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Identification of novel risk factors for community-acquired Clostridium difficile infection using spatial statistics and geographic information system analyses.
Abstract
BACKGROUND: The rate of community-acquired Clostridium difficile infection (CA-CDI)
is increasing. While receipt of antibiotics remains an important risk factor for CDI,
studies related to acquisition of C. difficile outside of hospitals are lacking. As
a result, risk factors for exposure to C. difficile in community settings have been
inadequately studied. MAIN OBJECTIVE: To identify novel environmental risk factors
for CA-CDI. METHODS: We performed a population-based retrospective cohort study of
patients with CA-CDI from 1/1/2007 through 12/31/2014 in a 10-county area in central
North Carolina. 360 Census Tracts in these 10 counties were used as the demographic
Geographic Information System (GIS) base-map. Longitude and latitude (X, Y) coordinates
were generated from patient home addresses and overlaid to Census Tracts polygons
using ArcGIS; ArcView was used to assess "hot-spots" or clusters of CA-CDI. We then
constructed a mixed hierarchical model to identify environmental variables independently
associated with increased rates of CA-CDI. RESULTS: A total of 1,895 unique patients
met our criteria for CA-CDI. The mean patient age was 54.5 years; 62% were female
and 70% were Caucasian. 402 (21%) patient addresses were located in "hot spots" or
clusters of CA-CDI (p<0.001). "Hot spot" census tracts were scattered throughout the
10 counties. After adjusting for clustering and population density, age ≥ 60 years
(p = 0.03), race (<0.001), proximity to a livestock farm (0.01), proximity to farming
raw materials services (0.02), and proximity to a nursing home (0.04) were independently
associated with increased rates of CA-CDI. CONCLUSIONS: Our study is the first to
use spatial statistics and mixed models to identify important environmental risk factors
for acquisition of C. difficile and adds to the growing evidence that farm practices
may put patients at risk for important drug-resistant infections.
Type
Journal articlePermalink
https://hdl.handle.net/10161/14655Published Version (Please cite this version)
10.1371/journal.pone.0176285Publication Info
Anderson, Deverick J; Rojas, Leoncio Flavio; Watson, Shera; Knelson, Lauren P; Pruitt,
Sohayla; Lewis, Sarah S; ... CDC Prevention Epicenters Program (2017). Identification of novel risk factors for community-acquired Clostridium difficile
infection using spatial statistics and geographic information system analyses. PLoS One, 12(5). pp. e0176285. 10.1371/journal.pone.0176285. Retrieved from https://hdl.handle.net/10161/14655.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Deverick John Anderson
Professor of Medicine
Hospital epidemiology, infection control, antibiotic stewardship, multidrug-resistant
organisms, device-related infections, surgical site infections, catheter-associated
bloodstream infections, cost of infections, infections in community hospitals
Luke Francis Chen
Associate Professor of Medicine
Epidemiology, Infection Prevention, Infection Control, Outbreak Investigations, Multi-drug
resistant organisms, multidrug-resistant gram-negative pathogens MDR GNR (e.g. ESBL,
CRE, KPC, NDM-1), C. difficile, MRSA infections health care epidemiology, HIV medicine,
respiratory viral infections, infection control and prevention, health care-associated
infections including bloodstream and surgical-site infections
This author no longer has a Scholars@Duke profile, so the information shown here reflects
their Duke status at the time this item was deposited.
Sarah Stamps Lewis
Associate Professor of Medicine
Rebekah Moehring
Associate Professor of Medicine
Daniel John Sexton
Professor Emeritus of Medicine
During the past 8 years my research interests have changed from a focus on tick-borne
disease and endocarditis to a primary focus on healthcare-associated infections (HAIs).
Specifically, I have been interested in HAIs in community hospitals. Using prospective
data collected as part of our surveillance activities in the Duke Infection Control
Outreach Network (DICON), I and my colleagues have focused on these specific areas
of research: • The accuracy and reliability of surveil
Alphabetical list of authors with Scholars@Duke profiles.

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