Welfare is a multidimensional construct and its quantification is of major scientific, societal and economic importance in veterinary medicine. The construction of indices that measure welfare validly and reliably remains a considerable challenge. A general methodology for constructing welfare indices can be adapted from human medicine (in particular, from methodologies to assess Quality of Life [QoL]) and modified to reflect the fact that all assessments of animal welfare must be observer-based. The methodology is based on the creation of individual, composite indices for distinct dimensions/domains of welfare such as pain, disease, or stress. The domains include behavioural, physiological and biochemical markers. We have established QoL methodologies in the assessment of acute and chronic pain in dogs and generalised this approach to farm animal welfare. We describe the development of a questionnaire with seven behavioural categories which are used to create a single pain score to assess acute pain in dogs. For chronic pain in dogs, a structured questionnaire with over 100 items has been devised, which the owner completes by indicating degree of agreement with each item using a seven-point Likert scale. The welfare measure includes pain as an integral component as well as husbandry, behavioural and physiological/biological measures. In each case, a profile of the individual indices can be studied and compared over time or among observers. These indices may also be combined to form a single composite welfare measure, should this be appropriate, using scaling models. In the welfare setting, we have both causal and indicator variables — and indeed, for farm animals, the causal variables may be sufficient cause for poor welfare (eg the presence of disease or inadequate husbandry).

Qualitative interviews of farmers were carried out as part of a project focusing on developing animal welfare assessment systems (AWASs) in dairy, pig and mink production systems (26 farms in total). The aims of the interviews were to investigate farmers’ perceptions and experience of how an AWAS worked, and to explore their expectations for future use of AWASs. All interviews were taped, transcribed and analysed using a grounded-theory approach. The importance of different elements of the AWAS differed between farmers, and between farmers and the AWAS project implementation group. More direct associations between welfare assessment and production results (and other ‘common measures ‘) were requested by farmers. The whole AWAS ‘package’ was viewed as being too complex and expensive for most farmers, particularly as it involved multiple assessments over time. A range of themes emerged from the analysis. One of these, here referred to as ‘us and them’, is explored and discussed in this paper. Farmers were concerned that the AWAS could be used negatively in relation to consumers and political decisions, and they underlined that if the AWAS was to be used as a decision support tool (ie a system to assist them in making decisions about improvements in their herds and to guide their initiatives and improvements), it should include dialogue and details of local farm conditions. Qualitative interviews were found to provide valuable insight into farmers’ perceptions and expectations of animal welfare assessment methods.

Assessment of mass-produced animal-housing equipment can serve as a basis for improving animal welfare. A number of European countries have adopted various legal approaches to such assessment. In Germany, welfare assessment of housing equipment is voluntary, but minimum standards can be set by regulation for the assessment procedure and for the qualifications of the persons involved. From a scientific perspective, the time and resource constraints pose some problems, particularly as they apply to a voluntary procedure. For reasons of practicability, certain compromises will be required. Nevertheless, it is important to ensure that each assessment procedure is based upon scientific principles and considers animal welfare aspects to a sufficient extent. A proposal for the minimum standards of an assessment procedure has been elaborated by the Animal Welfare Committee of the German Agricultural Society (Deutsche Landwirtschafts-Gesellschaft, DLG), a shortened version of which is presented here. The animal welfare impact of such a regulated but voluntary procedure will be less than that of an obligatory assessment; however, the relatively flexible approach may still significantly contribute to the improvement of welfare aspects of livestock housing.

A single solution to promote higher animal welfare across the whole EU is unlikely due to significant regional differences and because what is most appropriate for each region depends on many factors. Based on analyses of eight member and candidate EU countries, this paper provides a conceptual framework, an ‘animal welfare roadmap’, which can be used to assess the stage of maturity of a country in farm animal welfare policy development and identify appropriate policy instruments and indicators to monitor progress towards higher animal welfare. The ‘roadmap’ consists of five sequential stages: increasing compliance with legislation; raising awareness; product development; mainstreaming; and integration of animal welfare with other issues. For each stage, specific policy instruments are identified alongside the category of stakeholders most likely to be influential in the implementation of each instrument. The policy instruments used to achieve these stages are those used by government departments/agencies, private enterprises, academic bodies or non-governmental organisations who formulate standards for animal welfare. These are supported by indicators best suited to document their effectiveness. Although we have emphasised how different situations and contexts within the EU mean that there is no single optimal policy instrument for the EU as a whole, but rather appropriate policy instruments should be selected according to the stage of development of a country or sector, we do propose a harmonised choice of indicators to allow benchmarking of changes at the EU level with regard to progress towards animal welfare.

The aim of this study was to assess the feasibility and test-retest reliability of the Welfare Quality® Animal Welfare Assessment Protocol for Growing Pigs. Twenty-three German pig farms were visited repeatedly by the same trained observers; each farm being visited six times during two fattening periods. The entire protocol assessment was carried out during each farm visit, ie a Qualitative Behaviour Assessment (QBA), behavioural observations (BO), a Human Animal Relationship test (HAR) and different individual parameters (IPs), eg bursitis and tail-biting. Test-retest reliability was evaluated by a Wilcoxon signed rank test (W) and by calculation of the Smallest Detectable Change (SDC) and Limits of Agreement (LoA). The QBA presented non-satisfactory agreement between farm visits. However, good agreement, in general, was found for the BO. For the HAR, no reliability could be detected. Most IPs were of acceptable agreement, with the exception of bursitis and manure on the body. Bursitis showed great differences, which can be explained by difficulties in the assessment when the animals moved around or their legs were dirty. The disagreement in the parameter manure on the body can be explained by seasonal effects. Disagreement was further found concerning the parameters coughing, sneezing, pleuritis, pneumonia and milkspots. Feasibility was good; both observers could be well-trained to fulfil the protocol. Furthermore, the time needed for an assessment did not exceed 6 h. The parts of the protocol that proved to be insufficiently reliable need to be addressed in the future in order to enhance and improve the objective measurement of animal welfare.

This research communication explores the value of routinely collected bulk tank milk quality data for estimating dairy cattle welfare at herd level. Selected bulk tank milk quality parameters (somatic cell count, total bacterial count, urea, protein and fat contents) recorded during the years 2014–2016 in 287 Italian dairy farms were compared with the animal welfare data of each farm. The welfare assessment data were extracted from the database of the Italian Reference Centre for Animal Welfare (CReNBA), which includes the outputs of the application of the CReNBA welfare assessment protocol for dairy cows, used at national level for on-farm controls. The statistical analysis was carried out using the correlation coefficient for Kendall's Tau ranks, in order to investigate the presence of a categoric relationship between the selected bulk tank milk quality parameters and the overall animal welfare score or the scores of the single areas A (farm management and staff training), B (housing) and C (animal-based measures). Somatic cell count, total bacterial count, urea and proteins demonstrated only a few statistically significant and very weak correlations with farm animal welfare data, while no significant correlations were obtained for milk fat content. Given the weak correlations found, the selected bulk tank milk parameters seems to be able to provide only limited information about the welfare level of the herd, thus it could be difficult to use them for drawing up a pre-screening model for identifying herds at risk of poor welfare.

Monitoring animal welfare (AW) in pig farms requires both proper indicators and a feasible approach. Animal-based measures (ABMs) are well-established AW indicators. Furthermore, AW screening at the slaughterhouses could be useful for identifying problems on farm. The aim of this study was to evaluate ABMs at the slaughterhouse and, when possible, to compare these ABMs with those collected on the farm. The study was carried out in northern Italy in a commercial abattoir and in a sample of farms. Animal-based measures were recorded on pigs from 62 batches of 54 farms, during ante-mortem (n=10 085 pigs) and post-mortem (n=7952 pigs) inspections. Sixteen of 54 farms were selected to compare ABMs collected at the slaughterhouse with ABMs collected on the farm. Overall, 2295 pigs (mean pigs examined per farm 119±45) were inspected at the slaughterhouse (group S) and 420 pigs (mean pigs per farm 26±5) on the farm (group F). Non-animal-based measures were also collected at the 16 farms. Differences between groups S and F, at the animal level, were assessed by a two-tailed paired Wilcoxon–Mann–Whitney test. Differences at the site of observation level (farm and slaughterhouse) were assessed by Fisher’s exact test using a hierarchical log-linear modelling for contingency tables. The most frequent ABMs at the slaughterhouse were manure on the body (47.7%), followed by dermatitis (28.0%), white spot (25.4%) and bursitis (24.7%). Recording ABMs at the slaughterhouse and on the farm usually yielded similar results; however, there were some exceptions. In particular, significant differences were found for non-uniformity of size (P<0.05) and dermatitis (P<0.001), which were higher at the slaughterhouse than on the farm. Results of log-linear modelling underlined the effect of the farm of origin on the percentage of pigs with bursitis, manure on the body and ear injuries that were observed at the slaughterhouse. In group S, significant associations between manure on the body and insufficient presence of clean and dry areas in the corresponding farm were found (P<0.05). Although these results should be interpreted with care due to the limited sample of farms, the slaughterhouse could be a feasible site of observation of ABMs, which could then be integrated in monitoring of AW on farm. Considering the number of slaughtered batches per farm, it would be possible to repeat assessments several times throughout the year for each farm, which could help provide an index for the continuous monitoring of AW.

In Germany all keepers of livestock are legally required to record animal welfare indicators as part of their on-farm self-assessment. The Association for Technology and Structures in Agriculture (Kuratorium für Technik und Bauwesen in der Landwirtschaft e.V. (KTBL)) has suggested the use of a particular set of animal welfare indicators in their publication Animal welfare indicators: Practical guide – Pigs. The aim of the present study was to evaluate the inter-observer reliability (Inter-OR) and intra-observer reliability (Intra-OR) of these indicators with respect to the welfare of fattening pigs. For the assessment of Inter-OR, three observers evaluated six KTBL animal welfare indicators. The Inter-OR of the indicators was calculated from the results using intra-class correlation coefficients (ICC). ‘Excellent’ Inter-OR results were found for the indicators tail length (ICC 0.89), skin lesions (ICC 0.77) and ear lesions (ICC 0.80). In contrast, the Inter-OR of the indicators tail lesions (ICC 0.46) and faecal soiling (ICC 0.47) were considered to be only ‘fair’ and that of the indicator lameness (ICC 0.36) as ‘poor’. For the evaluation of the Intra-OR, the same three observers assessed the welfare of 162 to 200 fattening pigs using the same welfare indicators in total eight times. Again ICCs, here per indicator and observer, were used to calculate the Intra-OR. The Intra-OR of the indicators faecal soiling (ICC 0.81) and ear lesions (ICC 0.97) lay in the ‘excellent’ range on average. While the Intra-OR of the indicators skin lesions (ICC 0.67), tail length (ICC 0.74) and lameness (ICC 0.60) could still be considered as being ‘good’, the Intra-OR of the indicator tail lesions (ICC 0.52) could only be assessed as being ‘fair’. From these results the significance of the KTBL indicators could be judged as follows: it is possible to use all the chosen indicators apart from the indicator tail lesions as an internal controlling instrument or as part of an internal weak-point analysis as long as the indicators are evaluated by the same person. A comparison of the indicators tail lesions, lameness and faecal soiling when assessed by different observers should be considered critically because the Inter-OR of these three indicators could only be considered as being ‘poor’ to ‘fair’.

Animal welfare has become an important subject of public and political debate, leading to the necessity of an objective evaluation system for on-farm use. As welfare is a multi-dimensional concept, it makes sense to use a multi-criteria aggregation system to obtain an overall welfare score. Such an aggregation system is provided by the Welfare Quality® Network. The present paper focusses on the assessment of the multi-criteria evaluation model included in the Welfare Quality® protocol for growing pigs in order to aggregate the animal-based indicators first to criteria, then to principles and finally to an overall welfare score. Specifically, the importance of the indicators on the overall assessment of growing pig farms is analysed in a given population which consisted of a total of 198 protocol assessments carried out on a sample of 24 farms in Germany. By means of partial least squares modelling, the influence of measures in the calculation procedure is estimated by calculation and interpretation of Variable Importance for Projection (VIP) scores. Variable Importance for Projection scores revealed some meaningful, unexpected influences as the multi-criteria evaluation model of Welfare Quality® aimed at avoiding interferences and double-counting. Some of these influences led to the assumption that some measures might have potential as iceberg indicators, whereas others showed lesser importance. Thus, feasibility can be gained by the deletion and special weighting of indicators according to their importance. Altogether, the study is an essential contribution to the further development of the Welfare Quality® protocols as well as the application of multi-criteria decision systems in the field of animal welfare science in general.