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Cross-cultural comparisons of obesity prevention in children: United Kingdom, Spain and China

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  • Full or part time
    Dr Adab
    Dr Frew
  • Application Deadline
    Applications accepted all year round

Project Description

Applications are invited for a 3-year fully-funded PhD Studentship starting October 2016.

Childhood obesity is a growing problem worldwide, with serious health, social and economic consequences. Socio-economic determinants and psychosocial impacts of obesity vary in different countries. For example, obesity is more common among more deprived sub-populations in the UK, whereas the converse is true in China.

The supervisory team are involved in three distinct childhood obesity prevention studies including: a UK-based cluster-randomised controlled trial (the WAVES study); a Spanish obesity management trial (Nereu programme) and a China-basedcluster-randomised controlled trial (CHIRPY DRAGON). The studies include children from a wide range of socio-economic backgrounds, with uniform data collection instruments across studies, which will allow cross-cultural comparisons across settings. Data on health-related quality of life (HQoL) and other data for economic evaluation of the interventions are collected/being collected.

This presents an opportunity for a PhD student to undertake cross-cultural comparison of the relationship between weight status and HQoL, examine the relative cost-effectiveness of weight prevention interventions, and identify the cost-drivers that impact on cost-effectiveness.

The selected PhD candidate will shape the specific research questions and to some extent the direction of the PhD. The studies are likely to include: i) systematic review of the cost-effectiveness evidence for obesity prevention interventions, focusing on resource use, measures of effectiveness, economic modelling assumptions and where the greatest areas of data uncertainty lie, ii) Review of theoretical approaches to cross-cultural comparisons of cost-effectiveness and of quality of life measures, iii) Analysis of data from across the separate studies, examining socioeconomic, gender and ethnic differences in impact of weight status on HQoL, iv) Comparison of cost-effectiveness across the three settings, v) Economic evaluation of the Chinese and Spanish interventions.

The candidate will have the opportunity to sit in selected modules from the MPH and Masters in Health Economics & Health Policy, depending on their training needs. They will develop an understanding of health economics, public health and in analysis of large datasets. The PhD will provide a strong foundation for either a health economics focused or more public health focused research career.

Person Specification
Applicants should have a strong background in either health economics, or public health. They should have a commitment to applied public health research and hold or realistically expect to obtain at least an Upper Second Class Honours Degree in a health related area. Candidates who have completed either an MPH or Masters in Health Economics are ideally suited.

How to apply
Enquiries and applications should be directed to [PGR Administrator] at [email protected] To apply, please send:

• A Detailed CV, including your nationality and country of birth;
• Names and addresses of two referees;
• A covering letter highlighting your research experience/capabilities;
• Copies of your degree transcripts;
• Evidence of your proficiency in the English language, if applicable.

Funding Notes

British and EU nationality applicants are eligible for both the cost of tuition fees and a yearly stipend (at RCUK rate) over the course of the PhD programme.

Non-EU applicants may apply, but the funding available will be limited to the equivalent of the cost of tuition and stipend (RCUK rate) for an EU applicant.

Studentship will be advertised until position filled

How good is research at University of Birmingham in Public Health, Health Services and Primary Care?

FTE Category A staff submitted: 44.70

Research output data provided by the Research Excellence Framework (REF)

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