Abstract: TH-PO707
Comparison of Actual vs. ZIP Code-Predicted Highest Educational Attainment in ESKD and Non-ESKD Participants
Session Information
- Diversity and Equity in Kidney Health - I
November 03, 2022 | Location: Exhibit Hall, Orange County Convention Center‚ West Building
Abstract Time: 10:00 AM - 12:00 PM
Category: Diversity and Equity in Kidney Health
- 800 Diversity and Equity in Kidney Health
Authors
- Dai, Yang, Icahn School of Medicine at Mount Sinai, New York, New York, United States
- Wen, Huei Hsun, Icahn School of Medicine at Mount Sinai, New York, New York, United States
- Nadkarni, Girish N., Icahn School of Medicine at Mount Sinai, New York, New York, United States
- Chan, Lili, Icahn School of Medicine at Mount Sinai, New York, New York, United States
Background
Research on the association of social determinants of health (SDOH) and clinical outcomes in participants with kidney disease often use SDOH measures identified using participants’ zip code and census data. However, in urban neighborhoods, zip code and census derived SDOH measures may be inaccurate.
Methods
We utilized data from participants ≥25 years old enrolled in the BioMe Biobank and from the Mount Sinai Kidney Center hemodialysis (HD) unit. All participants completed a questionnaire regarding the highest education obtained, age, gender, and race/ethnicity. The participants’ zip code was obtained from the EHR and those with a New York City zip code were kept. We then used data from the American Community Survey data from the year the participant completed the survey to predict the highest level of education given participants’ zip code, gender, and race/ethnicity. ESKD participants were identified by ICD9/10 codes or by enrollment in a HD unit. Non-ESKD participants were age, gender, and race/ethnicity matched to the ESKD participants.
Results
732 participants with ESKD and 732 matched non-ESKD participants were identified. Patient demographics are presented in Figure 1A. Average age was 58±13 years in both ESKD and non-ESKD cohorts, and the number of unique zip codes was 130 and 137 respectively. Correct prediction of education was significantly different between participants with and without ESKD, correctly identified in 32% of participants with ESKD and 27% of non-ESKD participants (Figure 1B & C), P=0.02. Lower prediction means that the predicted education level is lower than the participant's actual education level. Higher prediction means predicted education was higher than the real degree. Results were similar across genders. Blacks and Hispanics had the highest concordance in ESKD participants and non-ESKD participants. Concordance between survey results and zip code predicted results was poor for both ESKD and non-ESKD participants, Κ0.05 and Κ 0.02 respectively.
Conclusion
In an urban city, zip code predicted educational attainment using census data is inaccurate in two thirds of participants with and without ESKD. Smaller geographic areas may result in improved concordance.
Funding
- NIDDK Support