Jarrod E. Dalton, PhD; Adam T. Perzynski, PhD; David A. Zidar, MD; Michael B. Rothberg, MD, MPH; Claudia J. Coulton, PhD; Alex T. Milinovich, BA; Douglas Einstadter, MD, MPH; James K. Karichu, PhD; Neal V. Dawson, MD
Disclaimer: The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.
Grant Support: This work was supported by the Clinical and Translational Science Collaborative of Cleveland, grant KL2TR000440 from the National Center for Advancing Translational Sciences (NCATS) component of the NIH, and the NIH Roadmap for Medical Research.
Disclosures: Dr. Dalton reports grants from NIH/NCATS during the conduct of the study. Dr. Perzynski reports personal fees from Global Health Metrics outside the submitted work. Mr. Milinovich reports grants from Novo Nordisk, Merck, Celgene, Otsuka, and Amgen outside the submitted work. Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M16-2543.
Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that she has no financial relationships or interests to disclose. Darren B. Taichman, MD, PhD, Executive Deputy Editor, reports that he has no financial relationships or interests to disclose. Cynthia D. Mulrow, MD, MSc, Senior Deputy Editor, reports that she has no relationships or interests to disclose. Deborah Cotton, MD, MPH, Deputy Editor, reports that she has no financial relationships or interest to disclose. Jaya K. Rao, MD, MHS, Deputy Editor, reports that she has stock holdings/options in Eli Lilly and Pfizer. Sankey V. Williams, MD, Deputy Editor, reports that he has no financial relationships or interests to disclose. Catharine B. Stack, PhD, MS, Deputy Editor for Statistics, reports that she has stock holdings in Pfizer and Johnson & Johnson.
Reproducible Research Statement:Study protocol and statistical code: Available from Dr. Dalton (e-mail, firstname.lastname@example.org). Data set: Limited data may be available under strict conditions; send inquires to Dr. Dalton (e-mail, email@example.com).
Requests for Single Reprints: Jarrod E. Dalton, PhD, Department of Quantitative Health Sciences, Lerner Research Institute, 9500 Euclid Avenue (JJN-3), Cleveland, OH 44195; e-mail, firstname.lastname@example.org.
Current Author Addresses: Dr. Dalton and Mr. Milinovich: Department of Quantitative Health Sciences, Lerner Research Institute, 9500 Euclid Avenue (JJN-3), Cleveland, OH 44195.
Drs. Perzynski, Einstadter, and Dawson: Center for Healthcare Research and Policy, Case Western Reserve University/MetroHealth Medical Center, 2500 MetroHealth Drive, Cleveland, OH 44109.
Dr. Zidar: Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, 11100 Euclid Avenue, Cleveland, OH 44106.
Dr. Rothberg: Center for Value-Based Care Research, Medicine Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195.
Dr. Coulton: Center on Urban Poverty and Community Development, Mandel School of Applied Social Sciences, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106.
Dr. Karichu: Roche Molecular Systems, 4300 Hacienda Drive, Pleasanton, CA 94588.
Author Contributions: Conception and design: J.E. Dalton, A.T. Perzynski, C.J. Coulton, A.T. Milinovich, N.V. Dawson.
Analysis and interpretation of the data: J.E. Dalton, A.T. Perzynski, D.A. Zidar, M.B. Rothberg, D. Einstadter, N.V. Dawson.
Drafting of the article: J.E. Dalton, A.T. Perzynski, D.A. Zidar, C.J. Coulton, A.T. Milinovich, J.K. Karichu, N.V. Dawson.
Critical revision for important intellectual content: J.E. Dalton, A.T. Perzynski, D.A. Zidar, M.B. Rothberg, D. Einstadter, J.K. Karichu, N.V. Dawson.
Final approval of the article: J.E. Dalton, A.T. Perzynski, D.A. Zidar, M.B. Rothberg, C.J. Coulton, A.T. Milinovich, D. Einstadter, J.K. Karichu, N.V. Dawson.
Provision of study materials or patients: J.E. Dalton.
Statistical expertise: J.E. Dalton.
Obtaining of funding: J.E. Dalton, N.V. Dawson.
Administrative, technical, or logistic support: J.E. Dalton, A.T. Milinovich, D. Einstadter, N.V. Dawson.
Collection and assembly of data: J.E. Dalton, A.T. Milinovich.
Inequality in health outcomes in relation to Americans' socioeconomic position is rising.
First, to evaluate the spatial relationship between neighborhood disadvantage and major atherosclerotic cardiovascular disease (ASCVD)–related events; second, to evaluate the relative extent to which neighborhood disadvantage and physiologic risk account for neighborhood-level variation in ASCVD event rates.
Observational cohort analysis of geocoded longitudinal electronic health records.
A single academic health center and surrounding neighborhoods in northeastern Ohio.
109 793 patients from the Cleveland Clinic Health System (CCHS) who had an outpatient lipid panel drawn between 2007 and 2010. The date of the first qualifying lipid panel served as the study baseline.
Time from baseline to the first occurrence of a major ASCVD event (myocardial infarction, stroke, or cardiovascular death) within 5 years, modeled as a function of a locally derived neighborhood disadvantage index (NDI) and the predicted 5-year ASCVD event rate from the Pooled Cohort Equations Risk Model (PCERM) of the American College of Cardiology and American Heart Association. Outcome data were censored if no CCHS encounters occurred for 2 consecutive years or when state death data were no longer available (that is, from 2014 onward).
The PCERM systematically underpredicted ASCVD event risk among patients from disadvantaged communities. Model discrimination was poorer among these patients (concordance index [C], 0.70 [95% CI, 0.67 to 0.74]) than those from the most affluent communities (C, 0.80 [CI, 0.78 to 0.81]). The NDI alone accounted for 32.0% of census tract–level variation in ASCVD event rates, compared with 10.0% accounted for by the PCERM.
Patients from affluent communities were overrepresented. Outcomes of patients who received treatment for cardiovascular disease at Cleveland Clinic were assumed to be independent of whether the patients came from a disadvantaged or an affluent neighborhood.
Neighborhood disadvantage may be a powerful regulator of ASCVD event risk. In addition to supplemental risk models and clinical screening criteria, population-based solutions are needed to ameliorate the deleterious effects of neighborhood disadvantage on health outcomes.
The Clinical and Translational Science Collaborative of Cleveland and National Institutes of Health.
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Dalton JE, Perzynski AT, Zidar DA, Rothberg MB, Coulton CJ, Milinovich AT, et al. Accuracy of Cardiovascular Risk Prediction Varies by Neighborhood Socioeconomic Position: A Retrospective Cohort Study. Ann Intern Med. [Epub ahead of print 29 August 2017]:. doi: 10.7326/M16-2543
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Published: Ann Intern Med. 2017.
Cardiology, Coronary Risk Factors, Emergency Medicine, Neurology, Prevention/Screening.
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Print ISSN: 0003-4819 | Online ISSN: 1539-3704
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