We study the central problem in data privacy: how to share data with an analyst while providing both privacy and utility guarantees to the user that owns the data. In this setting, we present an estimation-theoretic analysis of the privacy-utility trade-off (PUT). Here, an analyst is allowed to reconstruct (in a mean-squared error sense) certain functions of the data (utility), while other private functions should not be reconstructed with distortion below a certain threshold (privacy). We demonstrate how χ 2 -information captures the fundamental PUT in this case and provide bounds for the best PUT. We propose a convex program to compute privacy-assuring mappings when the functions to be disclosed and hidden are known a priori and the data distribution is known. We derive lower bounds on the minimum mean-squared error of estimating a target function from the disclosed data and evaluate the robustness of our approach when an empirical distribution is used to compute the privacy-assuring mappings instead of the true data distribution. We illustrate the proposed approach through two numerical experiments.Index Terms-Estimation, privacy-utility trade-off, minimum mean-squared error.

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Background: Diabetes is the leading cause of chronic kidney disease (CKD) and a major risk factor in the progression of kidney failure or end-stage kidney disease. An estimated 34.2 million Americans have diabetes, and 1 in 3 adults with diabetes may have CKD, many of whom do not know they have it. Interventions to increase CKD awareness and its complications may help promote early testing and identification among adults with diabetes. The American Kidney Fund (AKF) developed a 5-minute CKD education session and focused this intervention in the District of Columbia-Maryland-Virginia (DMV) metropolitan area. Methods­: In 2020, AKF administered a 5-item questionnaire at two AKF kidney disease screening events to assess CKD knowledge before and after 5-minute CKD education sessions. Individuals demonstrating CKD risk factors, including self-reported history of diabetes or elevated blood sugar level results, attended the education sessions. We compared responses from 129 participants and performed a paired samples t-test to determine the education sessions’ effectiveness in improving CKD knowledge. Results: The average pre-post scores increased from 57% to 89% (t(128)=10.65, p<0.001), with the largest gains in understanding the definition of CKD (11% to 86%, t(128)=17.62, p<0.001). There was a significant difference in pre-post scores for identifying diabetes and high blood pressure as the top risk factors for CKD (49% to 86%, t(128)=6.62, p<0.001). For the best ways to prevent CKD, keeping a healthy blood sugar level and healthy blood pressure level was also significant (65% to 89%, t(128)=4.91, p<0.001). Conclusion: Our study demonstrated low awareness of CKD risk factors. Educational sessions are effective for improving CKD knowledge and increasing awareness about diabetes as a major risk factor. Our study supports the expansion of CKD-related educational programs for populations at high risk for CKD. Disclosure L. Vo: None. M. Paris: None. M. Alawode: None. M. Spigler: None.