{"doi":"10.1093/aje/kwae271","title":"The association between long-term PM2.5 exposure and risk for pancreatic cancer: an application of social informatics","abstract":"There is a profound need to identify modifiable risk factors to screen and prevent pancreatic cancer. Air pollution, including fine particulate matter (PM2.5), is increasingly recognized as a risk factor for cancer. We conducted a case-control study using data from the electronic health record (EHR) of Duke University Health System, 15-year residential history, NASA satellite fine particulate matter (PM2.5), and neighborhood socioeconomic data. Using deterministic and probabilistic linkage algorithms, we linked residential history and EHR data to quantify long-term PM2.5 exposure. Logistic regression models quantified the association between a 1 interquartile range (IQR) increase in PM2.5 concentration and pancreatic cancer risk. The study included 203 cases and 5027 controls (median age of 59 years, 62% female, 26% Black). Individuals with pancreatic cancer had higher average annual exposure (9.4 μg/m3) as compared to an IQR increase in average annual PM2.5, which was associated with greater odds of pancreatic cancer (odds ratio = 1.20; 95% CI, 1.00-1.44). These findings highlight the link between elevated PM2.5 exposure and increased pancreatic cancer risk. They may inform screening strategies for high-risk populations and guide air pollution policies to mitigate exposure. This article is part of a Special Collection on Environmental Epidemiology.","journal":"American Journal of Epidemiology","year":2024,"id":443018,"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":8,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9403,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1257168,"name":"Kay Jowers","orcid":"0009-0008-8389-3997","position":1,"is_corresponding":false},{"id":464952,"name":"Zidanyue Yang","orcid":"0000-0002-4843-4313","position":2,"is_corresponding":false},{"id":1257169,"name":"Sharmistha Guha","orcid":"0000-0002-9335-0952","position":3,"is_corresponding":false},{"id":1257170,"name":"Xuan Lin","orcid":"0000-0002-7272-7271","position":4,"is_corresponding":false},{"id":380978,"name":"Sarah B. Peskoe","orcid":"0000-0002-1190-3606","position":5,"is_corresponding":false},{"id":1257667,"name":"H. N. McManus","orcid":null,"position":6,"is_corresponding":false},{"id":695558,"name":"Lisa M. McElroy","orcid":"0000-0003-2366-2579","position":7,"is_corresponding":false},{"id":791074,"name":"Mercedes A. Bravo","orcid":"0000-0003-1777-9869","position":8,"is_corresponding":false},{"id":1257171,"name":"Jerome P. Reiter","orcid":"0000-0002-8374-3832","position":9,"is_corresponding":false},{"id":218550,"name":"Eric A. Whitsel","orcid":"0000-0003-4843-3641","position":10,"is_corresponding":false},{"id":1257172,"name":"Christopher Timmins","orcid":"0000-0002-4792-4943","position":11,"is_corresponding":false},{"id":280855,"name":"Nrupen A. Bhavsar","orcid":"0000-0002-9937-5560","position":0,"is_corresponding":true}],"reference_count":38,"raw_metadata":null,"created_at":"2026-07-19T02:01:24.471942Z","pmid":"39123098","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":[]}