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An epidemiological analysis of equine welfare data from regulatory inspections by the official competent authorities

Published online by Cambridge University Press:  09 December 2016

P. L. Hitchens*
Affiliation:
Department of Animal Environment and Health, Swedish University of Agricultural Sciences (SLU), Box 7068, 750 07 Uppsala, Sweden
J. Hultgren
Affiliation:
Department of Animal Environment and Health, Swedish University of Agricultural Sciences (SLU), Box 234, 532 23 Skara, Sweden
J. Frössling
Affiliation:
Department of Animal Environment and Health, Swedish University of Agricultural Sciences (SLU), Box 234, 532 23 Skara, Sweden National Veterinary Institute(SVA), 751 89 Uppsala, Sweden
U. Emanuelson
Affiliation:
Department of Clinical Sciences, Swedish University of Agricultural Sciences (SLU), Box 7054, 750 07 Uppsala, Sweden
L. J. Keeling
Affiliation:
Department of Animal Environment and Health, Swedish University of Agricultural Sciences (SLU), Box 7068, 750 07 Uppsala, Sweden
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Abstract

Determining welfare status in a population is the first step in efforts to improve welfare. The primary objective of this study was to explore a new epidemiological approach for analysis of data from official competent authorities that pertain to compliance with animal welfare legislation. We reviewed data already routinely collected as part of Swedish official animal welfare inspections for 2010–13, using a checklist containing 45 checkpoints (CPs). These covered animal-, resource- and management-based measures of equine welfare. The animal-based CPs were measures that directly related to the animal and included social contact, body condition, hoof condition and cleanliness. Non-compliance with one or more of the animal-based CPs was used as a binary outcome of poor equine welfare; 95% confidence intervals (CI) were estimated using the exact binomial distribution. Associations were determined using multivariable logistic regression, adjusting for clustering on premises. Resource- and management-based CPs (model inputs) were reduced by principal component analysis. Other input factors included premises characteristics (e.g. size, location) and inspection characteristics (e.g. type of inspection). There were 30 053 premises with horses from 21 counties registered by the Swedish Board of Agriculture. In total 13 321 inspections of premises were conducted at 28.4% (n=8532) of all registered premises. For random inspections, the premises-prevalence of poor equine welfare was 9.5% (95% CI 7.5, 11.9). Factors associated with poor equine welfare were non-compliance with requirements for supervision, care or feeding of horses, facility design, personnel, stable hygiene, pasture and exercise area maintenance, as well as the owner not being notified of the inspection, a previous complaint or deficiency, spring compared with autumn, and not operating as a professional equine business. Horses at premises compliant with stabling and shelter requirements had significantly better welfare if they also complied with documentation requirements. We present a novel approach for analysis of equine welfare data from regulatory inspections by the official competent authorities, and propose on-going analyses and benchmarking of trends in animal-based measures over time. We also suggest how such a database could be further improved to facilitate future epidemiological analyses of risk factors associated with poor equine welfare. The study has implications for other competent authorities and researchers collaborating in the area of animal welfare epidemiology.

Type
Research Article
Copyright
© The Animal Consortium 2016 

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Footnotes

a

Present address: Equine Centre, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, 250 Princes Hwy, Werribee 3030, Australia.

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