Factors driving increases in Clostridioides difficile infection rates in England: a national case−control study, 2019 to 2024

BACKGROUND Numbers of Clostridioides difficile infections (CDI) in England have risen since 2021, but for unclear reasons. AIM This study’s objective was to understand factors driving CDI increases, and their relative impact. METHODS We conducted a case–control study in England from 2019/20 to 2023/24, with CDI case data linked to hospitalisation episodes. Controls were non-CDI related hospitalisation episodes. A logistic regression model estimated odds ratios (ORs) for primary care prescribing, comorbidities, demographic factors, region and testing rates. To assess temporal changes, the model was fitted to 2019/20 data to predict, from 2020/21 onwards, case numbers, which were compared to observations. The relative contribution of factors to the model performance was evaluated by their stepwise inclusion into it, starting from a baseline considering hospitalisation numbers. Prediction improvements were assessed after each incorporation. RESULTS The strongest CDI risk factors were prescriptions (e.g. OR for clindamycin: 5.22; p < 0.001), comorbidities (OR: 1.17; p < 0.001), and age (OR: 1.03; p < 0.001). All ethnicities except White negatively associated with CDIs. Among regions, the North West and Yorkshire and Humber had the highest ORs (1.17 and 1.15 respectively; p < 0.001). Demographic changes and antibiotic use explained 12.6% of the difference between observed cases in 2023/24 and our baseline model whereas including comorbidities and testing rates explained 65.3%. CONCLUSION Increases in overall hospital admissions, comorbidities and testing largely explained rising case numbers, which also stemmed from an ageing population, demographic changes and more primary care antibiotic prescribing . Nevertheless, these factors did not fully account for observed increases, so further determinants should be sought.

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Journal
Eurosurveillance
Published
2026-09-17
DOI
https://doi.org/10.2807/1560-7917.es.2026.31.37.2500888
Primary Topic
Clostridium difficile and Clostridium perfringens research
Type
article
Field-Weighted Citation Impact
0.00
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article

Factors driving increases in Clostridioides difficile infection rates in England: a national case−control study, 2019 to 2024

André Charlett, Julie V. Robotham, James Stimson, Timothy Whiteley et al.
Eurosurveillance
Clostridium difficile and Clostridium perfringens research
article

Factors driving increases in Clostridioides difficile infection rates in England: a national case−control study, 2019 to 2024

André Charlett, Julie V. Robotham, James Stimson, Timothy Whiteley, Russell Hope, Thomas Inns, Dakshika Jeyaratnam, Zahin Amin‐Chowdhury, Dimple Chudasama, Stephanie Evans, C. Stevens, Laura Fellowes, Rebecca Oettle
article en

Abstract

BACKGROUND Numbers of Clostridioides difficile infections (CDI) in England have risen since 2021, but for unclear reasons. AIM This study’s objective was to understand factors driving CDI increases, and their relative impact. METHODS We conducted a case–control study in England from 2019/20 to 2023/24, with CDI case data linked to hospitalisation episodes. Controls were non-CDI related hospitalisation episodes. A logistic regression model estimated odds ratios (ORs) for primary care prescribing, comorbidities, demographic factors, region and testing rates. To assess temporal changes, the model was fitted to 2019/20 data to predict, from 2020/21 onwards, case numbers, which were compared to observations. The relative contribution of factors to the model performance was evaluated by their stepwise inclusion into it, starting from a baseline considering hospitalisation numbers. Prediction improvements were assessed after each incorporation. RESULTS The strongest CDI risk factors were prescriptions (e.g. OR for clindamycin: 5.22; p < 0.001), comorbidities (OR: 1.17; p < 0.001), and age (OR: 1.03; p < 0.001). All ethnicities except White negatively associated with CDIs. Among regions, the North West and Yorkshire and Humber had the highest ORs (1.17 and 1.15 respectively; p < 0.001). Demographic changes and antibiotic use explained 12.6% of the difference between observed cases in 2023/24 and our baseline model whereas including comorbidities and testing rates explained 65.3%. CONCLUSION Increases in overall hospital admissions, comorbidities and testing largely explained rising case numbers, which also stemmed from an ageing population, demographic changes and more primary care antibiotic prescribing . Nevertheless, these factors did not fully account for observed increases, so further determinants should be sought.

EurosurveillanceVol. 31(37)
UK Health Security Agency (GB)
Reduced inequalities
Openalex Percentile: Top 11%
Clostridium difficile and Clostridium perfringens research
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