Osteoarthritis is the most common joint disease diagnosed in veterinary medicine and poses considerable challenges to canine welfare. This study aimed to investigate prevalence, duration and risk factors of appendicular osteoarthritis in dogs under primary veterinary care in the UK. The VetCompassTM programme collects clinical data on dogs attending UK primary-care veterinary practices. The study included all VetCompassTM dogs under veterinary care during 2013. Candidate osteoarthritis cases were identified using multiple search strategies. A random subset was manually evaluated against a case definition. Of 455,557 study dogs, 16,437 candidate osteoarthritis cases were identified; 6104 (37%) were manually checked and 4196 (69% of sample) were confirmed as cases. Additional data on demography, clinical signs, duration and management were extracted for confirmed cases. Estimated annual period prevalence (accounting for subsampling) of appendicular osteoarthritis was 2.5% (CI95: 2.4–2.5%) equating to around 200,000 UK affected dogs annually. Risk factors associated with osteoarthritis diagnosis included breed (e.g. Labrador, Golden Retriever), being insured, being neutered, of higher bodyweight and being older than eight years. Duration calculation trials suggest osteoarthritis affects 11.4% of affected individuals’ lifespan, providing further evidence for substantial impact of osteoarthritis on canine welfare at the individual and population level.

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Abstract.It is important to understand the relative contribution of primary and secondary particles to regional and global aerosol so that models can attribute aerosol radiative forcing to different sources. In large-scale models, there is considerable uncertainty associated with treatments of particle formation (nucleation) in the boundary layer (BL) and in the size distribution of emitted primary particles, leading to uncertainties in predicted cloud condensation nucleiCorrespondence to: C. L. Reddington (c.reddington@see.leeds.ac.uk) (CCN) concentrations. Here we quantify how primary particle emissions and secondary particle formation influence size-resolved particle number concentrations in the BL using a global aerosol microphysics model and aircraft and ground site observations made during the May 2008 campaign of the European Integrated Project on Aerosol Cloud Climate Air Quality Interactions (EUCAARI). We tested four different parameterisations for BL nucleation and two assumptions for the emission size distribution of anthropogenic and wildfire carbonaceous particles. When we emit carbonaceous particles at small sizes (as recommended by the Aerosol Intercomparison project, AEROCOM), the spatial distributions of Published by Copernicus Publications on behalf of the European Geosciences Union. C. L. Reddington et al.: Primary vs. secondary contributions to PN concentrationscampaign-mean number concentrations of particles with diameter >50 nm (N 50 ) and >100 nm (N 100 ) were well captured by the model (R 2 ≥0.8) and the normalised mean bias (NMB) was also small (−18 % for N 50 and −1 % for N 100 ). Emission of carbonaceous particles at larger sizes, which we consider to be more realistic for low spatial resolution global models, results in equally good correlation but larger bias (R 2 ≥0.8, NMB = −52 % and −29 %), which could be partly but not entirely compensated by BL nucleation. Within the uncertainty of the observations and accounting for the uncertainty in the size of emitted primary particles, BL nucleation makes a statistically significant contribution to CCN-sized particles at less than a quarter of the ground sites. Our results show that a major source of uncertainty in CCN-sized particles in polluted European air is the emitted size of primary carbonaceous particles. New information is required not just from direct observations, but also to determine the "effective emission size" and composition of primary particles appropriate for different resolution models.

While the incorporation of mathematical and engineering methods has greatly advanced in other areas of the life sciences, they have been under-utilized in the field of animal welfare. Exceptions are beginning to emerge and share a common motivation to quantify 'hidden' aspects in the structure of the behaviour of an individual, or group of animals. Such analyses have the potential to quantify behavioural markers of pain and stress and quantify abnormal behaviour objectively. This review seeks to explore the scope of such analytical methods as behavioural indicators of welfare. We outline four classes of analyses that can be used to quantify aspects of behavioural organization. The underlying principles, possible applications and limitations are described for: fractal analysis, temporal methods, social network analysis, and agent-based modelling and simulation. We hope to encourage further application of analyses of behavioural organization by highlighting potential applications in the assessment of animal welfare, and increasing awareness of the scope for the development of new mathematical methods in this area.

Background Evidence-based comparison of the disorder-specific welfare burdens of major canine conditions could better inform targeting of stakeholder resources, to maximise improvement of health-related welfare in UK dogs. Population-level disease related welfare impact offers a quantitative, welfare-centred framework for objective disorder prioritisation, but practical applications have been limited to date due to sparse reliable evidence on disorder-specific prevalence, severity and duration across the canine disease spectrum. The VetCompass™ Programme collects de-identified electronic health record data from dogs attending primary-care clinics UK-wide, and is well placed to fill these information gaps. Results The eight common, breed-related conditions assessed were anal sac disorder, conjunctivitis, dental disease, dermatitis, overweight/obese, lipoma, osteoarthritis and otitis externa. Annual period prevalence estimates (based on confirming 250 cases from total potential cases identified from denominator population of 455, 557 dogs) were highest for dental disorder (9.6%), overweight/obese (5.7%) and anal sac disorder (4.5%). Dental disorder (76% of study year), osteoarthritis (82%), and overweight/obese (70%) had highest annual duration scores. Osteoarthritis (scoring 13/21), otitis externa (11/21) and dermatitis demonstrated (10/21) highest overall severity scores. Dental disorder (2.47/3.00 summative score), osteoarthritis (2.24/3.00) and overweight/obese (1.67/3.00) had highest VetCompass Welfare Impact scores overall. Discussion Of the eight common, breed-related disorders assessed, dental disorder, osteoarthritis and overweight/obese demonstrated particular welfare impact, based on combinations of high prevalence, duration and severity. Future work could extend this methodology to cover a wider range of disorders. Conclusions Dental disorders, osteoarthritis and overweight/obese have emerged as priority areas for health-related welfare improvement in the UK dog population. This study demonstrated applicability of a standardised methodology to assess the relative health-related welfare impact across a range of canine disorders using VetCompass clinical data.