Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality: a time-series study
文献类型：期刊论文
| 作者 | Fang, Xin1; Li, Runkui2,3; Kan, Haidong4,5,6; Bottai, Matteo1; Fang, Fang7; Cao, Yang1,8 |
| 刊名 | Bmj open
 |
| 出版日期 | 2016 |
| 卷号 | 6期号:8页码:10 |
| ISSN号 | 2044-6055 |
| DOI | 10.1136/bmjopen-2016-011487 |
| 通讯作者 | Fang, xin(xin.fang@ki.se) |
| 英文摘要 | Objective: to demonstrate an application of bayesian model averaging (bma) with generalised additive mixed models (gamm) and provide a novel modelling technique to assess the association between inhalable coarse particles (pm10) and respiratory mortality in time-series studies. design: a time-series study using regional death registry between 2009 and 2010. setting: 8 districts in a large metropolitan area in northern china. participants: 9559 permanent residents of the 8 districts who died of respiratory diseases between 2009 and 2010. main outcome measures: per cent increase in daily respiratory mortality rate (mr) per interquartile range (iqr) increase of pm10 concentration and corresponding 95% confidence interval (ci) in single-pollutant and multipollutant (including nox, co) models. results: the bayesian model averaged gamm (gamm+ bma) and the optimal gamm of pm10, multipollutants and principal components (pcs) of multipollutants showed comparable results for the effect of pm10 on daily respiratory mr, that is, one iqr increase in pm10 concentration corresponded to 1.38% vs 1.39%, 1.81% vs 1.83% and 0.87% vs 0.88% increase, respectively, in daily respiratory mr. however, gamm+ bma gave slightly but noticeable wider cis for the single-pollutant model (-1.09 to 4.28 vs -1.08 to 3.93) and the pcs-based model (-2.23 to 4.07 vs -2.03 vs 3.88). the cis of the multiple-pollutant model from two methods are similar, that is, -1.12 to 4.85 versus -1.11 versus 4.83. conclusions: the bma method may represent a useful tool for modelling uncertainty in time-series studies when evaluating the effect of air pollution on fatal health outcomes. |
| WOS关键词 | GENERALIZED ADDITIVE-MODEL ; PARTICULATE MATTER ; EUROPEAN CITIES ; SELECTION ; EXPOSURE ; SPLINES ; CHINA ; PM10 ; TEMPERATURE ; POLLUTANTS |
| WOS研究方向 | General & Internal Medicine |
| WOS类目 | Medicine, General & Internal |
| 语种 | 英语 |
| WOS记录号 | WOS:000382336700043 |
| 出版者 | BMJ PUBLISHING GROUP |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2376266 |
| 专题 | 中国科学院大学 |
| 通讯作者 | Fang, Xin |
| 作者单位 | 1.Karolinska Inst, Inst Environm Med, Biostat Unit, Stockholm, Sweden 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China 3.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China 4.Fudan Univ, Key Lab Publ Hlth Safety, Minist Educ, Sch Publ Hlth, Shanghai, Peoples R China 5.Fudan Univ, Key Lab Hlth Technol Assessment, Minist Hlth, Sch Publ Hlth, Shanghai, Peoples R China 6.Fudan Univ, Shanghai Key Lab Atmospher Particle Pollut & Prev, Shanghai, Peoples R China 7.Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden 8.Univ Orebro, Clin Epidemiol & Biostat, Sch Med Sci, Orebro, Sweden |
| 推荐引用方式 GB/T 7714 | Fang, Xin,Li, Runkui,Kan, Haidong,et al. Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality: a time-series study[J]. Bmj open,2016,6(8):10. |
| APA | Fang, Xin,Li, Runkui,Kan, Haidong,Bottai, Matteo,Fang, Fang,&Cao, Yang.(2016).Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality: a time-series study.Bmj open,6(8),10. |
| MLA | Fang, Xin,et al."Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality: a time-series study".Bmj open 6.8(2016):10. |
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来源：中国科学院大学
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