Investigation of Stillbirth Rate Using Logistic Regression Analysis in Holstein Friesian Calves
Abstract
Logistic regression analysis is a
method to determine the reason-result relationship of independent variable(s)
with dependent variable, 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<0.05). The
model showed good fit, based on Hosmer-Lemeshow goodness of fit statistics
(P>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.
Keywords
References
- Antonogeorgos G, D.B. Panagiotakos, K.N. Priftis and A. Tzonou. 2009. Logistic regression and linear discriminant analyses in evaluating factors associated with asthma prevalence among 10- to 12-years-old children: divergence and similarity of the two statistical methods. International Journal of Pediatrics, 2009:2009.
- Atashi H. 2011. Factors affecting stillbirth and effects of stillbirth on subsequent lactation performance in a Holstein dairy herd in İsfahan. Iranian Journal of Veterinary Research, Shiraz University 12:24-30.
- Bicalho RC, K.N. Galvao, S.H. Cheong, R.O. Gilbert, L.D. Warnick and C.L. Guard. 2007. Effect of stillbirth on dam survival and reproduction performance in Holstein dairy cows. Journal of Dairy Science. 90:2797-2803.
- Çokluk Ö, G. Şekercioğlu and S. Büyüköztürk. 2010. Multivariable Statistics for Social Sciences (In Turkish). Pegem Akademi Yayıncılık, Ankara.
- Cook D, P. W.M. Dixon, M.S. Duckworth, K. Kaiser, W.Q. Koehler, W.Q. Meeker and W.R. Stephenson. 2001. Binary response and logistic regression analysis. Part of the Iowa State University NSF/ILI project, Beyond Traditional Statistical Methods. Available at http://www.public.iastate. edu/~stat415/ stephenson/stat415_chapter3.pdf (accessed 3 August 2015).
- Field A. 2005. Discovering Statistics Using SPSS. 2nd ed. London: Sage.
- Hair J, B. B. Black, B. Babin, R. Anderson and R. Tatham. 2006. Multivariate Data Analysis, 6th ed. Upper Saddle River, NJ: Prentice-Hall.
- Hosmer D.W. and S. Lemeshow. 2000. Applied Logistic Regression. John Wiley & Sons, New York.
- Johnson R.A. and D.W. Wichern. 2005. Applied Multivariate Statistical Analysis, Prentice Hall, Upper Saddle River, New Jersey.
- Mertler C.A. and R.A. Vannatta. 2005. Advanced and Multivariate Statistical Methods: Practical Application and Interpretation, 3rd ed. Pyrczak, Los Angeles.