Effects of temperature and humidity on acute myocardial infarction hospitalization in a super-aging society View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2021-11-24

AUTHORS

Takumi Higuma, Kihei Yoneyama, Michikazu Nakai, Toshiki Kaihara, Yoko Sumita, Mika Watanabe, Shunichi Doi, Yoshihiro Miyamoto, Satoshi Yasuda, Yuki Ishibashi, Masaki Izumo, Yasuhiro Tanabe, Tomoo Harada, Hisao Ogawa, Yoshihiro J. Akashi

ABSTRACT

Weather conditions affect the incidence of acute myocardial infarction (AMI). However, little is known on the association of weather temperature and humidity with AMI hospitalizations in a super-aging society. This study sought to examine this association. We included 87,911 consecutive patients with AMI admitted to Japanese acute-care hospitals between April 1, 2012 and March 31, 2015. The primary outcome was the number of AMI hospitalizations per day. Multilevel mixed-effects linear regression models were used to estimate the association of the average temperature and humidity, 1 day before hospital admission, with AMI hospitalizations, after adjusting for weather, hospital, and patient demographics.Lower temperature and humidity were associated with an increased number of AMI hospitalizations (coefficient − 0.500 [− 0.524 to − 0.474] per °C change, p < 0.001 and coefficient − 0.012 [− 0.023 to − 0.001] per % change, p = 0.039, respectively). The effects of temperature and humidity on AMI hospitalization did not differ by age and sex (all interaction p > 0.05), but differed by season. However, higher temperatures in spring (coefficient 0.089 [0.025 to 0.152] per °C change, p = 0.010) and higher humidity in autumn (coefficient 0.144 [0.121 to 0.166] per % change, p < 0.001) were risk factors for AMI hospitalization. Increased average temperatures and humidity, 1 day before hospitalization, are associated with a decreased number of AMI hospitalizations. More... »

PAGES

22832

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-021-02369-x

DOI

http://dx.doi.org/10.1038/s41598-021-02369-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1142906282

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/34819601


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27 schema:description Weather conditions affect the incidence of acute myocardial infarction (AMI). However, little is known on the association of weather temperature and humidity with AMI hospitalizations in a super-aging society. This study sought to examine this association. We included 87,911 consecutive patients with AMI admitted to Japanese acute-care hospitals between April 1, 2012 and March 31, 2015. The primary outcome was the number of AMI hospitalizations per day. Multilevel mixed-effects linear regression models were used to estimate the association of the average temperature and humidity, 1 day before hospital admission, with AMI hospitalizations, after adjusting for weather, hospital, and patient demographics.Lower temperature and humidity were associated with an increased number of AMI hospitalizations (coefficient − 0.500 [− 0.524 to − 0.474] per °C change, p < 0.001 and coefficient − 0.012 [− 0.023 to − 0.001] per % change, p = 0.039, respectively). The effects of temperature and humidity on AMI hospitalization did not differ by age and sex (all interaction p > 0.05), but differed by season. However, higher temperatures in spring (coefficient 0.089 [0.025 to 0.152] per °C change, p = 0.010) and higher humidity in autumn (coefficient 0.144 [0.121 to 0.166] per % change, p < 0.001) were risk factors for AMI hospitalization. Increased average temperatures and humidity, 1 day before hospitalization, are associated with a decreased number of AMI hospitalizations.
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36 acute care hospitals
37 acute myocardial infarction
38 acute myocardial infarction hospitalizations
39 admission
40 age
41 association
42 autumn
43 average temperature
44 conditions
45 consecutive patients
46 days
47 decreased number
48 demographics
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50 effect of temperature
51 factors
52 high humidity
53 high temperature
54 hospital
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58 incidence
59 infarction
60 linear regression models
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62 mixed-effects linear regression models
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64 myocardial infarction
65 myocardial infarction hospitalizations
66 number
67 outcomes
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