Extreme ambient temperatures and cardiorespiratory emergency room visits: assessing risk by comorbid health conditions in a time series study.

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. 99th percentile of temperature distribution vs. 75th 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. 1st 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.

Heat-health warning systems: a comparison of the predictive capacity of different approaches to identifying dangerously hot days.

OBJECTIVES: We compared the ability of several heat-health warning systems to predict days of heat-associated mortality using common data sets. METHODS: Heat-health warning systems initiate emergency public health interventions once forecasts have identified weather conditions to breach predetermined trigger levels. We examined 4 commonly used trigger-setting approaches: (1) synoptic classification, (2) epidemiologic assessment of the temperature-mortality relationship, (3) temperature-humidity index, and (4) physiologic classification. We applied each approach in Chicago, Illinois; London, United Kingdom; Madrid, Spain; and Montreal, Canada, to identify days expected to be associated with the highest heat-related mortality. RESULTS: We found little agreement across the approaches in which days were identified as most dangerous. In general, days identified by temperature-mortality assessment were associated with the highest excess mortality. CONCLUSIONS: Triggering of alert days and ultimately the initiation of emergency responses by a heat-health warning system varies significantly across approaches adopted to establish triggers.

Developing a harmonized heat warning and information system for Ontario: a case study in collaboration.

BACKGROUND: Heat wave early warning systems help alert decision-makers and the public to prepare for hot weather and implement preventive actions to protect health. Prior to harmonization, public health units across Ontario either used independent systems with varying methodologies for triggering and issuing public heat warnings or did not use any system. The federal government also issued heat warnings based on different criteria. During heat events, adjacent public health units in Ontario and the federal government would routinely call heat warnings at different times with separate public messages, leading to confusion. This article describes the collaborative process and key steps in developing a harmonized Heat Warning and Information System (HWIS) for Ontario. SETTING: Public health units across Ontario, Canada, collaborated with the federal and provincial government to develop the harmonized HWIS for Ontario. INTERVENTION: In 2011, stakeholders identified the need to develop a harmonized system across Ontario to improve heat warning services, warning criteria, and health messaging. Through a 5-year process facilitated by a non-governmental organization, the three levels of government collaborated to establish the Ontario HWIS. OUTCOMES: The province-wide HWIS was implemented in 2016 with the Ontario Ministry of Health and Long-Term Care's release of the harmonized HWIS Standard Operating Practice, which outlined the notification and warning process. IMPLICATIONS: The lessons learned could help spur action in other provinces and jurisdictions internationally in the development of similar health evidence-based warning systems, including in particular those for protecting public health during extreme heat events.

Towards establishing evidence-based guidelines on maximum indoor temperatures during hot weather in temperate continental climates.

Rising environmental temperatures represent a major threat to human health. The activation of heat advisories using evidence-based thresholds for high-risk outdoor ambient temperatures have been shown to be an effective strategy to save lives during hot weather. However, although the relationship between weather and human health has been widely defined by outdoor temperature, corresponding increases in indoor temperature during heat events can also be harmful to health especially in vulnerable populations. In this review, we discuss our current understanding of the relationship between outdoor temperature and human health and examine how human health can also be adversely influenced by high indoor temperatures during heat events. Our assessment of the existing literature revealed a high degree of variability in what can be considered an acceptable indoor temperature because there are differences in how different groups of people may respond physiologically and behaviorally to the same living environment. Finally, we demonstrate that both non-physiological (e.g., geographical location, urban density, building design) and physiological (e.g., sex, age, fitness, state of health) factors must be considered when defining an indoor temperature threshold for preserving human health in a warming global climate.

Increased coronary heart disease and stroke hospitalisations from ambient temperatures in Ontario.

OBJECTIVE: To assess the associations between ambient temperatures and hospitalisations for coronary heart disease (CHD) and stroke. METHODS: Our study comprised all residents living in Ontario, Canada, 1996-2013. For each of 14 health regions, we fitted a distributed lag non-linear model to estimate the cold and heat effects on hospitalisations from CHD, acute myocardial infarction (AMI), stroke and ischaemic stroke, respectively. These effects were pooled using a multivariate meta-analysis. We computed attributable hospitalisations for cold and heat, defined as temperatures above and below the optimum temperature (corresponding to the temperature of minimum morbidity) and for moderate and extreme temperatures, defined using cut-offs at the 2.5th and 97.5th temperature percentiles. RESULTS: Between 1996 and 2013, we identified 1.4 million hospitalisations from CHD and 355 837 from stroke across Ontario. On cold days with temperature corresponding to the 1st percentile of temperature distribution, we found a 9% increase in daily hospitalisations for CHD (95% CI 1% to 16%), 29% increase for AMI (95% CI 15% to 45%) and 11% increase for stroke (95% CI 1% to 22%) relative to days with an optimal temperature. High temperatures (the 99th percentile) also increased CHD hospitalisations by 6% (95% CI 1% to 11%) relative to the optimal temperature. These estimates translate into 2.49% of CHD hospitalisations attributable to cold and 1.20% from heat. Additionally, 1.71% of stroke hospitalisations were attributable to cold. Importantly, moderate temperatures, rather than extreme temperatures, yielded the most of the cardiovascular burdens from temperatures. CONCLUSIONS: Ambient temperatures, especially in moderate ranges, may be an important risk factor for cardiovascular-related hospitalisations.

Ambient Temperature and the Risk of Renal Colic: A Population-Based Study of the Impact of Demographics and Comorbidity.

PURPOSE: To examine the impact of ambient temperature on the incidence of emergency department (ED) admissions for acute renal colic and the potential influence demographics and comorbid conditions may have on this. METHODS: We conducted a population-based time series analysis using linked healthcare databases in Ontario, Canada, which included all residents, aged ≥19 years, who were admitted to an ED from April 2002 to December 2013. The primary outcome was daily number of renal colic emergency department admissions. A distributed lag nonlinear model with 21 days of lag was applied to estimate the cumulative effect of temperature on colic admissions. We estimated risks for cold and heat, defined as temperatures below and above the optimal temperature, which corresponded to the point with minimum risk of colic admissions. We conducted stratified analyses using selected demographics and comorbidities. RESULTS: During the study period, 423,396 patients presented to an ED with colic. There was a significantly increased risk of colic as ambient temperature increased (rate ratio [RR] = 1.30, 95% confidence interval [CI]: 1.20, 1.42). Subgroup analysis demonstrated an increased risk associated with heat for both genders; however, this risk was more pronounced in males with extreme heat (RR = 1.64 vs 1.22, p = 0.006). In contrast to other age groups, there was an increased risk for those in their 40s (RR = 1.42), 50s (RR = 1.54), and 60s (RR = 1.31) (p = 0.02). CONCLUSION: Increasing ambient temperature was associated with increased risk of ED visits for colic, particularly in males and those aged 40 to 69 years.

Assessment of the effect of cold and hot temperatures on mortality in Ontario, Canada: a population-based study.

BACKGROUND: Ambient high temperature is associated with death; however, heat-related risk of death has not been quantified systematically in Ontario, the most populous province in Canada. Less is known about cold-related risk in this population. Our objective was to quantify the health impact from cold and hot temperatures in Ontario. METHODS: The study population consisted of all residents of Ontario who died between Jan. 1, 1996, and Dec. 31, 2010, from any nonaccidental cause. A case-crossover analysis was applied to assess the relation between daily temperature fluctuation and deaths from nonaccidental and selected causes in cold (December-February) and warm (June-August) seasons, respectively, adjusting for various potential confounders. Risk estimates were obtained for each census division, then pooled across Ontario. We examined potential effect modification for selected comorbidities and sociodemographic characteristics. RESULTS: In warm seasons, each 5°C increase in daily mean temperature was associated with a 2.5% increase in nonaccidental deaths (95% confidence interval [CI] = 1.3% to 3.8%) on the day of exposure (lag 0). In cold seasons, each 5°C decrease in daily temperature was associated with a 3.0% (95% CI 1.8% to 4.2%) increase in nonaccidental deaths, which persisted over 7 days (lag 0-6). The cold-related effects (lag 0-6) were stronger for cardiovascular-related deaths (any cardiovascular death: 4.1%, 95% CI 2.3% to 5.9%; ischemic heart disease: 5.8%, 95% CI 3.6% to 8.1%), especially among people less than 65 years of age (8.0%, 95% CI 3.0% to 13.0%). Conversely, heat most strongly increased respiratory-related deaths during admission to hospital (26.0%, 95% CI 0% to 61.4%). Across Ontario, each 5°C change in daily temperature was estimated to induce 7 excess deaths per day in cold seasons and 4 excess deaths in warm seasons. INTERPRETATION: Heat contributed to excess deaths in Ontario, although the effect of cold weather appeared to be greater. Further work is required to better define high-risk subgroups, which might include the homeless and people with inadequately heated housing.

Hospitalizations from Hypertensive Diseases, Diabetes, and Arrhythmia in Relation to Low and High Temperatures: Population-Based Study.

Little is known about the extent to which ambient temperatures contribute to the burden of hospitalizations from hypertensive diseases, diabetes, and arrhythmia. To fill this knowledge gap, we conducted a time-series study comprising entire population of Ontario, Canada during 1996-2013. A distributed lag non-linear model was developed to estimate the cumulative effect of temperatures over a 21-day lag period. We computed the burden of hospitalizations attributable to cold and heat. Furthermore, we separated the burden into components related to mild and extreme temperatures. Compared to the temperature with minimum risk of morbidity, cold temperatures (1(st) percentile) were associated with a 37% (95% confidence interval: 5%, 78%) increase in hypertension-related hospitalizations whereas no significant association with hot temperatures (99(th) percentile) was observed. Cold and hot temperatures were also associated with a 12% (1%, 24%) and a 30% (6%, 58%) increase in diabetes-related hospitalizations, respectively. Arrhythmia was not linked to temperatures. These estimates translate into ~10% of hypertension-related hospitalizations attributable to total cold, and ~9% from mild cold. Similarly, ~11% of diabetes-related hospitalizations were due to total heat, virtually all of which were from mild heat. In conclusion, ambient temperatures, especially in moderate ranges, contribute to excess hospitalizations from hypertension and diabetes.

Association of weather and air pollution interactions on daily mortality in 12 Canadian cities.

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.