Façades, floors and maps – Influence of exposure measurement error on the association between transportation noise and myocardial infarction

Vienneau, Danielle; Héritier, Harris; Foraster, María; Eze, Ikenna C.; Schaffner, Emmanuel; Thiesse, Laurie; Rudzik, Franziska; Habermacher, Manuel; Köpfli, Micha; Pieren, Reto; Brink, Mark; Cajochen, Christian; Wunderli, Jean Marc; Probst‐Hensch, Nicole; Röösli, Martin

doi:10.1016/j.envint.2018.12.015

Cited by 49 publications

(39 citation statements)

References 41 publications

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“…Without information on how long study participants actually spend at home, there is likely to be both over-and underestimation of the true exposure. The common convention of using the loudest house façade may also systematically overestimate noise exposure, and better traffic noise measurements will improve the precision of future studies [84]. Improved noise measurements in future studies might also help attenuate the problem of heterogeneity, which was considerable in the meta-analyses for road and railway traffic noise.…”

Section: Discussionmentioning

confidence: 99%

Traffic Noise and Mental Health: A Systematic Review and Meta-Analysis

Hegewald

Schubert

Freiberg

et al. 2020

IJERPH

114

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Recent evidence suggests that traffic noise may negatively impact mental health. However, existing systematic reviews provide an incomplete overview of the effects of all traffic noise sources on mental health. We conducted a systematic literature search and summarized the evidence for road, railway, or aircraft noise-related risks of depression, anxiety, cognitive decline, and dementia among adults. We included 31 studies (26 on depression and/or anxiety disorders, 5 on dementia). The meta-analysis of five aircraft noise studies found that depression risk increased significantly by 12% per 10 dB LDEN (Effect Size = 1.12, 95% CI 1.02–1.23). The meta-analyses of road (11 studies) and railway traffic noise (3 studies) indicated 2–3% (not statistically significant) increases in depression risk per 10 dB LDEN. Results for road traffic noise related anxiety were similar. We did not find enough studies to meta-analyze anxiety and railway or aircraft noise, and dementia/ cognitive impairment and any traffic noise. In conclusion, aircraft noise exposure increases the risk for depression. Otherwise, we did not detect statistically significant risk increases due to road and railway traffic noise or for anxiety. More research on the association of cognitive disorders and traffic noise is required. Public policies to reduce environmental traffic noise might not only increase wellness (by reducing noise-induced annoyance), but might contribute to the prevention of depression and anxiety disorders.

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Section: Discussionmentioning

confidence: 99%

Traffic Noise and Mental Health: A Systematic Review and Meta-Analysis

Hegewald

Schubert

Freiberg

et al. 2020

IJERPH

114

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“…First, we were unable to obtain detailed street addresses for the study subjects due to data confidentiality, and thus, we were unable to assign exposures to their residential addresses. Previous studies have shown that the finer scale introduced less measurement error, and subsequent bias and use of noise maps to represent residential exposure may underestimate noise-induced health effects (Eriksson et al 2013;Vienneau et al 2019). Since a single postal code in Toronto (with an average size of ∼ 0:011 km 2 ) only corresponds to a block face, a community mailbox, or an apartment/business building, we assume the variations of exposure within a postal code could be small.…”

Section: Discussionmentioning

confidence: 99%

Exposure to Road Traffic Noise and Incidence of Acute Myocardial Infarction and Congestive Heart Failure: A Population-Based Cohort Study in Toronto, Canada

Bai

Shin

Oiamo

et al. 2020

Environ Health Perspect

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BACKGROUND: Epidemiological evidence for the association between traffic-related noise and the incidence of major cardiovascular events such as acute myocardial infarction (AMI) and congestive heart failure (CHF) is inconclusive, especially in North America. OBJECTIVES: We evaluated the associations between long-term exposure to road traffic noise and the incidence of AMI and CHF. METHODS: Our study population comprised ∼ 1 million people 30-100 years of age who lived in Toronto, Canada, from 2001 to 2015 and were free of AMI (referred to as the AMI cohort) or CHF (the CHF cohort) at baseline. Outcomes were ascertained from health administrative databases using validated algorithms. Annual average noise levels were estimated as the A-weighted equivalent sound pressure level over the 24-h period (LAeq24) and during nighttime (LAeqNight), respectively, using propagation modeling, and assigned to participants' annual six-digit postal code addresses during follow-up. We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for incident AMI and CHF in relation to LAeq24 and LAeqNight using random-effects Cox proportional hazards models adjusting for individual-and census tract-level covariates, including traffic-related air pollutants [e.g., ultrafine particles (UFPs) and nitrogen dioxide]. RESULTS: During follow-up, there were 37,441 AMI incident cases and 95,138 CHF incident cases. Each interquartile range change in LAeq24 was associated with an increased risk of incident AMI (

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“…erefore, it is necessary to further study the high-precision separation algorithm. (2) e independent combustion noise calculation method (the spectral filtering method) and the piston slap noise calculation method (the calculation method of piston slap noise based on the dynamic model) are mainly based on mathematical algorithms and models to calculate independent combustion noise and piston slap noise. e calculated results can reflect the main characteristics of combustion noise and piston slap noise.…”

Section: Calculation Methods Of Piston Slap Noise Based On Dynamic Modelmentioning

confidence: 99%

“…In order to illustrate the performance of the TVF-EMD-RobustICA method, the simulated signal is adopted in the above equation (2). First, the mixed signal is separated by the TVF-EMD method, and the separation result is shown in Figure 3.…”

Section: E Single-channel Algorithm Based On Tvf-emd Andmentioning

confidence: 99%

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Noise Source Separation of an Internal Combustion Engine Based on a Single‐Channel Algorithm

Yao

Xiang

Qian

et al. 2019

Shock and Vibration

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The separation and identification technology of noise sources is the focus and hot spot in the field of internal combustion engine noise research. Combustion noise and piston slap noise are the main noise sources of an internal combustion engine. However, both combustion noise and piston slap noise occur almost at the top dead center. They mix in the time domain and frequency domain. It is difficult to accurately and effectively separate them. A single-channel algorithm which combines time-varying filtering-based empirical mode decomposition (TVF-EMD) and robust independent component analysis (RobustICA) methods is proposed to separate them. Firstly, the TVF-EMD method is utilized to decompose the single-channel noise signal into several intrinsic mode functions (IMFs). Then, the RobustICA method is applied to extract the independent components. Finally, related prior knowledge and time-frequency analysis are employed to identify noise sources. Furthermore, the spectral filtering method and the calculation method of piston slap noise based on the dynamic model are further carried out to verify separation results. The simulation and experimental research results show the effectiveness of the proposed method.

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Façades, floors and maps – Influence of exposure measurement error on the association between transportation noise and myocardial infarction

Cited by 49 publications

References 41 publications

Traffic Noise and Mental Health: A Systematic Review and Meta-Analysis

Traffic Noise and Mental Health: A Systematic Review and Meta-Analysis

Exposure to Road Traffic Noise and Incidence of Acute Myocardial Infarction and Congestive Heart Failure: A Population-Based Cohort Study in Toronto, Canada

Noise Source Separation of an Internal Combustion Engine Based on a Single‐Channel Algorithm

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