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Culling is an important management tool in dairy herds, as it affects herd economics and animal welfare. In relation to health, culling is usually studied as a consequence of health disorders, but it can also be regarded as a tool to manage health in the herd by making strategic culling decisions. In this study, we used data from the Danish Cattle Database in herd-wise survival analyses to investigate factors associated with culling, in relation to udder health, in 1,452 dairy herds. The data included milk yield, somatic cell counts (SCC), parity, and different disease related factors with a special focus on udder health. In each herd, observations and survival analyses were divided into five groups: mid lactation heifers, late lactation heifers, early lactation cows, mid lactation cows, and late lactation cows. The results showed that a high average milk yield reduced the culling hazard, and a number of risk factors (e.g., parity, a high SCC or treatment of mastitis) were associated with an increased hazard for culling. Importantly, the strength and direction of many of these associations was dependent on the lactation stage. The resulting coefficients were further analysed by principal component analysis and clustering to explore variations in culling risk factors amongst herds. In some herds, parity was an important factor for culling, while in other herds, average milk yield, SCC, or udder health were more important factors. However, clusters were substantially overlapping, indicating that the decision making process underlying culling is complex and multifactorial., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Societal pressure to limit the use of antibiotics in livestock production systems, including dairy cattle systems, is consistently increasing. To motivate farmers to reduce antibiotic usage, it is important to understand the factors that determine whether a cow will be treated with antibiotics or not. If farmers' usual practices regarding antibiotic treatments are taken into account, they may be motivated to adopt control measures that can facilitate prudent use of antibiotics and are at the same time cost-effective. In this study, we analyzed database recordings of milk yield and somatic cell count from the routine milk recording scheme, clinical registrations of mastitis and PCR results, and cow factors such as days in milk and parity in relation to antibiotic treatments for 518 dairy herds in Denmark. Farm-wise logistic regressions were used to predict antimicrobial treatment based on these factors. The resulting regression coefficients of 422 herds were further analyzed by principal component analysis and clustering to determine the driving predictors for treatment in different groups of farms. The results showed that determinants that were most important for predicting antibiotic treatments vary from one farm to another. Health indicators such as PCR or somatic cell count were most indicative for treatment on some farms, whereas other groups seemed to depend more on production factors (milk yield) or later culling of the cows. This shows that farmers behave differently and differences can be identified in register data. This information can be considered when developing cost-effective herd-specific control measures of mastitis to promote prudent use of antibiotics in Danish dairy cattle farms., (The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).)