Abstract

Environmental noise (originating mainly from traffic) has been implicated as a risk factor for adverse cardiovascular outcomes. Systematic reviews of the associations between noise from transportation-related sources (e.g., road, air and rail) and cardiovascular diseases concluded that individuals exposed to higher levels of noise are at increased risk for hypertension and ischemic heart disease, making exposure to traffic-related noise a potential public health problem. Therefore, it is important to understand the magnitude of exposure and to use this information to determine associated health risks.
 

As a pilot study, noise levels of 10 selected locations in Toronto were measured continuously for a full week to explore temporal variability. In addition, 30-minute samples were taken over 200 locations within the Greater Toronto Area to explore the spatial variability. The objective of this study is to explore and describe the heterogeneity of environmental noise using these samples and additional information collected by Public Health Ontario.

Acknowledgements

Thanks to Ray Copes and Hong Chen, Environmental and Occupational Health, Public Health Ontario for providing this data.
 

Please address queries about the data to Lennon Li (Lennon.li@oahpp.ca), Analytic Services Unit, Knowledge Services, Public Health Ontario.

Background

Exposure to traffic-related noise is ubiquitous in modern society. Yet, environmental noise (originating mainly from traffic) has been implicated as a risk factor for adverse cardiovascular outcomes. A systematic review of the associations between noise from transport sources (e.g., road, air and rail) and cardiovascular diseases concluded that individuals exposed to higher levels of traffic-related noise are at increased risk for hypertension and ischemic heart disease. Acute exposure to noise is hypothesized to activate sympathetic and endocrine stress, and over a longer term it may result in permanent vascular changes such as increasing stress hormones and blood pressure, which may predispose individuals to arterial hypertension.
 

Thus, exposure to traffic-related noise has the potential to pose a tremendous public health burden. Indeed, in a recent report from World Health Organization it is estimated that 3% of myocardial infarction cases (or 1629 new cases) in Germany in 1999 were due to noise from road traffic. To reduce potential health impacts that may result from environmental noise in Ontario, it is important to understand the magnitude of exposure to the population and to use this information to determine associated health risks. Unfortunately, the measurement of population exposure to environmental noise is virtually nonexistent at present in Ontario.
 

Public Health Ontario (PHO) took its initiative and collected environmental noise data in two cycles in different seasons, see next section for detailed description. Our primary objective is to understand the spatial and temporal patterns in the data collected in Cycle 1. Our secondary objective is to see how the Cycle 2 data compares with the Cycle 1 data, refer to the objective section for details.

Data collection

Ideally, measurements taken over time and at multiple locations that cover the entire area are needed. However, this needs to be balanced with time constraints, equipment safety and human resources. Two sampling strategies were used to balance these competing needs: a) convenience sampling on weeklong sites to explore temporal variability, a total of 10 sites were selected for continuous measurement for a full week. b) Lattice (regular grids) with close pairs sampling on short-term monitoring sites to explore spatial variability. A total of 70 equally spaced sites (3km apart) were selected to ensure of the coverage of Great Toronto Area, and another 130 random locations were generated for mobile sampling. To avoid systematic bias due to sampling date, Toronto is divided into 40 regular grids with approximately 5 sites per grid and sampling order of each grid is randomized. Additional 41 locations were selected within 200 meters from these 200 sites to capture spatial correlation in short distances. As a result, a total 241 locations were sampled within Greater Toronto Area with measurement of 30 minutes each during 9am-5pm on week days. Information on traffic count and land use etc. for each site was also collected.
 

A sound meter was used to measure the level of noise at each sampling site. The measurements were taken continuously (fractions of a second) for 30 minutes at mobile sampling site and a week at weeklong sampling site. The meter measures average sound pressure levels and then converts those into a log-scale decibel reading (dB). Because the measurements are continuous, the data need to be average onto different time units (e.g., seconds, minutes) for output and analysis, this average is called Leq (equivalent steady sound level of a noise energy-averaged over time, see page 3 of this document). Note that this average is not the arithmetic mean of the raw measurement data therefore it is not sensible to take the arithmetic means of the Leqs. The datasets provided here give 30 minutes average Leqs for both mobile and weeklong sampling sites using the following formula:
 

where Li = level reading i (dB) at a fraction of a second and n = total number of readings in 30 minutes. You could directly use the Leqs in the data as the outcome in the analysis.