{"doi":"10.1093/aje/kwad089","title":"Air Pollution and Cardiovascular and Thromboembolic Events in Older Adults With High-Risk Conditions","abstract":"Little epidemiologic research has focused on pollution-related risks in medically vulnerable or marginalized groups. Using a nationwide 50% random sample of 2008-2016 Medicare Part D-eligible fee-for-service participants in the United States, we identified a cohort with high-risk conditions for cardiovascular and thromboembolic events (CTEs) and linked individuals with seasonal average zip-code-level concentrations of fine particulate matter (particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM2.5)). We assessed the relationship between seasonal PM2.5 exposure and hospitalization for each of 7 CTE-related causes using history-adjusted marginal structural models with adjustment for individual demographic and neighborhood socioeconomic variables, as well as baseline comorbidity, health behaviors, and health-service measures. We examined effect modification across geographically and demographically defined subgroups. The cohort included 1,934,453 individuals with high-risk conditions (mean age = 77 years; 60% female, 87% White). A 1-μg/m3 increase in PM2.5 exposure was significantly associated with increased risk of 6 out of 7 types of CTE hospitalization. Strong increases were observed for transient ischemic attack (hazard ratio (HR) = 1.039, 95% confidence interval (CI): 1.034, 1.044), venous thromboembolism (HR = 1.031, 95% CI: 1.027, 1.035), and heart failure (HR = 1.019, 95% CI: 1.017, 1.020). Asian Americans were found to be particularly susceptible to thromboembolic effects of PM2.5 (venous thromboembolism: HR = 1.063, 95% CI: 1.021, 1.106), while Native Americans were most vulnerable to cerebrovascular effects (transient ischemic attack: HR = 1.093, 95% CI: 1.030, 1.161).","journal":"American Journal of Epidemiology","year":2023,"id":334503,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":21,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9024,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":627623,"name":"Kevin Josey","orcid":"0000-0003-2490-6272","position":1,"is_corresponding":false},{"id":998973,"name":"Poonam Gandhi","orcid":null,"position":2,"is_corresponding":false},{"id":1062927,"name":"Jung Hyun Kim","orcid":"0000-0003-4248-3760","position":3,"is_corresponding":false},{"id":998509,"name":"Aayush Visaria","orcid":"0000-0002-2170-212X","position":4,"is_corresponding":false},{"id":915741,"name":"Benjamin R. Bates","orcid":"0000-0001-5948-1396","position":5,"is_corresponding":false},{"id":71914,"name":"Joel Schwartz","orcid":"0000-0001-6168-378X","position":6,"is_corresponding":false},{"id":1040205,"name":"David Robinson","orcid":"0000-0002-9834-9045","position":7,"is_corresponding":false},{"id":281090,"name":"Soko Setoguchi","orcid":"0000-0002-1583-752X","position":8,"is_corresponding":false},{"id":106068,"name":"Rachel C. Nethery","orcid":"0000-0001-9895-1477","position":0,"is_corresponding":true}],"reference_count":38,"raw_metadata":null,"created_at":"2026-07-19T01:09:48.843291Z","pmid":"37070398","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}