Using a tobit regression model to analyse risk factors for foot-pad dermatitis in commercially grown broilers.
A model was developed to explain the influence of different local and regional factors on the prevalence of foot-pad dermatitis in broilers at the time of slaughter. Data from a recent two-year study of broiler foot-health in Sweden were used to construct the model. The model was based on regression analysis, using a Tobit model for censored data. This type of Tobit regression model has been used for several decades in econometrics and can also be found in the medical-scientific literature. It has, however, reportedly not been used in veterinary medicine although there appears to be several situations where it should be considered useful. Week of slaughter was significantly (p < 0.001) associated with total foot-pad score, which decreased over time. The birds' age at slaughter was also significantly (p < 0.01) associated with total foot-pad score. Five out of the 11 slaughterhouses included in the study were included as significant (p < 0.01) variables in the final model. Three feed suppliers (p < 0.05) and four regions (p < 0.01) were also included as significant variables in the model. There were also significant (p < 0.001) interactions between several of these factors (mainly, between the time variable and specific slaughterhouses, feed suppliers or regions, respectively). The information gathered in this study regarding the influence of a number of risk factors for the development of foot-pad dermatitis and their reciprocal interactions will enable us to modify the Swedish broiler foot-health programme.
Ekstrand
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Department of Animal Environment and Health, Faculty of Veterinary Medicine, Swedish University of Agricultural Sciences, Skara, Sweden. Lotta.Berg@hmh.slu.se
Carpenter
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D000003:Abattoirs; D000818:Animals; D002645:Chickens; D003625:Data Collection; D005533:Foot Dermatoses / Q000453:epidemiology / Q000662:veterinary*; D011159:Population Surveillance; D011201:Poultry Diseases / Q000453:epidemiology*; D012044:Regression Analysis; D012307:Risk Factors; D013548:Sweden / Q000453:epidemiology