Survival analysis of lamb mortality in a terminal sire composite population.

Abstract

Records of mortality during the first year of life of 8,642 lambs from a composite population at the U.S. Meat Animal Research Center were studied using survival and logistic analyses. The traditional logistic approach analyzes the binary response of whether or not a lamb survived until a particular time point, thus disregarding information on the actual age at death. Survival analysis offers an alternative way to study mortality, wherein the response variable studied is the precise age at death while accounting for possible record censoring. Lamb mortality was studied across five periods based on management practices: birth to weaning, birth to 120 d of age, birth to 365 d of age, weaning to 365 d of age, and 120 to 365 d of age. Explanatory variables included in the models were sex, type of birth, age of dam, and whether or not a lamb was raised in a nursery. The survival analysis was implemented using Weibull and Cox proportional hazards models with sire as random effect. The logistic approach evaluated sire, animal, and maternal effects models. Lambs culled during any period were treated as censored in the survival analyses and were assumed alive in the logistic analyses. Similar estimates of the explanatory variables were obtained from the survival and logistic analyses, but the survival analyses had lower standard errors than the logistic analyses, suggesting a slight superiority of the former approach. Heritability estimates were generally consistent across all periods ranging from 0.15 to 0.21 in the Weibull model, 0.12 to 0.20 in the Cox model, 0.08 to 0.11 in the logistic sire model, 0.04 to 0.05 in the logistic animal model, and 0.03 to 0.07 in the maternal effects logistic model. Maternal effects were important in the early stages of lamb life, but the maternal heritability was less than 0.07 in all the stages studied with a negative correlation (-0.86 to -0.61) between direct and maternal effects. The estimates of additive genetic variance indicate that the use of survival analysis estimates in breeding schemes could allow for effective selection against mortality, thereby improving sheep productivity, welfare, and profitability.