Evidence map›Paper›PMID 38681549›Full record

ArticleHeliyon2024

Associations of ambient temperature with the CO poisoning risk in China.

Xiao Deng, Ye Jin, Yuan Yuan, Yuan Wang, Pengpeng Ye, Chengye Sun, Leilei Duan

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Xiao DengNational Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, 10050, China.
Ye JinNational Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 10050, China.
Yuan YuanNational Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, 10050, China.
Yuan WangNational Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 10050, China.
Pengpeng YeNational Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 10050, China.
Chengye SunNational Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, 10050, China.
Leilei DuanNational Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 10050, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although studies have explored the relationship between temperature and CO poisoning, the results are not consistent, and there is still a lack of early warning criteria of temperature related to CO poisoning. In order to comprehensively study the exposure-response relationship between daily average temperature and CO poisoning, and to further explore the early warning criteria of temperature related to CO poisoning, we used daily cases of CO poisoning in 31 National Injury Surveillance System (NISS) surveillance sites in seven administrative geographical regions of China and daily meteorological data obtained from the China Meteorological Science Data Sharing Service Platform from 2009 to 2019 to do the analysis. Daily meteorological data of 698 weather stations across China were interpolated at a 0.01° × 0.01°spatial resolution, which were then applied to extract the daily meteorological data of all included NISS sites. The Distributed Lag Non-linear Model (DLNM) model was applied to estimate the exposure-response associations (relative risk, RR) of daily mean temperature with CO poisoning, which was then further used to identify early warning criteria of temperature related to CO poisoning. A total of 10,618 CO poisoning cases were included in this study, with an average of 0.4 cases per day. There was generally a reverse J-shaped association between temperature and CO poisoning risk, indicating that both low and high temperature may increase the risk of CO poisoning, but low temperature usually has a longer lagged effects than high temperature. Spatialy, the exposure-response associations between temperatue and CO poisoning largely varied among regions, with greater effects of low temperatures in Southern China than in Northern China. The cumulative effects (RR, lag0-6 days) of 10 % percentile temperature ranged from 1.13 (95%CI: 1.01,1.26) in East China to 1.73 (95%CI:1.63,1.83) in South China. We also observed significant spatial variations in the early warning criteria of temperature related to CO poisoning across China. However, the patterns of high temperature effects on CO poisoning and the warning criteria of high temperature were mixed across China. In conclusions, both low temperature and high temperature may increase the risk of CO poisoning in China, and the effect of low temperature is more obvious, especially in South China, Northeast China, and North China. In addition, there is an urgent need to establish air temperature early warning and grading criteria for CO poisoning in different areas of China.

Identifiers

PMID38681549
PMCPMC11052907

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.