Premature mortality analysis of 52,000 deceased cats and dogs exposes socioeconomic disparities

Monitoring mortality rates offers crucial insights into public health by uncovering the hidden impacts of diseases, identifying emerging trends, optimising resource allocation, and informing effective policy decisions. Here, we present a novel approach to analysing premature mortality in companion animals, utilising data from 28,159 deceased dogs and 24,006 deceased cats across the United Kingdom. By employing PetBERT-ICD, an automated large language model (LLM) based International Classification of Disease 11 syndromic classifier, we reveal critical insights into the causes and patterns of premature deaths. Our findings highlight the significant impact of behavioural conditions on premature euthanasia in dogs, particularly in ages one to six. We also identify a 19% increased risk of premature mortality in brachycephalic dog breeds, raising important animal welfare concerns. Our research establishes a strong correlation between socioeconomic status and premature mortality in cats and dogs. Areas with the lowest Index of Multiple Deprivation (IMD) scores show nearly a 50% reduction in the risk of premature mortality across cats and dogs, underscoring the powerful impact that socioeconomic factors can have on pet health and longevity. This research underscores the necessity of examining the socioeconomic disparities affecting animal health outcomes. By addressing these inequities, we can better safeguard the well-being of our companion animals.

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Publication Details

Journal
Scientific Reports
Published
2024-11-20
DOI
https://doi.org/10.1038/s41598-024-77385-8
Citations
3
Primary Topic
Human-Animal Interaction Studies
Type
article
Field-Weighted Citation Impact
1.65

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article

Premature mortality analysis of 52,000 deceased cats and dogs exposes socioeconomic disparities

Sean Farrell, Peter‐John M. Noble, Noura Al Moubayed, Katharine L. Anderson
3 citations
Scientific Reports
Human-Animal Interaction Studies
1.65
article

Premature mortality analysis of 52,000 deceased cats and dogs exposes socioeconomic disparities

Sean Farrell, Peter‐John M. Noble, Noura Al Moubayed, Katharine L. Anderson
article en
3 citations

Abstract

Monitoring mortality rates offers crucial insights into public health by uncovering the hidden impacts of diseases, identifying emerging trends, optimising resource allocation, and informing effective policy decisions. Here, we present a novel approach to analysing premature mortality in companion animals, utilising data from 28,159 deceased dogs and 24,006 deceased cats across the United Kingdom. By employing PetBERT-ICD, an automated large language model (LLM) based International Classification of Disease 11 syndromic classifier, we reveal critical insights into the causes and patterns of premature deaths. Our findings highlight the significant impact of behavioural conditions on premature euthanasia in dogs, particularly in ages one to six. We also identify a 19% increased risk of premature mortality in brachycephalic dog breeds, raising important animal welfare concerns. Our research establishes a strong correlation between socioeconomic status and premature mortality in cats and dogs. Areas with the lowest Index of Multiple Deprivation (IMD) scores show nearly a 50% reduction in the risk of premature mortality across cats and dogs, underscoring the powerful impact that socioeconomic factors can have on pet health and longevity. This research underscores the necessity of examining the socioeconomic disparities affecting animal health outcomes. By addressing these inequities, we can better safeguard the well-being of our companion animals.

Scientific ReportsVol. 14(1)
University of Liverpool (GB), Durham University (GB), Dogs Trust (GB)
Dogs Trust, Directorate for Biological Sciences
Good health and well-being
Openalex Percentile: Top 14%
Human-Animal Interaction Studies
1.65
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Premature mortality analysis of 52,000 deceased cats and dogs exposes socioeconomic disparities — Sean Farrell, Peter‐John M. Noble, et al. · Scientific Reports (2024) | TGRS Research Map | TGRS