Anatomically distinct adipose tissues represent variable risks to metabolic health in man and some other mammals. Quantitative-imaging of internal adipose depots is problematic in large animals and associations between regional adiposity and health are poorly understood. This study aimed to develop and test a semi-quantitative system (EQUIFAT) which could be applied to regional adipose tissues. Anatomically-defined, photographic images of adipose depots (omental, mesenteric, epicardial, rump) were collected from 38 animals immediately post-mortem. Images were ranked and depot-specific descriptors were developed (1 = no fat visible; 5 = excessive fat present). Nuchal-crest and ventro-abdominal-retroperitoneal adipose depot depths (cm) were transformed to categorical 5 point scores. The repeatability and reliability of EQUIFAT was independently tested by 24 observers. When half scores were permitted, inter-observer agreement was substantial (average κw: mesenteric, 0.79; omental, 0.79; rump 0.61) or moderate (average κw; epicardial, 0.60). Intra-observer repeatability was tested by 8 observers on 2 occasions. Kappa analysis indicated perfect (omental and mesenteric) and substantial agreement (epicardial and rump) between attempts. A further 207 animals were evaluated ante-mortem (age, height, breed-type, gender, body condition score [BCS]) and again immediately post-mortem (EQUIFAT scores, carcass weight). Multivariable, random effect linear regression models were fitted (breed as random effect; BCS as outcome variable). Only height, carcass weight, omental and retroperitoneal EQUIFAT scores remained as explanatory variables in the final model. The EQUIFAT scores developed here demonstrate clear functional differences between regional adipose depots and future studies could be directed towards describing associations between adiposity and disease risk in surgical and post-mortem situations.
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 September 2017.
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