This paper reviews animal-based welfare indicators to develop a valid, reliable, and feasible on-farm welfare assessment protocol for dairy goats. The indicators were considered in the light of the 4 accepted principles (good feeding, good housing, good health, appropriate behavior) subdivided into 12 criteria developed by the European Welfare Quality program. We will only examine the practical indicators to be used on-farm, excluding those requiring the use of specific instruments or laboratory analysis and those that are recorded at the slaughterhouse. Body condition score, hair coat condition, and queuing at the feed barrier or at the drinker seem the most promising indicators for the assessment of the "good feeding" principle. As to "good housing," some indicators were considered promising for assessing "comfort around resting" (e.g., resting in contact with a wall) or "thermal comfort" (e.g., panting score for the detection of heat stress and shivering score for the detection of cold stress). Several indicators related to "good health," such as lameness, claw overgrowth, presence of external abscesses, and hair coat condition, were identified. As to the "appropriate behavior" principle, different criteria have been identified: agonistic behavior is largely used as the "expression of social behavior" criterion, but it is often not feasible for on-farm assessment. Latency to first contact and the avoidance distance test can be used as criteria for assessing the quality of the human-animal relationship. Qualitative behavior assessment seems to be a promising indicator for addressing the "positive emotional state" criterion. Promising indicators were identified for most of the considered criteria; however, no valid indicator has been identified for "expression of other behaviors." Interobserver reliability has rarely been assessed and warrants further attention; in contrast, short-term intraobserver reliability is frequently assessed and some studies consider mid- and long-term reliability. The feasibility of most of the reviewed indicators in commercial farms still needs to be carefully evaluated, as several studies were performed under experimental conditions. Our review highlights some aspects of goat welfare that have been widely studied, but some indicators need to be investigated further and drafted before being included in a valid, reliable, and feasible welfare assessment protocol. The indicators selected and examined may be an invaluable starting point for the development of an on-farm welfare assessment protocol for dairy goats.

Score 1Presence of residual horns (scurs) on the head of adult goats that have been disbudded when kids.The total number of goats in the pen presenting these conditions is recorded. Queuing (AWIN, 2015)At feeding A goat is queuing if it is standing within 0.5 m behind another goat that is feeding/ drinking, with the head oriented towards the feed barrier/ water place. At drinkingHair coat condition (AWIN, 2015; Battini et al., 2015a) Poor hair coatThe hair coat is matted, rough, scurfy, uneven, shaggy hair coat, frequently longer than normal. Oblivion (AWIN, 2015)An oblivious goat seems physically or/and mentally isolated compared to the rest of the group, frequently facing the wall or other parts of the housing structure, sometimes with ears down. Abnormal lying (Mattiello et al., 2015)

The AWIN project aimed at developing an on-farm welfare assessment protocol for adult dairy goats. A prototype protocol was tested in 30 intensive dairy goat farms to evaluate its feasibility in farms of different size. Time for applying the prototype was recorded and any other constraint was taken into account. Moreover, data collected during the prototype testing provided information on the prevalence of welfare issues in intensive dairy goat farms in Northern Italy. The prototype included 25 animal-based indicators (14 group-and 11 individual-level indicators). The prototype showed a good on-farm feasibility and it was highly accepted among stakeholders, as its application did not interfere with the daily routine. Approximately 2 h were required for the application of the prototype. When feeding racks were available, using them for locking the animals during the individual assessment resulted advantageous to speed the data collection and to reduce handling stress to the goats and disturbance to the farmers. Farm size and different management systems influenced the prevalence of some indicators, with small farms in general better welfare conditions compared to larger farms. The results of the present study represent an important starting point to set up an epidemiological database that may lead to improve the welfare status of goats. ARTICLE HISTORY

Simple SummaryThe Animal Welfare Indicators (AWIN) project developed a practical welfare assessment protocol for lactating dairy goats in intensive husbandry systems, using animal-based indicators that cover the whole multidimensional concept of animal welfare. The strict collaboration between scientists and stakeholders resulted in an easy-to-use protocol that provides farmers or veterinarians with comprehensive but clear feedback on the welfare status of the herd in less than three hours. The protocol, which highlights key points and motivates farmers to achieve improvements, has received much attention from interested parties.AbstractWithin the European AWIN project, a protocol for assessing dairy goats’ welfare on the farm was developed. Starting from a literature review, a prototype including animal-based indicators covering four welfare principles and 12 welfare criteria was set up. The prototype was tested in 60 farms for validity, reliability, and feasibility. After testing the prototype, a two-level assessment protocol was proposed in order to increase acceptability among stakeholders. The first level offers a more general overview of the welfare status, based on group assessment of a few indicators (e.g., hair coat condition, latency to the first contact test, severe lameness, Qualitative Behavior Assessment), with no or minimal handling of goats and short assessment time required. The second level starts if welfare problems are encountered in the first level and adds a comprehensive and detailed individual evaluation (e.g., Body Condition Score, udder asymmetry, overgrown claws), supported by an effective sampling strategy. The assessment can be carried out using the AWIN Goat app. The app results in a clear visual output, which provides positive feedback on welfare conditions in comparison with a benchmark of a reference population. The protocol may be a valuable tool for both veterinarians and technicians and a self-assessment instrument for farmers.

Background: Population health measurements are recognised as appropriate tools to support public health monitoring. Yet, there is still a lack of tools that offer a basis for policy appraisal and for foreseeing impacts on health equity. In the context of persistent regional inequalities, it is critical to ascertain which regions are performing best, which factors might shape future health outcomes and where there is room for improvement. Methods: Under the EURO-HEALTHY project, tools combining the technical elements of multi-criteria value models and the social elements of participatory processes were developed to measure health in multiple dimensions and to inform policies. The flagship tool is the Population Health Index (PHI), a multidimensional measure that evaluates health from the lens of equity in health determinants and health outcomes, further divided into sub-indices. Foresight tools for policy analysis were also developed, namely: (1) scenarios of future patterns of population health in Europe in 2030, combining group elicitation with the Extreme-World method and (2) a multi-criteria evaluation framework informing policy appraisal (case study of Lisbon). Finally, a WebGIS was built to map and communicate the results to wider audiences. Results: The Population Health Index was applied to all European Union (EU) regions, indicating which regions are lagging behind and where investments are most needed to close the health gap. Three scenarios for 2030 were produced-(1) the 'Failing Europe' scenario (worst case/increasing inequalities), (2) the 'Sustainable Prosperity' scenario (best case/decreasing inequalities) and (3) the 'Being Stuck' scenario (the EU and Member States maintain the status quo). Finally, the policy appraisal exercise conducted in Lisbon illustrates which policies have higher potential to improve health and how their feasibility can change according to different scenarios. Conclusions: The article makes a theoretical and practical contribution to the field of population health. Theoretically, it contributes to the conceptualisation of health in a broader sense by advancing a model able to integrate multiple aspects of health, including health outcomes and multisectoral determinants. Empirically, the model and tools are closely tied to what is measurable when using the EU context but offering opportunities to be upscaled to other settings.