Generalized additive mixed model on the analysis of total transport losses of market-weight pigs1

Abstract

Transportation losses of market-weight pigs are an animal welfare concern, and result in direct economic impact for producers and abattoirs. Such losses are related to multiple factors including pig genetics, human handling, management, and weather conditions. Understanding the factors associated with total transport losses (TTL) is important to the swine industry because it can aid decision-making, and help in the development of transportation strategies to minimize the risk of losses. Hence, the objective of this study was to investigate factors associated with TTL on market-weight pigs in typically field conditions for Midwestern United States using a generalized additive mixed model (GAMM). The final quasi-binomial GAMM included the fixed (main and interactions) effects of abattoir of destination, type of driver, average market weight, distance traveled, wind speed, precipitation, and temperature-humidity index (THI), as well as the random effects of truck companies and the combination of site of origin and period of the year. Results indicate significant associations between TTL and the main effect of all explanatory variables (P < 0.05), except for wind speed and precipitation. Interactions of average market weight × abattoir, and wind speed × precipitation were also significant. A complex nonlinear relationship between TTL and model covariates were observed for distance traveled, THI, and interaction terms. This study showed that TTL of market-weight pigs are caused by a complex system involving multiple interacting factors, which can be potentially managed to mitigate the risk of losses. In addition, the GAMM showed to be a simple and flexible approach to model TTL because it can capture nonlinear relationships, handle non-normal data, and can potentially accommodate data structure.

Field Trial of Factors Associated With the Presence of Dead and Non-ambulatory Pigs During Transport Across Three Colombian Slaughterhouses

“…Total transport losses (DOAs and non-ambulatory pigs) were associated with the truck driver in this study. Similar results were reported by Passafaro et al ( 58 ) Who found that transport losses were lower when trucks were driven by owners rather than employees, because owners have a vested interest and therefore are more careful in handling and moving pigs throughout the transport process, compared to hired drivers. Other researchers have reported that the level of knowledge in pig behavior and the handling skills of drivers directly influences animal welfare ( 26 ).…”

“…Many factors have been associated with the effect of the driver on animal welfare such as: attitude and empathy toward animals ( 32 , 60 ), years of experience as a truck driver ( 29 ), work pressure and interpersonal relationships training ( 59 ), coaching and driving style, among others ( 45 ). These results suggest that understanding in greater depth the differences between drivers may further explain transportation losses, and therefore be useful to the swine industry to contract, hire, or train truck driver ( 58 ).…”

“…However, in this study, farm visits were not conducted and therefore, relevant information related to animal handling, preparation for travel, fasting conditions, loading, managerial and administrative aspects, personnel training, as well as other factors that may have a stressor effect on the animals were not considered. Understanding the factors associated with the presence of DOAs and non-ambulatory pigs (total transport losses) can be of help in decision making and the development of transport strategies to minimize risk and decrease economic losses during swine pre-slaughter, as described by Passafaro et al ( 58 ). It is important to remember that previous research has shown that multiple concurrent interacting factors such as handling intensity, transport floor space, water and food deprivation and distance moved during handling, among others, have additional effects on the metabolic responses of non-ambulatory pigs (NANI, NAI and DOAs) ( 20 , 58 ).…”

The Association of the Oxford Classification Score with Longitudinal Estimated Glomerular Filtration Rate Decline in Patients with Immunoglobulin A Nephropathy: A Mixed-Method Study

“…Demographic and clinicopathologic data at biopsy were obtained from our IgAN database. The following baseline covariates were analyzed in the multivariable models as they were potential confounders for the progression of renal damage (the generalized additive mixed model [GAMM] 28 automatically included the initial eGFR as a covariate): age, gender, mean artery pressure (MAP, calculated as 1/3 × systolic blood pressure [SBP] + 2/3 × diastolic blood pressure [DBP]), proteinuria (measured using 24 h urine protein excretion [g/d]), and the Oxford Classification MEST-C score.…”

“…GAMMs were used to investigate the fixed effects of the Oxford Classification of M, E, S, T, and C associations with longitudinal changes in eGFR. 28 In these models, the dependent variable (eGFR) was evaluated at the baseline visit and during all follow-up visits, whereas the independent variables were only assessed at the baseline visit (Oxford Classification scores M, E, S, T, and C). Age, gender, MAP, proteinuria, and the Oxford Classification MEST-C score were adjusted in the multivariable models to determine whether the effects of M, E, S, T, and C on the changes in eGFR were independent.…”