|Southey, B. - UNIV. ILLINOIS|
|Rodriguez-Zas, S. - UNIV. ILLINOIS|
Submitted to: Journal of Animal Science Supplement
Publication Type: Abstract Only
Publication Acceptance Date: April 6, 2003
Publication Date: June 22, 2003
Citation: SOUTHEY, B.R., RODRIGUEZ-ZAS, S.L., LEYMASTER, K.A. COMPETING RISKS ANALYSIS OF LAMB MORTALITY. JOURNAL OF ANIMAL SCIENCE SUPPLEMENT. 2003. v. 81(SUPPL. 1) p. 68. Abstract No. 268. Technical Abstract: Survival is often represented as the time elapsed between two events (e.g., birth to mortality) or until the end of period considered. The typical survival models assume one type of terminal event thereby ignoring that there could be multiple causes of mortality. A competing risks model that accounts for different causes of mortality was evaluated. Discrete survival methods using a complementary log-log link function were applied to lamb mortality records from a composite population at the U.S. Meat Animal Research Center. Causes of mortality were grouped into disease, maternal (e.g., dystocia), pneumonia and other causes. A total 8301 lamb survival records from birth to weaning were analyzed using sire, animal and maternal effect mixed models including sex, contemporary group, type of birth and age of dam as fixed effects. The results showed substantial differences on the effect of lamb sex among mortality categories. The influence of birth type and age of dam on survival showed little variation with mortality category. Estimates of variance components from the sire and animal models compared to the maternal model indicated maternal components were present. Estimates of heritability from a maternal effects model ranged between 10 and 20% and varied with the mortality category. Results from the maternal category were consistent with literature studies on parturition, lamb behavior and selection for rearing ability. These results indicate that failure to account for the cause of the terminal event on mortality and longevity studies may hide important genetic differences. Therefore, breeding programs are likely to be ineffective when the multiple causes involved in time to event traits such as mortality and longevity are ignored.