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Date Available

4-24-2028

Year of Publication

2026

Document Type

Graduate Capstone Project

Degree Name

Master of Public Health (M.P.H.)

College

Public Health

Department/School/Program

Public Health

Faculty

Dr. Mary E. Lacy

Committee Member

Dr. Florence Fulk

Faculty

Dr. Daniela Moga

Abstract

Urinary tract infections (UTIs) are among the most common bacterial infections and occur more frequently among individuals with diabetes mellitus. Recurrent UTIs (rUTIs) contribute to increased healthcare utilization, reduced quality of life, and greater risk of complications, yet population-level estimates and risk factors among U.S. adults with diabetes remain incompletely characterized. A cross-sectional study was conducted using the Merative MarketScan® Commercial Claims and Encounters database (2020–2023), including 673,535 adults ( ≥ 18 years) with diabetes mellitus defined by ≥ 2 ICD-10 claims and ≥ 12 months of continuous enrollment. UTIs were identified using ICD-10 code N39.0, and rUTIs were defined as ≥ 2 UTIs within 6 months or ≥ 3 within 12 months. We used multivariable logistic regression models to estimate adjusted odds ratios (aORs) and 95% confidence intervals. Overall, 14.70% of individuals experienced at least one UTI and 6.76% experienced rUTIs. Female sex was strongly associated with both UTI (aOR ≈ 3.52) and rUTI (aOR ≈ 3.03), and older age was associated with increasing odds, particularly among those aged ≥ 65 years as compared to those aged < 45 (UTI aOR ≈ 1.54; rUTI aOR ≈ 1.99). Clinical factors including diabetic autonomic neuropathy and chronic kidney disease were associated with increased odds of both UTI and rUTI, with the strongest association between urolithiasis and both UTI (aOR ≈ 3.72) and rUTI (aOR ≈ 4.51). UTIs and rUTIs represent a substantial burden among adults with diabetes, highlighting the importance of identifying high-risk subgroups to inform targeted prevention and management strategies aimed at reducing recurrence and associated morbidity.

Funding Information

The project described was supported by the National Institutes of Health National Center for Advancing Translational Sciences through grants UL1TR000117 and UL1TR001998. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. 

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