Southern Regional Station, ICAR- National Dairy Research Institute, Bengaluru, 560030, India.
ICAR-National Institute of Animal Nutrition and Physiology, Bengaluru, 560030, India.
BMC Vet Res. 2024 May 25;20(1):229. doi: 10.1186/s12917-024-04093-w.
A thorough understanding of lameness prevalence is essential for evaluating the impact of this condition on the dairy industry and assessing the effectiveness of preventive strategies designed to minimize its occurrence. Therefore, this cross-sectional study aimed to ascertain the prevalence of lameness and identify potential risk factors associated with lameness in Holstein Friesian crossbred cows across both commercial and smallholder dairy production systems in Bengaluru Rural District of Karnataka, India.
The research encompassed six commercial dairy farms and 139 smallholder dairy farms, involving a total of 617 Holstein Friesian crossbred cattle. On-site surveys were conducted at the farms, employing a meticulously designed questionnaire. Lameness in dairy cattle was assessed subjectively using a locomotion scoring system. Both bivariate and binary logistic regression models were employed for risk assessment, while principal components analysis (PCA) was conducted to address the high dimensionality of the data and capture the underlying structure of the explanatory variables.
The overall lameness prevalence of 21.9% in commercial dairy farms and 4.6% in smallholder dairy farms. Various factors such as age, body weight, parity, body condition score (BCS), floor type, hock and knee injuries, animal hygiene, provision of hoof trimming, and the presence of hoof lesions were found to be significantly associated with lameness. Binary logistic regression analysis indicated that the odds of lameness in crossbred cows increased with higher parity, decreased BCS, presence of hard flooring, poor animal hygiene, and the existence of hoof lesions. These factors were identified as potential risk factors for lameness in dairy cows. Principal component analysis unveiled five components explaining 71.32% of the total variance in commercial farms and 61.21% in smallholder dairy farms. The extracted components demonstrated higher loadings of housing and management factors (such as hoof trimming and provision of footbath) and animal-level factors (including parity, age, and BCS) in relation to lameness in dairy cows.
The findings suggest that principal component analysis effectively reduces the dimensionality of risk factors. Addressing these identified risk factors for lameness is crucial for the strategic management of lameness in dairy cows. Future research in India should investigate the effectiveness of management interventions targeted at the identified risk factors in preventing lameness in dairy cattle across diverse environments.
全面了解跛行的流行情况对于评估该疾病对奶业的影响以及评估旨在尽量减少其发生的预防策略的有效性至关重要。因此，这项横断面研究旨在确定印度卡纳塔克邦班加罗尔农村地区的荷斯坦-弗里森杂交奶牛在商业和小规模奶牛养殖系统中的跛行流行率，并确定与跛行相关的潜在风险因素。
该研究包括六个商业奶牛场和 139 个小规模奶牛场，共涉及 617 头荷斯坦-弗里森杂交奶牛。在农场进行现场调查，使用精心设计的问卷。使用运动评分系统对奶牛的跛行情况进行主观评估。使用双变量和二项逻辑回归模型进行风险评估，同时进行主成分分析（PCA）以解决数据的高维性并捕获解释变量的潜在结构。
商业奶牛场的跛行总流行率为 21.9%，小规模奶牛场的跛行总流行率为 4.6%。年龄、体重、胎次、体况评分（BCS）、地板类型、跗关节和膝关节损伤、动物卫生、提供蹄修剪以及存在蹄部病变等各种因素均与跛行显著相关。二项逻辑回归分析表明，随着胎次的增加、BCS 的降低、硬地板的存在、较差的动物卫生以及蹄部病变的存在，杂交奶牛跛行的几率增加。这些因素被确定为奶牛跛行的潜在风险因素。主成分分析揭示了在商业农场中解释总方差的 71.32%和小规模奶牛场中解释总方差的 61.21%的五个成分。提取的成分显示，与奶牛跛行相关的畜舍和管理因素（如蹄修剪和提供洗脚盆）和动物水平因素（包括胎次、年龄和 BCS）的负荷更高。
研究结果表明，主成分分析有效地降低了风险因素的维度。解决这些确定的跛行风险因素对于奶牛跛行的战略管理至关重要。印度的未来研究应调查针对确定的风险因素的管理干预措施在预防不同环境下奶牛跛行方面的有效性。
