Evidence map›Paper›PMID 30208045›Full record

ArticlePloS one2018

Welfare-Adjusted Life Years (WALY): A novel metric of animal welfare that combines the impacts of impaired welfare and abbreviated lifespan.

Kendy Tzu-Yun Teng, Brecht Devleesschauwer, Charline Maertens De Noordhout, Peter Bennett, Paul D McGreevy, Po-Yu Chiu, Jenny-Ann L M L Toribio, Navneet K Dhand

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.8field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 39 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 3 countries.

Kendy Tzu-Yun TengSydney School of Veterinary Science, Faculty of Science, University of Sydney, Camperdown, NSW, Australia.ORCID 0000-0003-3200-1545
Brecht DevleesschauwerDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Charline Maertens De NoordhoutInstitute of Health and Society, Faculty of Public Health, Catholic University of Louvain, Brussels, Belgium.
Peter BennettSydney School of Veterinary Science, Faculty of Science, University of Sydney, Camperdown, NSW, Australia.ORCID 0000-0002-7209-4996
Paul D McGreevySydney School of Veterinary Science, Faculty of Science, University of Sydney, Camperdown, NSW, Australia.
Po-Yu ChiuNational Taiwan University Veterinary Hospital, Taipei, Taiwan.
Jenny-Ann L M L ToribioSydney School of Veterinary Science, Faculty of Science, University of Sydney, Camperdown, NSW, Australia.
Navneet K DhandSydney School of Veterinary Science, Faculty of Science, University of Sydney, Camperdown, NSW, Australia.
The University of Sydney · AUGhent University · BENational Taiwan University Hospital · TWUCLouvain · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, separate measures are used to estimate the impact of animal diseases on mortality and animal welfare. This article introduces a novel metric, the Welfare-Adjusted Life Year (WALY), to estimate disease impact by combining welfare compromise and premature death components. Adapting the Disability-Adjusted Life Year approach used in human health audits, we propose WALY as the sum of a) the years lived with impaired welfare due to a particular cause and b) the years of life lost due to the premature death from the same cause. The years lived with impaired welfare are the product of the average duration of each welfare impediment, reflecting the actual condition that compromises animal welfare, the probability of an incident case developing and impaired welfare weights, representing the degree of impaired welfare. The years of life lost are calculated using the standard expected lifespan at the time of premature death. To demonstrate the concept, we estimated WALYs for 10 common canine diseases, namely mitral valve disease, dilated cardiomyopathy, chronic kidney disease, diabetes mellitus, atopic dermatitis, splenic haemangiosarcoma, appendicular osteosarcoma, cranial cruciate ligament disease, thoracolumbar intervertebral disc disease and cervical spondylomyelopathy. A survey of veterinarians (n = 61) was conducted to elicit impaired welfare weights for 35 welfare impediments. Paired comparison was the primary method to elicit weights, whereas visual analogue scale and time trade-off approaches rescaled these weights onto the desired scale, from 0 (the optimal welfare imaginable) to 1 (the worst welfare imaginable). WALYs for the 10 diseases were then estimated using the impaired welfare weights and published epidemiological data on disease impacts. Welfare impediment "amputation: one limb" and "respiratory distress" had the lowest and highest impaired welfare weights at 0.134 and 0.796, rescaled with a visual analogue scale, and 0.117 and 0.857, rescaled with time trade-off. Among the 10 diseases, thoracolumbar intervertebral disc disease and atopic dermatitis had the smallest and greatest adverse impact on dogs with WALYs at 2.83 (95% UI: 1.54-3.94) and 9.73 (95% uncertainty interval [UI]: 7.17-11.8), respectively. This study developed the WALY metric and demonstrated that it summarises welfare compromise as perceived by humans and total impact of diseases in individual animals. The WALY can potentially be used for prioritisation of disease eradication and control programs, quantification of population welfare and longitudinal surveillance of animal welfare in companion animals and may possibly be extended to production animals.

Indexed as

Animal WelfareLongevityQuality-Adjusted Life YearsAnimalsDog DiseasesDogsGlobal Burden of Disease

Identifiers

PMID30208045
PMCPMC6135394
OpenAlexW2890889106

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.