Investigation of Stillbirth Rate Using Logistic Regression Analysis in Holstein Friesian Calves

Abstract

Logistic relationship regression of independent analysis is variable(s) amethod with to determine dependent the variable, reason-result which has binary or multiple categorical structures. In this study, sex of calf, parity and calving year-season effects on stillbirth were analyzed with binary logistic regression analysis. Study material was obtained from the USA National Association of Animal Breeders collected among 2003-2005 with a total of 404460 birth records of single born calves. According to the results, sex of calf, parity and calving year-season effects on stillbirth were found statistically significant (P[removed]0.12). When all variables were analyzed together in the same model, stillbirth rate of female calves compared to male calves was found to be more than 1.03 times higher. In addition, risk of stillbirth was decreased by increasing parity. On the other hand, the risk of stillbirth in summer calves was found to be higher than winter calves. In our country, data sets on stillbirth rates should be collected and risk factors that have an effect on stillbirth must be detected and then calf deaths could be controlled here, too.