Assessing the difference in contamination of retail meat with multidrug-resistant bacteria using for-consumer package label claims that indicate on-farm antibiotic use practices- United States, 2016-2019.

BACKGROUND: Antibiotic use in food-producing animals can select for antibiotic resistance in bacteria that can be transmitted to people through contamination of food products during meat processing. Contamination resulting in foodborne illness contributes to adverse health outcomes. Some livestock producers have implemented antibiotic use reduction strategies marketed to consumers on regulated retail meat packaging labels ("label claims"). OBJECTIVE: We investigated whether retail meat label claims were associated with isolation of multidrug-resistant organisms (MDROs, resistant to ≥3 classes of antibiotics) from U.S. meat samples. METHODS: We utilized retail meat data from the U.S. Food and Drug Administration National Antimicrobial Resistance Monitoring System (NARMS) collected during 2016-2019 for bacterial contamination of chicken breast, ground turkey, ground beef, and pork chops. We used modified Poisson regression models to compare the prevalence of MDRO contamination among meat samples with any antibiotic restriction label claims versus those without such claims (i.e., conventionally produced). RESULTS: In NARMS, 62,338 meat samples were evaluated for bacterial growth from 2016-2019. Of these, 24,446 (39%) samples had label claims that indicated antibiotic use was restricted during animal production. MDROs were isolated from 2252 (4%) meat samples, of which 71% (n = 1591) were conventionally produced, and 29% (n = 661) had antibiotic restriction label claims. Compared with conventional samples, meat with antibiotic restriction label claims had a statistically lower prevalence of MDROs (adjusted prevalence ratio: 0.66; 95% CI: 0.61, 0.73). This relationship was consistent for the outcome of any bacterial growth. IMPACT: This repeated cross-sectional analysis of a nationally representative retail meat surveillance database in the United States supports that retail meats labeled with antibiotic restriction claims were less likely to be contaminated with MDROs compared with retail meat without such claims during 2016-2019. These findings indicate the potential for the public to become exposed to bacterial pathogens via retail meat and emphasizes a possibility that consumers could reduce their exposure to environmental reservoirs of foodborne pathogens that are resistant to antibiotics.

Distance and destination of retail meat alter multidrug resistant contamination in the United States food system.

Antibiotic-resistant infections are a global concern, especially those caused by multidrug-resistant (MDR) bacteria, defined as those resistant to more than three drug classes. The animal agriculture industry contributes to the antimicrobial resistant foodborne illness burden via contaminated retail meat. In the United States, retail meat is shipped across the country. Therefore, understanding geospatial factors that influence MDR bacterial contamination is vital to protect consumers and inform interventions. Using data available from the United States Food and Drug Administration's National Antimicrobial Resistance Monitoring System (NARMS), we describe retail meat shipping distances using processor and retailer locations and investigated this distance as a risk factor for MDR bacteria meat contamination using log-binomial regression. Meat samples collected during 2012-2014 totaled 11,243, of which 4791 (42.61%) were contaminated with bacteria and 835 (17.43%) of those bacteria were MDR. All examined geospatial factors were associated with MDR bacteria meat contamination. After adjustment for year and meat type, we found higher prevalence of MDR contamination among meat processed in the south (relative adjusted prevalence ratio [aPR] 1.35; 95% CI 1.06-1.73 when compared to the next-highest region), sold in Maryland (aPR 1.12; 95% CI 0.95-1.32 when compared to the next-highest state), and shipped from 194 to 469 miles (aPR 1.59; 95% CI 1.31-1.94 when compared to meats that traveled < 194 miles). However, sensitivity analyses revealed that New York sold the meat with the highest prevalence of MDR Salmonella contamination (4.84%). In this secondary analysis of NARMS data, both geographic location where products were sold and the shipping distance were associated with microbial contamination on retail meat.

Probabilistic Machine Learning with Low-Cost Sensor Networks for Occupational Exposure Assessment and Industrial Hygiene Decision Making.

Occupational exposure assessments are dominated by small sample sizes and low spatial and temporal resolution with a focus on conducting Occupational Safety and Health Administration regulatory compliance sampling. However, this style of exposure assessment is likely to underestimate true exposures and their variability in sampled areas, and entirely fail to characterize exposures in unsampled areas. The American Industrial Hygiene Association (AIHA) has developed a more realistic system of exposure ratings based on estimating the 95th percentiles of the exposures that can be used to better represent exposure uncertainty and exposure variability for decision-making; however, the ratings can still fail to capture realistic exposure with small sample sizes. Therefore, low-cost sensor networks consisting of numerous lower-quality sensors have been used to measure occupational exposures at a high spatiotemporal scale. However, the sensors must be calibrated in the laboratory or field to a reference standard. Using data from carbon monoxide (CO) sensors deployed in a heavy equipment manufacturing facility for eight months from August 2017 to March 2018, we demonstrate that machine learning with probabilistic gradient boosted decision trees (GBDT) can model raw sensor readings to reference data highly accurately, entirely removing the need for laboratory calibration. Further, we indicate how the machine learning models can produce probabilistic hazard maps of the manufacturing floor, creating a visual tool for assessing facility-wide exposures. Additionally, the ability to have a fully modeled prediction distribution for each measurement enables the use of the AIHA exposure ratings, which provide an enhanced industrial decision-making framework as opposed to simply determining if a small number of measurements were above or below a pertinent occupational exposure limit. Lastly, we show how a probabilistic modeling exposure assessment with high spatiotemporal resolution data can prevent exposure misclassifications associated with traditional models that rely exclusively on mean or point predictions.

Contamination of Retail Meat Samples with Multidrug-Resistant Organisms in Relation to Organic and Conventional Production and Processing: A Cross-Sectional Analysis of Data from the United States National Antimicrobial Resistance Monitoring System, 2012-2017.

BACKGROUND: During food animal production, animals are exposed to, colonized by, and sometimes infected with bacteria that may contaminate animal products with susceptible and multidrug-resistant organisms (MDRO). The United States' Organic Foods Production Act resulted in decreased antibiotic use in some animal production operations. Some studies have reported that decreased antibiotic use is associated with reduced MDRO on meat. OBJECTIVES: The aim of this study was to investigate associations of meat production and processing methods with MDRO and overall bacterial contamination of retail meats. METHODS: Bacterial contamination data from 2012 to 2017 for chicken breast, ground beef, ground turkey, and pork chops were downloaded from the National Antimicrobial Resistance Monitoring System. Poisson regression models with robust variance were used to estimate associations with MDRO contamination and any contamination (adjusted for year and meat type) overall, and according to bacteria genus (Salmonella, Campylobacter, Enterococcus, Escherichia coli) and meat type. RESULTS: A total of 39,349 retail meat samples were linked to 216 conventional, 123 split (conventional and organic), and three organic processing facilities. MDRO contamination was similar in conventionally produced meats processed at split vs. conventional facilities but was significantly lower in organically produced meats processed at split facilities [adjusted prevalance ratio (aPR)=0.43; 95% CI: 0.30, 0.63]. Meat processed by split vs. conventional processors had higher or similar MDRO contamination for all tested bacterial genera except Campylobacter (aPR=0.29; 95% CI: 0.13, 0.64). The prevalence of any contamination was lower in samples processed at split vs. conventional facilities for aggregated samples (aPR=0.70; 95% CI: 0.68, 0.73) and all meat types and bacterial genera. DISCUSSION: Organically produced and processed retail meat samples had a significantly lower prevalence of MDRO than conventionally produced and processed samples had, whereas meat from split processors had a lower prevalence of any contamination than samples from conventional processors had. Additional studies are needed to confirm findings and clarify specific production and processing practices that might explain them. https://doi.org/10.1289/EHP7327.

Benzene Exposure and Cancer Risk from Commercial Gasoline Station Fueling Events Using a Novel Self-Sampling Protocol.

Tens of millions of individuals go to gasoline stations on a daily basis in the United States. One of the constituents of gasoline is benzene, a Group 1 carcinogen that has been strongly linked to both occupational and non-occupational leukemias. While benzene content in gasoline is federally regulated, there is approximately a thirty-year data gap in United States research on benzene exposures from pumping gasoline. Using a novel self-sampling protocol with whole air canisters, we conducted a gasoline pumping exposure assessment for benzene, toluene, ethylbenzene, and xylene (BTEX) on Baltimore, MD consumers. Geometric mean exposures (geometric standard deviations) were 3.2 (2.7) ppb,9.5 (3.5) ppb, 2.0 (2.8) ppb, and 7.3 (3.0) ppb, respectively, on 32 samples. Using the benzene exposures, we conducted consumer and occupational probabilistic risk assessments and contextualized the risk with ambient benzene exposure risk. We found that the consumer scenarios did not approach the 1:1,000,000 excess risk management threshold and that the occupational scenario did not exceed the 1:10,000 excess risk management threshold. Further, in all Monte Carlo trials, the ambient risk from benzene exposure exceeded that of pumping risk for consumers, but that in approximately 30% of occupational trials, the pumping risk exceeded the ambient risk.