{"doi":"10.1371/journal.pone.0269650","title":"Spatial environmental factors predict cardiovascular and all-cause mortality: Results of the SPACE study","abstract":"BACKGROUND: Environmental exposures account for a growing proportion of global mortality. Large cohort studies are needed to characterize the independent impact of environmental exposures on mortality in low-income settings. METHODS: We collected data on individual and environmental risk factors for a multiethnic cohort of 50,045 individuals in a low-income region in Iran. Environmental risk factors included: ambient fine particular matter air pollution; household fuel use and ventilation; proximity to traffic; distance to percutaneous coronary intervention (PCI) center; socioeconomic environment; population density; local land use; and nighttime light exposure. We developed a spatial survival model to estimate the independent associations between these environmental exposures and all-cause and cardiovascular mortality. FINDINGS: Several environmental factors demonstrated associations with mortality after adjusting for individual risk factors. Ambient fine particulate matter air pollution predicted all-cause mortality (per μg/m3, HR 1.20, 95% CI 1.07, 1.36) and cardiovascular mortality (HR 1.17, 95% CI 0.98, 1.39). Biomass fuel use without chimney predicted all-cause mortality (reference = gas, HR 1.23, 95% CI 0.99, 1.53) and cardiovascular mortality (HR 1.36, 95% CI 0.99, 1.87). Kerosene fuel use without chimney predicted all-cause mortality (reference = gas, HR 1.09, 95% CI 0.97, 1.23) and cardiovascular mortality (HR 1.19, 95% CI 1.01, 1.41). Distance to PCI center predicted all-cause mortality (per 10km, HR 1.01, 95% CI 1.004, 1.022) and cardiovascular mortality (HR 1.02, 95% CI 1.004, 1.031). Additionally, proximity to traffic predicted all-cause mortality (HR 1.13, 95% CI 1.01, 1.27). In a separate validation cohort, the multivariable model effectively predicted both all-cause mortality (AUC 0.76) and cardiovascular mortality (AUC 0.81). Population attributable fractions demonstrated a high mortality burden attributable to environmental exposures. INTERPRETATION: Several environmental factors predicted cardiovascular and all-cause mortality, independent of each other and of individual risk factors. Mortality attributable to environmental factors represents a critical opportunity for targeted policies and programs.","journal":"PLoS ONE","year":2022,"id":269678,"datarank":0.41588830833596724,"base_score":2.772588722239781,"endowment":2.772588722239781,"self_citation_contribution":0.41588830833596724,"citation_network_contribution":0.0,"self_endowment_contribution":0.41588830833596724,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":15,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7245,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":484866,"name":"Mahdi Nalini","orcid":"0000-0002-7464-9756","position":1,"is_corresponding":false},{"id":247795,"name":"Samrachana Adhikari","orcid":"0000-0001-9954-5999","position":2,"is_corresponding":false},{"id":786797,"name":"Jackie Szymonifka","orcid":"0000-0001-6114-6175","position":3,"is_corresponding":false},{"id":48371,"name":"Arash Etemadi","orcid":"0000-0002-3458-1072","position":4,"is_corresponding":false},{"id":109603,"name":"Farin Kamangar","orcid":"0000-0003-4169-7978","position":5,"is_corresponding":false},{"id":275785,"name":"Masoud Khoshnia","orcid":"0000-0001-7352-8058","position":6,"is_corresponding":false},{"id":933364,"name":"Tyler McChane","orcid":null,"position":7,"is_corresponding":false},{"id":39080,"name":"Akram Pourshams","orcid":"0000-0002-7950-3983","position":8,"is_corresponding":false},{"id":275784,"name":"Hossein Poustchi","orcid":"0000-0003-4566-3628","position":9,"is_corresponding":false},{"id":22794,"name":"Sadaf G Sepanlou","orcid":"0000-0002-3669-5129","position":10,"is_corresponding":false},{"id":217938,"name":"Christian C. Abnet","orcid":"0000-0002-3008-7843","position":11,"is_corresponding":false},{"id":241828,"name":"Neal D. Freedman","orcid":"0000-0003-0074-1098","position":12,"is_corresponding":false},{"id":265963,"name":"Paolo Boffetta","orcid":"0000-0002-3811-2791","position":13,"is_corresponding":false},{"id":275792,"name":"Reza Malekzadeh","orcid":"0000-0002-9820-6335","position":14,"is_corresponding":false},{"id":300673,"name":"Rajesh Vedanthan","orcid":"0000-0001-7138-2382","position":15,"is_corresponding":false},{"id":932902,"name":"Michael Hadley","orcid":"0000-0002-3794-7877","position":0,"is_corresponding":true}],"reference_count":35,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:27:22.602796Z","pmid":"35749347","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":[]}