Profiling Detection and Classification of Lameness Methods in British Dairy Cattle Research: A Systematic Review and Meta-Analysis

Abstract

Lameness is a serious concern in the dairy sector, reflecting its high incidence and impact on animal welfare and productivity. Research has provided figures on its frequency using different methodologies, making it difficult to compare results and hindering farm-level decision-making. The study's objectives were to determine the frequency levels of lameness in British dairy cattle through a meta-analysis approach, and to understand the chronological patterns of how lameness cases are detected and classified in scientific research. A systematic review was conducted using PRISMA-P guidelines for article selection. Random-effects models estimated the pooled frequency measure of lameness with heterogeneity managed through subgroup analysis and meta-regression. Sixty-eight papers were identified, 50 included prevalence and 36 incidence data. The pooled prevalence of lameness in British dairy cattle was estimated at 29.5% (95% CI 26.7-32.4%) whilst all-cause lameness incidence rate indicated 30.9 cases of lameness per 100 cow-years (95% CI 24.5-37.9). The pooled cause-specific lameness incidence rate per 100 cow-years was 66.1 (95% CI 24.1-128.8) for white line disease, 53.2 (95% CI 20.5-101.2) for sole ulcer, 53.6 (95% CI 19.2-105.34) for digital dermatitis, with 51.9 (95% CI 9.3-129.2) attributable to other lameness-related lesions. Heterogeneity levels remained high. Sixty-nine papers contributed to a chronological overview of lameness data source. Although the AHDB Dairy mobility scoring system (MSS) was launched in the UK in 2008 and adopted shortly after by the British Dairy sector as the standard tool for assessing lameness, other methods are used depending on the investigator. Automated lameness detection systems may offer a solution for the subjective nature of MSSs, yet it was utilized in one study only. Despite the recognition of under-reporting of lameness from farm records 22 (31.9%) studies used this data source. The diversity of lameness data collection methods and sources was a key finding. It limits the understanding of lameness burden and the refinement of policy making for lameness. Standardizing case definition and research methods would improve knowledge of and ability to manage lameness. Regardless of the measurement method lameness in British dairy cattle is high.

Preventive Hoof Trimming and Animal-Based Welfare Measures Influence the Time to First Lameness Event and Hoof Lesion Prevalence in Dairy Cows

“…Overall, the incidence rate of lameness in hoof-trimmed cows from GR and NGR was 27.4 cases/100 cows/month (3.6 cases/cow/year) and 31.9 cases/100 cows/month (4.2 cases/cow/year), respectively. The present result is consistent with the lameness incidence rate reported in cows from freestalls during dry periods (4.2 cases/cow/year) (33) but lower compared to 7.4 cases/cow/year recorded in lactating cows from a freestall herd (34) and pooled lameness incidence in grazing herds (64.6/100 cow-years) (16). The high lameness incidence rate could be attributed to the enrollment of primiparous and older cows, which are more susceptible to lameness episodes, management practice, and the presence of control groups that were not trimmed during lactation.…”

“…Lameness levels vary under different management systems, with studies reporting higher prevalence in non-grazing or confined cows than those kept on pasture-based herds (14,15). Factors such as prolonged standing time, reduced lying time, and little exercise were suggested to enhance the development of hoof lesions in confined and non-grazing dairy cows (16). These events contribute to detrimental hoof traits including disproportionate heel height, too-long dorsal wall, greater imbalance in weight distribution between the front and hind hooves (3,17), and increasing the need for preventive or curative hoof trimming (HT) (18).…”

Estimating the burden of multiple endemic diseases and health conditions using Bayes’ Theorem: A conditional probability model applied to UK dairy cattle

“…Diseases and conditions ranked in order of decreasing prevalence. Disease/condition Prevalence (proportion) Reference Lameness 0.30 a Afonso et al (2020) Mastitis 0.30 b Hanks and Kossaibati (2020) Subclinical ketosis 0.22 c Suthar et al (2013) GIN disease 0.21 d Scott et al (2019) Neosporosis 0.15 e Reichel et al (2013) Metritis 0.10 c Suthar et al (2013) Fasciolosis 0.10 f May et al (2019) Cystic ovary 0.09 g Gröhn et al (1995) Milk fever 0.08 Esslemont and Kossaibati (1996) Paratuberculosis 0.07 Woodbine et al (2009) Retained placenta 0.05 h Dubuc and Denis-Robichaud (2017) Displaced abomasum 0.03 c Suthar et al (2013) Dystocia 0.02 Rumph and Faust (2006) a Pooled prevalence. b Median value reported.…”

Global Burden of Animal Diseases: a novel approach to understanding and managing disease in livestock and aquaculture

“…The GBADs Programme relies on a massive volume of data from multiple data sources, including scientific articles published in journals, national animal censuses, electronic farm and agribusiness records, and agriculture statistics curated by the World Health Organization (WHO), the Food and Agriculture Organization of the United Nations (FAO) and the OIE. These data sets display considerable heterogeneity in their methodological design and descriptors (54), creating a challenging environment in which to use this information to make meaningful comparisons -for example, between diseases in various production systems and different countries -in a consistent and transparent way.…”