Research Data Leeds Repository

Sexism of Fat: Is it sufficient to use only one sex in obesity research?

MacCannell, Amanda and Whitehead, Anna and Moran, Amy and Roberts, Lee (2020) Sexism of Fat: Is it sufficient to use only one sex in obesity research? University of Leeds. [Dataset] https://doi.org/10.5518/853

Dataset description

There is a weight issue weighing down the public health care systems across the world. Although obesity is prevalent in both males and females, the location of fat and impact on cardiometabolic health is strikingly different. These differences are apparent in the clinical setting, but there remains a bias towards using a single sex in mouse models to create simpler and cheaper experiments. The bias towards using a single sex in experiments skews the results and only offers translational research to one half of the human population. We examined sex differences and their effect on obesity by inducing obesity in both male and female mice by feeding them high fat diet (HFD) for 10 weeks. Mice were weighed weekly and after 10 weeks of HFD feeding, mice underwent metabolic tests to determine the impact of obesity. Male mice became obese after only 1 week of HFD feeding, however it took female mice 9 weeks of HFD feeding to become obese. Male mice were more susceptible to diabetes and male mice lost increased metabolic difference when fed HFD. This study highlights the importance of using both sexes to study obesity and associated diseases while highlighting novel differences in metabolism between sexes.

Additional information:	This poster won first prize in the Leeds Doctoral College Showcase: Online Poster Conference 2020
Subjects:	A000 - Medicine & dentistry
Divisions:	Faculty of Medicine and Health > School of Medicine
Date deposited:	03 Aug 2020 15:06
URI:	http://archive.researchdata.leeds.ac.uk/id/eprint/720
Additional details Additional details Creators: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type MacCannell, Amanda https://orcid.org/0000-0002-1294-5250 University of Leeds https://doi.org/10.13039/501100000777 Crossref Whitehead, Anna University of Leeds https://doi.org/10.13039/501100000777 Crossref Moran, Amy University of Leeds https://doi.org/10.13039/501100000777 Crossref Roberts, Lee https://orcid.org/0000-0002-1455-5248 University of Leeds https://doi.org/10.13039/501100000777 Crossref Type of data: Dataset Research funders: NSERC / CRSNG, British Heart Foundation, Cardiovascular Research Leeds UK, Medical Research Council Publication date: 2020 Legal and ethical issues: Images sourced from https://www.rawpixel.com Resource language: English Metadata language: English Publisher: University of Leeds Contact Email Address: umamac@leeds.ac.uk Last Modified: 05 Aug 2020 10:56

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