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Lavigne E.,Public Health Agency of Canada | Gasparrini A.,London School of Hygiene and Tropical Medicine | Wang X.,Public Health Agency of Canada | Chen H.,Public Health Ontario | And 5 more authors.
Environmental Health: A Global Access Science Source | Year: 2014

Background: Extreme ambient temperatures are an increasing public health concern. The aim of this study was to assess if persons with comorbid health conditions were at increased risk of adverse cardiorespiratory morbidity during temperature extremes. Methods. A time series study design was applied to 292,666 and 562,738 emergency room (ER) visits for cardiovascular and respiratory diseases, respectively, that occurred in Toronto area hospitals between April 1st 2002 and March 31st 2010. Subgroups of persons with comorbid health conditions were identified. Relative risks (RRs) and their corresponding 95% confidence intervals (CIs) were estimated using a Poisson regression model with distributed lag non-linear model, and were adjusted for the confounding influence of seasonality, relative humidity, day-of-the-week, outdoor air pollutants and daily influenza ER visits. Effect modification by comorbid health conditions was tested using the relative effect modification (REM) index. Results: Stronger associations of cardiovascular disease ER visits were observed for persons with diabetes compared to persons without diabetes (REM = 1.12; 95% CI: 1.01 - 1.27) with exposure to the cumulative short term effect of extreme hot temperatures (i.e. 99§ssup§th§esup§ percentile of temperature distribution vs. 75§ssup§th§esup§ percentile). Effect modification was also found for comorbid respiratory disease (REM = 1.17; 95% CI: 1.02 - 1.44) and cancer (REM = 1.20; 95% CI: 1.02 - 1.49) on respiratory disease ER visits during short term hot temperature episodes. The effect of extreme cold temperatures (i.e. 1§ssup§st§esup§ percentile of temperature distribution vs. 25th percentile) on cardiovascular disease ER visits were stronger for individuals with comorbid cardiac diseases (REM = 1.47; 95% CI: 1.06 - 2.23) and kidney diseases (REM = 2.43; 95% CI: 1.59 - 8.83) compared to those without these conditions when cumulated over a two-week period. Conclusions: The identification of those most susceptible to temperature extremes is important for public health officials to implement adaptation measures to manage the impact of extreme temperatures on population health. © 2014 Lavigne et al.; licensee BioMed Central Ltd.

PubMed | Special Program of Sustainable Development and Health Equity, Health Canada, World Health Organization, Canadian Coalition for Green Health Care and 4 more.
Type: Journal Article | Journal: Revista panamericana de salud publica = Pan American journal of public health | Year: 2016

Extreme weather events have revealed the vulnerability of health care facilities and the extent of devastation to the community when they fail. With climate change anticipated to increase extreme weather and its impacts worldwide-severe droughts, floods, heat waves, and related vector-borne diseases-health care officials need to understand and address the vulnerabilities of their health care systems and take action to improve resiliency in ways that also meet sustainability goals. Generally, the health sector is among a countrys largest consumers of energy and a significant source of greenhouse gas emissions. Now it has the opportunity lead climate mitigation, while reducing energy, water, and other costs. This Special Report summarizes several initiatives and compares three toolkits for implementing sustainability and resiliency measures for health care facilities: the Canadian Health Care Facility Climate Change Resiliency Toolkit, the U.S. Sustainable and Climate Resilient Health Care Facilities Toolkit, and the PAHO SMART Hospitals Toolkit of the World Health Organization/Pan American Health Organization. These tools and the lessons learned can provide a critical starting point for any health system in the Americas.

Paterson J.A.,McGill University | Ford J.D.,McGill University | Ford L.B.,McGill University | Lesnikowski A.,McGill University | And 3 more authors.
BMC Public Health | Year: 2012

Background: Climate change is among the major challenges for health this century, and adaptation to manage adverse health outcomes will be unavoidable. The risks in Ontario - Canadas most populous province - include increasing temperatures, more frequent and intense extreme weather events, and alterations to precipitation regimes. Socio-economic-demographic patterns could magnify the implications climate change has for Ontario, including the presence of rapidly growing vulnerable populations, exacerbation of warming trends by heat-islands in large urban areas, and connectedness to global transportation networks. This study examines climate change adaptation in the public health sector in Ontario using information from interviews with government officials. Methods: Fifty-three semi-structured interviews were conducted, four with provincial and federal health officials and 49 with actors in public health and health relevant sectors at the municipal level. We identify adaptation efforts, barriers and opportunities for current and future intervention. Results: Results indicate recognition that climate change will affect the health of Ontarians. Health officials are concerned about how a changing climate could exacerbate existing health issues or create new health burdens, specifically extreme heat (71%), severe weather (68%) and poor air-quality (57%). Adaptation is currently taking the form of mainstreaming climate change into existing public health programs. While adaptive progress has relied on local leadership, federal support, political will, and inter-agency efforts, a lack of resources constrains the sustainability of long-term adaptation programs and the acquisition of data necessary to support effective policies. Conclusions: This study provides a snapshot of climate change adaptation and needs in the public health sector in Ontario. Public health departments will need to capitalize on opportunities to integrate climate change into policies and programs, while higher levels of government must improve efforts to support local adaptation and provide the capacity through which local adaptation can succeed. © 2012 Paterson et al.; licensee BioMed Central Ltd.

Lesnikowski A.C.,McGill University | Lesnikowski A.C.,University of British Columbia | Ford J.D.,McGill University | Berrang-Ford L.,McGill University | And 6 more authors.
Global Environmental Change | Year: 2013

Our understanding of whether adaptive capacity on a national level is being translated into adaptation policies, programs, and projects is limited. Focusing on health adaptation in Annex I Parties to the UNFCCC, we examine whether statistically significant relationships exist between regulatory, institutional, financial, and normative aspects of national-level adaptive capacity and systematically measured adaptation. Specifically, we (i) quantify adaptation actions in Annex I nations, (ii) identify potential factors that might impact progress on adaptation and select measures for these factors, and (iii) calculate statistical relationships between factors and adaptation actions across countries. Statistically significant relationships are found between progress on adaptation and engagement in international environmental governance, national environmental governance, perception of corruption in the public sector, population size, and national wealth, as well as between responsiveness to health vulnerabilities, population size and national wealth. This analysis contributes two key early empirical findings to the growing literature concerning factors facilitating or constraining adaptation. While country size and wealth are necessary for driving higher levels of adaptation, they may be insufficient in the absence of policy commitments to environmental governance. Furthermore, governance and/or incentive frameworks for environmental governance at the national level may be an important indicator of the strength of national commitments to addressing health impacts of climate change. © 2013 Elsevier Ltd.

Casati B.,Consortium Ouranos | Yagouti A.,Climate Change and Health Office | Chaumont D.,Consortium Ouranos
Journal of Applied Meteorology and Climatology | Year: 2013

Public health planning needs the support of evidence-based information on current and future climate, which could be used by health professionals and decision makers to better understand and respond to the health impacts of extreme heat. Climate models provide information regarding the expected increase in temperatures and extreme heat events with climate change and can help predict the severity of future health impacts, which can be used in the public health sector for the development of adaptation strategies to reduce heat-related morbidity and mortality. This study analyzes the evolution of extreme temperature indices specifically defined to characterize heat events associated with health risks, in the context of a changing climate. The analysis is performed by using temperature projections from the Canadian Regional Climate Model. A quantile-based statistical correction is applied to the projected temperatures, in order to reduce model biases and account for the representativeness error. Moreover, generalized Pareto distributions are used to extend the temperature distribution upper tails and extrapolate the statistical correction to extremes that are not observed in the present but that might occur in the future. The largest increase in extreme daytime temperatures occurs in southern Manitoba, Canada, where the already overly dry climate and lack of soil moisture can lead to an uncontrolled enhancement of hot extremes. The occurrence of warm nights and heat waves, on the other hand, is already large and will increase substantially in the communities of the Great Lakes region, characterized by a humid climate. Impact and adaptation studies need to account for the temperature variability due to local effects, since it can be considerably larger than the model natural variability. © 2013 American Meteorological Society.

Paterson J.,Climate Change and Health Office | Berr P.,Climate Change and Health Office | Ebi K.,ClimAdapt LLC | Varangu L.,Canadian Coalition for Green Health Care
International Journal of Environmental Research and Public Health | Year: 2014

Climate change will increase the frequency and magnitude of extreme weather events and create risks that will impact health care facilities. Health care facilities will need to assess climate change risks and adopt adaptive management strategies to be resilient, but guidance tools are lacking. In this study, a toolkit was developed for health care facility officials to assess the resiliency of their facility to climate change impacts. A mixed methods approach was used to develop climate change resiliency indicators to inform the development of the toolkit. The toolkit consists of a checklist for officials who work in areas of emergency management, facilities management and health care services and supply chain management, a facilitator’s guide for administering the checklist, and a resource guidebook to inform adaptation. Six health care facilities representing three provinces in Canada piloted the checklist. Senior level officials with expertise in the aforementioned areas were invited to review the checklist, provide feedback during qualitative interviews and review the final toolkit at a stakeholder workshop. The toolkit helps health care facility officials identify gaps in climate change preparedness, direct allocation of adaptation resources and inform strategic planning to increase resiliency to climate change © 2014 by the authors; licensee MDPI, Basel, Switzerland.

Cheng J.J.,McMaster University | Berry P.,Climate Change and Health Office
International Journal of Public Health | Year: 2013

Objectives: Many public health adaptation strategies have been identified in response to climate change. This report reviews current literature on health co-benefits and risks of these strategies to gain a better understanding of how they may affect health. Methods: A literature review was conducted electronically using English language literature from January 2000 to March 2012. Of 812 articles identified, 22 peer-reviewed articles that directly addressed health co-benefits or risks of adaptation were included in the review. Results: The co-benefits and risks identified in the literature most commonly relate to improvements in health associated with adaptation actions that affect social capital and urban design. Health co-benefits of improvements in social capital have positive influences on mental health, independently of other determinants. Risks included reinforcing existing misconceptions regarding health. Health co-benefits of urban design strategies included reduced obesity, cardiovascular disease and improved mental health through increased physical activity, cooling spaces (e.g., shaded areas), and social connectivity. Risks included pollen allergies with increased urban green space, and adverse health effects from heat events through the use of air conditioning. Conclusions: Due to the current limited understanding of the full impacts of the wide range of existing climate change adaptation strategies, further research should focus on both unintended positive and negative consequences of public health adaptation. © 2012 The Author(s).

Cheng J.J.,McMaster University | Cheng J.J.,Climate Change and Health Office | Berry P.,Climate Change and Health Office
International Journal of Public Health | Year: 2013

Objectives: This study aimed at developing a list of key human health indicators for quantifying the health impacts of climate change in Canada. Methods: A literature review was conducted in OVID Medline to identify health morbidity and mortality indicators currently used to quantify climate change impacts. Public health frameworks and other studies of climate change indicators were reviewed to identify criteria with which to evaluate the list of proposed key indicators and a rating scale was developed. Total scores for each indicator were calculated based on the rating scale. Results: A total of 77 health indicators were identified from the literature. After evaluation using the chosen criteria, 8 indicators were identified as the best for use. They include excess daily all-cause mortality due to heat, premature deaths due to air pollution (ozone and particulate matter 2.5), preventable deaths from climate change, disability-adjusted life years lost from climate change, daily all-cause mortality, daily non-accidental mortality, West Nile Disease incidence, and Lyme borreliosis incidence. Conclusions: There is need for further data and research related to health effect quantification in the area of climate change. © 2013 The Author(s).

Vanos J.K.,Environmental Health Research Bureau | Vanos J.K.,Texas Tech University | Cakmak S.,Environmental Health Research Bureau | Kalkstein L.S.,University of Miami | Yagouti A.,Climate Change and Health Office
Air Quality, Atmosphere and Health | Year: 2015

It has been well established that both meteorological attributes and air pollution concentrations affect human health outcomes. We examined all cause nonaccident mortality relationships for 28 years (1981–2008) in relation to air pollution and synoptic weather type (encompassing air mass) data in 12 Canadian cities. This study first determines the likelihood of summertime extreme air pollution events within weather types using spatial synoptic classification. Second, it examines the modifying effect of weather types on the relative risk of mortality (RR) due to daily concentrations of air pollution (nitrogen dioxide, ozone, sulfur dioxide, and particulate matter <2.5 μm). We assess both single- and two-pollutant interactions to determine dependent and independent pollutant effects using the relatively new time series technique of distributed lag nonlinear modeling (DLNM). Results display dry tropical (DT) and moist tropical plus (MT+) weathers to result in a fourfold and twofold increased likelihood, respectively, of an extreme pollution event (top 5 % of pollution concentrations throughout the 28 years) occurring. We also demonstrate statistically significant effects of single-pollutant exposure on mortality (p < 0.05) to be dependent on summer weather type, where stronger results occur in dry moderate (fair weather) and DT or MT+ weather types. The overall average single-effect RR increases due to pollutant exposure within DT and MT+ weather types are 14.9 and 11.9 %, respectively. Adjusted exposures (two-way pollutant effect estimates) generally results in decreased RR estimates, indicating that the pollutants are not independent. Adjusting for ozone significantly lowers 67 % of the single-pollutant RR estimates and reduces model variability, which demonstrates that ozone significantly controls a portion of the mortality signal from the model. Our findings demonstrate the mortality risks of air pollution exposure to differ by weather type, with increased accuracy obtained when accounting for interactive effects through adjustment for dependent pollutants using a DLNM. © 2014, The Author(s).

Mirzaei P.A.,Concordia University at Montréal | Haghighat F.,Concordia University at Montréal | Nakhaie A.A.,Concordia University at Montréal | Yagouti A.,Climate Change and Health Office | And 3 more authors.
Building and Environment | Year: 2012

Urban Heat Island (UHI) effects have caused extensive economic and health related issues to many city residents, especially the most vulnerable such as elderly people living in buildings without air conditioners or mechanical ventilation systems. To reinforce the resiliency of individuals and communities in facing extreme heat event, cities are developing reliable tools to predict the indoor thermal characteristics using available building characteristics, climate data and socio-economical factors.In this study, a novel approach is proposed to predict the indoor thermal conditions in these buildings. First, a measurement campaign is conducted to monitor indoor thermal condition within 55 buildings in most vulnerable regions on the Island of Montreal. Two models, Simplified and Advanced, are developed to predict hourly indoor dry-bulb temperatures. Both models use an advanced Artificial Neural Network (ANN) technique. The Simplified ANN Model generates a correlation between airport weather observations and monitored indoor dry-bulb temperatures. On the other hand, the Advanced Model includes ten influential parameters, which represent the effect of neighboring environment, building characteristics and its usage patterns on the indoor thermal condition. Comparison of these two predictive models is conducted on different levels of simulation and validation. The Advanced Model shows better accuracy in predicting the indoor thermal conditions, thus justifying the use of neighborhood specific parameters to forecast indoor environment condition in an urban heat island area. © 2012 Elsevier Ltd.

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