Which Is Not True About High-density Animal Farming?
Environ Health Perspect. 2014 May; 122(5): 464–470.
Research
High-Density Livestock Production and Molecularly Characterized MRSA Infections in Pennsylvania
Joan A. Casey,ane, 2 Bo Shopsin,3 Sara Eastward. Cosgrove,4 Keeve E. Nachman,1, 2 Frank C. Curriero,1, 5 Hannah R. Rose,three and Brian Southward. Schwartz 
1, 6, vii
Joan A. Casey
1Department of Ecology Health Sciences, Johns Hopkins Bloomberg Schoolhouse of Public Wellness, Baltimore, Maryland, USA
2Eye for a Livable Time to come, Johns Hopkins University, Baltimore, Maryland, USA
Bo Shopsin
3Department of Medicine, New York Academy Schoolhouse of Medicine, New York, New York, U.s.
Sara Due east. Cosgrove
4Division of Infectious Illness, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
Keeve Eastward. Nachman
1Department of Ecology Wellness Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
2Center for a Livable Future, Johns Hopkins Academy, Baltimore, Maryland, USA
Frank C. Curriero
aneSection of Ecology Health Sciences, Johns Hopkins Bloomberg School of Public Wellness, Baltimore, Maryland, United states
5Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
Hannah R. Rose
iiiDepartment of Medicine, New York University Schoolhouse of Medicine, New York, New York, U.s.
Brian S. Schwartz
1Department of Ecology Wellness Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
6Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, Us
sevenCentre for Health Inquiry, Geisinger Health System, Danville, Pennsylvania, Us
Received 2013 Jul xv; Accustomed 2014 Feb 6.
Abstruse
Groundwork: European studies suggest that living near high-density livestock production increases the adventure of sequence blazon (ST) 398 methicillin-resistant Staphylococcus aureus (MRSA) colonization. To our noesis, no studies take evaluated associations between livestock product and human being infection past other strain types.
Objectives: We evaluated associations between MRSA molecular subgroups and high-density livestock production.
Methods: We conducted a yearlong 2012 prospective report on a stratified random sample of patients with civilisation-confirmed MRSA infection; we oversampled patients from the Geisinger Health Organisation with exposure to high-density livestock production in Pennsylvania. Isolates were characterized using S. aureus protein A (spa) typing and detection of Panton-Valentine leukocidin (PVL) and scn genes. We compared patients with one of two specific MRSA strains with patients with all other strains of MRSA isolates, using logistic regression that accounted for the sampling design, for two different exposure models: one based on the location of the animals (livestock model) and the other on crop field application of manure (crop field model).
Results: Of 196 MRSA isolates, we identified 30 spa types, 47 PVL-negative and fifteen scn-negative isolates, and no ST398 MRSA. Compared with quartiles ane–three combined, the highest quartiles of swine livestock and dairy/veal crop field exposures were positively associated with community-onset-PVL-negative MRSA (CO-PVL-negative MRSA vs. all other MRSA), with adapted odds ratios of 4.24 (95% CI: 1.60, 11.25) and 4.88 (95% CI: 1.40, 17.00), respectively. The association with CO-PVL-negative MRSA infection increased across quartiles of dairy/veal livestock exposure (trend p = 0.05).
Conclusions: Our findings propose that other MRSA strains, across ST398, may be involved in livestock-associated MRSA infection in the United States.
Citation: Casey JA, Shopsin B, Cosgrove SE, Nachman KE, Curriero FC, Rose 60 minutes, Schwartz BS. 2014. High-density livestock product and molecularly characterized MRSA infections in Pennsylvania. Environ Health Perspect 122:464–470; http://dx.doi.org/10.1289/ehp.1307370
Introduction
Over the past decade, the incidence of community-associated methicillin-resistant Staphylococcus aureus (S. aureus) (CA-MRSA) infection has increased in the Us (Dukic et al. 2013). These CA-MRSA infections cost tertiary-party payers between $478 and $2,200 1000000 annually (Lee et al. 2013). Beginning in the mid-2000s, European research suggested that a portion of the increased incidence of CA-MRSA might exist owing to high-density livestock production because studies had isolated the aforementioned MRSA strains from infected farmers and their livestock (Harrison et al. 2013; Hartmeyer et al. 2010). In Europe, multilocus sequence blazon (ST) 398 has been the most common colonizer of livestock, specifically swine, and swine farmers (Graveland et al. 2010; Lewis et al. 2008). This association has led many to refer to ST398 equally livestock-associated MRSA (LA-MRSA) (Price et al. 2012). Importantly, pathways for community transmission have been identified, with MRSA isolated from the air and soil at least 150 one thousand from swine facilities (Gibbs et al. 2006; Schulz et al. 2012) and from meat processing and consumption (Molla et al. 2012; Waters et al. 2011).
To our noesis, no N American studies have evaluated residence in rural communities equally a risk factor for MRSA infection of specific molecular types. Four studies of colonization in farmers take disparate findings. The kickoff reported ST398 as the simply blazon colonizing swine and farmers (Smith et al. 2009); the 2d found mainly ST398, but also ST5 (Khanna et al. 2008); and ii more recent studies identified ST5 [t002 by South. aureus protein A (spa) typing (Monecke et al. 2011)] equally the primary colonizer of swine and of veterinary students visiting farms (Frana et al. 2013; Molla et al. 2012). In the U.s., ST5 has been considered to exist a health care–associated MRSA clone, only it has begun to appear in the community in persons without health care risk factors (Klevens et al. 2006). Nearly all MRSA isolates associated with livestock colonization lack the genes encoding Panton-Valentine leukocidin (PVL) (Smith et al. 2009; Sunde et al. 2011). Finally, recent studies have reported that scn, the cistron encoding staphylococcal complement inhibitor (SCIN), is often absent in MRSA strains that colonize livestock (McCarthy et al. 2011; Sung et al. 2008; Verkaik et al. 2011).
In a previous report in Pennsylvania using electronic wellness records from 2005 through 2010 from a big health care system, we reported associations betwixt CA-MRSA infection and residential proximity to high-density livestock operations and the ingather fields to which manure was practical (Casey et al. 2013b). Due to the retrospective written report blueprint, we were unable to obtain MRSA isolates from patients. The objectives of the nowadays written report were to a) prospectively collect MRSA isolates from patients residing in communities with and without high-density livestock production, b) characterize these isolates by spa typing and polymerase chain reaction (PCR) for the presence of lukF-lukS genes (encoding PVL) and for the scn gene, and c) appraise associations of high-density livestock production with the molecular subgroups.
Methods
Setting, written report design, and participants. The study expanse was a 38-county region of primal and northeast Pennsylvania with 3.8 million inhabitants in which Geisinger Health System provides master intendance services from 41 community practice clinics (Figure one). The chief care population is representative of the region'southward population (Casey et al. 2013b). Nosotros compared patients infected with two specific MRSA strains to patients infected with all other strains as described below. Institutional review boards at the Geisinger Wellness System and the Johns Hopkins Bloomberg Schoolhouse of Public Health approved the study and waived informed consent.
High-density livestock product and MRSA infection, Geisinger Health Intendance System, Pennsylvania.
Patients with MRSA infection identified past culture betwixt 1 January 2012 and 31 December 2012, who had a Geisinger primary care provider, were eligible for inclusion. The cases were stratified as community-onset or infirmary-onset and as residing in an area of high-density livestock production or not. Infections were classified as community-onset (CO) infections if the patient had a positive civilisation collected in the outpatient setting or ≤ ii days afterward hospital admission. Infections were classified as hospital-onset (HO) if the patient had a positive civilisation collected > 2 days after hospital admission (David and Daum 2010). Onset date was defined as the date the culture was ordered. Patients living in a ZIP code with a loftier-density livestock operation or a crop field to which manure from such an operation was practical were divers as residing in an area of high-density livestock production, every bit described in detail below. Using these example definitions, we completed a random stratified sample (a sample was evaluated because of budgetary limitations) to select cases into four a priori categories (Table 1). Nosotros over-selected patients who resided in areas of high-density livestock production to ameliorate the power to detect associations.
Table one
Patients identified and included in the present assay according to MRSA subtype and exposure in their residential ZIP code.
| Grouping | High-density livestock production | No high-density livestock product | Total |
|---|---|---|---|
| CO-MRSA | |||
| Patients included [n (%)] | 70 (42.2) | 96 (57.8) | 166 |
| Total patients [northward (%)] | 321 (32.v) | 667 (67.5) | 988 |
| Sample weight a | 4.59 | 6.95 | |
| HO-MRSA | |||
| Patients included [n (%)] | 11 (36.seven) | 19 (63.iii) | thirty |
| Total patients [n (%)] | 54 (22.5) | 186 (77.5) | 240 |
| Sample weight a | four.91 | nine.79 | |
| Total patients included (n) | 81 | 115 | 196 |
| Total patients identified (n) | 375 | 853 | 1,128 |
| Abbreviations: CO, community-onset; HO, hospital-onset. a Sample weight was calculated equally the total number of patients identified in each stratum divided by the number of patients sampled from that stratum for the nowadays analysis. | |||
Patient data collection. MRSA isolates (one per patient) nerveless in clinical practice settings were sent to a central laboratory, grown on conventional blood agar plates, and stored at 4°C. A research assistant selected advisable isolates and obtained samples for transport using sterile swab applicators (BBL Cultureswabs; Becton Dickinson, Franklin Lakes, NJ). A total of 203 unique isolates collected from sites of infection were sent unrefrigerated to New York University Langone Medical Heart for genotypic testing, where isolates were subcultured onto agar plates and incubated overnight at 37°C. DNA was and then extracted by mechanical lysis. Nosotros obtained information on patient demographics and inpatient, outpatient, and emergency section encounters, procedures, medication orders, and laboratory information from the electronic health records. Antimicrobial resistance testing on clindamycin, erythromycin, gentamicin, rifampin, tetracycline, trimethoprim–sulfamethoxazole, and vancomycin was also available from the electronic wellness records. Multidrug resistance was reported equally resistance to three or more unique antimicrobials.
Genotyping. Dna sequence analysis of the protein A cistron variable repeat region (spa typing) was completed using the primers TIGR-F (v´-GCCAAAGCGCTAACCTTTTA-three´) and TIGR-R (five´-TCCAGCTAATAACGCTGCAC-three´) (Shopsin et al. 1999). Spa types were assigned a StaphType (eastward.g., t008, t002) using the Ridom SpaServer database (http://www.spaserver.ridom.de). We subsequently mapped spa types to clonal complex (CC) categories (CC5 or CC5-similar, CC8 or CC8-like, or other) using the Ridom SpaServer spa to multilocus sequence type (MLST) database (http://spa.ridom.de/mlst.shtml). We also checked for the presence of PVL genes using S. aureus ATCC 49775 (ATCC, Manassas, VA) as a reference strain and primers as previously described (Lina et al. 1999). The presence of scn was determined by an additional PCR (Sung et al. 2008).
Earlier literature from northern Europe suggested that ST398 would be a cause of human infection in those exposed to high-density livestock production (Hartmeyer et al. 2010; Wulf et al. 2012); yet, we did not identify any ST398 infections. Therefore, before beginning statistical analysis, nosotros identified 2 other strains of interest. Although most CA-MRSA contains PVL genes (David and Daum 2010), most MRSA (both ST5 and ST398) isolated from humans and animals with exposure to high-density livestock production in North America has been PVL-negative (Frana et al. 2013; Price et al. 2012; Tattevin et al. 2012). Therefore, nosotros selected community-onset PVL-negative (CO-PVL-negative) MRSA isolates equally a unique group with potential ties to high-density livestock production. Nosotros created a 2d molecular subgroup based on recent evidence that but nearly 25% of animal S. aureus isolates carry the scn gene, whereas human isolates conduct information technology virtually 90% of the time (Sung et al. 2008; Verkaik et al. 2011). To complete the analysis, nosotros created two case groups—CO-PVL-negative MRSA and scn-negative MRSA—and compared these groups to patients with all other MRSA types.
Geospatial estimates of high-density livestock exposure. Pennsylvania Deed 38 of 2005 (2005) requires food management plans (NMPs) to regulate full-bodied animal operations, operations where livestock density exceeds two animal equivalent units (AEUs; 1,000 pounds of brute weight) per acre and where the total number of AEUs exceeds viii. NMPs item appropriate manure treatment, storage, and land application to ingather fields, both on-site where the animals are raised and off-site. NMPs as well comprise data on operation location and acreage and livestock type. In improver, the Pennsylvania Department of Environmental Protection requires NMPs from the largest operations called concentrated brute feeding operations (> ane,000 AEUs, or 301–one,000 AEUs and a full-bodied animal operation, or per federal regulation) (U.Southward. Ecology Protection Bureau 2012). For our analysis, we divers a high-density livestock operation equally a) > 2 AEUs per acre and > 8 AEUs total, or b) > 300 AEUs full.
Nosotros used ArcGIS (version ten.0; Esri, Redlands, CA) to geocode livestock operations, treated crop fields, and patients at their home address. Although patients were sampled using presence of high-density livestock production in their Nothing code, this benchmark was non used to generate exposure metrics. Nosotros created ii exposure metrics for livestock operations (swine or dairy/veal):
Exposure for patient j = Σ north i = 1(ai /dij two), [1]
where n is the number of operations, ai is the AEUs of livestock at operation i, and dij 2 is the squared distance (in meters) between operation i and patient j. In improver, we created ii metrics for exposure to treated ingather fields (swine or dairy/veal manure applications) during the season of infection:
Exposure for patient j = Σ n k = i(ck /dkj 2), [ii]
where n is the number of treated crop fields, ck is the concentration of manure (gallons per square meter) practical to field k during the flavor of diagnosis, and dkj ii is the squared distance (in meters) between field centroid k and patient j (Casey et al. 2013b). We modeled the exposure variables as quartiles to let for nonlinear associations and for ease of interpretation.
Statistical methods. A multivariable logistic regression model was used to guess associations between exposures and outcomes (i.east., CO-PVL-negative MRSA or scn-negative MRSA vs. all other MRSA strains combined). By study blueprint, we oversampled cases living in Cypher codes with high-density livestock production. To account for this sampling design while obtaining unbiased regression estimates and robust standard errors, each participant was assigned a sample weight equal to the total number of MRSA patients identified in a stratum/full number included in the nowadays assay (Table 1), a mensurate of the number of patients represented by each sampled individual (Vittinghoff et al. 2005). We used the p-value from Fisher's exact test to compare molecular profiles of the ii subgroups of interest to all other MRSA isolates (Table 2).
Table 2
Onset location, Ridom spa types, and PVL presence past MRSA subgroup [northward (%)].
| Characteristic | CO-PVL-negative a (n = 23) | scn-negative a (n = 15) | All other MRSA (n = 162) |
|---|---|---|---|
| CO-MRSA | 23 (100) b | 12 (lxxx.0) | 135 (83.3) |
| CC5 or CC5-like | |||
| t002 | 9 (39.i) b | i (6.vii) | 17 (10.5) |
| t010 | 2 (8.7) b | 0 | 0 |
| t045 | 0 | one (half-dozen.7) | 1 (0.6) |
| t062 | i (4.3) | 0 | 0 |
| t088 | 3 (13.0) b | one (6.7) | 0 |
| t105 | 1 (4.3) | 1 (vi.7) | 2 (ane.two) |
| t306 | 1 (4.iii) | 0 | 0 |
| t6614 | 1 (4.3) | 1 (half-dozen.7) | 0 |
| Other c | 0 | 0 | three (1.eight) |
| CC8 or CC8-similar | |||
| t008 | 0 b | 7 (46.vii) | 115 (71.0) |
| t024 | 0 | 1 (6.vii) | six (3.seven) |
| t068 | 0 | 0 | ii (1.ii) |
| t121 | 0 | 1 (half dozen.7) | 2 (1.2) |
| t622 | 0 | 0 | iii (1.nine) |
| Other d | 0 | 0 | seven (4.three) |
| Other CC | |||
| t125 | 1 (iv.three) | 1 (6.vii) | 0 |
| t948 | i (4.3) | 0 | 0 |
| t9964 | i (4.3) | 0 | 0 |
| t11970 | 1 (iv.3) | 0 | 0 |
| Other east | 0 | 0 | iii (i.nine) |
| Novel f | 1 (four.3) | 0 | ane (0.six) |
| PVL-positive | 0 b | 9 (60.0) b | 140 (86.4) |
| Percentages practise not add to 100 due to rounding. a Iv patients were in both the CO-PVL-negative group and the scn-negative grouping. b p-Value < 0.05 comparison two subgroups of interest to all other MRSA using Fisher'south exact exam. c One each of t437, t539, and t85. d One each of t064, t206, t211, t304, t681, t692, t1610. e One each of t216, t316, t11971. f Novel spa type. | |||
Models were constructed with attention to the small sample size. Our primary models compared the highest quartile of exposure to livestock or treated crop fields to all other quartiles combined. In addition, we modeled quartiles of exposure as an ordinal variable (0, ane, 2, 3) and used the p-value of the resulting coefficient as a test of linear tendency. For CO-PVL-negative MRSA, we as well estimated associations with individual quartiles of exposure relative to the lowest quartile, but numbers of observations were too small to run comparable models for scn-negative MRSA. Similarly, adjustment for confounders selected based on a priori information (Casey et al. 2013a, 2013b) was express to models of CO-PVL-negative MRSA. Specifically, nosotros adjusted for sex activity, age (continuous), ever-smoking status, season of infection [winter (December–February) vs. all other seasons combined], physician order for an antibiotic in the 365 to xiv days preceding diagnosis, and ever-receiving Medical Assistance as wellness insurance [as a surrogate for low individual socioeconomic status (Bratu et al. 2006; Casey et al. 2013b)]. Nosotros were unable to adjust models for race/ethnicity and to isolate sources considering data were off-support (Oakes 2006). Nosotros did not adjust for location of onset because location was part of the CO-PVL-negative MRSA definition. Statistical analyses were performed using Stata xi.two (StataCorp, College Station, TX) using the svy commands for weighted regression and R version 3.0.0 (R Foundation for Statistical Calculating, Vienna, Republic of austria).
Results
Study population characteristics. From 1 January to 31 December 2012 we collected data on 203 MRSA infections (from a pool of 1,128 patients with MRSA infection) from patients in twenty counties in Pennsylvania. The assay included 196 isolates (Effigy i) later exclusion of isolates lacking the mecA gene (n = iv) and patients who could non be geocoded or resided outside the study area (n = 3). We identified 30 unique Ridom spa types, 47 PVL-negative isolates and 15 scn-negative isolates, and no ST398 MRSA (Table 2). Four isolates were both CO-PVL-negative and scn-negative. Patients with CO-PVL-negative MRSA (n = 23) too as patients with scn-negative MRSA (n = xv) were older than patients in the all other MRSA group (n = 162) (Table iii). Patients with the two MRSA strains of involvement were less probable to reside in cities than were patients with all other MRSA strains (Tabular array 3). Patients in the 3rd and fourth quartiles of swine livestock exposure were more probable than those in the first and second quartiles to exist diagnosed in the autumn (Table three). Approximately 95% of patients with MRSA onset in the winter fell into the kickoff or second quartile of swine and dairy/veal crop field exposure (data not shown).
Table 3
Patient demographic and clinical characteristics of MRSA subgroups by swine livestock exposure quartile a [data are north (%) unless otherwise indicated]
| Feature | CO-PVL-negative (n = 23) b | scn-negative (n = xv) b | All other MRSA (n = 162) | Swine (quartile) | |||
|---|---|---|---|---|---|---|---|
| i | 2 | 3 | 4 | ||||
| Sex, male person | xv (65.2) | eleven (73.3) | 85 (52.five) | 28 (26.two) | 25 (23.4) | 24 (22.four) | 30 (28.0) |
| Age at infection or visit [median (interquartile range)] (years) | 54.2 (32.3–75.two) | 52.8 (xiv.6–75.1) | 32.eight (14.four–55.ii) | 46.0 (17.3–62.4) | 33.vi (22.v–54.7) | 31.1 (9.8–51.7) | 37.five (13.6–59.one) |
| Race/ethnicity c | |||||||
| Non-Hispanic white | 22 (95.7) | xv (100) | 155 (95.7) | 44 (23.four) | 49 (26.1) | 48 (25.5) | 47 (25.0) |
| Non-Hispanic black | 1 (four.4) | 0 | half-dozen (3.7) | 5 (71.4) | 0 | 0 | 2 (28.vi) |
| Other | 0 | 0 | one (0.6) | 0 | 0 | 1 (100) | 0 |
| Never-smoker | 16 (69.6) | x (66.7) | 139 (85.viii) | 39 (23.9) | 43 (26.4) | xl (24.five) | 41 (25.ii) |
| Season of onset | |||||||
| Wintertime | 7 (30.4) | 3 (twenty.0) | 27 (16.vii) | 12 (34.3) | 7 (20.0) | vii (20.0) | 9 (25.vii) |
| Leap | 5 (21.vii) | 4 (26.seven) | 37 (22.8) | xvi (34.viii) | xiii (28.3) | 9 (19.vi) | 8 (17.4) |
| Summer | 7 (30.4) | five (33.three) | 39 (24.1) | 10 (twenty.iv) | 16 (32.7) | 12 (24.5) | 11 (22.5) |
| Autumn | iv (17.4) | three (xx.0) | 59 (36.four) | 11 (16.7) | 13 (19.7) | 21 (31.viii) | 21 (31.eight) |
| Antibiotic prescription in previous year | 5 (21.7) | vi (40.0) | 65 (40.ane) | 21 (27.6) | 20 (26.3) | fifteen (nineteen.vii) | 20 (26.3) |
| Source | |||||||
| Pare/soft tissue | nineteen (82.6) | 11 (73.3) | 141 (87.0) | 36 (25.9) | 39 (28.1) | 28 (twenty.1) | 36 (25.nine) |
| Respiratory | 0 | 2 (13.3) | 15 (9.three) | 6 (35.iii) | iv (23.five) | iv (23.5) | 3 (17.7) |
| Bone | ii (8.7) | ane (half dozen.7) | 2 (one.2) | 1 (25.0) | 0 | 2 (50.0) | 1 (25.0) |
| Other | 2 (8.seven) | 1 (six.7) | 4 (2.5) | 0 | 3 (42.9) | ii (28.6) | two (28.half dozen) |
| Antibiotic resistance d | |||||||
| Clindamycin | 12 (52.2) | 2 (13.3) | 32 (19.8) | 10 (21.7) | 11 (23.9) | 13 (28.3) | 12 (26.one) |
| Erythromycin | 18 (78.three) | 12 (80.0) | 149 (92.0) | 43 (24.4) | 46 (26.i) | 46 (26.1) | 41 (23.three) |
| Tetracycline | 4 (17.4) | one (6.7) | 4 (two.five) | 2 (25.0) | 2 (25.0) | 2 (25.0) | 2 (25.0) |
| TMP-SMZ | 1 (four.four) | 1 (6.7) | 2 (1.ii) | two (66.7) | 1 (33.3) | 0 | 0 |
| Multidrug eastward | 14 (60.9) | 3 (20.0) | 33 (20.4) | 12 (24.5) | xi (22.five) | 14 (28.6) | 12 (24.5) |
| Community blazon | |||||||
| Urban center | 1 (4.4) | 0 | 23 (fourteen.2) | xi (45.8) | iii (12.5) | 9 (37.five) | i (iv.2) |
| Borough | 11 (47.8) | 5 (33.3) | 44 (27.2) | 15 (25.ix) | 15 (25.nine) | viii (thirteen.8) | 20 (34.5) |
| Township | 11 (47.8) | 10 (66.7) | 95 (58.vi) | 23 (twenty.2) | 31 (27.2) | 32 (28.ane) | 28 (24.6) |
| Medical Aid | |||||||
| Never received | 15 (65.2) | 10 (66.7) | 127 (78.four) | 35 (23.three) | 37 (24.7) | 41 (27.three) | 37 (24.7) |
| Location of onset | |||||||
| Community | 27 (100) | xv (83.3) | 135 (83.3) | 41 (24.7) | 43 (25.9) | forty (24.1) | 42 (25.3) |
| Infirmary | 0 | 3 (xvi.vii) | 27 (16.7) | 8 (26.7) | half-dozen (20.0) | 9 (30.0) | vii (23.3) |
| No. of patients with high-density livestock product in their residential ZIP code | 9 (39.1) | seven (46.7) | 67 (41.4) | 1 (1.ii) | 17 (21.0) | 25 (30.9) | 38 (46.ix) |
| Abbreviations: previous year, 365 to 14 days before infection; TMP-SMZ, trimethoprim– sulfamethoxazole. a Quartile 1: swine livestock exposure < 6.20 AEU/km2; quartile ii: 6.xx–16.00 AEU/km2; quartile 3: 16.01–33.40 AEU/km2; quartile 4: > 33.41 AEU/km2. b Four patients were in both the CO-PVL-negative grouping and the scn-negative grouping. c Race/ethnicity was missing for two members of the all other MRSA isolates comparison grouping. d Resistance to gentamicin was observed in one CO-PVL-negative isolate, and intermediate resistance to rifampin was observed in one all other MRSA isolates. e Resistance to three or more unique antimicrobials. | |||||||
Molecular testing. Nosotros identified 30 spa types, but 2 predominated: t008 [due north = 122 (62.two%)] and t002 [n = 27 (13.8%)] (Table 2). Almost all t008, n = 116 (95.i%), was community-onset, whereas the majority of t002, n = 17 (63.0%), was hospital-onset. Isolates lacking scn (n = 15) were distributed across multiple spa types, and lxxx% (due north = 12) were community-onset. CO-PVL-negative isolates were more often than not spa types associated with CC5.
Antimicrobial susceptibility. CO-PVL-negative strains were more often resistant to antibiotics commonly used to treat MRSA infection (i.e., clindamycin, tetracycline, and trimethoprim–sulfamethoxazole) than all other CO-PVL-positive MRSA strains. The 30 hospital-onset (HO)-MRSA isolates were resistant to more antibiotics compared with CO-MRSA: clindamycin (83.three% vs. 12.7%), tetracycline (half dozen.7% vs. 3.6%), trimethoprim–sulfamethoxazole (3.iii% vs. 1.two%), and multidrug (83.iii% vs. 14.5%). Resistance patterns did not announced to exist associated with agriculture exposure variables, only tetracycline resistance in a modest number of isolates (n = 4) was associated with infection past CO-PVL-negative MRSA (p = 0.02).
Associations with livestock and ingather field manure exposure. High-density livestock production was not associated with scn-negative MRSA infection in unadjusted analysis (Tabular array four). Swine livestock exposure was associated with CO-PVL-negative MRSA in unadjusted and adapted analysis (Tabular array 4), which appeared driven by the clan in the quaternary quartile of exposure (Figure 2). At that place was a positive but nonsignificant clan with the dichotomized dairy/veal livestock exposure variable [odds ratio (OR) = 2.42; 95% CI: 0.85, half dozen.88]. There was a tendency (p = 0.05) of increasing odds of CO-PVL-negative MRSA across quartiles of dairy/veal livestock exposure; however, all ORs were increasingly imprecise with higher exposure for individual versus everyman quartile exposures (Figure 2). Those in the highest quartile of swine ingather field exposure had an OR of 2.38 (95% CI: 0.78, 7.28) of being a CO-PVL-negative MRSA case compared with those in quartiles 1–3 (Table four). Dichotomous dairy/veal crop field exposure was associated with CO-PVL-negative MRSA in adjusted analyses (OR = 4.88; 95% CI: ane.40, 17.00) (Table four). Neither crop field variable evidenced a statistically significant trend beyond quartiles (Figure 2). Associations strengthened slightly equally nosotros added sex, historic period, ever-smoking, antibiotic society, and Medical Assist to the models. Season of onset was a strong confounder in the crop field exposure models [e.g., the unadjusted OR of 0.79 (95% CI: 0.20, three.09) increased to 2.38 (95% CI: 0.78, 7.28) (Table 4) for the swine crop field model, primarily due to the inclusion of season as a variable].
Table 4
Unadjusted and adapted a associations of dichotomous exposures with CO-PVL-negative MRSA and scn-negative MRSA compared with all other MRSA (north/N).
| Exposure | CO-PVL-negative b | scn-negative b | ||||
|---|---|---|---|---|---|---|
| All other MRSA (n/N) | Unadjusted OR (95% CI) | Adapted OR c (95% CI) | All other MRSA (due north/Northward) | Unadjusted OR (95% CI) | ||
| Livestock | ||||||
| Swine (quartile) | 1, 2, 3 | 12/124 | one.0 | ane.0 | 12/125 | 1.0 |
| 4 d | xi/37 | 3.55 (i.41, 8.94) | iv.24 (one.60, 11.25) | iii/37 | 0.79 (0.20, 3.09) | |
| Dairy/veal (quartile) | 1, ii, 3 | xv/122 | one.0 | 1.0 | 13/122 | 1.0 |
| 4 east | viii/40 | one.57 (0.61, 4.05) | two.42 (0.85, 6.88) | 2/forty | 0.47 (0.x, two.24) | |
| Treated crop field | ||||||
| Swine (quartile) | 1, 2, 3 | 15/121 | ane.0 | 1.0 | xiv/121 | 1.0 |
| 4 f | viii/41 | 1.55 (0.59, 4.05) | two.38 (0.78, 7.28) | 1/41 | 0.xviii (0.02, 1.43) | |
| Dairy/veal (quartile) | 1, 2, 3 | fourteen/123 | 1.0 | i.0 | 13/123 | 1.0 |
| iv k | 9/39 | 2.28 (0.89, five.83) | 4.88 (1.40, 17.00) | two/39 | 0.46 (0.10, 2.20) | |
Clan of swine and dairy/veal seasonal ingather field quartiles and livestock quartiles with CO-PVL-negative MRSA status from adapted models. Adapted for sex, age, ever-smoking status, antibody club in the 365 to 14 days before infection, flavor, and receipt of Medical Assistance. *p-Value for linear trend ≤ 0.05 (quartiles included every bit a single variable with values 1, two, three, and 4).
Discussion
This assay compared patients infected by two specific MRSA strains to patients infected by all other MRSA strains and found a number of associations with high-density livestock production. The livestock model incorporated AEUs at the farming operation and distance to the patient residence; whereas the ingather field model incorporated manure volume, crop field area, and distance to the patient residence. Although adjusted estimates were imprecise because of modest sample numbers, each exposure variable was associated with increased odds of CO-PVL-negative MRSA infection, and three of four were statistically significant. Specifically, there were increased odds comparing the fourth quartiles to the other three quartiles of both swine livestock exposure and dairy/veal ingather field exposure. There was too a significant tendency of increasing odds across the 4 quartiles for dairy/veal livestock exposure. For the fourth exposure variable, swine ingather field, the OR in the fourth quartile versus the other 3 was higher, but not statistically significant. Unexpectedly, we did not identify whatsoever patients with MRSA infection due to ST398, the MRSA subtype that previously has been associated with livestock operations, mainly based on studies of colonization in Europe. This raises two bug. First, to understand risk factors for MRSA infection, nosotros need to study MRSA infection rather than colonization. Second, although ST398 may be prevalent among swine and swine farmers in the United States, other strains found on farms may actually be more than important for infection.
When we did not identify whatsoever infections due to ST398, nosotros evaluated associations of livestock production with two other MRSA strains compared with all other MRSA strains. To our knowledge, but one U.S. study has reported PVL-positive MSRA isolated from swine (Osadebe et al. 2013). Associations with CO-PVL-negative MRSA were of interest because many highly successful human epidemic MRSA clones, like CC5, practice not incorporate PVL genes and take recently been isolated from swine and swine farmers in the U.s. (Frana et al. 2013; Molla et al. 2012; Osadebe et al. 2013). We observed 8 tetracycline-resistant isolates, 4 of which were CO-PVL-negative MRSA. This resistance could plausibly be a marking of high-density livestock production equally tetracycline is the antibody most commonly sold for use in U.S. subcontract animals, and isolates resistant to tetracycline accept been observed in workers at industrial livestock operations (Food and Drug Administration 2010; Rinsky et al. 2013). In addition, only 6.seven% of HO-MRSA was resistant to tetracycline, suggesting that the clan of CO-PVL-negative MRSA is not likely attributable to the health care system. Likewise, we selected scn-negative MRSA strains because we expected MRSA associated with livestock product to lack scn (McCarthy et al. 2011; Sung et al. 2008; Verkaik et al. 2011). Previous work showing option against scn in animate being hosts dealt primarily with ST398 (McCarthy et al. 2011), a strain of MRSA already adapted to animals (Price et al. 2012). Because the scn gene produces a protein that hinders phagocytosis of South. aureus by human neutrophils (Sung et al. 2008), this piece of work might not interpret directly to human-adapted strains of MRSA (e.g., ST5 or ST8), especially in the study of infection rather than colonization.
A few U.South. studies have molecularly characterized MRSA isolated from agricultural workers (Frana et al. 2013; Molla et al. 2012; Osadebe et al. 2013; Smith et al. 2009, 2013). Because those studies only described MRSA railroad vehicle in persons with straight contact with swine, they may have low utility regarding inference about MRSA infection in the community. Two studies reported transient carriage (< 24 hours) after brusk-term exposure to pigs and veal calves (Frana et al. 2013; van Cleef et al. 2011). Even if carriage persists after exposure, and the take a chance of infection increases, infection is not assured (Davis et al. 2004).
The body of literature on MRSA carriage is besides relevant to the absence of ST398 amongst our MRSA isolates. Although at that place is aplenty prove that those in contact with livestock have increased prevalence of ST398 MRSA colonization (Graveland et al. 2010; Smith et al. 2009; Voss et al. 2005), information propose that ST398 MRSA infection is rare (Golding et al. 2010; Salmenlinna et al. 2010; Wulf et al. 2012). Strains of MRSA adapted primarily to animals (east.chiliad., ST398) may have a diminished ability to infect humans (Graveland et al. 2011; Price et al. 2012). A contempo Italian written report reported a much greater proportion of ST398 amidst MRSA-colonized patients compared with those with a MRSA infection where ST8 was most prevalent (Monaco et al. 2013).
Misreckoning by occupation or socioeconomic status may accept impacted our associations. We could non obtain patient occupation from the electronic health records and, therefore, cannot exclude the possibility that some CO-PVL-MRSA cases were occupational versus community acquired. We adapted for Medical Assistance, a surrogate for depression socioeconomic status that was associated with MRSA infection in our previous study (Casey et al. 2013b), simply we acknowledge that in that location may be rest confounding due to socioeconomic status. Since the CO-PVL-negative MRSA group had several characteristics of health care–associated MRSA [(HA-MRSA), east.g., older age, antibiotic resistance, lack of PVL genes, many spa type t002] the clan with high-density livestock production could have arisen if HA-MRSA was more than common in rural areas. However, in a previous study conducted in this region, HA-MRSA was not more than common in rural areas (Casey et al. 2013b). Besides, HA-MRSA in the nowadays assay defined by common epidemiologic criteria (Morrison et al. 2006) was not associated with high-density livestock production (information not shown). We adjusted models for flavor of onset because, as expected, MRSA patients with onset in the wintertime had low exposure to treated crop fields (manure awarding is restricted in the winter).
The novel observations in this study require replication. Nosotros completed assay on a limited number of patients with a MRSA infection and, although nosotros incorporated several aspects of operations and crop fields into our individual-level exposure estimates, we did not collect environmental samples. Finally, we could not calculate incidence rates because we included merely patients with MRSA infection.
Conclusions
To our knowledge, no previous studies in the Usa take evaluated associations between patients infected with specific MRSA strains and high-density livestock product. We identified associations of CO-PVL-negative MRSA with swine and dairy/veal livestock operations and application of dairy/veal manure to crop fields. Our findings were based on minor numbers of observations and indirect estimates of exposure, just if confirmed, take important implications for the role of livestock operations in the MRSA epidemic, the different roles of colonization and infection studies, and the identification of other MRSA strains that may be arising from high-density livestock production. To help estimate the public health burden that loftier-density livestock production may place on the U.S. wellness care system, future studies should use MRSA infection, along with colonization, as their outcomes of interest. Our written report likewise indicates the need to look beyond MRSA ST398 when investigating MRSA infection associated with high-density livestock production in the United states.
Acknowledgments
We acknowledge the contributions of D.K. Mercer, J.J. DeWalle, M.S. Krutsick, and S.H. Brandau, who participated in written report management, data drove, and patient geocoding, and D. Altman, who assisted with microbiologic testing.
Footnotes
This enquiry was supported by the New York University–Geisinger Seed Grant Program, the Johns Hopkins Middle for a Livable Hereafter, the Johns Hopkins Sommer Scholarship, and the National Plant of Environmental Health Sciences (National Institutes of Health, grant ES07141).
The authors declare they have no actual or potential competing financial interests.
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