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

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 fetuses. 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 fetuses 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

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

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&lt;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.</jats:p

DETERMINATION OF PREDICTION EQUATIONS TO ESTIMATE BODY CONDITION SCORE FROM BODY SIZE AND TESTICULAR TRAITS OF YANKASA RAMS

The study was aimed to develop prediction models using stepwise multiple linear regressionanalysis for estimating the body condition score (BCS) from the body weight (BW), testicular length(TL), testicular diameter (TD) and scrotal circumference (SC) of indigenous Yankasa rams. Data wereobtained from 120 randomly selected rams with approximately two and half years of age, from differentextensively managed herds in Nasarawa State, Nigeria. Although pairwise phenotypic correlationsindicated strong association (P&lt;0.01) among the measured variables, there was collinearity problembetween BW and SC as revealed by the variance inflation factors (VIF) and tolerance valves (T). TheVIT was higher than 10 (VIF = 19.45 and 16.65 for BW and SC, respectively). The Twas smaller than0.1 (T = 0.05 and 0.06 in BW and SC, respectively). BW was retained among the collinear variables, andwas singly accounted for 83.7% of the variation in BCS. However, a slight improvement was obtainedfrom the prediction of BCS from BW and TL [coefficient of determination (R2), adjusted R2 and rootmean squares error (RMSE) were 85.3%, 85.1% and 0.305, respectively]. The prediction of the BCS ofYankasa rams from BW and testicular measurements could therefore be a potential tool for sustainableproduction and improvement of small ruminants in Nigeria