Risk factors associated with the different categories of piglet perinatal mortality in French farms.

We aimed to identify mortality patterns and to establish risk factors associated with different categories of piglet perinatal mortality in French farms. At farm level, the analyses were performed on data from 146 farms that experienced perinatal mortality problems. At piglet level, the analyses were performed on data from 155 farms (7761 piglets). All data were collected over a period of 10 years (2004-14) by a consulting company, using a non-probability sampling at farm level and a random sampling at sow level. Six main categories of mortality, determined by standardised necropsy procedure, represented 84.5% of all the perinatal deaths recorded. These six categories were, in order of significance: Death during farrowing, Non- viable, Early sepsis, Mummified, Crushing and Starvation. At farm level, the percentage of deaths due to starvation was positively correlated to the percentage of deaths due to crushing and the percentage of deaths during farrowing (r>0.30, P<0.05) .The percentage of deaths due to crushing was negatively correlated to the percentage of deaths due to early sepsis (r<-0.30, P<0.05) and positively correlated to the deaths due to acute disease (r>0.30, P<0.05). Patterns of perinatal mortality at farm level were identified using a principal component analysis. Based on these, the farms could be classified, using ascending hierarchical classification, into three different clusters, highlighting issues that underlie farm differences. Risk factors were compared at piglet level for the different categories of death. Compared to other categories of death, deaths during farrowing were significantly fewer during the night than during the day. Compared to other categories of death, the likelihood of non-viable piglets tended to be higher in summer than other seasons. A smaller number of deaths in the litter was also identified for the piglets classified as non-viable or mummified. For the six main categories of perinatal mortality, the piglets which died from a specific category tended to have more littermates which died from the same category. Parity and litter size also had more significant effects on certain categories of death compared to others. The study provides novel information on the risk factors associated with specific categories of piglet perinatal mortality. The classification of farms into the 3 different clusters could lead to a more targeted management of perinatal mortality on individual farms.