PMC:7786642 / 18572-19602 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"171","span":{"begin":680,"end":683},"obj":"Chemical"},{"id":"172","span":{"begin":793,"end":796},"obj":"Chemical"},{"id":"173","span":{"begin":56,"end":65},"obj":"Disease"}],"attributes":[{"id":"A173","pred":"tao:has_database_id","subj":"173","obj":"MESH:D003643"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"We observe a 4.4% (95% CrI: 3.7%, 5.1%) increase in the mortality risk for every 1 μg/m3 increase in the long-term exposure to PM2.5, based on model 1 (Fig. 3 \u0026 Supplemental Material Table S5). When we adjust for spatial autocorrelation the effect increases slightly but the credible intervals are wider, 5.4% (95% CrI: 2.5%, 8.4%), whereas it is similar when we adjust for confounding 4.9% (95% CrI: 3.7%, 6.2%) (Fig. 3 \u0026 Supplemental Material Table S5). The effect is weak when we account for confounders and spatial autocorrelation 1.4% (95% CrI: −2.1%, 5.1%) (Fig. 3 \u0026 Supplemental Material Table S5). The posterior probability of a positive effect is lower than observed for NO2, and equal to 0.78. The spatial relative risk follows similar patterns as the one reported in the models for NO2, with the posterior median relative risk varying from 0.24 (95% CrI: 0.12, 0.46) to 2.26 (95% CrI: 1.32, 3.85) in model 2 and from 0.30 (95% CrI: 0.15, 0.57) to 1.90 (95% CrI: 1.14, 3.17) in model 4 (Supplemental Material, Fig. S18)."}

{"project":"LitCovid-sentences","denotations":[{"id":"T158","span":{"begin":0,"end":27},"obj":"Sentence"},{"id":"T159","span":{"begin":28,"end":193},"obj":"Sentence"},{"id":"T160","span":{"begin":194,"end":319},"obj":"Sentence"},{"id":"T161","span":{"begin":320,"end":400},"obj":"Sentence"},{"id":"T162","span":{"begin":401,"end":455},"obj":"Sentence"},{"id":"T163","span":{"begin":456,"end":605},"obj":"Sentence"},{"id":"T164","span":{"begin":606,"end":703},"obj":"Sentence"},{"id":"T165","span":{"begin":704,"end":865},"obj":"Sentence"},{"id":"T166","span":{"begin":866,"end":895},"obj":"Sentence"},{"id":"T167","span":{"begin":896,"end":942},"obj":"Sentence"},{"id":"T168","span":{"begin":943,"end":972},"obj":"Sentence"},{"id":"T169","span":{"begin":973,"end":1030},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"We observe a 4.4% (95% CrI: 3.7%, 5.1%) increase in the mortality risk for every 1 μg/m3 increase in the long-term exposure to PM2.5, based on model 1 (Fig. 3 \u0026 Supplemental Material Table S5). When we adjust for spatial autocorrelation the effect increases slightly but the credible intervals are wider, 5.4% (95% CrI: 2.5%, 8.4%), whereas it is similar when we adjust for confounding 4.9% (95% CrI: 3.7%, 6.2%) (Fig. 3 \u0026 Supplemental Material Table S5). The effect is weak when we account for confounders and spatial autocorrelation 1.4% (95% CrI: −2.1%, 5.1%) (Fig. 3 \u0026 Supplemental Material Table S5). The posterior probability of a positive effect is lower than observed for NO2, and equal to 0.78. The spatial relative risk follows similar patterns as the one reported in the models for NO2, with the posterior median relative risk varying from 0.24 (95% CrI: 0.12, 0.46) to 2.26 (95% CrI: 1.32, 3.85) in model 2 and from 0.30 (95% CrI: 0.15, 0.57) to 1.90 (95% CrI: 1.14, 3.17) in model 4 (Supplemental Material, Fig. S18)."}