To reduce the likelihood of carcass contamination with Salmonella and other foodborne pathogens, numerous intervention strategies have been implemented in harvest facilities (Reed, 1995). Additionally, there is ongoing interest in preharvest strategies for reducing pathogen load in the gastrointestinal tracts or on the hides of animals (Attenborough and Matthews, 2000; Stephens et al., 2007). To facilitate preharvest intervention, additional understanding of the complex distribution of these pathogens in the feedlot setting is needed. Salmonella transmission to cattle on-farm can occur in many ways. Feed ingredients such as corn, hay, silage, cottonseed, and other additions may be contaminated by wild birds (Kapperud and Rosef, 1983; Malmqvist et al., 1995; Refsum et al., 2003), mammalian carriers (Davies and Wray, 1995; Malmqvist et al., 1995; Letellier et al., 1999), or surface-water runoff while in the field (Vaessen et al., 1998). Contamination may occur during processing, transport (Fedorka-Cray et al., 1997; Dargatz et al. , 2005), or on-site. Ingestion of contaminated surface water (Fossler et al., 2005b) or water from contaminated troughs (Branham et al., 2005) can also result in transmission. Additionally, animal-to-animal transmission may occur (Khaitsa et al., 2007), and management factors are likely to play a role (Fossler et al., 2005b). Knowledge of risk factors affecting Salmonellashedding can assist in planning preharvest strategies for reducing pathogen loads. Contributing to the epidemiologic evidence for relationships between dietary, social, physical, and other feedlot-related characteristics and Salmonella prevalence was an objective of this national study. Materials and Methods A stratified random sample of feedlots with [greater than or equalto] 1000-head capacity in 12 major cattle-feeding states (Arizona, California, Colorado, Idaho, Iowa, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Washington) was selected to participatein the study (Dargatz et al., 2003). Data were collected on 520 operations via personal interview from August 16 through September 22, 1999. These states accounted for 95.8% of the cattle on feed in lots with [greater than or equal to] 1000-head capacity in the U.S. as of January 1,1999. From the participating feedlots a convenience sample of 73 feedlots, based on laboratory capacity, was selected for fecalsample collection without regard to Salmonella infection status. Veterinary medical officers visited each feedlot once in the period from October 1999 through March 2000, and again in the period from April 2000 through September 2000. Data collectors were instructed to visit each feedlot approximately 6 months apart. At each visit, the pens of cattle that had been at the feedlot the shortest and the longest amounts of time and a randomly chosen pen were selected for sampling to investigate the frequency of recovery of Salmonella at different stages of feeding. For each pen of cattle sampled, health and management data (Tables 1 and 2) were provided by feedlot managers. Ingredient data were collected for the ration fed at the time of sampling. Within each pen 25 fresh fecalsamples (approximately 25 g) were collected from individual pats off pen floors as previously described (Dargatz et al., 2003). Collection of 25 samples per pen allowed 95% confidence of detecting at least one positiveanimal if the within pen prevalence was 10% or more, assuming 100% test sensitivity and specificity. Separate tongue depressors were used to collect each sample from the top of a fecal pat into a whirlpak bag, shipped with ice pack for overnight delivery to a single laboratory for immediate cultureupon receipt. Data and sample collectors received training before the study to standardize the collection process. Laboratory techniques Each sample was evaluated by bacteriologic culture for Salmonella using methods described previously (Wells et al., 2001). Approximately 1 g of feces from each sample was incubated in 9 mL each of GN Hajna broth (Difco Laboratories, Detroit, MI) and tetrathionate broth (Difco Laboratories) at 37[degrees]C for 24 and 48 h, respectively. Then, a 100 [micro]L aliquot of each culture was transferred to RappaportVassiladis broth R-10 (Difco Laboratories), incubated overnight, andthen streaked to brilliant green agar with sulfadiazine (Difco Laboratories) and xylose-lysine tergitol 4 agar (Difco Laboratories). Plates were incubated for 18-24 h at 37[degrees]C. Up to four colonies having the typical appearance of Salmonella (white to red opaque colonies surrounded by red zones on brilliant green agar with sulfadiazine,or pink to red colonies with a black center on xylose-lysine tergitol 4 agar) were inoculated into agar slants for biochemical confirmation. Presumptive positive isolates were serogrouped using serogroup specific antisera (Difco Laboratories) and were sent to the National Veterinary Services Laboratory (Ames, IA) for serotyping. Statistical techniques All analysis accounted for sampling design, nesting of pens withinfeedlots, and lack of independence within pens. Continuous variableswere graphed to identify natural cut points for creation of categories. When these were not clear, the data were divided into quartiles or halves for univariate analysis (Table 1). The association between factors and Salmonella culture status was evaluated using a chi-squaretest (SUDAAN version 9.0.1, CROSSTAB procedure). Variables were considered for inclusion in a multivariable logistic regression model (SUDAAN version 9.0.1, LOGISTIC procedure) if the chi-square p-value was<0.25. A backward elimination approach was utilized until all variables remaining in the model were significantly associated with the outcome ( p < 0.05). Biologically plausible two-way interactions among remaining main effect variables were examined. Since 18.3% (119/149) of positivesamples were on a single feedlot, a second model was constructed after excluding the 149 samples fromthis feedlot. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for variables in the models. To assess the fit of eachmodel, sensitivity and specificity of the model-predicted outcomes were assessed by treating the observed status as the gold standard. A probability cut point of [greater than or equal to] 0.5 was used for predicted outcome; samples with a predicted probability of [greater than or equal to] 50% that they were positive were classified as positive. Results Descriptive results from the study have been reported elsewhere (Dargatz et al., 2003). For the first model, 10,243 fecalsamples from 415 pens from 73 feedlots were included. Salmonella was isolated from650 samples (6%) from 92 pens (22%) on 37 feedlots (51%). The five most common serotypes included Anatum (n = 195), Montevideo (n = 127),Reading (n = 69), Newport (n = 63), and Kentucky (n = 57). For the second model, 10,094 fecalsamples from 409 pens were included. Salmonella was isolated from 531 samples (5.3%) from 86 pens (21.0%) on 36 feedlots (50.0%). Risk factors Of the 55 variables considered as potential risk factors associated with detection of Salmonella-positive fecalsamples (Tables 1 and 2), 30 were eligible for entry into the first model; 4 variables representing the use of chlortetracycline, chlortetracycline/sulfamethazine, oxytetracycline, and tetracycline in feed or water were combined into a single variable, so 26 candidate variables were evaluated. In addition to tetracycline use, other variables that met the screening criterion included season, region, feedlot size, pen density, mass treatment of cattle in pen with injectable antibiotics, any dairy cattlein pen, percent sick in pen, any deaths in pen, single herd of origin, frequency of water trough cleaning, grain processing method, and the presence or absence of specific ingredients in penrations, including soybean meal; cottonseed; cottonseedmeal; urea; other proteins; brewer’sgrains; whole wheat; a coccidiostat; alfalfa, clover, or sorghum hay; cottonseed hulls; alfalfa, clover, or sorghumsilage; corngluten; tallow; and other byproducts. Variables for sex of the predominant number of animals in pen, sourcing any cattle in pen from salebarn, entry weight, average weight of cattle in pen at sampling, days on feed at time of sampling, remaining days on feed at time of sampling, whether animals in the pen were dewormed, distance traveled to feedlot, and the ration ingredients and/or additives including sorghum,other concentrates, ionophore, cornsilage, other roughage, and tylosin in feed or water were not eligible for model entry due to a chi-square p > 0.25. Variables for use of bacitracin, neomycin, or virginiamycin could not be analyzed because these antimicrobials were not utilized. Use of sulfa antimicrobials could not be analyzed owing to their use on a single operation. The rationvariables for wheat fines/mids, chicken waste, barley, potato waste, and beet pulp were excludedfrom the model because of sparse data, as each of these ingredients was used on less than 10% of feedlots and in only one region. The rationvariable for corn was excluded from the model due to sparse data. Fifteen variables remained in the multivariable model using all observations (Table 3). Samples collected in all other seasons were more likely to have Salmonella detected compared to the January through March season. Samples collected from feedlots in the southern region were also more likely to have Salmonella detected (OR = 3.23; CI, 1.57-6.64) as were samples collected from feedlots with less than 8000-head capacity (OR = 7.99; CI, 3.60-17.71). Other variables that were positively associated with the detection of Salmonella included whether cattle in a pen were from multiple herds of origin (OR = 8.37; CI, 4.22-16.60), and inclusion of cottonseed hulls (OR = 5.19; CI, 1.87-14.41), corngluten (OR = 7.11; CI, 3.96-12.79), other protein sources(OR = 3.10; CI, 1.78-5.38), brewer’sgrains (OR = 26.85; CI, 9.89-72.86), or hay (OR = 2.56; CI, 1.28-5.09) in the ration. Factors associated with decreased risk of Salmonella detection included use of a tetracycline-class antimicrobial in feed or water within 2 weeks beforefecal sampling (OR = 0.08; CI, 0.02-0.32), inclusion of urea (OR = 0.46; CI, 0.30-0.69), and use of alfalfa, clover, or sorghumsilage (OR = 0.35; CI, 0.15-0.83) in the penration. After removing the data for the feedlot with 18.3% of the positivesamples, a slightly different model resulted (Table 3). Seven of thevariables from the model with the full dataset were retained in the second model. These included having a single herd of origin for cattle in a pen and the following ration ingredients: urea; cottonseed hulls; alfalfa, clover, or sorghumsilage; corngluten; brewers’grains or malt; and tetracycline-class antimicrobials. Three additional variables were added to the model: grain processing method, soybean meal,and use of a coccidiostat in rations. Biologically plausible two-wayinteractions were examined. Unfortunately, since all of these variables except one were feed related, interaction terms resulted in sparse data for some of the combinations of variables, so these interactions could not be analyzed. Sensitivity and specificity for the complete dataset model were 18% and 100%, respectively. Within this population, the positive predictive value for the model was 70% and the negative predictive value for the model was 95%. For the second model, sensitivity and specificity were 20% and 99%, respectively. The positive predictive value was approximately 54% and the negative predictive value was approximately 96%. Discussion Other research findings are consistent with an increase in likelihood of Salmonella detection in samples from pens with cattle from more than one herd of origin. Change in social groups has been shown to increase fecalshedding of Salmonella in production animals (Callawayet al., 2006); this may be due to the stress that accompanies reestablishing a dominance hierarchy (Morrow-Tesch et al., 1994). Another explanation for this finding is the transmission of Salmonella to previously uninfected cattle once commingling occurs (Khaitsa et al., 2007). This possibility of transmission is consistent with the increase in percent positivesamples seen as length of time on feed increased.The potentially stress-related increase in Salmonella in samples from pens with cattle from more than one herd of origin may also occur in other situations where social groups of cattle are mixed, such as in transport to slaughter (Reicks et al., 2007). In both models, the inclusion of cottonseed hulls in the penrations was associated with an increase in likelihood of Salmonella detection. Cottonseed-component feeds sampled on the farm (Davis et al., 2003) and at the processor (McChesney et al., 1995) have tested positive for Salmonella in several studies. Feeding whole cottonseed or cottonseed hulls has been associated with increased risk of Salmonella ina previous National Animal Health Monitoring System (NAHMS) feedlot study (Losinger et al., 1997). Physiologically, when fat-supplementeddiets are fed, ruminal pH tends to be greater, and volatile fatty acid (VFA) concentration is generally lower (Elliott et al., 1999). Increased production of VFA may more effectively inhibit growth of Salmonella (Mattila et al., 1988), whereas decreased production of ruminalVFAs may be less likely to inhibit growth. In both models, corngluten and brewers’grains in penrations were associated with an increase in likelihood of Salmonella detection. Although we did not differentiate between wet and dry cornglutenfeed, total ruminal VFAs have been shown to decrease linearly with increasing levels of wet cornglutenfeed (Sindt et al., 2002), and growthof Salmonella may be inhibited in the presence of high concentrations of VFA (Mattila et al., 1988). Feeding brewers’grains was associated with an increased risk of Salmonella detection in fecalsamples from the NAHMS Dairy’96 study (Kabagambe et al., 2000). Wet brewers’grains have a high moisture content that may promote Salmonella growth (Preston, 1998). Due to the magnitude of association between these variables and the outcome variable, more work is indicated to understand risk associated with feeding by-products from the biofuel industry.A recent study found no association between feeding wet corn distillers’ grains and pen-level prevalence of Salmonella spp. (Jacob et al., 2008). In both models, urea and silage in the penrations were associatedwith a decrease in likelihood of Salmonella detection, as was the use of tetracyclines in feed and water. Urea’s protective effects may be due to replacement of another protein component with greater likelihood of contamination. Well-fermented silage has a high lactic acid content; lactic acid has an antimicrobial effect on Salmonella in vitro (De Keersmaecker et al., 2006). In a Netherlands dairy study, grasssupplemented with silage was shown to have an apparent protective effect against Salmonella Dublin infection when compared with grass-only feed (Vaessen et al., 1998). While tetracycline use may be associated with a decreased prevalence of salmonellae, prudent antimicrobial use is advised (Fossler et al., 2005a). Although tetracycline use maydecrease the overall prevalence of salmonellae, those that remain may be more resistant to tetracyclines. This is of concern not only from animal health and food safety perspectives but perhaps from an ecologic perspective as well. Factors that did not remain in the second model included season, region, and feedlot size, as well as other protein, hay, whole wheat, cottonseedmeal, and tallow in the penrations. Season has been associated with Salmonellashedding in dairycattle in a number of studies; shedding tends to be more common in the summer months (Evans, 1996; Kabagambe et al., 2000; Wells et al., 2001; Fossler et al., 2005a; Davison et al., 2006). Additionally, survival of Salmonella in the environment may be increased in the summer months, although soil composition, moisture, and temperature fluctuation appear to play a role (Holley et al., 2006; Semenov et al., 2007). While climate may play a role in Salmonellashedding, and heat stress may be a factor that contributes to increased shedding, the two regionsthat were compared during the study both included plains states withsomewhat similar climates. Factors present in the second model that were not significant in the full dataset model included grain-processing method, soybean meal,and a coccidiostat in penration. That grain-processing method stayed in the second model is consistent with findings from a Colorado feedlot study in which a higher percentage of dry-corn samples than high-moisture cornsamples tested positive for Salmonella bacteria (4.0% vs. 0.6%, respectively) (Dargatz et al., 2005). Generally, high-moisture corn is more digestible than dry-rolled corn (Ladely et al., 1995; Archibeque et al., 2006). As noted above, higher digestibility can result in increased production of VFAs, which may more effectively inhibit growth of Salmonella. Soybean-meal feedsamples have tested positive for Salmonella in several feed-sample studies (McChesney et al., 1995; Kidd et al., 2002). Coccidiosis is an opportunistic disease that can develop in conjunction with other stress factors. As both Salmonellashedding and coccidiosis tend to be associated with physiologic stress, the presence of both agents may act synergistically to increase excretion of Salmonella; therefore, the use of a coccidiostat may play a protective role. Such an effect has been demonstrated experimentally in poultry (Kosugi et al., 1986). An alternative explanation is that the protective effect of coccidiostat use seen in the second model may be a reflection of other management differences between pens with Salmonella and those without. Because ionophores are labeled in the use of coccidiosis, one might expect to see a similar effect of ionophores in rations,but an in vitro study suggests that ionophore feeding has minimal effect on ruminant Salmonella populations (Edrington et al., 2003). The low sensitivity and positive predictive value of both models indicate that other factors than those examined here are involved in predicting the presence of Salmonella in feedlotpensamples. The lackof sensitivity may be due to the presence of other factors that werenot measured. Also, it is possible that the sensitivity of the sampling and testing procedure resulted in misclassification of truly positivesamples (and pens). For example, testing environmental samples from each pen may have been a more efficient way to identify fecal culture-positive pens than using fresh samples, which were generally representative of individual animals (Warnick et al., 2003). Misclassification would make it more difficult to identify factors associated with the presence of Salmonella but would increase the specificity of the model. Pens in each feedlot were sampled once in the period from October 1999 through March 2000 and once in the period from April through September 2000, intervals during which a number of pen-level changes can occur, whereas a longitudinal approach with more frequent sampling might be of higher sensitivity. The variability in digestibility of particular ration components may play a role in Salmonella replication. Data on previous exposure to various ration components was not collected. As such, previous exposures to those that have longer-term effects would not be detected in this analysis. Additionally, recent dietary changes would not be detected in this analysis. Gastrointestinal flora can be affected by many factors, including dietary changes and other stressors (Rostagno et al., 2009). 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Can stress in farm animals increase food safety risk?Foodborne Pathog Dis 2009;6:767-776. Semenov AV, van Bruggen AH, van Overbeek L, et al. Influence of temperature fluctuations on Escherichia coli O157:H7 and Salmonella enterica serovar Typhimurium in cow manure. FEMS Micobiol Ecol 2007;60:419-428. Sindt JJ, Drouillard JS, Thippareddi H, et al. Evaluation of finishing performance, carcass characteristics, acid-resistant E. coli andtotal coliforms from steers fed combinations of wet corngluten feedand steam-flaked corn. J Anim Sci 2002;80:3328-3335. Stephens TP, Loneragan GH, Karunasena E, Brashears MM. Reduction of Escherichia coli O157 and Salmonella in feces and on hides of feedlotcattle using various doses of a direct-fed microbial. J Food Prot 2007;70:2386-2391. Vaessen MA, Veling J, Frankena K, et al. Risk factors for Salmonella Dublin infection on dairy farms. Vet Q 1998;20:97-99. Voetsch AC, Van Gilder TJ, Angulo FJ, et al. FoodNet estimate of the burden of illness caused by nontyphoidal Salmonella infections in the United States. CID 2004;38(Suppl 3): S127-S134. Warnick LD, Kaneene J, Ruegg P, et al. Evaluation of herd samplingfor Salmonella isolation on midwest and northeast US dairy farms. Prev Vet Med 2003;60:195-206. Wells SJ, Fedorka-Cray PJ, Dargatz DA, et al. Fecalshedding of Salmonella spp. by dairycows on farm and at cull cowmarkets. J Food Prot 2001;64:3-11. Alice L. Green, (1) David A. Dargatz, (2) Bruce A. Wagner, (2) Paula J. Fedorka-Cray, (3) Scott R. Ladely, (3) and Chris A. Kopral (2) (1) Tennessee Department of Health, Communicable and EnvironmentalDisease Services, Nashville, Tennessee. (2) Centers for Epidemiology and Animal Health, Animal and Plant Health Inspection Service, Veterinary Services, U.S. Department of Agriculture, Fort Collins, Colorado. (3) Richard B. Russell Research Center, Agricultural Research Service, U.S. Department of Agriculture, Athens, Georgia. Address correspondence to: Alice L. Green, M.S., D.V.M. Tennessee Department of Health Communicable and Environmental Disease Services Cordell Hull Building, 1st Floor 425 5th Ave. North Nashville, TN 37243 E-mail: alice.l.green@gmail.com TABLE 1. PERCENTAGE OF SAMPLES FROM WHICH SALMONELLA WAS RECOVERED BY STATISTICALLY SIGNIFICANT FEEDLOT AND PEN-LEVEL MANAGEMENT VARIABLES (ALL FEEDLOTS) Number of Variable Description p-Value samples Season <0.01 Jan-March 3025 April-June 2930 July-Sept 2450 Oct-Dec 1838 Region <0.01 North IA, ID, NE, SD, WA 5138 South CA, CO, KS, NM, OK, TX 5105 Size (one-time feedlot <0.01 capacity) Less than 8000 head 5370 8000 head or more 4873 Any dairyanimals in 0.01 pen Yes 924 No 9319 Pen density category 0.09 Less than 167 sqft per 2551 animal 167 or more sqft per 7442 animal Mass treatment with <0.01 injectable abx (anytime before sampling) Yes 1110 No or DK (a) 9133 Cumulative percent 0.09 sick category 0 to less than 3 pct 5406 sick in pen 3 or more pct sick in 4763 pen Any in pen died since 0.21 arrival Yes 4101 No 6142 Single herd of origin 0.03 Yes 1903 No or DK (b) 8340 Water trough cleaning 0.07 category Cleaned less than 1 4823 week ago Cleaned 1 week or more 5105 ago Number Percent Variable Description positive positive Season Jan-March 86 2.8 April-June 205 7.0 July-Sept 286 11.7 Oct-Dec 73 4.0 Region North IA, ID, NE, SD, WA 248 4.83 South CA, CO, KS, NM, OK, TX 402 7.87 Size (one-time feedlot capacity) Less than 8000 head 418 7.78 8000 head or more 232 4.76 Any dairyanimals in pen Yes 112 12.1 No 538 5.8 Pen density category Less than 167 sqft per 215 8.40 animal 167 or more sqft per 389 5.20 animal Mass treatment with injectable abx (anytime before sampling) Yes 121 10.9 No or DK (a) 529 5.8 Cumulative percent sick category 0 to less than 3 pct 274 5.1 sick in pen 3 or more pct sick in 376 7.9 pen Any in pen died since arrival Yes 201 4.9 No 449 7.3 Single herd of origin Yes 62 3.3 No or DK (b) 588 7.1 Water trough cleaning category Cleaned less than 1 259 5.4 week ago Cleaned 1 week or more 390 7.6 ago Number Percent Variable Description negative negative Season Jan-March 2939 97.2 April-June 2725 93.0 July-Sept 2164 88.3 Oct-Dec 1765 96.0 Region North IA, ID, NE, SD, WA 4890 95.2 South CA, CO, KS, NM, OK, TX 4703 92.1 Size (one-time feedlot capacity) Less than 8000 head 4952 92.22 8000 head or more 4641 95.24 Any dairyanimals in pen Yes 812 87.90 No 8781 94.2 Pen density category Less than 167 sqft per 2336 91.6 animal 167 or more sqft per 7053 94.8 animal Mass treatment with injectable abx (anytime before sampling) Yes 989 89.1 No or DK (a) 8604 94.2 Cumulative percent sick category 0 to less than 3 pct 5132 94.9 sick in pen 3 or more pct sick in 4387 92.1 pen Any in pen died since arrival Yes 3900 95.1 No 5693 92.7 Single herd of origin Yes 1841 96.7 No or DK (b) 7752 93.0 Water trough cleaning category Cleaned less than 1 4564 94.6 week ago Cleaned 1 week or more 4715 92.4 ago (a) Includes 149 samples without data. (b) Includes 941 samples without data. pct, percent. TABLE 2. PERCENTAGE OF SAMPLES FROM WHICH SALMONELLA WAS RECOVERED BY STATISTICALLY SIGNIFICANT FEEDLOT AND PEN-LEVEL FEED AND WATER-RELATED VARIABLES (ALL FEEDLOTS) Number of Variable Description p-Value samples How grain is processed 0.23 Steam flaked, ground 3107 high moisture (high- moisture grain) Dry roll, cracked, 6827 unprocessed whole grain, other (dry grain) Barley in ration <0.01 Yes 375 No 9743 Brewers’grains in <0.01 ration Yes 590 No 9528 Corn in ration 0.20 Yes 9461 No 657 Whole wheat <0.01 Yes 872 No 9246 Wheat fines/mids <0.01 Yes 499 No 9619 Coccidiostat 0.21 (Amprolium, Decoquinate) in pen ration Yes 748 No 9370 Canola meal 0.18 Yes 175 No or DK (a) 9943 Chicken waste <0.01 Yes 25 No or DK (a) 10093 Cottonseed whole 0.04 Yes 491 No or DK (a) 9627 Cottonseedmeal <0.01 Yes 1538 No or DK (a) 8580 Soybean meal <0.01 Yes 2762 No or DK (a) 7356 Urea <0.01 Yes 6086 No or DK (a) 4032 Other proteins <0.01 Yes 1613 No or DK (b) 8505 Alfalfa, clover, or <0.01 sorghum hay Yes 7600 No 2518 Cottonseed hulls <0.01 Yes 1059 No 9059 Alfalfa, clover, or <0.01 sorghumsilage Yes 1492 No 8626 Corngluten <0.01 Yes 2900 No 7218 Beet pulp <0.01 Yes 325 No 9793 Tallow <0.01 Yes 2404 No 7714 Potato Waste <0.01 Yes 774 No 9344 Other byproducts <0.01 Yes 2482 No 7636 Any bacitracin use in Yes N/A 0 feed or water No 10243 Chlortetracycline in <0.01 feed or water within 2 weeks before sampling Yes, within 2 weeks 715 Yes, but not within 1065 2 weeks No, never 8463 Chlortet/sulfa in feed <0.01 or water within 2 weeks before sampling Yes, within 2 weeks 134 Yes, but not within 390 2 weeks No, never 9719 Oxytet in feed or <0.01 water within 2 weeks before sampling Yes, within 2 weeks 299 Yes, but not within 574 2 weeks No, never 9370 Any tetracycline use 0.08 (chlortet, chlortet/ sulfa, tet, oxytet) Yes, within 2 weeks 1223 Yes, but not within 2004 2 weeks No, never 7016 Any virginiamycin use N/A in feed or water Yes 0 No 10243 Number Percent Variable Description positive positive How grain is processed Steam flaked, ground 179 5.80 high moisture (high- moisture grain) Dry roll, cracked, 460 6.74 unprocessed whole grain, other (dry grain) Barley in ration Yes 1 0.3 No 648 6.7 Brewers’grains in ration Yes 183 31.0 No 466 4.9 Corn in ration Yes 582 6.2 No 67 10.2 Whole wheat Yes 9 1.0 No 640 6.9 Wheat fines/mids Yes 140 28.1 No 509 5.3 Coccidiostat (Amprolium, Decoquinate) in pen ration Yes 22 2.9 No 627 6.7 Canola meal Yes 22 12.6 No or DK (a) 627 6.3 Chicken waste Yes 1 4.0 No or DK (a) 648 6.4 Cottonseed whole Yes 11 2.2 No or DK (a) 638 6.6 Cottonseedmeal Yes 165 10.7 No or DK (a) 484 5.6 Soybean meal Yes 96 3.5 No or DK (a) 553 7.5 Urea Yes 201 3.3 No or DK (a) 448 11.1 Other proteins Yes 233 14.5 No or DK (b) 416 4.9 Alfalfa, clover, or sorghum hay Yes 423 5.6 No 226 9.0 Cottonseed hulls Yes 184 17.4 No 465 5.1 Alfalfa, clover, or sorghumsilage Yes 25 1.7 No 624 7.2 Corngluten Yes 278 9.6 No 371 5.1 Beet pulp Yes 4 1.2 No 645 6.6 Tallow Yes 91 3.8 No 558 7.2 Potato Waste Yes 2 0.3 No 647 6.9 Other byproducts Yes 262 10.6 No 387 5.1 Any bacitracin use in Yes 0 N/A feed or water No 650 6.4 Chlortetracycline in feed or water within 2 weeks before sampling Yes, within 2 weeks 5 0.7 Yes, but not within 35 3.3 2 weeks No, never 610 7.2 Chlortet/sulfa in feed or water within 2 weeks before sampling Yes, within 2 weeks 5 3.7 Yes, but not within 1 0.3 2 weeks No, never 644 6.6 Oxytet in feed or water within 2 weeks before sampling Yes, within 2 weeks 14 4.7 Yes, but not within 105 18.3 2 weeks No, never 531 5.7 Any tetracycline use (chlortet, chlortet/ sulfa, tet, oxytet) Yes, within 2 weeks 24 2.0 Yes, but not within 140 7.0 2 weeks No, never 486 6.9 Any virginiamycin use in feed or water Yes 0 N/A No 650 6.4 Number Percent Variable Description negative negative How grain is processed Steam flaked, ground 2928 94.2 high moisture (high- moisture grain) Dry roll, cracked, 6367 93.3 unprocessed whole grain, other (dry grain) Barley in ration Yes 374 99.7 No 9095 93.4 Brewers’grains in ration Yes 407 69.0 No 9062 95.1 Corn in ration Yes 8879 93.9 No 590 89.8 Whole wheat Yes 863 99.0 No 8606 93.1 Wheat fines/mids Yes 359 71.9 No 9110 94.7 Coccidiostat (Amprolium, Decoquinate) in pen ration Yes 726 97.1 No 8743 93.3 Canola meal Yes 153 87.4 No or DK (a) 9167 93.7 Chicken waste Yes 24 96.0 No or DK (a) 9445 93.6 Cottonseed whole Yes 480 97.8 No or DK (a) 8989 93.4 Cottonseedmeal Yes 1373 89.3 No or DK (a) 8096 94.4 Soybean meal Yes 2666 96.5 No or DK (a) 6803 92.5 Urea Yes 5885 96.7 No or DK (a) 3584 88.9 Other proteins Yes 1380 85.6 No or DK (b) 8089 95.1 Alfalfa, clover, or sorghum hay Yes 7177 94.4 No 2292 91.0 Cottonseed hulls Yes 875 82.6 No 8594 94.9 Alfalfa, clover, or sorghumsilage Yes 1467 98.3 No 8002 92.8 Corngluten Yes 2622 90.4 No 6847 94.9 Beet pulp Yes 321 98.8 No 9148 93.4 Tallow Yes 2313 96.2 No 7156 92.8 Potato Waste Yes 772 99.7 No 8697 93.1 Other byproducts Yes 2220 89.4 No 7249 94.9 Any bacitracin use in Yes feed or water No 9593 93.7 Chlortetracycline in feed or water within 2 weeks before sampling Yes, within 2 weeks 710 99.3 Yes, but not within 1030 96.7 2 weeks No, never 7853 92.8 Chlortet/sulfa in feed or water within 2 weeks before sampling Yes, within 2 weeks 129 96.3 Yes, but not within 389 99.7 2 weeks No, never 9075 93.4 Oxytet in feed or water within 2 weeks before sampling Yes, within 2 weeks 285.0 95.3 Yes, but not within 469 81.7 2 weeks No, never 8839.0 94.3 Any tetracycline use (chlortet, chlortet/ sulfa, tet, oxytet) Yes, within 2 weeks 1199 98.0 Yes, but not within 1864 93.0 2 weeks No, never 6530 93.1 Any virginiamycin use in feed or water Yes No 9593 93.7 (a) Includes 149 samples without data. (b) Includes 74 samples without data. N/A, not available. TABLE 3. ALL-OPERATION AND SECOND LOGISTIC REGRESSION MODELS FOR RISK FACTORS ASSOCIATED WITH ISOLATION OF SALMONELLA SPP. All operations All 95% operations confidence Variable Categories odds ratio interval Season Jan-March 1.0 Apr-June 3.69 1.76-7.77 July-Sept 4.04 2.09-7.81 Oct-Dec 4.39 1.81-10.64 Region North (IA,ID, NE, 1.0 SD, WA) South (CA, CO, KS, 3.23 1.57-6.64 NM, OK, TX) Feedlot size (one- Less than 8000 head 7.99 3.60-17.71 time capacity) 8000 head or more 1.0 Single herd of Yes 0.12 0.06-0.24 origin No or DK 1.0 Grain processing steam flaked or Not in model method ground high moisture corn dry roll, cracked or unprocessed whole grain Soy in penration Yes Not in model No Urea in penration Yes 0.46 0.30-0.69 No or DK 1.0 Other protein in Yes 3.10 1.78-5.38 penration No or DK 1.0 (includes but not limited to sunflower products, feather meal unspecified plant protein, and alfalfa) Cottonseed hulls Yes 5.19 1.87-14.41 in penration No or DK 1.0 Alfalfa, clover, Yes 0.35 0.15-0.83 or sorghum No or DK 1.0 silage in pen ration Hay in penration Yes 2.56 1.28-5.09 No or DK 1.0 Corngluten in pen Yes 7.11 3.96-12.79 ration No 1.0 Brewersgrains/ Yes 26.85 9.89-72.86 malt in pen No or DK 1.0 ration Whole wheat in pen Yes 0.11 0.03-0.35 ration No or DK 1.0 Cottonseedmeal in Yes 4.10 2.07-8.12 penration No or DK 1.0 Tallow in pen Yes 0.37 0.16-0.88 ration No or DK 1.0 Coccidiostat Yes Not in model (Amprolium, Deco No 4.50 2.03-10.01 quinate) in pen ration Tetracycline-class Yes, within 2 weeks 0.08 0.02-0.32 antimicrobials before sampling in penration Yes, but not before 0.47 0.20-1.10 sampling No 1.0 Final 95% Final odds confidence Variable Categories ratio interval Season Jan-March Not in model Apr-June July-Sept Oct-Dec Region North (IA,ID, NE, Not in model SD, WA) South (CA, CO, KS, NM, OK, TX) Feedlot size (one- Less than 8000 head Not in model time capacity) 8000 head or more Single herd of Yes 0.19 0.09-0.43 origin No or DK 1.0 Grain processing steam flaked or 1.0 method ground high moisture corn dry roll, cracked 2.99 1.55-5.75 or unprocessed whole grain Soy in penration Yes 2.74 1.58-4.75 No Urea in penration Yes 0.27 0.16-0.44 No or DK 1.0 Other protein in Yes Not in model penration No or DK (includes but not limited to sunflower products, feather meal unspecified plant protein, and alfalfa) Cottonseed hulls Yes 8.34 3.58-19.42 in penration No or DK 1.0 Alfalfa, clover, Yes 0.31 0.12-0.79 or sorghum No or DK 1.0 silage in pen ration Hay in penration Yes Not in model No or DK Corngluten in pen Yes 10.35 5.98-17.91 ration No 1.0 Brewersgrains/ Yes 26.35 10.33-67.20 malt in pen No or DK 1.0 ration Whole wheat in pen Yes ration No or DK Not in model Cottonseedmeal in Yes Not in model penration No or DK Tallow in pen Yes ration No or DK Not in model Coccidiostat Yes 1.0 (Amprolium, Deco No quinate) in pen ration Tetracycline-class Yes, within 2 weeks 0.04 0.02-0.09 antimicrobials before sampling in penration Yes, but not before 0.23 0.06-0.80 sampling No 1.0
