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Abstract: SA-PO034

Individual vs. Neighborhood-Level Social Determinants of Health and ESKD Mortality

Session Information

Category: Diversity and Equity in Kidney Health

  • 900 Diversity and Equity in Kidney Health

Authors

  • Kang, Dasol, Weill Cornell Medicine, New York, New York, United States
  • Simmons, Will, Weill Cornell Medicine, New York, New York, United States
  • Roychoudhury, Arindam, Weill Cornell Medicine, New York, New York, United States
  • Kim, Kwan, Weill Cornell Medicine, New York, New York, United States
  • Silberzweig, Jeffrey I., Weill Cornell Medicine, New York, New York, United States
  • Sawinski, Deirdre L., Weill Cornell Medicine, New York, New York, United States
  • Tummalapalli, Sri Lekha, Weill Cornell Medicine, New York, New York, United States
Background

Social determinants of health (SDOH) have a substantial impact on disease morbidity and mortality. Neighborhood-level SDOH indices are increasingly being used for clinical risk prediction and resource allocation to improve health equity. However, whether neighborhood-level SDOH are independently associated with mortality among incident end-stage kidney disease (ESKD) patients is unknown.

Methods

We identified patients with incident ESKD admitted to the Rogosin Institute, a New York City-based non-profit dialysis organization, and excluded patients with missing Social Vulnerability Index (SVI) and acute kidney injury requiring dialysis. We used Cox regression to generate four nested prediction models for mortality. Model 1 adjusted for age, sex, and race and ethnicity. Model 2 additionally adjusted for primary cause of ESKD and 31 Elixhauser comorbidities. Model 3 additionally adjusted for individual SDOH (marital status and employment). Model 4 additionally adjusted for census tract-level SVI, which incorporates Census variables of socioeconomic status, household composition and disability, minority status and language, and housing type and transportation.

Results

Of 3,585 patients with incident ESKD, the median age was 62 (IQR 50 – 73). A total of 56% were male, 37% non-Hispanic Black, 24% non-Hispanic White, 15% Hispanic, and 14% were Asian. The mortality prediction model containing age, sex, and race and ethnicity had a Harrell’s C-statistic of 0.7028. Adding cause of ESKD and comorbidities improved prediction performance (Harrell’s C 0.7585, likelihood ratio [LR] test p<0.001). Individual SDOH also improved prediction performance (Harrell’s C 0.7652, LR test p<0.001). Census tract-level SVI and SVI themes did not improve mortality prediction (Harrell’s C 0.7653, LR test p = 0.645).

Conclusion

Neighborhood-level SVI did not improve mortality prediction in a diverse cohort of incident ESKD patients in New York City, independent of demographics, comorbidities, and individual-level SDOH. Neighborhood-level SDOH indices may have limited utility to predict clinical outcomes in the ESKD population.