The linkage among ambulance transports, death and climate parameters in Asahikawa City, Japan

Kataoka, Hironao; Mochimasu, Kazumi Dokai; Katayama, Akihiko; Kanda, Kanae; Sakano, Noriko; Tanaka, Keiko; Miyatake, Nobuyuki

doi:10.1007/s12199-014-0429-z

Cited by 5 publications

(5 citation statements)

References 10 publications

(23 reference statements)

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“…We previously reported a significant relationship between air temperature and the total number of deaths, but not the number of deaths stratified by causes in Sakata city [17], Takamatsu city [18], Asahikawa city [19], and all 47 prefectures of Japan [20]. The number of ambulance transports was found to be associated with air temperature, and lower air temperature (winter season) was also closely associated with a higher total number of deaths [17][18][19][20]. Therefore, an effective strategy to prevent deaths affected by air temperature is required in Japan.…”

Section: Introductionmentioning

confidence: 87%

Relationship between Air Temperature Parameters and the Number of Deaths Stratified by Cause in Gifu Prefecture, Japan

et al. 2020

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Objective: It is well known that air temperature is closely related to health outcomes. We investigated the relationship between air temperature parameters and the number of deaths stratified by cause in Gifu prefecture, Japan. Methods: The number of deaths stratified by cause in Gifu prefecture Japan between January 2007 and December 2016 was obtained from the official homepage of Gifu prefecture, Japan. Air temperature parameters (°C), i.e., the mean air temperature, mean of the highest air temperature, mean of the lowest air temperature, the highest air temperature, and the lowest air temperature during the same period in Gifu city were also obtained from the Japan Meteorological Agency official home page. The relationship between air temperature parameters and the number of deaths was evaluated in an ecological study. Results: The number of deaths due to heart disease, cerebrovascular disease, pneumonia, accidents, or renal failure in January (coldest winter season in Japan) was the highest among the months. Simple correlation analysis also demonstrated a significant and negative relationship between air temperature parameters and the number of deaths due to heart disease, cerebrovascular disease, senility, pneumonia, accidents, and renal failure. Conclusion: Lower air temperature may be associated with a higher number of deaths due to diseases in Gifu prefecture, Japan.

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Section: Introductionmentioning

confidence: 87%

Relationship between Air Temperature Parameters and the Number of Deaths Stratified by Cause in Gifu Prefecture, Japan

et al. 2020

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“…Heat waves have also been studied in depth through stratification by age group (Díaz et al 2015a), and even the effect of high temperatures on pregnant women has been analysed (Schifano et al 2013;Carolan-Olah and Frankowska 2014;Arroyo et al 2016). In addition, the impact of heat on health has been examined via other health indicators, such as hospital admissions (Mastrangelo et al 2006;Linares and Díaz 2008;Hanzlíková et al 2015), visits to primary care centres, and even emergency home care (Ng et al 2014;Kataoka et al 2015;Calkins et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Spatial variability in threshold temperatures of heat wave mortality: impact assessment on prevention plans

Carmona

Linares

Ortíz

et al. 2017

International Journal of Environmental Health Research

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Spain's current heat wave prevention plans are activated according to administrative areas. This study analyses the determination of threshold temperatures for triggering prevention-plan activation by reference to isoclimatic areas, and describes the public health benefits. We subdivided the study area - the Madrid Autonomous Region (MAR) - into three, distinct, isoclimatic areas: 'North', 'Central' and 'South', and grouped daily natural-cause mortality (ICD-10: A00-R99) in towns of over 10,000 inhabitants (2000-2009 period) accordingly. Using these three areas rather than the MAR as a whole would have resulted in a possible decrease in mortality of 73 persons (38-108) in the North area, and in aborting unnecessary activation of the plan 153 times in the Central area and 417 times in the South area. Our results indicate that extrapolating this methodology would bring benefits associated with a reduction in attributable mortality and improved effectiveness of public health interventions.

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“…We performed 2 studies; First, to confirm the association between ambulance transports and meteorological data, we performed a retrospective and statistical analysis similar to the previous reports. 6 , 7 Second, we made prediction models for daily ambulance transports using meteorological and calendarial factors and evaluated their accuracies to test the utility of the DL-based models.…”

Section: Methodsmentioning

confidence: 99%

“…In Japan, weather, or meteorological factors are related to ambulance dispatches, the number of deaths, and traumas. [2][3][4] Also, the total numbers of deaths have a relationship with air temperatures, [5][6][7][8] and winter also relates to trauma like fractures 9 and motor vehicle accidents. 10 However, there are 4 seasons in Japan with meteorological flections.…”

Section: Introductionmentioning

confidence: 99%

“…The risk factors for these diseases may vary depending on the seasons. [11][12][13] Therefore, previous studies on the relationship between the weather and ambulance dispatches have been limited to univariate analysis using quadratic functions 6,7 or multivariate analysis using regression formula with separation by seasons or months focusing on specific diseases. [2][3][4]10,11 Furthermore, some studies focused on the "chronological" changes of the meteorological factors in the former days because physical responses to environmental changes may be delayed.…”

Section: Introductionmentioning

confidence: 99%

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Prediction Model of Deep Learning for Ambulance Transports in Kesennuma City by Meteorological Data

Watanabe¹,

Narita²,

Katsuki³

et al. 2021

OAEM

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Purpose With the aging population in Japan, the prediction of ambulance transports is needed to save the limited medical resources. Some meteorological factors were risks of ambulance transports, but it is difficult to predict in a classically statistical way because Japan has 4 seasons. We tried to make prediction models for ambulance transports using the deep learning (DL) framework, Prediction One (Sony Network Communications Inc., Tokyo, Japan), with the meteorological and calendarial variables. Materials and Methods We retrospectively investigated the daily ambulance transports and meteorological data between 2017 and 2019. First, to confirm their association, we performed classically statistical analysis. Second, to test the DL framework’s utility for ambulance transports prediction, we made 3 prediction models for daily ambulance transports (total daily ambulance transports more than 5 or not, cardiopulmonary arrest (CPA), and trauma) using meteorological and calendarial factors and evaluated their accuracies by internal cross-validation. Results During the 1095 days of 3 years, the total ambulance transports were 5948, including 240 CPAs and 337 traumas. Cardiogenic CPA accounted for 72.3%, according to the Utstein classification. The relation between ambulance transports and meteorological parameters by polynomial curves were statistically obtained, but their r 2 s were small. On the other hand, all DL-based prediction models obtained satisfactory accuracies in the internal cross-validation. The areas under the curves obtained from each model were all over 0.947. Conclusion We could statistically make polynomial curves between the meteorological variables and the number of ambulance transport. We also preliminarily made DL-based prediction models. The DL-based prediction for daily ambulance transports would be used in the future, leading to solving the lack of medical resources in Japan.

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The linkage among ambulance transports, death and climate parameters in Asahikawa City, Japan

Abstract: A weak linkage among climate parameters, total ambulance transports and the number of deaths was noted in Asahikawa City, Japan. However, these associations were not as high as expected.

Cited by 5 publications

References 10 publications

Relationship between Air Temperature Parameters and the Number of Deaths Stratified by Cause in Gifu Prefecture, Japan

Relationship between Air Temperature Parameters and the Number of Deaths Stratified by Cause in Gifu Prefecture, Japan

Spatial variability in threshold temperatures of heat wave mortality: impact assessment on prevention plans

Prediction Model of Deep Learning for Ambulance Transports in Kesennuma City by Meteorological Data

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