TRA-2-2 NEIGHBORHOOD SOCIOECONOMIC STATUS AND MAJOR ATHEROSCLEROTIC EVENT RATES: AN ANALYSIS OF GEOCODED ELECTRONIC HEALTH DATA

Monday, October 24, 2016: 10:15 AM
Bayshore Ballroom Salon F, Lobby Level (Westin Bayshore Vancouver)

Jarrod E. Dalton, PhD, Cleveland Clinic and Case Western Reserve University, Cleveland, OH, Adam T. Perzynski, PhD, Case Western Reserve University at MetroHealth, Cleveland, OH, David A. Zidar, M.D., Ph.D., University Hospitals Case Medical Center, Cleveland, OH, Michael B. Rothberg, MD, MPH, Cleveland Clinic, Beachwood, OH, Claudia J. Coulton, Ph.D., Case Western Reserve University, Cleveland, OH, Alex T. Milinovich, BA, Cleveland Clinic, Cleveland, OH and Neal V. Dawson, MD, Case Western Reserve University at MetroHealth Medical Center, Cleveland, OH

Purpose:

   Inequality in health outcomes in relation to Americans' socioeconomic status (SES) is rising, despite recent evidence that the life expectancy gap between black and white Americans may be decreasing1,2. Cardiovascular disease, still the leading cause of death for Americans, merits study with respect to the socioeconomic spectrum. The objectives of our study were: i) to evaluate the relationship between neighborhood-level SES and major atherosclerotic cardiovascular disease (ASCVD)-related events (myocardial infarction, stroke, and cardiovascular death); and ii) to evaluate the relative extent to which neighborhood SES and physiological risk explain neighborhood-level variation in ASCVD event rates.

Method:

   We analyzed EHR data from 78,488 Cleveland Clinic patients living in Northeast Ohio who had an outpatient lipid panel drawn between 2007 and 2010, the date of which serving as study baseline. The follow-up time for major ASCVD events was 5 years. We applied Bayesian spatial analytic techniques3 (specifically, Weibull spatial autoregression with a Besag-York-Mollie4  covariance structure) to model ASCVD event rates across Northeast Ohio census tracts. Exposures of interest were census-tract-level socioeconomic status, which was defined as the first principal component of eight U.S. census measures (percent on Medicaid, percent uninsured, median income, percent with supplemental income, etc.); and the American College of Cardiology/American Heart Association Pooled Cohort Equations Risk Model (PCERM) estimated 5-year probability of major ASCVD events.

Result:

   We found substantial geographic variation in PCERM-adjusted ASCVD event risk that mirrored variation in neighborhood SES (see Figures). Neighborhood SES alone accounted for 29% of unexplained census-tract-level variation in ASCVD event rates, compared to 6.6% explained by the PCERM alone. Incrementally speaking, the PCERM explained 4.7% of this variation after adjusting for effects of neighborhood SES.

Conclusion:

   Rates of major ASCVD events in low-SES communities were over three times that of high-SES communities, and neighborhood SES explained over four times the amount of neighborhood-level variation in event rates than the established ASCVD risk model. The incremental explained variation attributable to the physiological variable-based PCERM – beyond the explained variation from neighborhood SES – was small. SES needs to be incorporated into risk-based decision-making procedures for primary prevention of ASCVD.

References:

[1] Bosworth (2016), Brookings Institution.
[2] Kochanek (2015), NCHS.
[3] Rue (2009), Journal of the Royal Statistical Society-B
[4] Besag (1991), Annals of the Institute of Statistical Mathematics.

 

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