Risk factors associated with lambing traits

Abstract

The objective of this study was to establish the risk factors associated with both lambing difficulty and lamb mortality in the Irish sheep multibreed population. A total of 135 470 lambing events from 42 675 ewes in 839 Irish crossbred and purebred flocks were available. Risk factors associated with producer-scored ewe lambing difficulty score (scale of one (no difficulty) to four (severe difficulty)) were determined using linear mixed models. Risk factors associated with the logit of the probability of lamb mortality at birth (i.e. binary trait) were determined using generalised estimating equations. For each dependent variable, a series of simple regression models were developed as well as a multiple regression model. In the simple regression models, greater lambing difficulty was associated with quadruplet bearing, younger ewes, of terminal breed origin, lambing in February; for example, first parity ewes experienced greater (P<0.001) lambing difficulty (1.56±0.02) than older ewes. The association between lambing difficulty and all factors persisted in the multiple regression model, and the trend in fixed effects level solutions did not differ from the trend observed in the simple regression models. In the simple regression analyses, a greater odds of lamb mortality was associated with male lambs (1.31 times more likely of death than females), lambs of very light (2 to 3 kg) and very heavy (>7.0 kg) birth weights, quadruplet born lambs and lambs that experienced a more difficult lambing (predicted probability of death for lambs that required severe and veterinary assistance of 0.15 and 0.32, respectively); lambs from dual-purpose breeds and born to younger ewes were also at greater risk of mortality. In the multiple regression model, the association between ewe parity, age at first lambing, year of lambing and lamb mortality no longer persisted. The trend in solutions of the levels of each fixed effect that remained associated with lamb mortality in the multiple regression model, did not differ from the trends observed in the simple regression models although the differential in relative risk between the different lambing difficulty scores was greater in the multiple regression model. Results from this study show that many common flock- and animal-level factors are associated with both lambing difficulty and lamb mortality and management of different risk category groups (e.g. scanned litter sizes, ewe age groups) can be used to appropriately manage the flock at lambing to reduce their incidence.