About the Project
The PhD Award
Sheffield Hallam University (SHU) is inviting applications for this PhD project in the Sport and Physical Activity Research Centre (SPARC), within the Health Research Institute. The project is part of our joint PhD programme with La Trobe University, Melbourne, Australia. Students on the joint PhD programme will be enrolled on a PhD at both institutions, with a supervisory team of academics from each institution. On successful completion, the candidate will be awarded a PhD jointly by both institutions.
This project is based at Sheffield Hallam, with an expectation that the successful candidate will spend up to 12 months at La Trobe during the course of the project. Further details and how to apply
The awards will provide:
- Tuition fees at Home/UK rates
- A bursary at UKRI national doctoral stipend rates (£15,285 for 2020/21)
- One economy return air fare between the UK and La Trobe University
- Up to £600 to assist with personal/health insurance expenses while resident at La Trobe for 3 years of full-time study. These scholarships are not available for part-time study.
Waist girth is used widely to determine an individual’s risk of conditions associated with obesity and metabolic syndrome (type 2 diabetes, cardiovascular disease). However, waist girth is a blunt tool that misses a significant sub-population of normal weight, metabolically obese individuals. As a result, treatment can be ineffective, or even absent. This problem was originally recognised within Asian populations but is increasingly being recognised as an issue affecting all ethnicities.
This PhD will focus on new and innovative ways of identifying metabolic risk based on body shape rather than simple girth measurements.
Aim of PhD Programme:
Assess alternative shape-based methods of measuring abdominal obesity for the purpose of better classifying risk level of individuals with metabolic syndrome.
- Review the literature on metabolic syndrome, CVD and diabetes risk (with a focus on waist girth, and the non-obese population)
- Assess the prevalence of metabolic syndrome within a large cohort and calculate the reliability of waist girth as a predictor of its associated risk factors. This objective will identify a) overweight, but metabolically healthy individuals b) normal weight but metabolically obese individuals.
- Apply shape-analysis methods to determine whether it can distinguish between groups a) and b) more effectively than waist-girth.
- Perform a cohort data collection stratified for age and gender to establish whether shape analysis methods can be applied objectively across demographics.
- Perform a clinical trial to determine whether shape analysis can be used to detect changes in metabolic syndrome and its associated risk factors
During your PhD you will link the pioneering work in 3D shape analysis being performed at the Advanced Wellbeing Research Centre (at SHU) with the assessment and management of lifestyle related health conditions for which it was founded.
Your PhD will increase knowledge of the clinical relevance linking risk factors and shape analysis for metabolic syndrome and provide data regarding assessment and ultimately the diagnosis of individuals with metabolic syndrome. These findings have the potential to revolutionise the way we detect metabolic syndrome and understand the relationship between our external form and internal function.
This broad-reaching PhD program would be suitable for candidates with a background in either Engineering, Public Health, Allied Health or Epidemiology. The supervisory team comprises academics with backgrounds in Engineering, Physiotherapy, Dietetics and Public Health to expertly guide a candidate through this program. Ideally candidates will have some research experience related to recruiting and testing participants and completing statistical analyses.
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Koster A, Stenholm S, Alley DE, Kim LJ, Simonsick EM, Kanaya AM, et al. Body Fat Distribution and Inflammation Among Obese Older Adults With and Without Metabolic Syndrome. Obesity. 2010 Dec 15;18(12):2354–61.
Paterson JM, Morton NM, Fievet C, Kenyon CJ, Holmes MC, Staels B, et al. Metabolic syndrome without obesity: Hepatic overexpression of 11 -hydroxysteroid dehydrogenase type 1 in transgenic mice. Proc Natl Acad Sci. 2004 May 4;101(18):7088–93.
Smith SR, Lovejoy JC, Greenway F, Ryan D, De Jonge L, De La Bretonne J, et al. Contributions of total body fat, abdominal subcutaneous adipose tissue compartments, and visceral adipose tissue to the metabolic complications of obesity. Metabolism. 2001;50(4):425–35.
van Namen M, Prendergast L, Peiris CL. Supervised lifestyle intervention for people with metabolic syndrome improves outcomes and reduces individual risk factors of metabolic syndrome: A systematic review and meta-analysis. Metabolism. 2019 Dec;101:153988.
Thelwell M, Chiu C, Bullas A, Hart J, Wheat J, Choppin S. An investigation of how shape-based anthropometry can complement traditional anthropometric techniques [in review]. Sci Reports. 2020;
Löffler-Wirth H, Engel C, Ahnert P, Alfermann D, Arelin K, Baber R, et al. The LIFE-Adult-Study: Objectives and design of a population-based cohort study with 10,000 deeply phenotyped adults in Germany. BMC Public Health. 2015;15(1):1–14.
WHO EC. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet (London, England). 2004;363(9403):157.
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