Perinatal mortality in German dairy cattle: Unveiling the importance of cow-level risk factors and their interactions using a multifaceted modelling approach.

Perinatal mortality (PM) is a common issue on dairy farms, leading to calf losses and increased farming costs. The current knowledge about PM in dairy cattle is, however, limited and previous studies lack comparability. The topic has also primarily been studied in Holstein-Friesian cows and closely related breeds, while other dairy breeds have been largely ignored. Different data collection techniques, definitions of PM, studied variables and statistical approaches further limit the comparability and interpretation of previous studies. This article aims to investigate the factors contributing to PM in two underexplored breeds, Simmental (SIM) and Brown Swiss (BS), while comparing them to German Holstein on German farms, and to employ various modelling techniques to enhance comparability to other studies, and to determine if different statistical methods yield consistent results. A total of 133,942 calving records from 131,657 cows on 721 German farms were analyzed. Amongst these, the proportion of PM (defined as stillbirth or death up to 48 hours of age) was 6.1%. Univariable and multivariable mixed-effects logistic regressions, random forest and multimodel inference via brute-force model selection approaches were used to evaluate risk factors on the individual animal level. Although the balanced random forest did not incorporate the random effect, it yielded results similar to those of the mixed-effect model. The brute-force approach surpassed the widely adopted backwards variable selection method and represented a combination of strengths: it accounted for the random effect similar to mixed-effects regression and generated a variable importance plot similar to random forest. The difficulty of calving, breed and parity of the cow were found to be the most important factors, followed by farm size and season. Additionally, four significant interactions amongst predictors were identified: breed-calving ease, breed-season, parity-season and calving ease-farm size. The combination of factors, such as secondiparous SIM breed on small farms and experiencing easy calving in summer, showed the lowest probability of PM. Conversely, primiparous GH cows on large farms with difficult calving in winter exhibited the highest probability of PM. In order to reduce PM, appropriate management of dystocia, optimal heifer management and a wider use of SIM in dairy production are possible ways forward. It is also important that future studies are conducted to identify farm-specific contributors to higher PM on large farms.

Improving Supervisor Confidence in Responding to Distressed Health Care Employees.

BACKGROUND: Professional distress and burnout are increasingly common among health professionals. This trend prompted stakeholders at a large multicenter health care system to survey supervisors for improvement opportunities. The stakeholders learned that workplace leaders lacked tools and direction for appropriately responding to distressed employees. The authors implemented a supervisor training video on providing resources to improve employee mental health. METHODS: Using the DMAIC (Define, Measure, Analyze, Improve, and Control) methodology, the authors conducted key stakeholder interviews to identify strengths, weaknesses, opportunities, and threats. Next, an e-mail survey was administered to a representative sample of supervisors that asked about degree of confidence in responding appropriately to distressed employees, with the response options "very confident," "somewhat confident," and "not at all confident." After identifying factors contributing to low supervisor confidence, the research team developed and disseminated a six-minute, on-demand video to train supervisors to respond appropriately to employees during a mental health crisis. The same group of supervisors were surveyed using the same survey after exposure to the video, and responses were collected from those who had viewed the video but had not answered the preintervention survey. RESULTS: The proportion of supervisors who responded "not at all confident" in the survey decreased from 7.1% (15/210) of responses to 0.8% (1/123), while the proportion of supervisors who chose "somewhat confident" increased significantly, from 62.9% (132/210) to 69.1% (85/123) (p = 0.03). Of the 28 supervisors who had not participated in the presurvey and viewed the video, none indicated that they were "not at all confident." The percentage of supervisors who felt distress "sometimes" or more frequently from navigating and supporting employee emotional concerns decreased nonsignificantly from 41.9% (88/210) to 37.4% (46/123) (p = 0.87). CONCLUSION: Simple, on-demand supervisor training videos can improve the confidence of supervisors to respond appropriately to distressed employees, which may indirectly contribute to improved employee mental health.

Status of udder health performance indicators and implementation of on farm monitoring on German dairy cow farms: results from a large scale cross-sectional study.

Regional benchmarking data enables farmers to compare their animal health situation to that of other herds and identify areas with improvement potential. For the udder health status of German dairy cow farms, such data were incomplete. Therefore, the aim of this study was (1) to describe the incidence of clinical mastitis (CM), (2) to describe cell count based udder health indicators [annual mean test day average of the proportion of animals without indication of mastitis (aWIM), new infection risk during lactation (aNIR), and proportion of cows with low chance of cure (aLCC); heifer mastitis rate (HM)] and their seasonal variation, and (3) to evaluate the level of implementation of selected measures of mastitis monitoring. Herds in three German regions (North: n = 253; East: n = 252, South: n = 260) with different production conditions were visited. Data on CM incidence and measures of mastitis monitoring were collected via structured questionnaire-based interviews. Additionally, dairy herd improvement (DHI) test day data from the 365 days preceding the interview were obtained. The median (Q0.1, Q0.9) farmer reported incidence of mild CM was 14.8% (3.5, 30.8%) in North, 16.2% (1.9, 50.4%) in East, and 11.8% (0.0, 30.7%) in South. For severe CM the reported incidence was 4.0% (0.0, 12.2%), 2.0% (0.0, 10.8%), and 2.6% (0.0, 11.0%) for North, East, and South, respectively. The median aWIM was 60.7% (53.4, 68.1%), 59.0% (49.7, 65.4%), and 60.2% (51.5, 67.8%), whereas the median aNIR was 17.1% (13.6, 21.6%), 19.9% (16.2, 24.9%), and 18.3% (14.4, 22.0%) in North, East, and South, respectively with large seasonal variations. Median aLCC was ≤1.1% (≤ 0.7%, ≤ 1.8%) in all regions and HM was 28.4% (19.7, 37.2%), 35.7% (26.7, 44.2%), and 23.5% (13.1, 35.9%), in North, East and South, respectively. Participation in a DHI testing program (N: 95.7%, E: 98.8%, S: 89.2%) and premilking (N: 91.1%, E: 93.7%, S: 90.2%) were widely used. Several aspects of udder health monitoring, including exact documentation of CM cases, regular microbiological analysis of milk samples and the use of a veterinary herd health consultancy service were not applied on many farms. The results of this study can be used by dairy farmers and their advisors as benchmarks for the assessment of the udder health situation in their herds.

Benchmarking calf health: Assessment tools for dairy herd health consultancy based on reference values from 730 German dairies with respect to seasonal, farm type, and herd size effects.

Good calf health is crucial for a successfully operating farm business and animal welfare on dairy farms. To evaluate calf health on farms and to identify potential problem areas, benchmarking tools can be used by farmers, herd managers, veterinarians, and other advisory persons in the field. However, for calves, benchmarking tools are not yet widely established in practice. This study provides hands-on application for on-farm benchmarking of calf health. Reference values were generated from a large dataset of the "PraeRi" study, including 730 dairy farms with a total of 13,658 examined preweaned dairy calves. At herd level, omphalitis (O, median 15.9%) was the most common disorder, followed by diarrhea (D, 15.4%) and respiratory disease (RD, 2.9%). Abnormal weight bearing (AWB) was rarely detected (median, 0.0%). Calves with symptoms of more than one disorder at the same time (multimorbidity, M) were observed with a prevalence of 2.3%. The enrolled farms varied in herd size, farm operating systems, and management practices and thus represented a wide diversity in dairy farming, enabling a comparison with similar managed farms in Germany and beyond. To ensure comparability of the data in practice, the reference values were calculated for the whole data set, clustered according to farm size (1-40 dairy cows (n = 130), 41-60 dairy cows (n = 99), 61-120 dairy cows (n = 180), 121-240 dairy cows (n = 119) and farms with more than 240 dairy cows (n = 138), farm operating systems (conventional (n = 666), organic (n = 64)) and month of the year of the farm visit. There was a slight tendency for smaller farms to have a lower prevalence of disorders. A statistically significant herd-size effect was detected for RD (p = 0.008) and D (p < 0.001). For practical application of these reference values, tables, diagrams, and an Excel® (Microsoft®) based calf health calculator were developed as tools for on-farm benchmarking (https://doi.org/10.6084/m9.figshare.c.6172753). In addition, this study provides a detailed description of the colostrum, feeding and housing management of preweaned calves in German dairy farms of different herd sizes and farm type (e.g., conventional and organic).

Do Pigs Have Adequate Space in Animal Transportation Vehicles?-Planimetric Measurement of the Floor Area Covered by Finishing Pigs in Various Body Positions.

In this study, the floor area covered by individual finishing pigs in various body positions was measured using a contrast-based planimetric method for computer-assisted analysis of two-dimensional images. Two hundred and thirty-two finishing pigs were weighed during the last fifth of the fattening period and measured in different body positions using contrast-based planimetry. Thirteen body positions were defined based on characteristic directions of the head, legs and body. The lowest average covered floor area was found for body position A (pig standing up straight, nose touching the ground) with 0.288 ± 0.026 m2. The highest average covered floor area for a standing pig amounted to 0.335 ± 0.030 m2 in body posture ES (pig standing curved sideways, head raised above the dorsal line) and, for a lying pig, 0.486 ± 0.040 m2 (posture LL, pig lying in fully lateral recumbent position). The covered floor surface significantly depended on the weight of the animal and the body posture. Allometric estimations previously described for calculating the floor area physically covered by a pig's body are not consistently precise in depicting the actual areas covered. The minimal floor area offered in animal transportation vehicles, according to European legislation, is insufficient in the case of all pigs lying in the fully recumbent position simultaneously, without the pigs being forced to partially overlap one another. Therefore, both allometric formulas and legislation should be modified on the basis of these results and further studies with pigs of modern genetic origin should be conducted.