Please see below for a complete list of papers, chapters and reports.
Association Between Road Traffic Noise and Incidence of Diabetes Mellitus and Hypertension in Toronto, Canada: A Population-Based Cohort Study
Background: Exposure to road traffic noise has been linked to cardiometabolic complications, such as elevated blood pressure and glucose dysregulation. However, epidemiologic evidence linking road traffic noise to diabetes mellitus and hypertension remains scarce. We examined associations between road traffic noise and the incidence of diabetes mellitus and hypertension in Toronto, Canada.
Methods and Results: Using the Ontario Population Health and Environment Cohort, we conducted a retrospective, population based cohort study of long-term residents of Toronto, aged 35 to 100 years, who were registered for provincial publicly funded health insurance, and were without a history of hypertension (n=701 174) or diabetes mellitus (n=914 607). Road traffic noise exposure levels were assessed by the equivalent continuous A-weighted sound pressure level (dBA) for the 24-hour day and the equivalent continuous A-weighted sound pressure level for the night (11 PM–7AM). Noise exposures were assigned to subjects according to their annual residential postal codes during the 15-year follow-up. We used random-effect Cox proportional hazards models adjusting for personal and area-level characteristics. From 2001 to 2015, each interquartile range increase in the equivalent continuous A-weighted sound pressure level (dBA) for the 24-hour day (10.0 dBA) was associated with an 8% increase in incident diabetes mellitus (95% CI, 1.07–1.09) and a 2% increase in hypertension (95% CI, 1.01–1.03). We obtained similar estimates with the equivalent continuous A-weighted sound pressure level for the night (11 PM–7AM). These results were robust to all sensitivity analyses conducted, including further adjusting for traffic-related air pollutants (ultrafine particles and nitrogen dioxide). For both hypertension and diabetes mellitus, we observed stronger associations with the equivalent continuous A-weighted sound pressure level (dBA) for the 24-hour day among women and younger adults (aged <60 years).
Conclusions: Long-term exposure to road traffic noise was associated with an increased incidence of diabetes mellitus and hypertension in Toronto. (J Am Heart Assoc. 2020;9:e013021. DOI: 10.1161/JAHA.119.013021.)
A combined emission and receptor-based approach to modelling environmental noise in urban environments
The state of practice for noise assessment utilizes established standards for emission and propagation modelling of linear and point sources. Recently, land use regression (LUR) modelling has emerged as an alternative method due to relatively low data and computing resource demands. However, a limitation of LUR modelling is that is does not account for noise attenuation and reflections by features of the built environment. This study demonstrates and validates a method that combines the two modelling frameworks to exploit their respective strengths: Emission and propagation based prediction of traffic noise, the predominant source of noise at the level of streetscapes, and a LUR-based correction for noise sources that vary on spatial scales beyond the streetscape.
Multi-criteria analysis, location-allocation modelling and stakeholder consultation identified 220 monitoring sites with optimal coverage for a 1-week sampling period. A subset of sites was used to validate a road traffic noise emission and propagation model and to specify a LUR model that predicted the contribution of other sources. The equivalent 24-h sound pressure level (LAeq) for all sites was 62.9 dBA (SD 6.4). This varied by time of day, weekday, types of roads and land uses. The traffic noise emission model demonstrated a high level of covariance with observed noise levels, with R2 values of 0.58, 0.60 and 0.59 for daytime, nighttime and 24-h periods, respectively. Combined with LUR models to correct for other noise sources, the hybrid models R2 values were 0.64, 0.71 and 0.67 for the respective time periods.
The study showed that road traffic noise emissions account for most of the variability of total environmental noise in Toronto. The combined approach to predict fine resolution noise exposures with emission and receptor-based models presents an effective alternative to noise modelling approaches based on emission and propagation or LUR modelling.
Neighbourhood Context and Composition Moderate the Noise Annoyance Dose-Response
Growing urban populations, conflicting land uses, and more traffic are exaggerating noise pollution in urban areas. Toronto is one of the cities facing challenges in tackling environmental noise. The significance of this research is based on a relative absence of literature on how noise sensitivity and annoyance are affected by non-acoustic factors, such as the built environment, demographic, and socio-economic factors. Data from a neighbourhood noise survey (n=552) in 2017 was combined with spatial data on the built environment and predicted noise exposures. Bivariate analysis and multivariate regression showed that socioeconomic and physical environment factors influence the noise annoyance responses. Specifically, residents in a neighborhood with high socioeconomic status and access to green space, and low night time noise levels, were more than twice as likely (Odds Ratio:2.35; p<0.001) to report high annoyance when evaluating the neighbourhood soundscape relative to residents of neighbourhoods with moderate socio-economic status and lower access to green space. Although nighttime noise levels appeared to be a strong predictor of neighbourhood differences in noise annoyance at home and in the neighbourhood, the findings demonstrate that noise perceptions are determined in part by neighbourhood contexts such as environmental quality and individual characteristics. For future research on noise perception the results warrant explicit consideration of shared neighbourhood perceptions of noise and environmental expectations.
Environmental Noise Study in the City of Toronto
This report summarizes the methods and findings of an environmental noise study in Toronto completed between August, 2016 and March, 2017. The study involved planning and implementation of a noise monitoring campaign under guidance from Toronto Public Health and the Noise Monitoring Project Advisory Committee. In total, 227 noise measurements of 220 different sites, each lasting a minimum of 1-week, were taken throughout the City of Toronto. The chosen sites captured areas where Toronto’s population is concentrated as well as the diversity of land uses found in the city. In addition, ‘Sites of interest’ were selected due to particular concerns surrounding noise emissions or exposures. In addition to conducting a comprehensive monitoring campaign, the study utilized modelling techniques to better understand the distribution of noise levels and population exposures in Toronto. This was based on the complementary use of a propagation model to estimate noise emissions from road traffic throughout the city and a receptor-based model to understand the influence of environmental characteristics on observed noise levels. The two approaches were combined to create maps that predict different noise levels for the entire city.
Refereed Journal Articles
Zhao, N., Prieura, j., Liu, Y., Kneeshaw, D., Lapointe, E., Paquette, A., Zinszer, K., Duprase, J., Villeneuve, P., Rainham, D., Lavigne, E., Chen, H., Van Den Bosch, M., Oiamo, T.H., Smargiassi, A. (2021). Tree characteristics and environmental noise in complex urban settings - a case study from Montreal, Canada. Environmental Research. 202: 111887.
Liu, Y., Oiamo, T.H., Rainham, D., Chen, H., Hatzopoulou, H., Brook, J., Davies, H., Goudreau, S., Smargiassi, A. (2021). Integrating random forests and propagation models for high-resolution noise mapping. Environmental Research. 195: 113357
Liu, y., Goudreau, S., Oiamo, T.H., Rainham, D., Hatzopoulou, M., Chen, H., Davies, H., Tremblay, M., Johnson, J., Bockstael, A., Leroux, T., Smargiassi, A. (2020). Comparison of land use regression and random forests models on estimating noise levels in five Canadian cities. Environmental Pollution. 256: 113367.
Oiamo, T.H., Stefanova, D. (2020). Neighbourhood context and composition moderate the noise annoyance dose-response. Canadian Acoustics. 48(2): n/a.
Shin, S., Bai, L., Oiamo, T.H., Burnett, R.T., Weichenthal, S., Jerrett, M., Kwong, J.C., Goldberg, M.S., Copes, R., Kopp, A., Chen, H. (2020). Exposure to road traffic noise and incidence of acute myocardial infarction and congestive heart failure: a population-based cohort study. Environmental Health Perspectives. 128(8): n/a.
Ng, D., Harris, A., Oiamo, T.H., Young, I. (2020). Spatial Distribution and Characteristics of Restaurant Inspection Results in Toronto, Ontario, 2017-2018. Food Protection Trends. 40(4): 232-240.
Johnson, M., Brook, J.R., Brook, R.D., Oiamo, T.H., Luginaah, I., Peters, P.A. and Spence, J.D., 2020. Traffic-Related Air Pollution and Carotid Plaque Burden in a Canadian City with Low-Level Ambient Pollution. Journal of the American Heart Association, 9(7), p.e013400.
Shin, S., Bai, L., Oiamo, T.H., Burnett, R.T., Weichenthal, S., Jerrett, M., Kwong, J.C., Goldberg, M.S., Copes, R., Kopp, A. and Chen, H., 2020. Association between road traffic noise and incidence of diabetes mellitus and hypertension in Toronto, Canada: a population‐based cohort study. Journal of the American Heart Association, 9(6), p.e013021.
Liu, Y., Goudreau, S., Oiamo, T.H., Rainham, D., Hatzopoulou, M., Chen, H., Davies, H., Tremblay, M., Johnson, J., Bockstael, A. and Leroux, T., 2020. Comparison of land use regression and random forests models on estimating noise levels in five Canadian cities. Environmental Pollution, 256, p.113367.
Orchard, T., Murie, A., Elash, H.L., Bunch, M., Middleton, C., Sadakhom, D., Oiamo, T.H. and Benoit, C., 2019. “People like us”: spatialised notions of health, stigma, power and subjectivity among women in street sex work. Culture, health & sexuality, 21(4), pp.478-494.
Oiamo, T.H., Davies, H., Rainham, D., Rinner, C., Drew, K., Macfarlane, R. 2018. A combined emission and receptor-based approach to modelling environmental noise in Toronto, Canada. Environmental Pollution, 242, 1387-1394.
Masoud, F.S., Minet, L., Liu, R., Plante, C., Goudreau, S., Oiamo, T.H., Smargiassi, A., Weichenthal, S., Hatzopoulou, M. 2018. Capturing the spatial variability of noise levels using land use regression models and comparing noise surfaces against personal exposures collected through a panel study. Environmental Research, 167, 662-672.
Orchard T., Murie, A., Elash, H., Bunch, M., Middleton, C., Sadakhom, D., Oiamo, T.H., Benoit, C. 2018. “People like us”: spatialized notions of health, stigma, power and subjectivity among women in street sex work. Culture, Health and Sexuality, 1-17.
Orchard T., Vale, J., Macphail, S., Wender, C., Oiamo T.H. 2016. “You just have to be smart”: Spatial Practices and Subjectivity among Women in Sex Work. Gender, Place and Culture, 23: 1572-1585.
Oiamo, T.H., Baxter, J. and Luginaah, I.N. 2015. Cumulative effects of noise and odour annoyances on environmental and health related quality of life. Social Science and Medicine, 146: 191-203.
Oiamo, T.H., Baxter, J., Grgicak-Mannion, A., Xu, X., Luginaah, I.N. 2015. Place effects on noise annoyance: cumulative exposures, odour annoyance and noise sensitivity as mediators of environmental context. Atmospheric Environment, 116, 183-193.
Oiamo, T.H., Johnson, M., Tang, K., Luginaah, I.N. 2015. Assessing traffic and industrial contributions to nitrogen dioxide and volatile organic compounds in a low pollution urban environment. Science of the Total Environment, 529, 149-157.
Oiamo, T.H. and Luginaah, I.N. 2013. Extricating sex and gender in air pollution research: a community based study on cardinal symptoms of exposure. International Journal of Environmental Research and Public Health, 10: 3801-3817.
Oiamo, T.H., Luginaah, I.N., Buzzelli, M., Tang, K., Xu, X., Brook, J.R. and Johnson, M. 2012. Assessing the spatial distribution of nitrogen dioxide in London, Ontario. Journal of the Air and Waste Management Association, 62: 1335-45.
Ciriello, J., Oiamo, T.H., Moreau, J.M., Turner, J.K. and Wagner, G.F. 2012. Effects of the calcium-regulating stanniocalcin-1 within the nucleus of the solitary tract on arterial pressure. Neuroscience, 207: 88-102.
Luginaah, I.N., Gorey, K.M., Oiamo, T.H., Tang, K.X., Holowaty, E.J., Hamm, C., and Wright, F.C. 2011. A geographical analysis of breast cancer clustering in Southern Ontario: generating hypotheses on environmental influences. International Journal of Environmental Health Research, 22: 232-48.
Oiamo, T.H., Atari, D.O., Luginaah, I. and Gorey, K. 2011. Air pollution and general practitioner access and utilization: a population based study in Sarnia, 'Chemical Valley,' Ontario. Environmental Health, 10:71.
Book Chapters and Encyclopedia Entries
Oiamo, T.H. Aasvang, G.M. 2020. Noise and Health. In: Kobayashi, A., Luginaah, I., Trivedi, A. (Ed.). International Encyclopedia of Human Geography, 2nd Edition. Elsevier.
Oiamo, T.H., Lafreniere, D. and Parr, J. 2016. The making of a key North American environment of mobility: the Windsor-Detroit borderland. In: Coates, C., Young, J., and Bradley, B. (Ed.). Moving Natures: Environment and Mobility in Canadian History. Calgary: University of Calgary Press and NiCHE series: Energy, Ecology, and the Environment.
Luginaah, I.N., Oiamo, T.H. and Armah, F.A. 2014. Environmental Health Geography. In: Cockerham, W.C., Dingwall, R. and Quah, S.R. (Ed.). The Wiley-Blackwell Encyclopedia of Health, Illness, Behavior, and Society. Wiley-Blackwell.
Oiamo, T.H. 2014. Ozone. In: Michalos, A.C. (Ed.). Encyclopedia of Quality of Life and Well-Being Research. Springer, Dordrecht, Netherlands. Springer, pp. 4559-4561.
Oiamo T.H., White, L.J., Johnson, M., Maoh, H. 2019. Developing a sustainability indicator weighted index for integrated urban modelling and health outcomes in SMARTPLANS. Canadian Transportation Research Forum 54th Annual Conference, Vancouver, BC, Canada.
Dimatulac, T., Maoh, H., Oiamo T.H., Johnson, M. 2019. Simulating the Future Impacts of Urban Transit System Improvements: Application to London, Ontario and Halifax, Nova Scotia. Canadian Transportation Research Forum 54th Annual Conference, Vancouver, BC, Canada.
Maoh, H., Dimatulac, T., Oiamo T.H., Johnson, M. 2019. Implementation of the SMARTPLANS Integrated Urban Model for Halifax, Nova Scotia and London, Ontario. Canadian Transportation Research Forum 54th Annual Conference, Vancouver, BC, Canada.
Maoh, H., Dimatulac, T., Oiamo T.H., Johnson, M., Stieb, D. 2019. Extending the SMARTPLANS Integrated Urban Modeling Framework to Evaluate the Impacts of Air Quality on Health Outcomes. Canadian Transportation Research Forum 54th Annual Conference, Vancouver, BC, Canada.
Oiamo T.H. and Luginaah, I.N. 2014. Traffic noise and annoyance in Windsor, Ontario: Community tolerance limits and effects of context on noise responses. Canadian Transportation Research Forum 49th Annual Conference, Windsor, ON, Canada.
Oiamo, T.H. (2021). Train yard noise and air quality (TYNAQ) study: Environmental noise final report. Final report to Health Canada.
Oiamo, T.H. (2020). Train yard noise and air quality (TYNAQ) study: Environmental noise progress report. Milestone report to Health Canada.
Stefanova, D., Jeong, CH., Brook, J.R., Evans, G., Hatzopoulou. M., Oiamo, T.H. 2019. The King Street Pilot Survey on Mobility and Environmental Perceptions. Final Report to Toronto Public Health.
Oiamo, T.H., Stefanova, D. 2018. Environmental Noise Impacts of the King Street Transit Pilot Project Summary Report. Final Report to the City of Toronto Transportation Services.
Roman, H., Raich, W., Oiamo, T.H. 2019. Economic Evaluation of Metro Vancouver’s Proposed Regulations Limiting the Emissions of Odorous Air Contaminants. Industrial Economics, Inc., Cambridge, MA, USA. Final Report prepared for Metro Vancouver, Burnaby, Canada.
Maoh, H., Oiamo, T.H., Dimutalec, T., Khan, S. 2018. Integrated Urban Modeling. SMARTPLANS Annual Report – Year 1. Final Report to Health Canada.
Maoh, H., Dimutalec, T., Khan, S., Oiamo, T.H., Maleki, M. 2018. Integrated Urban Modeling: SMARTPLANS Stakeholder Report – Year 2. Final Report to Health Canada.
Drew, K., Macfarlane, R., Oiamo, T.H., Mullaly, M., Stefanova, D., Campbell, M. 2017. How Loud is too Loud? Health Impacts of Environmental Noise in Toronto. Technical Report. Toronto Public Health.
Oiamo, T.H., Davies, H., Rainham, D., Rinner, C., Drew, K., Sabaliauskas, K., Macfarlane, R. 2017. Environmental Noise Study in the City of Toronto. Final Report to Toronto Public Health.
Oiamo, T.H., Stefanova, S., Drew, K., Macfarlane, R. 2017. Mitigation Measures and Strategies for Environmental Noise in Toronto. Final Report to Toronto Public Health.
Oiamo, T.H. 2016. Examining effects of physical features in the built environment on air pollution and environmental noise covariance. Final Report to Health Canada.
Luginaah, I.N., Buzzelli, M., Tang, K., Oiamo, T.H. 2011. Developing a walkability index based on the spatial distribution of nitrogen dioxide. Final Report to Health Canada.
Luginaah, I.N., Buzzelli, M., Tang, K., Oiamo, T.H. 2011. Assessing the distribution of nitrogen dioxide using land use regression in Ottawa and London, Ontario. Final report to Health Canada.
Oiamo, T.H., McKernan, N., Bergsma, B.M. 2009. City of London Naturalization and Restoration Manual. Parks Planning and Design, Planning and Development Department, London, Ontario.