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Identification of novel risk factors for community-acquired Clostridium difficile infection using spatial statistics and geographic information system analyses

Author

Listed:
  • Deverick J Anderson
  • Leoncio Flavio Rojas
  • Shera Watson
  • Lauren P Knelson
  • Sohayla Pruitt
  • Sarah S Lewis
  • Rebekah W Moehring
  • Emily E Sickbert Bennett
  • David J Weber
  • Luke F Chen
  • Daniel J Sexton
  • the CDC Prevention Epicenters Program

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

Suggested Citation

  • Deverick J Anderson & Leoncio Flavio Rojas & Shera Watson & Lauren P Knelson & Sohayla Pruitt & Sarah S Lewis & Rebekah W Moehring & Emily E Sickbert Bennett & David J Weber & Luke F Chen & Daniel J S, 2017. "Identification of novel risk factors for community-acquired Clostridium difficile infection using spatial statistics and geographic information system analyses," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-13, May.
    • Handle: RePEc:plo:pone00:0176285
    DOI: 10.1371/journal.pone.0176285
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