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Original Investigation |

High-Density Livestock Operations, Crop Field Application of Manure, and Risk of Community-Associated Methicillin-Resistant Staphylococcus aureus Infection in Pennsylvania

Joan A. Casey, MA1,2; Frank C. Curriero, PhD, MA1,3; Sara E. Cosgrove, MD, MS2,4; Keeve E. Nachman, PhD, MHS1,5,6; Brian S. Schwartz, MD, MS1,2,7
[+] Author Affiliations
1Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
2Johns Hopkins School of Medicine, Baltimore, Maryland
3Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
4Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
5Department of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
6Johns Hopkins Center for a Livable Future, Baltimore, Maryland
7Geisinger Health System, Danville, Pennsylvania
JAMA Intern Med. 2013;173(21):1980-1990. doi:10.1001/jamainternmed.2013.10408.
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Importance  Nearly 80% of antibiotics in the United States are sold for use in livestock feeds. The manure produced by these animals contains antibiotic-resistant bacteria, resistance genes, and antibiotics and is subsequently applied to crop fields, where it may put community members at risk for antibiotic-resistant infections.

Objective  To assess the association between individual exposure to swine and dairy/veal industrial agriculture and risk of methicillin-resistant Staphylococcus aureus (MRSA) infection.

Design, Setting, and Participants  A population-based, nested case-control study of primary care patients from a single health care system in Pennsylvania from 2005 to 2010. Incident MRSA cases were identified using electronic health records, classified as community-associated MRSA or health care–associated MRSA, and frequency matched to randomly selected controls and patients with skin and soft-tissue infection. Nutrient management plans were used to create 2 exposure variables: seasonal crop field manure application and number of livestock animals at the operation. In a substudy, we collected 200 isolates from patients stratified by location of diagnosis and proximity to livestock operations.

Main Outcomes and Measures  Community-associated MRSA, health care–associated MRSA, and skin and soft-tissue infection status (with no history of MRSA) compared with controls.

Results  From a total population of 446 480 patients, 1539 community-associated MRSA, 1335 health care-associated MRSA, 2895 skin and soft-tissue infection cases, and 2914 controls were included. After adjustment for MRSA risk factors, the highest quartile of swine crop field exposure was significantly associated with community-associated MRSA, health care-associated MRSA, and skin and soft-tissue infection case status (adjusted odds ratios, 1.38 [95% CI, 1.13-1.69], 1.30 [95% CI, 1.05-1.61], and 1.37 [95% CI, 1.18-1.60], respectively); and there was a trend of increasing odds across quartiles for each outcome (P ≤ .01 for trend in all comparisons). There were similar but weaker associations of swine operations with community-associated MRSA and skin and soft-tissue infection. Molecular testing of 200 isolates identified 31 unique spa types, none of which corresponded to CC398 (clonal complex 398), but some have been previously found in swine.

Conclusions and Relevance  Proximity to swine manure application to crop fields and livestock operations each was associated with MRSA and skin and soft-tissue infection. These findings contribute to the growing concern about the potential public health impacts of high-density livestock production.

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Figure 1.
Crop Field Locations and Methicillin-Resistant Staphylococcus aureus (MRSA) Rates

Crop field locations and rates of MRSA per 1000 Geisinger Health System (GHS) primary care patients in townships, boroughs, and cities. Rates in communities with fewer than 50 GHS patients were not estimated. The map demonstrates that crop fields were often located in areas with a range of human population densities.

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Figure 2.
Three Methods Used to Identify and Locate Crop Fields

A, Aerial photograph (top) or map (bottom) were located using Google Earth (n = 135). B, Operation addresses known and located using ArcGIS, version 10 (Esri) (n = 420). C, County and township known and addresses were located by identifying cropland, hay land, and pastureland on a land use map and randomly selecting a point within the eligible land use types (n = 131).

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