Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands.
Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands.
Prev Vet Med. 2022 Feb;199:105563. doi: 10.1016/j.prevetmed.2021.105563. Epub 2021 Dec 18.
Minimizing antimicrobial use (AMU) in livestock is needed to control antimicrobial resistance (AMR). In the Netherlands, the livestock sector reduced AMU by almost 70 % since 2009, but this reduction stagnated in recent years. With only therapeutic AMU allowed, it is clear that besides socio-economic and behavioral factors, also the farm technical characteristics influence the conditions under which farmers need AMU. These characteristics pertain to farm management, including biosecurity, vaccination schemes, nutrition, micro-climate and husbandry practices. Identifying farm-related risk factors for AMU is needed to control AMR in a sustainable and pragmatic way. This need, often concerns the overall contribution of seemingly related (rather than individualized) factors. Here, risk factors for AMU in pig and calf farms were determined using two approaches: a typical risk factor analysis based on generalized estimating equations (GEEs) or hierarchical mixed-effects models and a multiblock partial least-squares regression analysis. These methods were applied to longitudinal data from two previous studies, i.e. a panel study and an intervention study involving 36 multiplier pig farms and 51 veal calf farms in the Netherlands, respectively. The multiblock analysis allowed us to quantify the importance of each factor and their respective block (i.e. farm management domain). For pigs, factors related to internal biosecurity had the highest impact on AMU, while for calves, these were mainly related to micro-climate. Structural characteristics, such as farm size and production type, followed in importance for both sectors. While both methods provided similar outcomes, the multiblock approach provided further insights by grouping and comparing factors believed to be inter-related.
为了控制抗菌药物耐药性(AMR),有必要减少畜牧业中的抗菌药物使用(AMU)。自 2009 年以来,荷兰的畜牧业已经将 AMU 减少了近 70%,但近年来这一减少趋势已经停滞。由于只允许治疗性 AMU,因此很明显,除了社会经济和行为因素外,农场的技术特征也会影响农民需要使用 AMU 的条件。这些特征与农场管理有关,包括生物安全、疫苗接种计划、营养、小气候和饲养管理实践。需要确定与农场相关的 AMU 风险因素,以便以可持续和务实的方式控制 AMR。这种需求通常涉及到看似相关(而不是个体化)因素的整体贡献。在这里,使用两种方法确定了猪和犊牛养殖场 AMU 的风险因素:一种是基于广义估计方程(GEE)或分层混合效应模型的典型风险因素分析,另一种是多块偏最小二乘回归分析。这些方法应用于来自两项先前研究的纵向数据,即一项面板研究和一项干预研究,分别涉及荷兰的 36 个乘法猪养殖场和 51 个犊牛养殖场。多块分析允许我们量化每个因素及其各自块(即农场管理领域)的重要性。对于猪,与内部生物安全相关的因素对 AMU 的影响最大,而对于犊牛,这些因素主要与小气候有关。结构特征,如农场规模和生产类型,对两个部门都很重要。虽然这两种方法提供了相似的结果,但多块方法通过分组和比较被认为相互关联的因素提供了进一步的见解。