From the aDepartment of Public Health and Clinical Medicine, Division of Occupational and Environmental Medicine, Umeå University, Umeå, Sweden; bAgeing and Living Conditions Programme, Umeå University, Umeå, Sweden; cCentre for Population Studies, Umeå University, Umeå, Sweden; and dDepartment of Public Health and Clinical Medicine, Division of Epidemiology and Global Health, Umeå University, Umeå, Sweden.
Climate change is projected to increase the frequency of extreme weather events. Short-term effects of extreme hot and cold weather and their effects on mortality have been thoroughly documented, as have epidemiologic and demographic changes throughout the 20th century. We investigated whether sensitivity to episodes of extreme heat and cold has changed in Stockholm, Sweden, from the beginning of the 20th century until the present.
We collected daily mortality and temperature data for the period 1901-2009 for present-day Stockholm County, Sweden. Heat extremes were defined as days for which the 2-day moving average of mean temperature was above the 98th percentile; cold extremes were defined as days for which the 26-day moving average was below the 2nd percentile. The relationship between extreme hot/cold temperatures and all-cause mortality, stratified by decade, sex, and age, was investigated through time series modeling, adjusting for time trends.
Total daily mortality was higher during heat extremes in all decades, with a declining trend over time in the relative risk associated with heat extremes, leveling off during the last three decades. The relative risk of mortality was higher during cold extremes for the entire period, with a more dispersed pattern across decades. Unlike for heat extremes, there was no decline in the mortality with cold extremes over time.
Although the relative risk of mortality during extreme temperature events appears to have fallen, such events still pose a threat to public health.
Public Health Agency of Canada, Centre for Food-Borne, Environmental and Zoonotic Infectious Diseases, Environmental Issues Division, Canada; Faculty of Medicine, Department of Community Health and Epidemiology, Queen's University, Canada. Electronic address: firstname.lastname@example.org.
The purpose of this study was to assess the effects of extreme ambient temperature on hospital emergency room visits (ER) related to mental and behavioral illnesses in Toronto, Canada.
A time series study was conducted using health and climatic data from 2002 to 2010 in Toronto, Canada. Relative risks (RRs) for increases in emergency room (ER) visits were estimated for specific mental and behavioral diseases (MBD) after exposure to hot and cold temperatures while using the 50th percentile of the daily mean temperature as reference. Poisson regression models using a distributed lag non-linear model (DLNM) were used. We adjusted for the effects of seasonality, humidity, day-of-the-week and outdoor air pollutants.
We found a strong association between MBD ER visits and mean daily temperature at 28?C. The association was strongest within a period of 0-4 days for exposure to hot temperatures. A 29% (RR=1.29, 95% CI 1.09-1.53) increase in MBD ER vists was observed over a cumulative period of 7 days after exposure to high ambient temperature (99th percentile vs. 50th percentile). Similar associations were reported for schizophrenia, mood, and neurotic disorers. No significant associations with cold temperatures were reported.
The ecological nature and the fact that only one city was investigated.
Our findings suggest that extreme temperature poses a risk to the health and wellbeing for individuals with mental and behavior illnesses. Patient management and education may need to be improved as extreme temperatures may become more prevalent with climate change.
Climate change is projected to increase the number and intensity of extreme weather events, for example heat waves. Heat waves have adverse health effects, especially for the elderly, since chronic diseases are more frequent in that group than in the population overall. The aim of the study was to investigate mortality during heat waves in an adult population aged 50 years or over, as well as in susceptible subgroups of that population in Rome and Stockholm during the summer periods from 2000 to 2008.
We collected daily number of deaths occurring between 15th May and 15th September each year for the population above 50 as well as the susceptible subgroups. Heat wave days were defined as two or more days exceeding the city specific 95th percentile of maximum apparent temperature (MAT). The relationship between heat waves and all-cause non-accidental mortality was investigated through time series modelling, adjusting for time trends.
The percent increase in daily mortality during heat waves as compared to normal summer days was, in the 50+ population, 22% (95% Confidence Interval (CI): 18-26%) in Rome and 8% (95% CI: 3-12%) in Stockholm. Subgroup specific increase in mortality in Rome ranged from 7% (95% CI:-17-39%) among survivors of myocardial infarction to 25% in the COPD (95% CI:9-43%) and diabetes (95% CI:14-37%) subgroups. In Stockholm the range was from 10% (95% CI: 2-19%) for congestive heart failure to 33% (95% CI: 10-61%) for the psychiatric subgroup.
Mortality during heat waves increased in both Rome and Stockholm for the 50+ population as well as in the considered subgroups. It should be evaluated if protective measures should be directed towards susceptible groups, rather than the population as a whole.
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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.
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.
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.
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.
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Persons affected by chronic heart and lung disease risk illness and death through exposure to extreme ambient heat. Here we describe their knowledge and awareness of the risks, and the degree to which they practice the protective behaviours recommended by public health and meteorological authorities.
Over the course of a hot Montreal summer, chronic cardiac and/or pulmonary insufficiency patients were recruited sequentially on site or by telephone from among attendees at five Montreal university hospital clinics. A one-hour face-to-face structured interview was completed by 238 patients, of whom 78% were at least 60 years of age.
Participants were well informed about extreme heat and its impact on health. Most see themselves as vulnerable to heat, recall extreme heat advisories, and all adopt at least one recommended protective measure. Of the participants, 68% spend time in an air-conditioned space during extreme heat episodes, and more than 75% reduce their physical activity and drink extra fluids. A small minority resists recourse to air conditioning: of those without, 32% have "little confidence in buying an air conditioner" even if so advised by their caregivers, and 25% would refuse to overnight in an air-conditioned shelter during a prolonged heat wave.
These chronically ill respondents perceive themselves as susceptible to extreme heat, have confidence in prevention, and almost all adopt recommended protective behaviours. A minority resists protective messaging.
This paper compares syndromic surveillance and predictive weather-based models for estimating emergency department (ED) visits for Heat-Related Illness (HRI). A retrospective time-series analysis of weather station observations and ICD-coded HRI ED visits to ten hospitals in south eastern Ontario, Canada, was performed from April 2003 to December 2008 using hospital data from the National Ambulatory Care Reporting System (NACRS) database, ED patient chief complaint data collected by a syndromic surveillance system, and weather data from Environment Canada. Poisson regression and Fast Orthogonal Search (FOS), a nonlinear time series modeling technique, were used to construct models for the expected number of HRI ED visits using weather predictor variables (temperature, humidity, and wind speed). Estimates of HRI visits from regression models using both weather variables and visit counts captured by syndromic surveillance as predictors were slightly more highly correlated with NACRS HRI ED visits than either regression models using only weather predictors or syndromic surveillance counts.
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Prolonged high temperatures and air pollution from wildfires often occur together, and the two may interact in their effects on mortality. However, there are few data on such possible interactions.
We analyzed day-to-day variations in the number of deaths in Moscow, Russia, in relation to air pollution levels and temperature during the disastrous heat wave and wildfire of 2010. Corresponding data for the period 2006-2009 were used for comparison. Daily average levels of PM10 and ozone were obtained from several continuous measurement stations. The daily number of nonaccidental deaths from specific causes was extracted from official records. Analyses of interactions considered the main effect of temperature as well as the added effect of prolonged high temperatures and the interaction with PM10.
The major heat wave lasted for 44 days, with 24-hour average temperatures ranging from 24°C to 31°C and PM10 levels exceeding 300 µg/m on several days. There were close to 11,000 excess deaths from nonaccidental causes during this period, mainly among those older than 65 years. Increased risks also occurred in younger age groups. The most pronounced effects were for deaths from cardiovascular, respiratory, genitourinary, and nervous system diseases. Continuously increasing risks following prolonged high temperatures were apparent during the first 2 weeks of the heat wave. Interactions between high temperatures and air pollution from wildfires in excess of an additive effect contributed to more than 2000 deaths.
Interactions between high temperatures and wildfire air pollution should be considered in risk assessments regarding health consequences of climate change.
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Dependence of the population morbidity on the ground-level ozone concentration in the summer of 2010 was studied in a city with low urbanization (Vyatskie Polyany, Kirov oblast) and in Moscow. At a high air temperature and low ozone concentration, the population morbidity was not associated with these parameters in Vyatskie Polyany. When the average daily ground-level ozone concentration exceeded 60 µg/m3 for 13 successive days, the correlation coefficient between ozone concentration and the number of ambulance calls was statistically significant, r = 0.62. Heavy smoke from forest fires reduced ozone concentration, and the number of emergency calls did not increase. In Moscow, the incidence of respiratory diseases and population mortality were growing up at high ozone concentrations.
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Human mortality is closely related to natural climate-determined levels of thermal environmental stress and the resulting thermophysiological strain. Most climate-mortality research has focused on seasonal extremes during winter and summer when mortality is the highest, while relatively little attention has been paid to mortality during the transitional seasons of autumn and spring. The body acclimatizes to heat in the summer and cold in winter and readjusts through acclimatization during the transitions between the two during which time the body experiences the thermophysiological strain of readjustment. To better understand the influences of weather on mortality through the acclimatization process, the aim here is to examine the periods that link very cold and very warms seasons. The study uses the Acclimatization Thermal Strain Index (ATSI), which is a comparative measure of short-term thermophysiological impact on the body. ATSI centers on heat exchange with the body’s core via the respiratory system, which cannot be protected. The analysis is based on data for a major city in the climatic region of the Russian Far East characterized by very hot summers and extremely cold winters. The results show that although mortality peaks in winter (January) and is at its lowest in summer (August), there is not a smooth rise through autumn nor a smooth decline through spring. A secondary peak occurs in autumn (October) with a smaller jump in May. This suggests the acclimatization from warm-to-cold produces more thermophysiological strain than the transition from cold-to-warm. The study shows that ATSI is a useful metric for quantifying the extent to which biophysical adaptation plays a role in increased strain on the body during re-acclimatization and for this reason is a more appropriate climatic indictor than air temperature alone. The work gives useful bioclimatic information on risks involved in transitional seasons in regions characterized by climatic extremes. This could be handy in planning and managing health services to the public and measures that might be used to help mitigate impacts.
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