The Association Between Neighborhood Socioeconomic Disadvantage and Chronic Obstructive Pulmonary Disease

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 disadvant...

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Detalles Bibliográficos
Autores principales: Galiatsatos, Panagis, Woo, Han, Paulin, Laura M, Kind, Amy, Putcha, Nirupama, Gassett, Amanda J, Cooper, Christopher B, Dransfield, Mark T, Parekh, Trisha M, Oates, Gabriela R, Barr, R Graham, Comellas, Alejandro P, Han, Meilan K, Peters, Stephen P, Krishnan, Jerry A, Labaki, Wassim W, McCormack, Meredith C, Kaufman, Joel D, Hansel, Nadia N
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7211318/
https://www.ncbi.nlm.nih.gov/pubmed/32440110
http://dx.doi.org/10.2147/COPD.S238933
Descripción
Sumario: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.

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