Sound and light levels in intensive care units in a large urban hospital in the United States. Chronobiol Int 2023; 40:759-768. [PMID: 37144470 PMCID: PMC10524721 DOI: 10.1080/07420528.2023.2207647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 11/18/2022] [Accepted: 04/21/2023] [Indexed: 05/06/2023]
Abstract
Intensive care units (ICUs) may disrupt sleep. Quantitative ICU studies of concurrent and continuous sound and light levels and timings remain sparse in part due to the lack of ICU equipment that monitors sound and light. Here, we describe sound and light levels across three adult ICUs in a large urban United States tertiary care hospital using a novel sensor. The novel sound and light sensor is composed of a Gravity Sound Level Meter for sound level measurements and an Adafruit TSL2561 digital luminosity sensor for light levels. Sound and light levels were continuously monitored in the room of 136 patients (mean age = 67.0 (8.7) years, 44.9% female) enrolled in the Investigation of Sleep in the Intensive Care Unit study (ICU-SLEEP; Clinicaltrials.gov: #NCT03355053), at the Massachusetts General Hospital. The hours of available sound and light data ranged from 24.0 to 72.2 hours. Average sound and light levels oscillated throughout the day and night. On average, the loudest hour was 17:00 and the quietest hour was 02:00. Average light levels were brightest at 09:00 and dimmest at 04:00. For all participants, average nightly sound levels exceeded the WHO guideline of < 35 decibels. Similarly, mean nightly light levels varied across participants (minimum: 1.00 lux, maximum: 577.05 lux). Sound and light events were more frequent between 08:00 and 20:00 than between 20:00 and 08:00 and were largely similar on weekdays and weekend days. Peaks in distinct alarm frequencies (Alarm 1) occurred at 01:00, 06:00, and at 20:00. Alarms at other frequencies (Alarm 2) were relatively consistent throughout the day and night, with a small peak at 20:00. In conclusion, we present a sound and light data collection method and results from a cohort of critically ill patients, demonstrating excess sound and light levels across multiple ICUs in a large tertiary care hospital in the United States. ClinicalTrials.gov, #NCT03355053. Registered 28 November 2017, https://clinicaltrials.gov/ct2/show/NCT03355053.
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Affiliation(s)
- Michael J Leone
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Hassan S Dashti
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Brain Data Science Platform, Broad Institute, Cambridge, Massachusetts, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Brian Coughlin
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Ryan A Tesh
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Syed A Quadri
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Abigail A Bucklin
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Noor Adra
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Parimala Velpula Krishnamurthy
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Elissa M Ye
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Aashritha Hemmige
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Subapriya Rajan
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Ezhil Panneerselvam
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Jasmine Higgins
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Muhammad Abubakar Ayub
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Division of Pulmonary and Critical Care, Department of Medicine, Massachusetts General Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Wolfgang Ganglberger
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Sleep & Health Zurich, University of Zurich, Zurich, Switzerland
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Luis Paixao
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Timothy T Houle
- Sleep & Health Zurich, University of Zurich, Zurich, Switzerland
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - B Taylor Thompson
- Division of Pulmonary and Critical Care, Department of Medicine, Massachusetts General Hospital, and Harvard Medical School, Boston, Massachusetts, USA
| | - Oluwaseun Johnson-Akeju
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Brain Data Science Platform, Broad Institute, Cambridge, Massachusetts, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Eyal Kimchi
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Robert J Thomas
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Medicine, Division of Pulmonary, Critical Care & Sleep, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - M Brandon Westover
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
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5
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Marshall NS, Cho G, Toelle BG, Tonin R, Bartlett DJ, D’Rozario AL, Evans CA, Cowie CT, Janev O, Whitfeld CR, Glozier N, Walker BE, Killick R, Welgampola MS, Phillips CL, Marks GB, Grunstein RR. The Health Effects of 72 Hours of Simulated Wind Turbine Infrasound: A Double-Blind Randomized Crossover Study in Noise-Sensitive, Healthy Adults. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:37012. [PMID: 36946580 PMCID: PMC10032045 DOI: 10.1289/ehp10757] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 02/09/2023] [Accepted: 02/21/2023] [Indexed: 05/26/2023]
Abstract
BACKGROUND Large electricity-generating wind turbines emit both audible sound and inaudible infrasound at very low frequencies that are outside of the normal human range of hearing. Sufferers of wind turbine syndrome (WTS) have attributed their ill-health and particularly their sleep disturbance to the signature pattern of infrasound. Critics have argued that these symptoms are psychological in origin and are attributable to nocebo effects. OBJECTIVES We aimed to test the effects of 72 h of infrasound (1.6-20 Hz at a sound level of ∼90 dB pk re 20μPa, simulating a wind turbine infrasound signature) exposure on human physiology, particularly sleep. METHODS We conducted a randomized double-blind triple-arm crossover laboratory-based study of 72 h exposure with a >10-d washout conducted in a noise-insulated sleep laboratory in the style of a studio apartment. The exposures were infrasound (∼90 dB pk), sham infrasound (same speakers not generating infrasound), and traffic noise exposure [active control; at a sound pressure level of 40-50 dB LAeq,night and 70 dB LAFmax transient maxima, night (2200 to 0700 hours)]. The following physiological and psychological measures and systems were tested for their sensitivity to infrasound: wake after sleep onset (WASO; primary outcome) and other measures of sleep physiology, wake electroencephalography, WTS symptoms, cardiovascular physiology, and neurobehavioral performance. RESULTS We randomized 37 noise-sensitive but otherwise healthy adults (18-72 years of age; 51% female) into the study before a COVID19-related public health order forced the study to close. WASO was not affected by infrasound compared with sham infrasound (-1.36 min; 95% CI: -6.60, 3.88, p=0.60) but was worsened by the active control traffic exposure compared with sham by 6.07 min (95% CI: 0.75, 11.39, p=0.02). Infrasound did not worsen any subjective or objective measures used. DISCUSSION Our findings did not support the idea that infrasound causes WTS. High level, but inaudible, infrasound did not appear to perturb any physiological or psychological measure tested in these study participants. https://doi.org/10.1289/EHP10757.
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Affiliation(s)
- Nathaniel S. Marshall
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Garry Cho
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
| | - Brett G. Toelle
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Renzo Tonin
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
- Renzo Tonin Associates, Sydney, Australia (Retired)
| | - Delwyn J. Bartlett
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Angela L. D’Rozario
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
- School of Psychology, Faculty of Science, University of Sydney, Sydney, New South Wales, Australia
| | - Carla A. Evans
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
| | - Christine T. Cowie
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
- South West Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Oliver Janev
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
| | | | - Nick Glozier
- Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Royal Prince Alfred Hospital, Camperdown, Sydney, New South Wales, Australia
| | - Bruce E. Walker
- Channel Islands Acoustics, Santa Barbara, California, USA (Retired)
| | - Roo Killick
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
| | - Miriam S. Welgampola
- Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Royal Prince Alfred Hospital, Camperdown, Sydney, New South Wales, Australia
| | - Craig L. Phillips
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
- School of Medicine, Macquarie University, Sydney, New South Wales, Australia
| | - Guy B. Marks
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
- South West Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Ronald R. Grunstein
- Woolcock Institute for Medical Research, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Royal Prince Alfred Hospital, Camperdown, Sydney, New South Wales, Australia
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