Risk factors associated with piglet pre-weaning mortality in a Midwestern U.S. swine production system from 2020 to 2022

IF 2.2 2区 农林科学 Q1 VETERINARY SCIENCES Preventive veterinary medicine Pub Date : 2024-08-16 DOI:10.1016/j.prevetmed.2024.106316
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Abstract

Piglet pre-weaning mortality (PWM) is a significant issue in the U.S. swine industry, causing economic losses and raising sustainability and animal welfare concerns. This study conducted a multivariable analysis to identify factors associated with PWM in a Midwestern U.S. swine production system. Weekly data from 47 sow farms (7207 weaning weeks) were captured from January 2020 to December 2022. Initially, 29 variables regarding farm infrastructure, productivity parameters, health status, and interventions were selected for univariate analysis to assess their association with PWM. The initial multivariable analysis included the variables with P < 0.20 in the univariate analyses. A backward stepwise model selection was conducted by excluding variables with P > 0.05, and the final multivariable model consisted of 19 significant risk factors and 6 interaction terms. The overall average PWM for the study population was 14.02 %. Yearly variations in PWM were observed, with the highest recorded in 2020 (16.61 %) and the lowest in 2021 (15.78 %). Cohorts with a pond water source, lower farrowing rate (71.9 %), higher farrowing parity (5.1), shorter gestation length (116.2 days), and using oxytocin during farrowing had increased PWM. The higher productivity parameters such as mummies rate, stillborn rate, and average total born, the higher the PWM was. Additionally, health status and intervention-related factors were associated with PWM, where higher PWM rates were observed in herds facing porcine reproductive and respiratory syndrome virus (PRRSV) outbreaks, porcine epidemic diarrhea virus (PEDV) positive, the weeks before and during feed medication, and weeks without using Rotavirus vaccine or Rotavirus feedback. Altogether, these results corroborate that PWM is a multifactorial problem, and a better understanding of the risk factors is essential in developing strategies to improve survival rates. Therefore, this study identified the major risk factors associated with PWM for groups of pigs raised under field conditions, and the results underscore the significance of data analysis in comprehending the unique challenges and opportunities inherent to each system.

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2020 年至 2022 年美国中西部猪生产系统中与仔猪断奶前死亡率相关的风险因素
仔猪断奶前死亡率(PWM)是美国养猪业的一个重要问题,它不仅造成经济损失,还引发了可持续发展和动物福利方面的问题。本研究对美国中西部的一个养猪生产系统进行了多变量分析,以确定与仔猪断奶前死亡率相关的因素。从 2020 年 1 月到 2022 年 12 月,研究人员采集了 47 个母猪养殖场(7207 个断奶周)的每周数据。最初选择了有关猪场基础设施、生产力参数、健康状况和干预措施的 29 个变量进行单变量分析,以评估它们与 PWM 的关系。最初的多变量分析包括单变量分析中 P < 0.20 的变量。通过排除 P > 0.05 的变量,进行了逆向逐步模型选择,最终的多变量模型由 19 个重要的风险因素和 6 个交互项组成。研究人群的总体平均血压波动率为 14.02%。PWM 逐年变化,2020 年最高(16.61%),2021 年最低(15.78%)。拥有池塘水源、产仔率较低(71.9 %)、产仔奇数较高(5.1)、妊娠期较短(116.2 天)以及产仔期间使用催产素的组群,其生产性能指标均有所提高。生产率参数越高,如木乃伊率、死胎率和平均总出生率,生产率指数就越高。此外,健康状况和干预相关因素也与PWM有关,在猪繁殖与呼吸综合征病毒(PRRSV)爆发、猪流行性腹泻病毒(PEDV)阳性、饲料用药前几周和用药期间以及未使用轮状病毒疫苗或轮状病毒反馈的几周,观察到较高的PWM率。总之,这些结果证实了猪传染性腹泻是一个多因素问题,而更好地了解风险因素对于制定提高存活率的策略至关重要。因此,本研究确定了在野外条件下饲养的猪群与传染性疾病相关的主要风险因素,其结果强调了数据分析在理解每个系统固有的独特挑战和机遇方面的重要性。
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来源期刊
Preventive veterinary medicine
Preventive veterinary medicine 农林科学-兽医学
CiteScore
5.60
自引率
7.70%
发文量
184
审稿时长
3 months
期刊介绍: Preventive Veterinary Medicine is one of the leading international resources for scientific reports on animal health programs and preventive veterinary medicine. The journal follows the guidelines for standardizing and strengthening the reporting of biomedical research which are available from the CONSORT, MOOSE, PRISMA, REFLECT, STARD, and STROBE statements. The journal focuses on: Epidemiology of health events relevant to domestic and wild animals; Economic impacts of epidemic and endemic animal and zoonotic diseases; Latest methods and approaches in veterinary epidemiology; Disease and infection control or eradication measures; The "One Health" concept and the relationships between veterinary medicine, human health, animal-production systems, and the environment; Development of new techniques in surveillance systems and diagnosis; Evaluation and control of diseases in animal populations.
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