# Impact of the implementation of differential privacy to decennial census data in understanding of health disparities in the United States

> **NIH NIH R03** · PENNSYLVANIA STATE UNIVERSITY, THE · 2022 · $79,095

## Abstract

Summary
The implementation of new differential-avoidance methods, based on differential privacy algorithms, to the 2020 U.S.
Census data and additional data products may affect the usefulness of these data, the accuracy of estimates and rates derived
from them, and critical knowledge about social phenomena such as health disparities. The U.S. Census has released a series
of demonstration products that allow comparisons between the counts produced under traditional and the proposed privacy
algorithm. We test the ramifications of differential privacy by studying changes in the county-level age-specific mortality
rates (ASMRs) for the overall population and racial/ethnic groups. We ask how changes in the denominators, due to the
implementation of differential privacy, result in different ASMRs. We further propose the examination of trends by
comparing the conclusions derived from 2000-2010 comparisons of ASMRs using mortality rates produced using both sets
of denominators. Further, we propose quantifying the changes produced by the implementation of differential privacy in the
empirical associations derived from regression models. We address these aims by examining mortality rates produced using
different vintages of the 2010 decennial counts produced using differential privacy and comparing them with those produced
using the traditional methods. These findings will highlight the consequences of implementing differential privacy for
research examining changes in rates produced by artificial population composition changes. Overall, we will demonstrate
the challenges of using the data products derived from the proposed disclosure avoidance method while highlighting critical
instances where scientific understandings may be negatively impacted.

## Key facts

- **NIH application ID:** 10349747
- **Project number:** 1R03HD107173-01
- **Recipient organization:** PENNSYLVANIA STATE UNIVERSITY, THE
- **Principal Investigator:** Alexis R Santos-Lozada
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $79,095
- **Award type:** 1
- **Project period:** 2022-04-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10349747

## Citation

> US National Institutes of Health, RePORTER application 10349747, Impact of the implementation of differential privacy to decennial census data in understanding of health disparities in the United States (1R03HD107173-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10349747. Licensed CC0.

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