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Acute fatal effects of short-lasting extreme temperatures in Stockholm, Sweden: evidence across a century of change.

https://arctichealth.org/en/permalink/ahliterature107127
Source
Epidemiology. 2013 Nov;24(6):820-9
Publication Type
Article
Date
Nov-2013
Author
Daniel Oudin Åström
Bertil Forsberg
Sören Edvinsson
Joacim Rocklöv
Author Affiliation
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.
Source
Epidemiology. 2013 Nov;24(6):820-9
Date
Nov-2013
Language
English
Publication Type
Article
Keywords
Adolescent
Adult
Age Distribution
Aged
Aged, 80 and over
Child
Child, Preschool
Extreme Cold - adverse effects
Extreme Heat - adverse effects
Female
Humans
Infant
Male
Middle Aged
Mortality - trends
Risk
Sex Distribution
Sweden - epidemiology
Time Factors
Young Adult
Abstract
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.
PubMed ID
24051892 View in PubMed
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Acute impacts of extreme temperature exposure on emergency room admissions related to mental and behavior disorders in Toronto, Canada.

https://arctichealth.org/en/permalink/ahliterature256377
Source
J Affect Disord. 2014 Feb;155:154-61
Publication Type
Article
Date
Feb-2014
Author
Xiang Wang
Eric Lavigne
Hélène Ouellette-kuntz
Bingshu E Chen
Author Affiliation
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: wanqus@gmail.com.
Source
J Affect Disord. 2014 Feb;155:154-61
Date
Feb-2014
Language
English
Publication Type
Article
Keywords
Adolescent
Adult
Canada
Child
Child, Preschool
Cities
Emergency Service, Hospital - utilization
Extreme Cold - adverse effects
Extreme Heat - adverse effects
Female
Humans
Infant
Male
Mental Disorders - therapy
Middle Aged
Nonlinear Dynamics
Poisson Distribution
Regression Analysis
Risk
Young Adult
Abstract
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.
PubMed ID
24332428 View in PubMed
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The effect of heat waves on mortality in susceptible groups: a cohort study of a mediterranean and a northern European City.

https://arctichealth.org/en/permalink/ahliterature269401
Source
Environ Health. 2015;14:30
Publication Type
Article
Date
2015
Author
Daniel Oudin Åström
Patrizia Schifano
Federica Asta
Adele Lallo
Paola Michelozzi
Joacim Rocklöv
Bertil Forsberg
Source
Environ Health. 2015;14:30
Date
2015
Language
English
Publication Type
Article
Keywords
Aged
Aged, 80 and over
Cities - epidemiology
Cohort Studies
Diabetes Mellitus - etiology - mortality
Extreme Heat - adverse effects
Female
Heart Failure - etiology - mortality
Humans
Male
Mental Disorders - etiology - mortality
Middle Aged
Mortality
Myocardial Infarction - epidemiology - etiology
Pulmonary Disease, Chronic Obstructive - etiology - mortality
Risk
Rome - epidemiology
Sweden - epidemiology
Abstract
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.
Notes
Cites: J Epidemiol Community Health. 2012 Sep;66(9):759-6022766781
Cites: Annu Rev Med. 2009;60:457-6918817460
Cites: Epidemiology. 2013 May;24(3):439-4623462524
Cites: BMJ. 2003 Jan 25;326(7382):21912543843
Cites: J Epidemiol Community Health. 2013 Aug;67(8):707-1223618771
Cites: Epidemiology. 2013 Nov;24(6):809-1924045717
Cites: Epidemiology. 2013 Nov;24(6):820-924051892
Cites: Glob Health Action. 2014;7:2273724647126
Cites: Environ Health Perspect. 2014 Aug;122(8):811-624780880
Cites: Environ Health. 2009;8:4019758453
Cites: Environ Health. 2009;8:5019909505
Cites: CMAJ. 2010 Jul 13;182(10):1053-6019703915
Cites: Environ Res. 2010 Aug;110(6):604-1120519131
Cites: Environ Health. 2010;9:3720637065
Cites: J Epidemiol Community Health. 2011 Jan;65(1):64-7019858539
Cites: Maturitas. 2011 Jun;69(2):99-10521477954
Cites: Occup Environ Med. 2011 Jul;68(7):531-620962034
Cites: Environ Health Perspect. 2012 Jan;120(1):19-2821824855
Cites: Occup Environ Med. 2007 Dec;64(12):827-3317600037
Cites: Am J Med. 1986 Nov;81(5):795-8003776986
Cites: Occup Environ Med. 1998 Oct;55(10):651-69930084
Cites: Epidemiology. 2005 Jan;16(1):67-7215613947
Cites: Epidemiology. 2006 May;17(3):315-2316570026
Cites: Arch Intern Med. 2007 Nov 12;167(20):2170-617698676
Cites: J Epidemiol Community Health. 2008 Mar;62(3):209-1518272735
Cites: Annu Rev Public Health. 2008;29:41-5518031221
Cites: Am J Epidemiol. 2008 Sep 15;168(6):632-718663214
Cites: Am J Respir Crit Care Med. 2009 Mar 1;179(5):383-919060232
Cites: Environ Health. 2012;11:5822943217
PubMed ID
25889290 View in PubMed
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Extreme ambient temperatures and cardiorespiratory emergency room visits: assessing risk by comorbid health conditions in a time series study.

https://arctichealth.org/en/permalink/ahliterature257201
Source
Environ Health. 2014;13(1):5
Publication Type
Article
Date
2014
Author
Eric Lavigne
Antonio Gasparrini
Xiang Wang
Hong Chen
Abderrahmane Yagouti
Manon D Fleury
Sabit Cakmak
Author Affiliation
Environmental Issues Division, Public Health Agency of Canada, Ottawa, Canada. eric.lavigne@phac-aspc.gc.ca.
Source
Environ Health. 2014;13(1):5
Date
2014
Language
English
Publication Type
Article
Keywords
Air Pollutants - analysis
Carbon Monoxide - analysis
Cardiovascular Diseases - epidemiology
Comorbidity
Emergency Service, Hospital - statistics & numerical data
Extreme Cold - adverse effects
Extreme Heat - adverse effects
Humans
Nitrogen Dioxide - analysis
Ontario - epidemiology
Ozone - analysis
Particulate Matter - analysis
Respiratory Tract Diseases - epidemiology
Risk
Sulfur Dioxide - analysis
Abstract
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.
Notes
Cites: Chest. 2007 Jun;131(6):1978-8117565034
Cites: Environ Health Perspect. 2006 Sep;114(9):1331-616966084
Cites: Scand J Public Health. 2008 Jul;36(5):516-2318567653
Cites: Epidemiology. 2008 Sep;19(5):711-918520615
Cites: Am J Respir Crit Care Med. 2009 Mar 1;179(5):383-919060232
Cites: Environ Health. 2009;8:4019758453
Cites: Sci Total Environ. 2010 Aug 1;408(17):3513-820569969
Cites: J Epidemiol Community Health. 2010 Sep;64(9):753-6019692725
Cites: Stat Med. 2010 Sep 20;29(21):2224-3420812303
Cites: Environ Res. 2011 Aug;111(6):853-6021684539
Cites: J Epidemiol Community Health. 2011 Sep;65(9):829-3121097937
Cites: Clin Exp Nephrol. 2011 Oct;15(5):627-3321629994
Cites: Environ Health Perspect. 2011 Dec;119(12):1719-2521827978
Cites: Environ Health Perspect. 2012 Jan;120(1):19-2821824855
Cites: Epidemiology. 2012 Jul;23(4):594-60622531668
Cites: Environ Health. 2012;11:3622613086
Cites: Sci Total Environ. 2012 Oct 1;435-436:74-922846766
Cites: Psychiatr Serv. 2012 Nov;63(11):1150-323117515
Cites: Environ Res. 2013 Jan;120:55-6223026801
Cites: Heart. 2013 Feb;99(3):195-20323150195
Cites: Epidemiology. 2013 May;24(3):439-4623462524
Cites: Sci Total Environ. 2013 Oct 1;463-464:931-4223872247
Cites: Epidemiology. 2013 Nov;24(6):809-1924045717
Cites: Biostatistics. 2005 Jan;6(1):39-4415618526
Cites: Epidemiology. 2005 Jan;16(1):67-7215613947
Cites: J Affect Disord. 2014 Feb;155:154-6124332428
Cites: Epidemiology. 2006 May;17(3):315-2316570026
Cites: Am J Public Health. 2008 Mar;98(3):435-4518235058
PubMed ID
24484632 View in PubMed
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Heat awareness and response among Montreal residents with chronic cardiac and pulmonary disease.

https://arctichealth.org/en/permalink/ahliterature150456
Source
Can J Public Health. 2009 May-Jun;100(3):237-40
Publication Type
Article
Author
Tom Kosatsky
Julie Dufresne
Lucie Richard
Annie Renouf
Nadia Giannetti
Jean Bourbeau
Marcel Julien
Joseph Braidy
Claude Sauvé
Author Affiliation
DSP de Montréal (Public Health), Montréal, QC. Tom.Kosatsky@bccdc.ca
Source
Can J Public Health. 2009 May-Jun;100(3):237-40
Language
English
Publication Type
Article
Keywords
Adult
Aged
Aged, 80 and over
Air Conditioning
Awareness
Data Interpretation, Statistical
Extreme Heat - adverse effects
Female
Health Behavior
Health Knowledge, Attitudes, Practice
Heart Failure
Humans
Male
Middle Aged
Pulmonary Disease, Chronic Obstructive
Quebec
Questionnaires
Socioeconomic Factors
Abstract
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.
PubMed ID
19507730 View in PubMed
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Modeling and syndromic surveillance for estimating weather-induced heat-related illness.

https://arctichealth.org/en/permalink/ahliterature133913
Source
J Environ Public Health. 2011;2011:750236
Publication Type
Article
Date
2011
Author
Alexander G Perry
Michael J Korenberg
Geoffrey G Hall
Kieran M Moore
Author Affiliation
Public Health Informatics Group, Kingston, Frontenac, Lennox & Addington Public Health, 221 Portsmouth Avenue, Kingston, ON, Canada K7M 1V5. alexander.perry@queensu.ca
Source
J Environ Public Health. 2011;2011:750236
Date
2011
Language
English
Publication Type
Article
Keywords
Adolescent
Adult
Aged
Child
Emergency Service, Hospital - utilization
Extreme Heat - adverse effects
Female
Forecasting
Heat Stress Disorders - epidemiology
Humans
Humidity - adverse effects
Male
Middle Aged
Nonlinear Dynamics
Ontario - epidemiology
Poisson Distribution
Population Surveillance - methods
Regression Analysis
Retrospective Studies
Time Factors
Wind
Young Adult
Abstract
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.
Notes
Cites: Environ Health Perspect. 2001 Dec;109(12):1241-811748031
Cites: CMAJ. 2010 Jul 13;182(10):1053-6019703915
Cites: Crit Care. 2004 Feb;8(1):1-214975035
Cites: Eur J Emerg Med. 2004 Feb;11(1):3-1115167186
Cites: Occup Environ Med. 2004 Nov;61(11):893-815477282
Cites: Biol Cybern. 1989;60(4):267-762706281
Cites: J Med Syst. 1999 Feb;23(1):41-5610321379
Cites: Med Sci Sports Exerc. 2005 Jan;37(1):84-9015632673
Cites: MMWR Morb Mortal Wkly Rep. 2006 Jul 28;55(29):796-816874294
Cites: Crit Care. 2006;10(6):R15617096836
Cites: Euro Surveill. 2006;11(12):225-917370967
Cites: Am J Public Health. 2007 Nov;97(11):2028-3417901433
Cites: Environ Health. 2008;7:518226218
Cites: CJEM. 2008 Mar;10(2):114-918371248
Cites: Arch Environ Occup Health. 2007 Winter;62(4):169-7618458019
Cites: Eur J Public Health. 2008 Jun;18(3):317-2218045814
Cites: Environ Health Perspect. 2009 Jan;117(1):61-719165388
Cites: BMC Med Inform Decis Mak. 2009;9:1419232122
Cites: Environ Res. 2009 Jul;109(5):600-619423092
Cites: Environ Health. 2010;9:1220219128
Cites: Epidemiol Rev. 2002;24(2):190-20212762092
PubMed ID
21647355 View in PubMed
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Mortality related to air pollution with the moscow heat wave and wildfire of 2010.

https://arctichealth.org/en/permalink/ahliterature258959
Source
Epidemiology. 2014 May;25(3):359-64
Publication Type
Article
Date
May-2014
Author
Dmitry Shaposhnikov
Boris Revich
Tom Bellander
Getahun Bero Bedada
Matteo Bottai
Tatyana Kharkova
Ekaterina Kvasha
Elena Lezina
Tomas Lind
Eugenia Semutnikova
Göran Pershagen
Source
Epidemiology. 2014 May;25(3):359-64
Date
May-2014
Language
English
Publication Type
Article
Keywords
Adolescent
Adult
Age Distribution
Aged
Aged, 80 and over
Air Pollution - adverse effects
Cause of Death
Child
Disasters
Environmental Exposure - adverse effects
Extreme Heat - adverse effects
Female
Fires
Humans
Male
Middle Aged
Mortality
Moscow
Retrospective Studies
Risk assessment
Sex Distribution
Time Factors
Urban Population
Young Adult
Abstract
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.
Notes
Cites: J Med Toxicol. 2012 Jun;8(2):166-7522194192
Cites: Annu Rev Public Health. 2008;29:41-5518031221
Cites: Epidemiology. 2010 Jan;21(1):47-5519907335
Cites: Environ Health. 2010;9:3720637065
Cites: Environ Res. 2010 Jan;110(1):89-9519819431
Cites: Am J Public Health. 2004 Sep;94(9):1518-2015333306
Cites: Am J Public Health. 1997 Sep;87(9):1515-89314806
Cites: Am J Epidemiol. 2005 Mar 15;161(6):585-9415746475
Cites: J Air Waste Manag Assoc. 2006 Jun;56(6):709-4216805397
Cites: Environ Res. 2006 Sep;102(1):29-3516716288
Cites: Am J Epidemiol. 2008 Jun 15;167(12):1476-8518408228
Cites: Occup Environ Med. 2008 Oct;65(10):691-618417550
Cites: J Expo Sci Environ Epidemiol. 2009 May;19(4):414-2218523459
Cites: J Epidemiol Community Health. 2011 Jan;65(1):64-7019858539
Cites: Epidemiology. 2011 Jan;22(1):68-7321150355
Cites: Environ Health Perspect. 2011 Feb;119(2):210-821084239
Cites: Maturitas. 2011 Jun;69(2):99-10521477954
Cites: Environ Res. 2011 Aug;111(6):811-621601845
Cites: Occup Environ Med. 2012 Mar;69(3):158-6221849344
Cites: Environ Health Perspect. 2012 May;120(5):695-70122456494
Cites: Eur Respir J. 2013 Sep;42(3):826-4323314896
Cites: Environ Health. 2012;11:2322490779
Cites: Environ Health Perspect. 2006 Sep;114(9):1344-716966086
Comment In: Epidemiology. 2014 May;25(3):365-724713879
PubMed ID
24598414 View in PubMed
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Ozone concentration in the ground atmosphere and morbidity during extreme heat in the summer of 2010.

https://arctichealth.org/en/permalink/ahliterature289934
Source
Dokl Biol Sci. 2017 Mar; 473(1):64-68
Publication Type
Journal Article
Date
Mar-2017
Author
S N Kotelnikov
E V Stepanov
V T Ivashkin
Author Affiliation
Prokhorov General Physics Institute, Russian Academy of Sciences, Moscow, Russia. skotelnikov@mail.ru.
Source
Dokl Biol Sci. 2017 Mar; 473(1):64-68
Date
Mar-2017
Language
English
Publication Type
Journal Article
Keywords
Air Pollutants - adverse effects
Air Pollution - adverse effects
Ambulances
Atmosphere - chemistry
Environmental Exposure
Extreme Heat - adverse effects
Humans
Moscow
Ozone - chemistry - isolation & purification
Seasons
Abstract
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.
Notes
Cites: Am J Respir Crit Care Med. 2004 Nov 15;170(10):1080-7 PMID 15282198
Cites: Epidemiology. 2005 Jul;16(4):427-9 PMID 15951659
Cites: Proc Am Thorac Soc. 2007 Jul;4(3):240-6 PMID 17607006
Cites: J Appl Physiol (1985). 1999 Jan;86(1):341-9 PMID 9887149
PubMed ID
28508202 View in PubMed
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Role of Acclimatization in Weather-Related Human Mortality During the Transition Seasons of Autumn and Spring in a Thermally Extreme Mid-Latitude Continental Climate.

https://arctichealth.org/en/permalink/ahliterature274243
Source
Int J Environ Res Public Health. 2015 Dec;12(12):14974-87
Publication Type
Article
Date
Dec-2015
Author
Christopher R de Freitas
Elena A Grigorieva
Source
Int J Environ Res Public Health. 2015 Dec;12(12):14974-87
Date
Dec-2015
Language
English
Publication Type
Article
Keywords
Acclimatization
Adolescent
Adult
Age Factors
Aged
Aged, 80 and over
Cause of Death
Child
Child, Preschool
Cold Temperature - adverse effects
Cold-Shock Response
Extreme Heat - adverse effects
Female
Forecasting
Heat Stress Disorders - mortality
Humans
Infant
Infant, Newborn
Male
Middle Aged
Mortality - trends
Russia
Seasons
Sex Factors
Young Adult
Abstract
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.
Notes
Cites: Int J Biometeorol. 2014 Jul;58(5):835-4223609900
Cites: Int J Biometeorol. 2014 Dec;58(10):2129-3724633499
Cites: Eur J Appl Physiol. 2013 Oct;113(10):2587-9423877484
Cites: Circ J. 2013;77(7):1854-6123595035
Cites: PLoS One. 2013;8(5):e6397123734179
Cites: Environ Health. 2013;12:1223374669
Cites: Respir Med. 2012 Oct;106(10):1362-822789953
Cites: Bull World Health Organ. 2012 Apr 1;90(4):279-288B22511824
Cites: Epidemiology. 2011 Nov;22(6):765-7221968768
Cites: Environ Health. 2009;8:4019758453
Cites: Int J Biometeorol. 2009 Jul;53(4):307-1519238456
Cites: Eur Respir J. 2009 Aug;34(2):295-30219251790
Cites: Epidemiology. 2009 Mar;20(2):205-1319194300
Cites: Toxicol Appl Pharmacol. 2008 Nov 15;233(1):146-6118313713
Cites: Eur J Appl Physiol. 2008 Sep;104(2):321-718193268
Cites: Occup Environ Med. 2007 Feb;64(2):93-10016990293
Cites: Arch Pathol Lab Med. 2006 Sep;130(9):1297-30416948514
Cites: Int J Environ Res Public Health. 2015 Jan;12(1):439-5425568973
Cites: Int J Biometeorol. 2015 Jul;59(7):791-825234750
Cites: Environ Health Perspect. 2006 Sep;114(9):1331-616966084
Cites: Med Sci Sports Exerc. 2006 Nov;38(11):2012-2917095937
Cites: Int J Epidemiol. 2000 Apr;29(2):274-910817125
Cites: Environ Res. 2003 May;92(1):8-1312706750
Cites: Int J Biometeorol. 2003 May;47(3):166-7512687450
Cites: Epidemiol Rev. 2002;24(2):190-20212762092
Cites: BMJ. 2004 Sep 18;329(7467):64715315961
Cites: J Appl Physiol. 1967 Jan;22(1):21-66017648
Cites: J Appl Physiol. 1974 Jul;37(1):103-74836574
Cites: Int J Biometeorol. 1981 Sep;25(3):191-87275347
Cites: Int J Biometeorol. 1985 Jun;29(2):97-1194008095
Cites: J Appl Physiol (1985). 1986 Oct;61(4):1586-93781970
Cites: Lancet. 1989 Jan 14;1(8629):62-52562880
Cites: Int J Biometeorol. 1989 Oct;33(3):157-642599676
Cites: J Appl Physiol (1985). 1991 Aug;71(2):590-51938732
Cites: Sports Med. 1991 Nov;12(5):302-121763248
Cites: Br Heart J. 1993 Dec;70(6):520-37506563
Cites: J Appl Physiol (1985). 1994 Jul;77(1):216-227961236
Cites: Chest. 1996 Sep;110(3):632-68797403
Cites: Int J Biometeorol. 1998 Dec;42(2):84-89923200
Cites: Eur Respir J. 1999 Apr;13(4):844-910362051
Cites: Am J Physiol. 1956 Jan;184(1):18-2813283084
Cites: Eur J Epidemiol. 2004;19(10):905-1315575348
Cites: Occup Environ Med. 2005 Oct;62(10):702-1016169916
Cites: J Physiol Anthropol Appl Human Sci. 2005 Sep;24(5):541-916237263
PubMed ID
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