Heat strain and mortality effects of prolonged central European heat wave—an example of June 2019 in Poland

Błażejczyk, Krzysztof; Twardosz, Robert; Wałach, Piotr; Czarnecka, Kaja; Błażejczyk, Anna

doi:10.1007/s00484-021-02202-0

Cited by 18 publications

(11 citation statements)

References 53 publications

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“…The occurrence of such thermally anomalous months may pose a direct threat to human health and lives, cause hindrance to transport and reduce the performance of the economy (Blazejczyk and Twardosz, 2010). The most extreme events in Europe's climate to date have included the extremely cold February1929 (Gumiński, 1931) and 1956 (Dizerens et al ., 2017), the January 1963 (Hirschi and Sinha, 2007), and the unusually warm August 2003 (Chase et al ., 2006), 2010 (Sidorenkov and Sumerova, 2012), as well as the June 2019 (Blazejczyk et al ., 2022).…”

Section: Introductionmentioning

confidence: 99%

Long‐term changes in the frequency of exceptionally cold and warm months in Europe (1831–2020)

Skrzyńska

Twardosz

2023

Intl Journal of Climatology

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The onset of periods with very high or low air temperatures has aroused general interest for a long time, which is understandable since it has many dangerous effects directly affecting humans. Such perilous climatic phenomena include exceptionally cold and exceptionally warm months, which this study investigates for all Europe and for its five physico‐geographic regions over the 190‐year period of 1831–2020. Therefore, the research in this paper includes two periods characteristic of the history of climate – the late Little Ice Age (LIA) and present‐day warming. The studies are based on average monthly air temperature values from 40 weather stations in Europe. In this paper, exceptionally cold months (ECMs) or exceptionally warm months (EWMs) are considered to have occurred when the average air temperature at a station differed from the respective long‐term average by at least two standard deviations. The highlights of the study include the identification of a drop in the number of ECMs by 20 over the entire 190‐year period, and a highly statistically significant increase in EWMs by 44 between 1980 and 2020. These changes proceeded with different intensities from one physico‐geographic region of Europe to another.

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Section: Introductionmentioning

confidence: 99%

Long‐term changes in the frequency of exceptionally cold and warm months in Europe (1831–2020)

Skrzyńska

Twardosz

2023

Intl Journal of Climatology

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“…The daily maximum UTCI was selected to reflect heat stress since human beings were hypothesized to be vulnerable to extreme weather conditions. According to the thresholds of the UTCI (Błażejczyk et al, 2010 ), thermoneutral conditions referred to UTCI between 9.1 and 26.0 °C, moderate heat stress referred to UTCI between 26.1 and 32.0 °C, strong heat stress referred to UTCI between 32.1 and 38.0 °C, and very strong heat stress referred to UTCI between 38.1 and 46.0 °C. In Hong Kong, none of the days in the analysis set was having extreme heat stress (UTCI ≥ 46.1 °C).…”

Section: Methodsmentioning

confidence: 99%

“…The UTCI not only incorporates multiple meteorological variables in a non-linear way, but, more importantly, it also classifies thermal stress based on human physiological responses. Ten thermal stress classifications, ranging from extreme cold stress (UTCI ≤ − 40.0 °C), to thermoneutral conditions (UTCI between 9.1 and 26.0 °C), and extreme heat stress (UTCI > 46.0 °C), were proposed to describe the extreme weather stress experienced by humans (Błażejczyk et al, 2010 ). However, investigations regarding the association between thermal stress and health outcomes, particularly heat stress, have been mostly conducted in Europe, which generally has a temperate climate.…”

Section: Introductionmentioning

confidence: 99%

Visits to the accident and emergency department in hot season of a city with subtropical climate: association with heat stress and related meteorological variables

et al. 2022

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Background Literature reporting the association between heat stress defined by universal thermal climate index (UTCI) and emergency department visits is mainly conducted in Europe. This study aimed to investigate the association between heat stress, as defined by the UTCI, and visits to the accident and emergency department (AED) in Hong Kong, which represents a subtropical climate region. Methods A retrospective study involving 13,438,846 AED visits in the public sector from May 2000 to September 2016, excluding 2003 and 2009, was conducted in Hong Kong. Age-sex-specific ANCOVA models of daily AED rates on heat stress and prolonged heat stress, adjusting for air quality, prolonged poor air quality, typhoon, rainstorm, year, day of the week, public holiday, summer vacation, and fee charging, were used. Results On a day with strong heat stress (32.1 °C ≤ UTCI ≤ 38.0 °C), the AED visit rate (per 100,000) increased by 0.9 (95% CI: 0.5, 1.3) and 1.7 (95% CI: 1.3, 2.1) for females and males aged 19–64 and 4.1 (95% CI: 2.7, 5.4) and 4.1 (95% CI: 2.6, 5.6) for females and males aged ≥ 65, while keeping other variables constant. On a day with very strong heat stress (38.1 °C ≤ UTCI ≤ 46.0 °C), the corresponding rates increased by 0.6 (95% CI: 0.1, 1.2), 2.2 (95% CI: 1.7, 2.7), 4.9 (95% CI: 3.1, 6.7), and 4.7 (95% CI: 2.7, 6.6), respectively. The effect size of heat stress associated with AED visit rates was negligible among those aged ≤ 18. Heat stress showed the greatest effect size for males aged 19–64 among all subgroups. Conclusion Biothermal condition from heat stress was associated with the health of the citizens in a city with a subtropical climate and reflected in the increase of daily AED visit. Public health recommendations have been made accordingly for the prevention of heat-related AED visits.

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“…In contrast, Schwartz et al have revealed that with each 1 • C temperature decrease the mortality ratio rises by 0.49% and the frequency of all-cause, circulatory, coronary heart disease, and ST-segment elevation myocardial infarction (STEMI) death (4). Blazejczyk et al (5) have shown that the number of deaths attributed to a strong heat stress was five times higher and the total mortality was almost 10% higher in June 2019 than the average for the period of 2010-2018 in Poland. Also, the exposure to an acute air pressure decrease more than 10.7 hPa within 7 days before STEMI increased the rate of STEMI (odds ratio 1.12, 95% CI 1.03-1.21) (6).…”

Section: Introductionmentioning

confidence: 98%

Machine Learning Analyzed Weather Conditions as an Effective Means in the Predicting of Acute Coronary Syndrome Prevalence

Włodarczyk

Mołek

Bochenek

et al. 2022

Front. Cardiovasc. Med.

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BackgroundThe prediction of the number of acute coronary syndromes (ACSs) based on the weather conditions in the individual climate zones is not effective. We sought to investigate whether an artificial intelligence system might be useful in this prediction.MethodsBetween 2008 and 2018, a total of 105,934 patients with ACS were hospitalized in Lesser Poland Province, one covered by two meteorological stations. The predicted daily number of ACS has been estimated with the Random Forest machine learning system based on air temperature (°C), air pressure (hPa), dew point temperature (Td) (°C), relative humidity (RH) (%), wind speed (m/s), and precipitation (mm) and their daily extremes and ranges derived from the day of ACS and from 6 days before ACS.ResultsOf 840 pairwise comparisons between individual weather parameters and the number of ACS, 128 (15.2%) were significant but weak with the correlation coefficients ranged from −0.16 to 0.16. None of weather parameters correlated with the number of ACS in all the seasons and stations. The number of ACS was higher in warm front days vs. days without any front [40 (29–50) vs. 38 (27–48), respectively, P < 0.05]. The correlation between the predicted and observed daily number of ACS derived from machine learning was 0.82 with 95% CI of 0.80–0.84 (P < 0.001). The greatest importance for machine learning (range 0–1.0) among the parameters reached Td daily range with 1.00, pressure daily range with 0.875, pressure maximum daily range with 0.864, and RH maximum daily range with 0.853, whereas among the clinical parameters reached hypertension daily range with 1.00 and diabetes mellitus daily range with 0.28. For individual seasons and meteorological stations, the correlations between the predicted and observed number of ACS have ranged for spring from 0.73 to 0.77 (95% CI 0.68–0.82), for summer from 0.72 to 0.76 (95% CI 0.66–0.81), for autumn from 0.72 to 0.83 (95% CI 0.67–0.87), and for winter from 0.76 to 0.79 (95% CI 0.71–0.83) (P < 0.001 for each).ConclusionThe weather parameters have proven useful in predicting the prevalence of ACS in a temperate climate zone for all the seasons, if analyzed with an artificial intelligence system. Simultaneously, the analysis of individual weather parameters or frontal scenarios has provided only weak univariate relationships. These findings will require validation in other climatic zones.

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Heat strain and mortality effects of prolonged central European heat wave—an example of June 2019 in Poland

Cited by 18 publications

References 53 publications

Long‐term changes in the frequency of exceptionally cold and warm months in Europe (1831–2020)

Long‐term changes in the frequency of exceptionally cold and warm months in Europe (1831–2020)

Visits to the accident and emergency department in hot season of a city with subtropical climate: association with heat stress and related meteorological variables

Machine Learning Analyzed Weather Conditions as an Effective Means in the Predicting of Acute Coronary Syndrome Prevalence

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