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

Bando, Masaki; Miyatake, Nobuyuki; Kataoka, Hironao; Kojima, Hiroshi; Tanaka, Naoko; Suzuki, Hiromi; Katayama, Akihiko

doi:10.3390/healthcare8010035

Cited by 6 publications

(7 citation statements)

References 26 publications

(51 reference statements)

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“…Consistent with this finding, we previously reported that the number of deaths due to renal failure was closely associated with air temperature parameters and was significantly higher in January than in other months in Gifu prefecture, which is centrally located in Japan [13]. However, the relationship between the number of deaths due to renal failure and air temperature parameters in other areas and throughout Japan remains unclear.…”

Section: Introductionsupporting

confidence: 69%

Relationship between the Number of Deaths Due to Renal Failure and Air Temperature Parameters in Hokkaido and Okinawa Prefectures, Japan

et al. 2021

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Background: The aim of the present study was to investigate the relationship between the number of deaths due to renal failure and air temperature parameters in Hokkaido (the northernmost region) and Okinawa (the southernmost region) prefectures, Japan. Methods: Monthly data on the number of deaths due to renal failure between January 2008 and December 2016 and annual population data were collected from the Hokkaido and Okinawa official prefecture websites. Air temperature parameters were obtained from the Japan Meteorological Agency. The relationship between the number of deaths due to renal failure and air temperature parameters was evaluated by an ecological study. Results: The number of deaths due to renal failure (per 100,000 people/month) in Hokkaido and Okinawa were 2.28 ± 0.30 and 1.17 ± 0.31. In Hokkaido, the number of deaths due to renal failure negatively correlated with air temperature parameters in both sexes. The number of deaths due to renal failure was significantly higher in January than from June to September in all subjects. However, in Okinawa, no significant difference was observed among months. Conclusions: The present results suggest that the relationship between the number of deaths due to renal failure and air temperature parameters differs between Hokkaido and Okinawa.

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Section: Introductionsupporting

confidence: 69%

Relationship between the Number of Deaths Due to Renal Failure and Air Temperature Parameters in Hokkaido and Okinawa Prefectures, Japan

et al. 2021

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“…A trend analysis of the number of deaths due to senility was conducted by the Jointpoint regression program, 4.8.0.1 (National Cancer Institute) [ 16 , 17 ]. To compare variations in the number of deaths due to senility with other major causes of death in Japan, we calculated the coefficient of variation (CV: standard deviation/mean) of 5 major causes of death each year between 1995 and 2018 in Japan, and compared CV (among 47 prefectures for 24 years) using the Kruskal-Wallis test and Steel test [ 18 ]. We also examined the relationship between the number of deaths due to senility and socioeconomic factors in Japan using simple and multiple regression analyses, where p < 0.05 was significant.…”

Section: Methodsmentioning

confidence: 99%

Changes and Variations in Death Due to Senility in Japan

et al. 2020

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Objective: The proportion of elderly individuals (≥65 years old) in Japan has markedly increased. However, the definition of senility in Japan is controversial. The aim of the present study was to investigate changes and variations in the number of deaths due to senility in Japan. Methods: Information on the number of deaths due to senility between 1995 and 2018 as well as other major causes of death was obtained from the Statistics Bureau of Japan official website. Changes and variations in the number of deaths due to senility were compared with other major causes of death in Japan. The relationships between the number of deaths due to senility and socioeconomic factors were also examined in an ecological study. Results: The number of deaths due to senility was 35.7 ± 23.2/one hundred thousand people/year during the observation period and has continued to increase. A change point was identified in 2004 by a Jointpoint regression analysis. Variations in the number of deaths due to senility, which were evaluated by a coefficient of variation, were significantly greater than those due to other major causes of death, i.e., malignant neoplasm, heart diseases, cerebrovascular diseases, and pneumonia. The number of elderly individuals (≥65 years old) (%) and medical bills per elderly subject (≥75 years old) correlated with the number of deaths due to senility. Conclusion: The number of deaths due to senility has been increasing, particularly since 2004. However, variations in the number of deaths due to senility were observed among all prefectures in Japan.

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“…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%

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

Cited by 6 publications

References 26 publications

Relationship between the Number of Deaths Due to Renal Failure and Air Temperature Parameters in Hokkaido and Okinawa Prefectures, Japan

Relationship between the Number of Deaths Due to Renal Failure and Air Temperature Parameters in Hokkaido and Okinawa Prefectures, Japan

Changes and Variations in Death Due to Senility in Japan

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

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