Guidelines to restrict consumption of red meat to under 350 g/wk based on colorectal cancer risk are not consistent with health evidence.

BACKGROUND: The Nordic Nutrition Recommendations of 2023 (NNR2023) incorporate sustainability, health, and nutrition in their food-based dietary guidelines (FBDGs). NNR2023 recommends a consumption of ≤350 g/wk of unprocessed red meat (RM) based on association with colorectal cancer (CRC). This recommendation is lower than other FBDGs such as the World Cancer Research Fund (WCRF) recommendation it is based on (350-500 g/wk). OBJECTIVE: To evaluate the empirical evidence and models cited by the NNR2023 to support the RM guidance. METHODS: We fitted least-assumption (LA) dose-response (DR) models to the studies included in two systematic reviews (SRs) selected by NNR2023 on the RM and CRC association. We compared them against six parametric models reported in the two SRs. We evaluated the statistical significance of modeled relative risks (RR) at different consumption levels. RESULTS: Twenty-one studies (20,604,188 patient-years) were analyzed. We found no significant association (RR = 1.04, 0.99-1.09) between 350g/wk of RM and CRC using the LA models, in agreement with the least restrictive models reported by Lescinsky et al., 2022 (RR = 1.11[0.89-1.38]) and WCRF (RR= 1.01[0.96-1.07]). The association was significant at 350 g/wk only under restricting assumptions such as monotonicity RR=1.3[1.01-1.64], and linearity RR = 1.06 [1.00-1.12]. No significant empirical association is observed under 567 g/wk based on evidence used by NNR2023. CONCLUSIONS: The sources cited by NNR2023 do not support a consumption restriction of ≤350 g/wk of RM due to CRC, and other studies omitted by NNR2023 do not support association between RM and CRC. We show that model assumptions rather than empirical evidence drive this recommendation. Model uncertainty should be explicitly incorporated in FBDGs.

Observational Dose-Response Meta-Analysis Methods May Bias Risk Estimates at Low Consumption Levels: The Case of Meat and Colorectal Cancer.

Observational studies of foods and health are susceptible to bias, particularly from confounding between diet and other lifestyle factors. Common methods for deriving dose-response meta-analysis (DRMA) may contribute to biased or overly certain risk estimates. We used DRMA models to evaluate the empirical evidence for colorectal cancer (CRC) association with unprocessed red meat (RM) and processed meats (PM), and the consistency of this association for low and high consumers under different modeling assumptions. Using the Global Burden of Disease project's systematic reviews as a start, we compiled a data set of studies of PM with 29 cohorts contributing 23,522,676 person-years and of 23 cohorts for RM totaling 17,259,839 person-years. We fitted DRMA models to lower consumers only [consumption < United States median of PM (21 g/d) or RM (56 g/d)] and compared them with DRMA models using all consumers. To investigate impacts of model selection, we compared classical DRMA models against an empirical model for both lower consumers only and for all consumers. Finally, we assessed if the type of reference consumer (nonconsumer or mixed consumer/nonconsumer) influenced a meta-analysis of the lowest consumption arm. We found no significant association with consumption of 50 g/d RM using an empirical fit with lower consumption (relative risk [RR] 0.93 (0.8-1.02) or all consumption levels (1.04 (0.99-1.10)), while classical models showed RRs as high as 1.09 (1.00-1.18) at 50g/day. PM consumption of 20 g/d was not associated with CRC (1.01 (0.87-1.18)) when using lower consumer data, regardless of model choice. Using all consumption data resulted in association with CRC at 20g/day of PM for the empirical models (1.07 (1.02-1.12)) and with as little as 1g/day for classical models. The empirical DRMA showed nonlinear, nonmonotonic relationships for PM and RM. Nonconsumer reference groups did not affect RM (P = 0.056) or PM (P = 0.937) association with CRC in lowest consumption arms. In conclusion, classical DRMA model assumptions and inclusion of higher consumption levels influence the association between CRC and low RM and PM consumption. Furthermore, a no-risk limit of 0 g/d consumption of RM and PM is inconsistent with the evidence.

The genomic and epidemiological virulence patterns of Salmonella enterica serovars in the United States.

The serovars of Salmonella enterica display dramatic differences in pathogenesis and host preferences. We developed a process (patent pending) for grouping Salmonella isolates and serovars by their public health risk. We collated a curated set of 12,337 S. enterica isolate genomes from human, beef, and bovine sources in the US. After annotating a virulence gene catalog for each isolate, we used unsupervised random forest methods to estimate the proximity (similarity) between isolates based upon the genomic presentation of putative virulence traits We then grouped isolates (virulence clusters) using hierarchical clustering (Ward's method), used non-parametric bootstrapping to assess cluster stability, and externally validated the clusters against epidemiological virulence measures from FoodNet, the National Outbreak Reporting System (NORS), and US federal sampling of beef products. We identified five stable virulence clusters of S. enterica serovars. Cluster 1 (higher virulence) serovars yielded an annual incidence rate of domestically acquired sporadic cases roughly one and a half times higher than the other four clusters combined (Clusters 2-5, lower virulence). Compared to other clusters, cluster 1 also had a higher proportion of infections leading to hospitalization and was implicated in more foodborne and beef-associated outbreaks, despite being isolated at a similar frequency from beef products as other clusters. We also identified subpopulations within 11 serovars. Remarkably, we found S. Infantis and S. Typhimurium subpopulations that significantly differed in genome length and clinical case presentation. Further, we found that the presence of the pESI plasmid accounted for the genome length differences between the S. Infantis subpopulations. Our results show that S. enterica strains associated with highest incidence of human infections share a common virulence repertoire. This work could be updated regularly and used in combination with foodborne surveillance information to prioritize serovars of public health concern.

Sleeping with the enemy: Maintaining ASF-free farms in affected areas.

African Swine Fever (ASF) continues to spread worldwide, with very limited eradication success in countries where the disease affects domestic pig populations. Various biosecurity tools exist to reduce the on-farm risk incursion of ASF and other diseases. However, their focus on overall biosecurity scores and benchmarking results in recommendations that are not always cost-effective. We propose to apply a risk analysis approach that actively involves farmers and farmworkers in identifying their weakest links in biosecurity and corresponding mitigation efforts. Furthermore, the approach's focus on describing and understanding pathways of introduction and/or spread specific to individual farms creates buy-in from producers for investing in biosecurity measures and improving compliance.

Codex Alimentarius Guidelines for Risk Analysis of Foodborne Antimicrobial Resistance Are Incompatible with Available Surveillance Data.

ABSTRACT: Foodborne antimicrobial-resistant (AMR) microorganisms are a global food safety concern. Antimicrobial drug use (AMU) in livestock may increase the risk of resistant foodborne bacterial infections in humans via contaminated animal products. Consequently, countries have implemented different livestock AMU restriction policies, opening the potential for trade disputes. AMR risk equivalence between countries with different AMU policies must be established by using scientifically justified risk assessments. The Codex Alimentarius Commission's Guidelines for Risk Analysis of Foodborne Antimicrobial Resistance (AMR Codex) recommends an approach that requires quantification of detailed information, for which, in many instances, little to no data exist. Using AMR Salmonella exposure from beef consumption as an example, we demonstrate the difficulty of implementing the AMR Codex by comparing key regionally specific parameters within the United States and European Union, two regions with substantial beef production and consumption, robust foodborne pathogen sampling and surveillance systems, and different AMU policies. Currently, neither region fully captures data for key regional variables to populate a detailed risk assessment as outlined in the AMR Codex, nor are they able to adequately link AMU in livestock to AMR infections in humans. Therefore, the AMR Codex guidelines are currently aspirational and not a viable option to assess the impact of livestock AMU reductions on the human health risk of AMR salmonellosis from beef or produce regionally comparable estimates of risk. More flexible risk assessment guidelines that more directly link livestock AMU to human health risk and are amenable to currently available data are needed to allow for country variations and to calculate comparable regional risk estimates, which can be used to guide international trade policy.

Partitioning, a Novel Approach to Mitigate the Risk and Impact of African Swine Fever in Affected Areas.

As African swine fever (ASF) continues to expand geographically, supplementary control strategies are needed to reduce disease risk and impact in affected areas. Full depopulation is central to current ASF control efforts, and its efficacy depends on surveillance and timely disease reporting, while resulting in large losses regardless of the producers' efforts to promptly detect, report, and contain the disease. This disconnect between prompt detection and reporting, and subsequent farm losses, can deter producers to invest in ASF detection and control. Alternative approaches are needed to incentivize individual producers to invest in early detection and reporting. We postulate that commercial swine farms may be effectively partitioned in separate units, or subpopulations, to which biosecurity, surveillance and control can be applied. The suggested Partitioning framework relies on three main components: 1. external and internal biosecurity to reduce the risk of ASF introduction and maintain separate subpopulations; 2. cost-effective on-farm ASF surveillance to enhance early detection; 3. response plans at the unit level, including culling of affected subpopulations, and demonstration of freedom from disease on the remaining ones. With such Partitioning approach, individual producers may reduce ASF risk on a farm and in the region, while also reducing ASF outbreak losses via targeted depopulation of affected units. It requires relevant legislation to incorporate the notion of within-farm subpopulations and provide a regulatory framework for targeted depopulation and substantiation of disease freedom. Its design should be tailored to fit individual farms. Partitioning can be an effective public-private partnership approach for ASF risk reduction. It should be driven by industry, as its benefits are accrued mainly by individual producers, but regulatory oversight is key to ensure proper implementation and avoid further disease spread. Partitioning's value is greatest for producers in ASF-affected regions, but ASF-free areas could also benefit from it for preparedness and early detection. It could also be adapted to other transboundary animal diseases and can be implemented as a stand-alone program or in conjunction with other efforts such as zoning and compartmentalization. Partitioning would contribute to the improved resilience and sustainability of the global pork industry and will benefit consumers and society through improved food security and animal welfare.

No Change in Risk for Antibiotic-Resistant Salmonellosis from Beef, United States, 2002-2010.

Restricting antibiotic use in food production animals is a target for reducing antimicrobial drug-resistant infections in humans. We used US surveillance data to estimate the probability of antibiotic-resistant nontyphoidal salmonellosis per meal made with beef during 2002-2010. Applying data for nontyphoidal Salmonella in raised-without-antibiotics cattle, we tested the effect of removing antibiotic use from all beef cattle production. We found an average of 1.2 (95% credible interval 0.6-4.2) antibiotic-resistant nontyphoidal salmonellosis cases per 1 million beef meals made with beef initially contaminated with antibiotic-resistant nontyphoidal Salmonella at slaughter or retail and 0.031 (95% credible interval 0.00018-0.14) cases per 1 million meals irrespective of beef contamination status. Neither outcome showed sustained change except for increases in 2003 and 2009 (>98% confidence) when larger or more outbreaks occurred. Switching all beef production to a raised-without-antibiotics system may not have a significant effect on antibiotic-resistant nontyphoidal salmonellosis (94.3% confidence).

The EAT-Lancet Commission's Dietary Composition May Not Prevent Noncommunicable Disease Mortality.

The recently published EAT-Lancet Commission report on dietary impacts on the environment suggested that their proposed diet could prevent more than 10 million annual premature mortalities from noncommunicable diseases globally. The report did not meet standards for transparency and replicability, nor did it fully account for statistical uncertainty. Our attempt to replicate the mortality calculations for the United States revealed flaws in the assumptions and methods used to estimate the avoided mortalities. After correcting some calculation errors and fully accounting for uncertainty in the avoided mortalities, the mortality reduction effect of the EAT-Lancet proposed diet in the USA is no greater than the impact of energy consumption changes that would prevent under-weight, over-weight, and obesity alone. As our findings call into question the global conclusions of the EAT-Lancet report, futher independent validation is needed before it can be used to inform dietary guidelines.

Probabilistic estimates of heterocyclic amines and polycyclic aromatic hydrocarbons concentrations in meats and breads applicable to exposure assessments.

Random effect meta-regressions were constructed to estimate concentrations of two heterocyclic amines (HCA) and eight polycyclic aromatic hydrocarbons (PAH) in meat and breads. Eighteen HCA studies and nine PAH studies of food concentration were assembled. Concentration was computed for beef, poultry, pork, and seafood, and bread. Fixed effect predictors included cooking time, form of the food, cooking method, interaction between form and cooking method, temperature at which the food was cooked, fuel of the flame source, percentage of fat, and other elements. Meat type was significant to all HCAs but only three of the PAHs. Cooking method or an interaction between cooking method and food form was significant in all the overall models for each compound, and 80% of models created for stratifications of the data based on meat type. Improvement on compilations such as the Computerized Heterocyclic Amines Resource for Research in Epidemiology of Disease (CHARRED) database comes from inclusion of additional studies, PAH compounds, more generalizable food categories, more cooking methods (such as smoking), and addition of seafood. Meta-regression allows parameters to be estimated with separation of between-study heterogeneity, and extrapolation of exposures to more foods. Resulting uncertainty estimates are useful in a probabilistic exposure assessment.

Probabilistic assessment of dietary exposure to heterocyclic amines and polycyclic aromatic hydrocarbons from consumption of meats and breads in the United States.

This probabilistic analysis estimated daily dietary exposures of the US population to heterocyclic amines and polycyclic aromatic hydrocarbons from meat and some varieties of bread. Mean concentrations for these foods grouped by cooking method and food form were combined with consumption data from the National Health and Nutritional Examination Survey (NHANES). Mean exposure to HCA2 (PhIP + MeIQx), was 565.3 ng/day (95% CrI: 403.73, 726.88), and to PAH8 (sum of BaP, ChY, BaA, BkF, BbF, DahA, IP, and BghiP), was 634.8 ng/day (568.38, 701.15). HCA2 exposures were not significantly different between meat types, but multiple differences were found between cooking types. Exposures to PAH8 in the mean consumers differed significantly between cooking methods, and were higher for beef than poultry (mean difference: 983 ng, 95%CrI: -77.0, 4076.0) and pork (990 ng, 95%CrI: 23.7, 4061.8), but not for any other food comparisons. Tradeoffs between exposures associated with a typical portion size of potential food replacements were also examined. Differences in HCA2 and PAH8 exposure are primarily driven by the preparation method rather than the type of meat. These findings should be considered in future studies linking PAH and HCA compounds with human health impacts.

Outbreak-Related Disease Burden Associated with Consumption of Unpasteurized Cow's Milk and Cheese, United States, 2009-2014.

The growing popularity of unpasteurized milk in the United States raises public health concerns. We estimated outbreak-related illnesses and hospitalizations caused by the consumption of cow's milk and cheese contaminated with Shiga toxin-producing Escherichia coli, Salmonella spp., Listeria monocytogenes, and Campylobacter spp. using a model relying on publicly available outbreak data. In the United States, outbreaks associated with dairy consumption cause, on average, 760 illnesses/year and 22 hospitalizations/year, mostly from Salmonella spp. and Campylobacter spp. Unpasteurized milk, consumed by only 3.2% of the population, and cheese, consumed by only 1.6% of the population, caused 96% of illnesses caused by contaminated dairy products. Unpasteurized dairy products thus cause 840 (95% CrI 611-1,158) times more illnesses and 45 (95% CrI 34-59) times more hospitalizations than pasteurized products. As consumption of unpasteurized dairy products grows, illnesses will increase steadily; a doubling in the consumption of unpasteurized milk or cheese could increase outbreak-related illnesses by 96%.

The Impact of Population, Contact, and Spatial Heterogeneity on Epidemic Model Predictions.

Our objective was to evaluate the effect that complexity in the form of different levels of spatial, population, and contact heterogeneity has in the predictions of a mechanistic epidemic model. A model that simulates the spatiotemporal spread of infectious diseases between animal populations was developed. Sixteen scenarios of foot-and-mouth disease infection in cattle were analyzed, involving combinations of the following factors: multiple production-types (PT) with heterogeneous contact and population structure versus single PT, random versus actual spatial distribution of population units, high versus low infectivity, and no vaccination versus preemptive vaccination. The epidemic size and duration was larger for scenarios with multiple PT versus single PT. Ignoring the actual unit locations did not affect the epidemic size in scenarios with multiple PT/high infectivity, but resulted in smaller epidemic sizes in scenarios using multiple PT/low infectivity. In conclusion, when modeling fast-spreading epidemics, knowing the actual locations of population units may not be as relevant as collecting information on population and contact heterogeneity. In contrast, both population and spatial heterogeneity might be important to model slower spreading epidemic diseases. Our findings can be used to inform data collection and modeling efforts to inform health policy and planning.

Small-scale pig farmers' behavior, silent release of African swine fever virus and consequences for disease spread.

The expanding distribution of African swine fever (ASF) is threatening the pig industry worldwide. Most outbreaks occur in backyard and small-scale herds, where poor farmers often attempt to limit the disease's economic consequences by the emergency sale of their pigs. The risk of African swine fever virus (ASFV) release via this emergency sale was investigated. Simulation modeling was used to study ASFV transmission in backyard and small-scale farms as well as the emergency sale of pigs, and the potential impact of improving farmers and traders' clinical diagnosis ability-its timeliness and/or accuracy-was assessed. The risk of ASFV release was shown to be high, and improving farmers' clinical diagnosis ability does not appear sufficient to effectively reduce this risk. Estimates obtained also showed that the distribution of herd size within the backyard and small-scale sectors influences the relative contribution of these farms to the risk of release of infected pigs. These findings can inform surveillance and control programs.

Cost-benefit analysis of vaccination against Mycobacterium avium ssp. paratuberculosis in dairy cattle, given its cross-reactivity with tuberculosis tests.

Johne's disease (JD), or paratuberculosis, is a chronic enteric disease of ruminants, caused by infection with Mycobacterium avium ssp. paratuberculosis (MAP). Johne's disease causes considerable economic losses to the US dairy industry, estimated to be over $200 million annually. Available control strategies include management measures to improve calf hygiene, test-and-cull strategies, and vaccination. Although the first 2 strategies have shown to reduce the prevalence of MAP, they require dedicated and long-term efforts from dairy producers, with often relatively slow progress. As a result, uptake of both strategies has not been as wide as expected given the economic benefits especially of improved hygiene. Vaccination has also been found to reduce the prevalence and economic losses of JD, but most economic estimates have been based on simulation of hypothetical vaccines. In addition, if an animal is vaccinated, cross-reactivity between MAP antibodies and bovine tuberculosis (BTB) antigens may occur, decreasing the specificity of BTB tests. Therefore, MAP vaccination would cause additional indirect costs to the BTB surveillance and control program. The objective of the present study was to use data from a MAP vaccine trial together with an epidemiologic and economic model to estimate the direct on-farm benefits of MAP vaccination and to estimate the indirect costs of MAP vaccination due to the cross-reactivity with BTB tests. Direct economic benefits of MAP vaccination were estimated at $8.03 (90% predictive interval: -$25.97 to $41.36) per adult animal per year, all accruing to the dairy producers. This estimate is likely an underestimation of the true direct benefits of MAP vaccination. In addition, indirect economic costs due to cross-reactivity were $2.14 per adult animal per year, making MAP vaccination economically attractive. Only in regions or states with a high frequency of BTB testing (because of, for example, Mycobacterium bovis outbreaks in a wild deer population) and areas where typically small groups of animals are BTB tested would MAP vaccination not be economically attractive.

Meta-analysis of adverse events in recent randomized clinical trials for dimethyl fumarate, glatiramer acetate and teriflunomide for the treatment of relapsing forms of multiple sclerosis.

PURPOSE/AIM OF THE STUDY: Trials of dimethyl fumarate (DMF) and teriflunomide, two new oral therapies for relapsing-remitting multiple sclerosis (RRMS) were recently published [1, 2, 3]. A comparison of their safety against glatiramer acetate-a prevalent injectable treatment-is relevant to inform therapy-switching decisions. The study objective was to conduct a systematic review and mixed treatment comparison of total AEs in RCTs of dimethyl fumarate 240 mg bid (DMF2) or tid (DMF3), glatiramer acetate 20 mg injectable daily (GA), and teriflunomide 7 mg (TERI7) or 14 mg (TERI14) daily in RRMS patients. MATERIALS AND METHODS: Articles were selected following Cochrane guidelines. A network meta-analysis was used to compare the odds of patients experiencing at least one AE between drugs, using placebo as baseline. Drugs were compared using the odds ratio (OR), credible interval (CrI), and confidence in OR≥1 (PrOR). The mean rank (best=1) and corresponding Surface-Under-Cumulative-Ranking (SUCRA) (best=100%) were reported. RESULTS: 3737 patients from three RCTs were included for analysis. Patients receiving GA exhibited the lowest AEs (DMF2 [OR=2.67, PrOR=98.7%], DMF3 [OR=1.92, PrOR=95.3%], Teri7 [OR=2.74, PrOR=95.2%], Teri14 [OR=3.03, PrOR=96.4%]), and equivalent to PB (OR=1.60; PrOR=94.3%). No other significant differences were found. GA also ranked with the lowest AEs (rank=1.2, SUCRA=96.0%), whereas DMF2 and Teri14 ranked highest (rank=4.8). CONCLUSIONS: RRMS patients treated with glatiramer have the lowest odds of experiencing AEs, while patients taking DMF or teriflunomide have similar, higher odds of developing AEs, suggesting that patients treated with glatiramer may have higher QoL than patients under DMF or teriflunomide.

Disease spread models to estimate highly uncertain emerging diseases losses for animal agriculture insurance policies: an application to the U.S. farm-raised catfish industry.

Emerging diseases (ED) can have devastating effects on agriculture. Consequently, agricultural insurance for ED can develop if basic insurability criteria are met, including the capability to estimate the severity of ED outbreaks with associated uncertainty. The U.S. farm-raised channel catfish (Ictalurus punctatus) industry was used to evaluate the feasibility of using a disease spread simulation modeling framework to estimate the potential losses from new ED for agricultural insurance purposes. Two stochastic models were used to simulate the spread of ED between and within channel catfish ponds in Mississippi (MS) under high, medium, and low disease impact scenarios. The mean (95% prediction interval (PI)) proportion of ponds infected within disease-impacted farms was 7.6% (3.8%, 22.8%), 24.5% (3.8%, 72.0%), and 45.6% (4.0%, 92.3%), and the mean (95% PI) proportion of fish mortalities in ponds affected by the disease was 9.8% (1.4%, 26.7%), 49.2% (4.7%, 60.7%), and 88.3% (85.9%, 90.5%) for the low, medium, and high impact scenarios, respectively. The farm-level mortality losses from an ED were up to 40.3% of the total farm inventory and can be used for insurance premium rate development. Disease spread modeling provides a systematic way to organize the current knowledge on the ED perils and, ultimately, use this information to help develop actuarially sound agricultural insurance policies and premiums. However, the estimates obtained will include a large amount of uncertainty driven by the stochastic nature of disease outbreaks, by the uncertainty in the frequency of future ED occurrences, and by the often sparse data available from past outbreaks.

Indirect comparisons of adverse events and dropout rates in early Parkinson's disease trials of pramipexole, ropinirole, and rasagiline.

The comparative safety profiles of monotherapeutic treatments for Parkinson's disease (PD) can provide valuable therapeutic information. The objective of this study was to perform an indirect comparison of Adverse Events (AEs) and Dropout Rates (DRs) among clinical trials of pramipexole, ropinirole, and rasagiline. Outcomes analyzed included DRs, total AEs, and AE categories: Cognitive (CG), Gastrointestinal (GI), and Sleep/Fatigue (SF). The odds-ratio (OR) and Credible Interval (CrI) of outcomes between products using placebo as common comparator was calculated using indirect meta-analytical methods. AEs incidences for subjects receiving rasagiline were not significantly different from placebo, whereas DRs were significantly lower than for placebo (OR = 0.55; 95% CrI = 0.34-0.88). Patients receiving pramipexole or ropinirole had higher incidence of all AEs and DRs than patients taking rasagiline, except for the nonsignificant incidence of CG for ropinirole vs. rasagiline (1.76; 0.69-4.70). The incidence of GI (2.11; 1.13-4.06) and SF (2.75; 1.42-5.47) was significantly higher for ropinirole than for pramipexole, whereas the incidence of CG was significantly lower for ropinirole than for pramipexole (0.22; 0.07-0.69). Findings suggest that subjects with early PD treated with rasagiline have fewer AEs and DRs than those treated with pramipexole or ropinirole. GI and SF AEs were highest for subjects treated with ropinirole, while individuals treated with pramipexole exhibited the highest incidence of cognitive AEs.