Effect of welfare standards and biosecurity practices on antimicrobial use in beef cattle

Antimicrobial resistance (AMR) driven by antimicrobial use (AMU) in livestock is a global concern. While research has linked improved animal welfare and biosecurity to AMU reduction in pigs and dairy cattle, the beef sector remains understudied. This study aimed to determine the relationship between welfare standards, biosecurity practices, and AMU in Italian beef cattle. The hypothesis was that higher welfare and biosecurity standards would correlate with lower AMU. Understanding these relationships is critical for developing effective on-farm strategies to promote prudent antimicrobial stewardship and mitigate the growing threat of AMR. The study's importance lies in its contribution to the limited research on AMU in beef cattle, a sector significantly contributing to overall antimicrobial consumption in the European Union. The findings could inform farm benchmarking and guide the development of targeted interventions to reduce AMU without compromising animal health and welfare. The Italian beef cattle industry, with its reliance on calves purchased from other EU countries and intensive fattening practices, presents a relevant case study for exploring these factors.

Extensive literature supports the link between animal welfare, biosecurity, and animal health. Improved welfare reduces stress, strengthening the immune system and decreasing disease susceptibility, thereby potentially lowering AMU. Similarly, robust biosecurity measures (both internal and external) prevent pathogen introduction and spread, improving animal health and reducing the need for antimicrobials. Studies in pigs and dairy cattle have shown this positive correlation, but data for beef cattle are scarce. Some research suggests that farmers' perceptions regarding antimicrobials—believing them essential for animal health—may hinder changes in management practices. However, other studies have shown poor welfare and health outcomes even with high AMU, indicating that this perception is not universally true. The European Innovation Partnership for Agricultural Productivity and Sustainability (EIP-AGRI) highlighted the need for more research into the welfare-AMU relationship in beef cattle. Existing studies on this topic in beef cattle are limited, emphasizing the importance of this research.

Data were collected from 27 specialized beef farms in the Veneto region of Italy between January 2016 and April 2019. The dataset included 1294 batches and 87,902 animals. Data on performance traits (body weight, average daily gain (ADG), mortality rate), AMU (number of parenteral treatments, defined daily dose for animals (DDDAit), and Treatment Incidence 100 (TI100)), and farm characteristics were gathered. On-farm assessments scored welfare, biosecurity, and emergency management (0-100%), with the latter two receiving low scores. The TI100 was calculated using the DDDAit and the European Medicines Agency's DDDvet, as well as indexes using only Highest Priority Critically Important Antimicrobials (HPCIA). Data were analyzed using SAS 9.4. Pearson correlations assessed relationships between welfare, biosecurity, and emergency management. ANOVA and generalized linear mixed models (GLMM) investigated the effects of welfare, biosecurity, and emergency management on different TI100 indexes, controlling for sex, season, farm, and breed. A modified Italian protocol for assessing dairy cow welfare was adapted for beef cattle, using a three-point scale for each of 56 items grouped into total welfare, biosecurity and emergency management sections. The scores were then converted to a percentage (0-100%).

The average farm had 596.8 heads (SD 295.9). The highest average score was for welfare (76%), followed by emergency management (39%) and biosecurity (24%). Improved welfare significantly reduced AMU (TI100it and TI100vet). There was a positive correlation between welfare and biosecurity. Performance traits (initial and final body weight, ADG, and length of fattening cycle) differed significantly between categories of welfare, biosecurity, and emergency management. Breeds showed significant differences in AMU across all TI100 indexes. The lowest initial body weight was reported for the highest category of total welfare, biosecurity and emergency management. The number of days spent in the production cycle was lower for the highest category of total welfare, while the opposite result was observed for biosecurity and emergency management.

The study's key finding—that improved welfare significantly reduces AMU—supports previous research and underscores the importance of incorporating welfare into antimicrobial stewardship strategies. The lack of significant effect of biosecurity and emergency management on AMU may be due to the low scores observed and potential bias towards lower scores, highlighting a critical area for improvement in Italian beef farms. The lower ADG and body weight associated with higher welfare levels warrant further investigation, considering potential tradeoffs between welfare and productivity. Breed differences in AMU and welfare scores suggest the need for breed-specific interventions. While the positive correlation between welfare and biosecurity supports the notion that comprehensive on-farm practices positively affect AMU, the low scores in biosecurity and emergency management emphasize the need for improvement in these areas to maximize the effectiveness of AMU reduction strategies.

This study demonstrated a significant link between improved animal welfare and reduced AMU in Italian beef cattle. However, low biosecurity and emergency management scores highlight substantial room for improvement. Future research should focus on longitudinal studies with controlled interventions to strengthen causal inferences and explore potential confounding factors. This study’s findings should drive the development of farm-specific targeted interventions in animal welfare and biosecurity practices to further reduce AMU in the beef sector.

The study's retrospective design and the matching of batch-level AMU data with farm-level welfare and biosecurity assessments may have influenced the results, particularly regarding the non-significant findings for biosecurity and emergency management. The limited sample size in certain categories (high biosecurity, high emergency management) may also have reduced statistical power. The lack of information on internal biosecurity likely underestimated its impact on AMU.