Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant
Abstract Background While the influence of meteorology on carbon monoxide (CO) poisoning has been reported, few data are available on the association between air pollutants and the prediction of CO poisoning. Our objective is to explore meteorological and pollutant patterns associated with CO poison...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2021-03-01
|
| Series: | BMC Proceedings |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12919-021-00206-7 |
| _version_ | 1819120946413305856 |
|---|---|
| author | Hai-Lin Ruan Wang-Shen Deng Yao Wang Jian-Bing Chen Wei-Liang Hong Shan-Shan Ye Zhuo-Jun Hu |
| author_facet | Hai-Lin Ruan Wang-Shen Deng Yao Wang Jian-Bing Chen Wei-Liang Hong Shan-Shan Ye Zhuo-Jun Hu |
| author_sort | Hai-Lin Ruan |
| collection | DOAJ |
| description | Abstract Background While the influence of meteorology on carbon monoxide (CO) poisoning has been reported, few data are available on the association between air pollutants and the prediction of CO poisoning. Our objective is to explore meteorological and pollutant patterns associated with CO poisoning and to establish a predictive model. Results CO poisoning was found to be significantly associated with meteorological and pollutant patterns: low temperatures, low wind speeds, low air concentrations of sulfur dioxide (SO2) and ozone (O38h), and high daily temperature changes and ambient CO (r absolute value range: 0.079 to 0.232, all P values < 0.01). Based on the above factors, a predictive model was established: “logitPj = aj - 0.193 * temperature - 0.228 * wind speed + 0.221 * 24 h temperature change + 1.25 * CO - 0.0176 * SO2 + 0.0008 *O38h; j = 1, 2, 3, 4; a1 = -4.12, a2 = -2.93, a3 = -1.98, a4 = -0.92.” The proposed prediction model based on combined factors showed better predictive capacity than a model using only meteorological factors as a predictor. Conclusion Low temperatures, wind speed, and SO2 and high daily temperature changes, O38h, and CO are related to CO poisoning. Using both meteorological and pollutant factors as predictors could help facilitate the prevention of CO poisoning. |
| first_indexed | 2024-12-22T06:28:45Z |
| format | Article |
| id | doaj.art-b68d1c5aa7e345faa70c318e7f1bb5cd |
| institution | Directory Open Access Journal |
| issn | 1753-6561 |
| language | English |
| last_indexed | 2024-12-22T06:28:45Z |
| publishDate | 2021-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Proceedings |
| spelling | doaj.art-b68d1c5aa7e345faa70c318e7f1bb5cd2022-12-21T18:35:45ZengBMCBMC Proceedings1753-65612021-03-0115S11910.1186/s12919-021-00206-7Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutantHai-Lin Ruan0Wang-Shen Deng1Yao Wang2Jian-Bing Chen3Wei-Liang Hong4Shan-Shan Ye5Zhuo-Jun Hu6Department of Emergency, Liuzhou Worker’s Hospital, The Fourth Affiliated Hospital of Guangxi Medical UniversityDepartment of Emergency, Liuzhou Worker’s Hospital, The Fourth Affiliated Hospital of Guangxi Medical UniversityDepartment of Emergency, Liuzhou Worker’s Hospital, The Fourth Affiliated Hospital of Guangxi Medical UniversityGuangxi Liuzhou Meteorological BureauGuangxi Liuzhou Environmental Protection BureauDepartment of Emergency, Liuzhou Worker’s Hospital, The Fourth Affiliated Hospital of Guangxi Medical UniversityDepartment of Respiration, Liuzhou Worker’s Hospital, The Fourth Affiliated Hospital of Guangxi Medical UniversityAbstract Background While the influence of meteorology on carbon monoxide (CO) poisoning has been reported, few data are available on the association between air pollutants and the prediction of CO poisoning. Our objective is to explore meteorological and pollutant patterns associated with CO poisoning and to establish a predictive model. Results CO poisoning was found to be significantly associated with meteorological and pollutant patterns: low temperatures, low wind speeds, low air concentrations of sulfur dioxide (SO2) and ozone (O38h), and high daily temperature changes and ambient CO (r absolute value range: 0.079 to 0.232, all P values < 0.01). Based on the above factors, a predictive model was established: “logitPj = aj - 0.193 * temperature - 0.228 * wind speed + 0.221 * 24 h temperature change + 1.25 * CO - 0.0176 * SO2 + 0.0008 *O38h; j = 1, 2, 3, 4; a1 = -4.12, a2 = -2.93, a3 = -1.98, a4 = -0.92.” The proposed prediction model based on combined factors showed better predictive capacity than a model using only meteorological factors as a predictor. Conclusion Low temperatures, wind speed, and SO2 and high daily temperature changes, O38h, and CO are related to CO poisoning. Using both meteorological and pollutant factors as predictors could help facilitate the prevention of CO poisoning.https://doi.org/10.1186/s12919-021-00206-7CO poisoningMeteorological factorsAir pollutant levelsPrediction |
| spellingShingle | Hai-Lin Ruan Wang-Shen Deng Yao Wang Jian-Bing Chen Wei-Liang Hong Shan-Shan Ye Zhuo-Jun Hu Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant BMC Proceedings CO poisoning Meteorological factors Air pollutant levels Prediction |
| title | Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant |
| title_full | Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant |
| title_fullStr | Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant |
| title_full_unstemmed | Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant |
| title_short | Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant |
| title_sort | carbon monoxide poisoning a prediction model using meteorological factors and air pollutant |
| topic | CO poisoning Meteorological factors Air pollutant levels Prediction |
| url | https://doi.org/10.1186/s12919-021-00206-7 |
| work_keys_str_mv | AT hailinruan carbonmonoxidepoisoningapredictionmodelusingmeteorologicalfactorsandairpollutant AT wangshendeng carbonmonoxidepoisoningapredictionmodelusingmeteorologicalfactorsandairpollutant AT yaowang carbonmonoxidepoisoningapredictionmodelusingmeteorologicalfactorsandairpollutant AT jianbingchen carbonmonoxidepoisoningapredictionmodelusingmeteorologicalfactorsandairpollutant AT weilianghong carbonmonoxidepoisoningapredictionmodelusingmeteorologicalfactorsandairpollutant AT shanshanye carbonmonoxidepoisoningapredictionmodelusingmeteorologicalfactorsandairpollutant AT zhuojunhu carbonmonoxidepoisoningapredictionmodelusingmeteorologicalfactorsandairpollutant |