A structural equation model to evaluate direct and indirect factors associated with a latent measure of mastitis in Belgian dairy herds

Abstract

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.