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The aim of the study was to investigate the application of binary logistic  regression to assess the potential factors associated with the prevalence of  abortion and stillbirth in indigenous goat breeds in Nasarawa State, north  central Nigeria. 5,268 kidding records of does from a total of 105  traditional goat herders from the year 2010-2011 were utilized in the study.  The goats which were of West African Dwarf (WAD), Red Sokoto (RS), Sahel (SH)  and WAD x RS crossbred (WR) genetic groups originated from different flocks  and were reared under the traditional extensive system. The risk factors  investigated were dam breed group, season, parity and number of foetuses. Of  the 5,268 kidding records, 570 (10.8%) and 520 (9.87%) were cases of abortion  and stillbirth, respectively. The logistic regression analysis revealed that  season, parity and number of foetuses were the parameters of utmost  importance (P<0.05) influencing the prevalence of abortion and stillbirth in  the four genetic groups investigated. The logistic regression models were  able to predict correctly 89.2 and 90.1% cases of abortion and stillbirth,  respectively. The present information may be exploited in management  practices to attenuate the incidence of abortion and stillbirth parturition,  thereby increasing the productivity of the animals.

biotechnology in animal husbandry/biotechnology in animal husbandry

Application of multivariate logistic regression model to assess factors of importance influencing prevalence of abortion and stillbirth in Nigerian goat breeds