Quantitative Genetics Group, Department of Animal Production, Faculty of Veterinary Medicine, University of Liège, 4000 Liège, Belgium.
Prev Vet Med. 2012 Dec 1;107(3-4):170-9. doi: 10.1016/j.prevetmed.2012.06.005. Epub 2012 Jul 7.
In dairy cattle, many farming practices have been associated with occurrence of mastitis but it is often difficult to disentangle the causal threads. Structural equation models may reduce the complexity of such situations. Here, we applied the method to examine the links between mastitis (subclinical and clinical) and risk factors such as herd demographics, housing conditions, feeding procedures, milking practices, and strategies of mastitis prevention and treatment in 345 dairy herds from the Walloon region of Belgium. During the period January 2006 to October 2007, up to 110 different herd management variables were recorded by two surveyors using a questionnaire for the farm managers and during a farm visit. Monthly somatic cell counts of all lactating cows were collected by the local dairy herd improvement association. Structural equation models were created to obtain a latent measure of mastitis and to reduce the complexity of the relationships between farming practices, between indicators of herd mastitis and between both. Robust maximum likelihood estimates were obtained for the effects of the herd management variables on the latent measure of herd mastitis. Variables associated directly (p<0.05) with the latent measure of herd mastitis were the addition of urea in the rations; the practices of machine stripping, of pre-and post-milking teat disinfection; the presence of cows with hyperkeratotic teats, of cubicles for housing and of dirty liners before milking; the treatment of subclinical cases of mastitis; and the age of the herd (latent variable for average age and parity of cows, and percentage of heifers in the herd). Treatment of subclinical mastitis was also an intermediate in the association between herd mastitis and post-milking teat disinfection. The study illustrates how structural equation model provides information regarding the linear relationships between risk factors and a latent measure of mastitis, distinguishes between direct relationships and relationships mediated through intermediate risk factors, allows the construction of latent variables and tests the directional hypotheses proposed in the model.
在奶牛养殖业中，许多养殖实践与乳腺炎的发生有关，但往往难以理清因果关系。结构方程模型可以降低这种复杂情况的复杂性。在这里，我们应用该方法来检验乳腺炎（亚临床和临床）与群体特征、住房条件、喂养程序、挤奶操作以及乳腺炎预防和治疗策略等风险因素之间的联系，这些风险因素在来自比利时瓦隆大区的 345 个奶牛场中进行了研究。在 2006 年 1 月至 2007 年 10 月期间，两名调查员使用农场经理调查问卷和农场访问，记录了多达 110 个不同的农场管理变量。当地奶牛群体改良协会每月收集所有泌乳奶牛的体细胞计数。构建结构方程模型，以获得乳腺炎的潜在衡量标准，并降低养殖实践之间、乳腺炎指标之间以及两者之间的关系的复杂性。使用稳健最大似然估计获得了农场管理变量对乳腺炎群体潜在衡量标准的影响。与乳腺炎群体潜在衡量标准直接相关（p<0.05）的变量包括日粮中添加尿素；机器挤奶、挤奶前后乳头消毒、存在角蛋白过度角化的奶牛、牛舍卧床和挤奶前脏衬垫、亚临床乳腺炎病例的治疗以及牛群的年龄（奶牛的平均年龄和胎次、牛群中小母牛的百分比的潜在变量）。亚临床乳腺炎的治疗也是乳腺炎与挤奶后乳头消毒之间关联的中间因素。该研究说明了结构方程模型如何提供有关风险因素与乳腺炎潜在衡量标准之间线性关系的信息，区分直接关系和通过中间风险因素介导的关系，允许构建潜在变量并检验模型中提出的定向假设。
