【4/18更新】CiNii ArticlesのCiNii Researchへの統合について

Quantitative Assessment of the Contribution of Meteorological Variables to the Prediction of the Number of Heat Stroke Patients for Tokyo

この論文をさがす

抄録

<p>This study reveals the best combination of meteorological variables for the prediction of the number of emergency transport due to heat stroke over 64 years old in Tokyo metropolis based on a generalized linear model using 2008-2016 data. Temperature, relative humidity, wind speed, and solar radiation were used as candidates of the explanatory variables. The variable selection with Akaike's information criterion (AIC) showed that all the four meteorological elements were selected for the prediction model. Additional analysis showed that the combination of daily mean temperature, maximum relative humidity, maximum wind speed, and total solar radiation as explanatory variables gives the best prediction, with approximately 19% less error than the conventional single-variable model which only uses the daily mean temperature. Finally, we quantitatively estimated the relative contribution of each variable to the prediction of the daily number of heat stroke patients using standardized partial regression coefficients. The result reveals that temperature is the largest contributor. Solar radiation is second, with approximately 20% of the temperature effect. Relative humidity and wind speed make relatively small contributions, each contributing approximately 10% and 9% of the temperature, respectively. This result provides helpful information to propose more sophisticated thermal indices to predict heat stroke risk.</p>

収録刊行物

  • SOLA

    SOLA 16 (0), 104-108, 2020

    公益社団法人 日本気象学会

被引用文献 (1)*注記

もっと見る

参考文献 (19)*注記

もっと見る

関連論文

もっと見る

関連研究データ

もっと見る

関連図書・雑誌

もっと見る

関連博士論文

もっと見る

関連プロジェクト

もっと見る

関連その他成果物

もっと見る

キーワード

詳細情報

問題の指摘

ページトップへ