Environmental Pharmacoepidemiology

5G-02 - Risk factors associated with Escherichia coli antimicrobial resistance in the community: A Geo-temporal Analysis

Tuesday, August 26, 2025

8:45 AM - 9:00 AM ET

Co-Author(s)

Chloé Corrie Hans Smit

University of Technology Sydney, Australia
CK

Caitlin Keighley

University of Wollongong, Australia
KR

Kris Rogers

University of Wollongong, Australia
SM

Spiros Miyakis

University of Wollongong, Australia
KT

Katja Taxis

University of Groningen
Groningen, Netherlands
NN

Nick Nicholas

Managing Director of The Demographer's Workshop, Australia
HR

Hamish Robertson

Queensland University of Technology, Australia

Presenting Author(s)

LP

Lisa Pont

University of Technology Sydney, Australia

Background: Geo-temporal analysis integrates spatial and temporal dimensions into pharmacoepidemiology, enabling the visualization and exploration of trends.

Objectives: This study investigates geo-temporal risk factors associated with urinary Escherichia coli AMR in the community-dwelling population.

Methods: Individual patient health records, government socioeconomic data, and microbiology data on Escherichia coli AMR in urine isolates were linked by area and year. Multi-level logistic regression analysis explored geo-temporal associations between potential risk factors, including antibiotic and corticosteroid use, comorbid diabetes, hospital admissions, socioeconomic status, and E. coli resistance to antibiotics commonly used for urinary tract infections.

Results: Geo-temporal risk factors for E. coli resistance varied by antibiotic. Higher socioeconomic status was associated with increased resistance to trimethoprim (OR = 1.27, 95% CI: 1.12–1.45). Areas with higher prevalence of comorbid diabetes showed increased resistance to amoxicillin (OR = 1.23, 95% CI: 1.03–1.47) and trimethoprim (OR = 1.21, 95% CI: 1.03–1.41). Higher general antibiotic use was linked to lower resistance to norfloxacin (OR = 0.63, 95% CI: 0.41–0.96), and higher cefalexin use was associated with lower resistance to cefalexin (OR = 0.22, 95% CI: 0.06–0.77).

Conclusions: This study highlights the value of geo-temporal analyses in pharmacoepidemiology, revealing the complexity of risk factors for Escherichia coli AMR in the community. The findings underscore the need for future research using patient-level data to further elucidate the mechanisms driving AMR.