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Ambient Temperature and Injury-Related Emergency Department Visits in China and Its Provinces: A Large National Case-Crossover Study.

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Title: Ambient Temperature and Injury-Related Emergency Department Visits in China and Its Provinces: A Large National Case-Crossover Study.
Authors: Guanhao He1, Yuan Wang2, Tao Liu1, Xiao Deng2, Jianxiong Hu1, Yuliang Er2, Pengpeng Ye2, Qijiong Zhu1, Ye Jin2, Cuirong Ji2, Ziqiang Lin1, Fengrui Jing1, Leilei Duan2 duanleilei@ncncd.chinacdc.cn, Wenjun Ma1 mawj@gdiph.org.cn
Source: Environmental Health Perspectives. Jun2026, Vol. 134 Issue 2, p148-159. 12p.
Subject Terms: *Air pollution, *Climate change, *Diseases, *Temperature, Injury risk factors, Wounds & injuries, Risk assessment, Public health surveillance, Statistical models, Research funding, Statistical sampling, Logistic regression analysis, Hospital emergency services, Symptoms, Hospitals, Descriptive statistics, Crossover trials, Odds ratio, Medical appointments, Cluster sampling, Comparative studies, Data analysis software, Confidence intervals, Forecasting, Sensitivity & specificity (Statistics)
Geographic Terms: China
Abstract: BACKGROUND: Temperature-related risks on nonaccidental morbidity or mortality have been well documented. However, limited studies have investigated the injury morbidity risk and burden attributed to ambient temperature. OBJECTIVE: The current study aimed to assess the injury morbidity risk and burden attributed to the ambient temperature in China. METHODS: A time-stratified case-crossover study was conducted in 31 provincial-level administrations across mainland China, and 11.5 million injury-related emergency department visits recorded in the National Injury Surveillance System (NISS) during 2006- 2021 were included in the study. An injury case refers to a patient who takes the first visit to the outpatient or emergency department in the NISS due to an injury. Daily meteorological data were collected from the fifth generation of European ReAnalysis-Land. A two-stage approach, including a conditional logistic regression and a multilevel meta-analysis, was applied to estimate the temperature-injury association, which was then applied to assess the morbidity burden attributable to temperature. RESULTS: We observed that injury risk increased 1.2% (95%CI: 1.0%-1.4%) for a 1 °C increase in daily mean temperature, with higher risk for males, children aged 0-4, and residents in the tropical and subtropical zone. We also found that animal injury, violence and attack, and injury in agricultural areas were more susceptible to temperature. Compared to the 2020s, we projected a 5.7 times increase of injury cases and a 10.4 times of attributable fraction due to temperature change driven by global warming in the 2090s under the SSP5-8.5 scenario in China. Our findings might be informative for injury prevention in the context of climate change in China. CONCLUSION: Our findings identify susceptible populations, regions, and mechanism-specific injuries when exposed to ambient temperature, which could be informative for injury prevention in the context of climate change in China. [ABSTRACT FROM AUTHOR]
Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Ambient Temperature and Injury-Related Emergency Department Visits in China and Its Provinces: A Large National Case-Crossover Study.
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  Data: <searchLink fieldCode="AR" term="%22Guanhao+He%22">Guanhao He</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Yuan+Wang%22">Yuan Wang</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Tao+Liu%22">Tao Liu</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Xiao+Deng%22">Xiao Deng</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Jianxiong+Hu%22">Jianxiong Hu</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Yuliang+Er%22">Yuliang Er</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Pengpeng+Ye%22">Pengpeng Ye</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Qijiong+Zhu%22">Qijiong Zhu</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Ye+Jin%22">Ye Jin</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Cuirong+Ji%22">Cuirong Ji</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Ziqiang+Lin%22">Ziqiang Lin</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Fengrui+Jing%22">Fengrui Jing</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Leilei+Duan%22">Leilei Duan</searchLink><relatesTo>2</relatesTo><i> duanleilei@ncncd.chinacdc.cn</i><br /><searchLink fieldCode="AR" term="%22Wenjun+Ma%22">Wenjun Ma</searchLink><relatesTo>1</relatesTo><i> mawj@gdiph.org.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Health+Perspectives%22">Environmental Health Perspectives</searchLink>. Jun2026, Vol. 134 Issue 2, p148-159. 12p.
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  Data: *<searchLink fieldCode="DE" term="%22Air+pollution%22">Air pollution</searchLink><br />*<searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink><br />*<searchLink fieldCode="DE" term="%22Diseases%22">Diseases</searchLink><br />*<searchLink fieldCode="DE" term="%22Temperature%22">Temperature</searchLink><br /><searchLink fieldCode="DE" term="%22Injury+risk+factors%22">Injury risk factors</searchLink><br /><searchLink fieldCode="DE" term="%22Wounds+%26+injuries%22">Wounds & injuries</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Public+health+surveillance%22">Public health surveillance</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+models%22">Statistical models</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+sampling%22">Statistical sampling</searchLink><br /><searchLink fieldCode="DE" term="%22Logistic+regression+analysis%22">Logistic regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Hospital+emergency+services%22">Hospital emergency services</searchLink><br /><searchLink fieldCode="DE" term="%22Symptoms%22">Symptoms</searchLink><br /><searchLink fieldCode="DE" term="%22Hospitals%22">Hospitals</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Crossover+trials%22">Crossover trials</searchLink><br /><searchLink fieldCode="DE" term="%22Odds+ratio%22">Odds ratio</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+appointments%22">Medical appointments</searchLink><br /><searchLink fieldCode="DE" term="%22Cluster+sampling%22">Cluster sampling</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+studies%22">Comparative studies</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Forecasting%22">Forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+%26+specificity+%28Statistics%29%22">Sensitivity & specificity (Statistics)</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: BACKGROUND: Temperature-related risks on nonaccidental morbidity or mortality have been well documented. However, limited studies have investigated the injury morbidity risk and burden attributed to ambient temperature. OBJECTIVE: The current study aimed to assess the injury morbidity risk and burden attributed to the ambient temperature in China. METHODS: A time-stratified case-crossover study was conducted in 31 provincial-level administrations across mainland China, and 11.5 million injury-related emergency department visits recorded in the National Injury Surveillance System (NISS) during 2006- 2021 were included in the study. An injury case refers to a patient who takes the first visit to the outpatient or emergency department in the NISS due to an injury. Daily meteorological data were collected from the fifth generation of European ReAnalysis-Land. A two-stage approach, including a conditional logistic regression and a multilevel meta-analysis, was applied to estimate the temperature-injury association, which was then applied to assess the morbidity burden attributable to temperature. RESULTS: We observed that injury risk increased 1.2% (95%CI: 1.0%-1.4%) for a 1 °C increase in daily mean temperature, with higher risk for males, children aged 0-4, and residents in the tropical and subtropical zone. We also found that animal injury, violence and attack, and injury in agricultural areas were more susceptible to temperature. Compared to the 2020s, we projected a 5.7 times increase of injury cases and a 10.4 times of attributable fraction due to temperature change driven by global warming in the 2090s under the SSP5-8.5 scenario in China. Our findings might be informative for injury prevention in the context of climate change in China. CONCLUSION: Our findings identify susceptible populations, regions, and mechanism-specific injuries when exposed to ambient temperature, which could be informative for injury prevention in the context of climate change in China. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1021/EHP.6c00148
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      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 148
    Subjects:
      – SubjectFull: Air pollution
        Type: general
      – SubjectFull: Climate change
        Type: general
      – SubjectFull: Diseases
        Type: general
      – SubjectFull: Temperature
        Type: general
      – SubjectFull: Injury risk factors
        Type: general
      – SubjectFull: Wounds & injuries
        Type: general
      – SubjectFull: Risk assessment
        Type: general
      – SubjectFull: Public health surveillance
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      – SubjectFull: Statistical sampling
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      – SubjectFull: Logistic regression analysis
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      – SubjectFull: Hospital emergency services
        Type: general
      – SubjectFull: Symptoms
        Type: general
      – SubjectFull: Hospitals
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Crossover trials
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      – SubjectFull: Odds ratio
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      – SubjectFull: Medical appointments
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      – SubjectFull: Cluster sampling
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      – SubjectFull: Confidence intervals
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      – SubjectFull: Forecasting
        Type: general
      – SubjectFull: Sensitivity & specificity (Statistics)
        Type: general
      – SubjectFull: China
        Type: general
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      – TitleFull: Ambient Temperature and Injury-Related Emergency Department Visits in China and Its Provinces: A Large National Case-Crossover Study.
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              Text: Jun2026
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