{"doi":"10.2147/copd.s238933","title":"&lt;p&gt;The Association Between Neighborhood Socioeconomic Disadvantage and Chronic Obstructive Pulmonary Disease&lt;/p&gt;","abstract":"Rationale: Individual socioeconomic status has been shown to influence the outcomes of patients with chronic obstructive pulmonary disease (COPD). However, contextual factors may also play a role. The objective of this study is to evaluate the association between neighborhood socioeconomic disadvantage measured by the area deprivation index (ADI) and COPD-related outcomes. Methods: Residential addresses of SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS) subjects with COPD (FEV 1 /FVC < 0.70) at baseline were geocoded and linked to their respective ADI national ranking score at the census block group level. The associations between the ADI and COPD-related outcomes were evaluated by examining the contrast between participants living in the most-disadvantaged (top quintile) to the least-disadvantaged (bottom quintile) neighborhood. Regression models included adjustment for individual-level demographics, socioeconomic variables (personal income, education), exposures (smoking status, packs per year, occupational exposures), clinical characteristics (FEV 1 % predicted, body mass index) and neighborhood rural status. Results: A total of 1800 participants were included in the analysis. Participants residing in the most-disadvantaged neighborhoods had 56% higher rate of COPD exacerbation (P< 0.001), 98% higher rate of severe COPD exacerbation (P=0.001), a 1.6 point higher CAT score (P< 0.001), 3.1 points higher SGRQ (P< 0.001), and 24.6 meters less six-minute walk distance (P=0.008) compared with participants who resided in the least disadvantaged neighborhoods. Conclusion: Participants with COPD who reside in more-disadvantaged neighborhoods had worse COPD outcomes compared to those residing in less-disadvantaged neighborhoods. Neighborhood effects were independent of individual-level socioeconomic factors, suggesting that contextual factors could be used to inform intervention strategies targeting high-risk persons with COPD. Keywords: health disparities, COPD, area deprivation index","journal":"International Journal of COPD","year":2020,"id":60555,"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":61,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9389,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":321792,"name":"Han Woo","orcid":null,"position":1,"is_corresponding":false},{"id":319951,"name":"Laura M. Paulin","orcid":"0000-0003-0265-6858","position":2,"is_corresponding":false},{"id":319952,"name":"Amy Kind","orcid":"0000-0002-7183-610X","position":3,"is_corresponding":false},{"id":319953,"name":"Nirupama Putcha","orcid":"0000-0002-0688-1836","position":4,"is_corresponding":false},{"id":319954,"name":"Amanda J. Gassett","orcid":"0000-0002-0889-7460","position":5,"is_corresponding":false},{"id":250082,"name":"Christopher B. Cooper","orcid":"0000-0002-6314-0903","position":6,"is_corresponding":false},{"id":250085,"name":"Mark T. Dransfield","orcid":"0000-0002-9207-1820","position":7,"is_corresponding":false},{"id":319955,"name":"Trisha M. Parekh","orcid":"0000-0002-2930-8960","position":8,"is_corresponding":false},{"id":319956,"name":"Gabriela R. Oates","orcid":"0000-0003-4052-1524","position":9,"is_corresponding":false},{"id":24685,"name":"R. Graham Barr","orcid":"0000-0001-8021-0072","position":10,"is_corresponding":false},{"id":250081,"name":"Alejandro P. Comellas","orcid":"0000-0003-1521-7520","position":11,"is_corresponding":false},{"id":250088,"name":"MeiLan K. Han","orcid":"0000-0002-9095-4419","position":12,"is_corresponding":false},{"id":250095,"name":"Stephen P. Peters","orcid":"0000-0003-4176-7999","position":13,"is_corresponding":false},{"id":250091,"name":"Jerry A. Krishnan","orcid":"0000-0001-5525-4778","position":14,"is_corresponding":false},{"id":309293,"name":"Wassim W. Labaki","orcid":"0000-0002-3203-5537","position":15,"is_corresponding":false},{"id":313967,"name":"Meredith C. McCormack","orcid":"0000-0003-1702-3201","position":16,"is_corresponding":false},{"id":266060,"name":"Joel D. Kaufman","orcid":"0000-0003-4174-9037","position":17,"is_corresponding":false},{"id":250087,"name":"Nadia N. Hansel","orcid":"0000-0002-8740-9751","position":18,"is_corresponding":false},{"id":321791,"name":"Panagis Galiatsatos","orcid":null,"position":0,"is_corresponding":true}],"reference_count":50,"raw_metadata":null,"created_at":"2026-07-18T21:09:05.493770Z","pmid":"32440110","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":[]}