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Japanese

Title 気象関連痛 (天気痛) の疫学, 臨床的特徴と発症予測情報サービス
Subtitle
Authors 佐藤純1,2,3, 上山亮佑4, 森田清輝4, 古谷敏之4, 大塚靖子4, 畠山清佳4, 戸田真弓1,3, 戸田南帆1,3
Authors (kana)
Organization 1中部大学 生命健康科学部 理学療法学科, 2愛知医科大学 医学部 学際的痛みセンター, 3パスカル・ユニバース株式会社, 4株式会社ウェザーニューズ
Journal PAIN RESEARCH
Volume 36
Number 2
Page 75-80
Year/Month 2021 / 7
Article 報告
Publisher 日本疼痛学会
Abstract 「気象関連痛の疫学」天気や季節などの影響を受けて, 症状が悪化する痛みは総じて「気象関連痛」あるいは「天気痛」と呼ばれている. 気象変化の影響を受けやすい慢性痛としては, 片頭痛, 緊張型頭痛, 関節リウマチ, 変形性関節症, 肩こり, 腰痛症, 線維筋痛症などの報告例が多い. たとえば, 20人の片頭痛患者に14日間, 1時間ごとに痛みを記録してもらい, そのときの気温・気圧・湿度との相関をみたところ, 気温と気圧が痛みに関与したことが報告されている. 腰痛症については, 6カ月間の調査で気象に敏感な患者群では気温と気圧が低い時に痛みの訴えが強いという報告がある. 関節炎の患者調査では, 気温の低下と高湿度で痛みとこわばりが悪化することが示されている.
Practice 臨床医学:外科系
Keywords Weather, Chronic pain, Weather prediction

English

Title The epidemiological and clinical features of weather-related pain (TENKITSU) and development of prediction information service for the onset of pain
Subtitle Review Article
Authors Jun Sato1,2,3, Ryosuke Ueyama4, Kiyoteru Morita4, Toshiyuki Furuya4, Yasuko Otsuka4, Sayaka Hatakeyama4, Mayumi Toda1,3, Naho Toda1,3
Authors (kana)
Organization 1Department of Physical Therapy, College of Life and Health Sciences, Chubu University, 2Multidisciplinary Pain Center, Aichi Medical University, 3Pascal Universe Co. Ltd., 4Weathernews Inc.
Journal PAIN RESEARCH
Volume 36
Number 2
Page 75-80
Year/Month 2021 / 7
Article Report
Publisher The Japanese Association for the Study of Pain
Abstract [Abstract] Weather changes accompanied by decreases in barometric pressure are suggested to trigger meteoropathy, i.e., weather-related pain. In this paper, the epidemiological and clinical features of weather-related pain (TENKITSU) are shown and the mechanism is briefly described. From the weather pain survey 2020, it is estimated that there are at least 10 million people who have weather pain in Japan, but it seems that it is difficult to deal with it in general clinical practice. It is necessary to establish a highly accurate meteoropathy forecast in order to establish effective preventive treatments. We conducted a large-scale Internet survey and built a predictive model. The survey period was about one year, and 35 surveys were done. We analyzed the correlation between the symptom reports obtained from weather news (WN) users (157,698 in total) and the barometric pressure data. The barometric pressure change pattern that contributes to the onset of weather-related pain was indexed. We found that obvious changes in atmospheric pressure, minute changes in atmospheric pressure (micro-pressure fluctuations) which occur as a precursor to the collapse of the weather, and diurnal fluctuations in atmospheric pressure (atmospheric tide) correlate with worsening of symptoms. Therefore, we weighted the contributions of these three factors, built a model that predicts the risk of developing weather pain up to 6 days ahead every 3 hours, and started using it at WN.
Practice Clinical surgery
Keywords Weather, Chronic pain, Weather prediction
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