Early-life risk factors predicting growth retardation and mortality in pigs: a multi-criteria approach.

Body weight (BW) variability throughout the production cycle remains a major challenge for the swine industry, particularly due to the negative impact of slow-growing pigs on production efficiency and batch uniformity. This study aimed to identify early-life risk factors associated with poor postnatal growth and mortality and to develop a multi-criteria predictive model for classifying pigs based on their early growth and survival potential. Data from 2,138 pigs (Pietrain × [Landrace × Yorkshire]) and 1,115 pigs (Pietrain × [Landrace × Large White]), collected from two commercial farms, were analyzed. Pigs were monitored from birth to weaning, with detailed records of farrowing traits, BW, body conformation indicators, colostrum intake (CI), and survival outcomes. Body weight on d 7 was the strongest predictor of weaning weight (R2 > 0.60), highlighting the critical influence of the first week on later growth. Logistic regression models were used to classify pigs as either compromised (defined as dead or alive with a BW below the 15th percentile of the BW distribution on d 7 of life and at weaning) or normal. The classification performance of the competing models, as well as the selection of the final model, was evaluated using the area under the curve (AUC) of the receiver operating characteristic curve. Subsequently, the optimal classification threshold was adjusted to balance sensitivity and positive predictive value. The final model, trained on d 7 data, achieved a high AUC (0.910), with BW on d 1, relative BW (RBW) on d 1, CI, and sow parity all significantly associated with the probability of being classified as compromised (P < 0.05). Each 100 g increase in BW on d 1 was associated with a 27.6% decrease in the odds of being compromised. Similarly, greater RBW on d 1 and CI were linked to a reduced risk. Pigs falling within the 10th percentile for BW on d 1, with low CI and negative RBW on d 1, showed the highest probability of being compromised by d 7. The model's robustness was confirmed through consistent performance across datasets. Density plots further validated the model, illustrating clear distributional differences between compromised and normal pigs. These findings suggest that a model based on easily measurable birth-related indicators can reliably identify pigs at risk of poor early-life performance. Such a tool holds strong potential for on-farm application to enhance pig management and reduce BW variability at slaughter.