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Exploring associations between mental health and weight status

Project title 
Exploring associations between mental health and weight status/metabolic health/nutrient intake

Supervisors names
Lee Hudson
Simon Russell

Background
Rates of childhood/adolescent obesity have remained high in recent years, in the UK and elsewhere with potential negative consequences for health. Research shows that overweight/obesity are associated with depression, anxiety and other mental health disorders. This association is bidirectional with evidence showing that people who experience depression and other mental health problems have an increased risk of developing obesity. Both obesity and mental health problems are socially patterned but longitudinal studies show that associations between obesity and mental health are not accounted for by socioeconomic confounding. Body weight may mediate the pathway between socioeconomic disadvantage and mental health outcomes in adolescence (including both negative and positive domains).
The aetiology of mental health problems is complex and multifactorial, and the extent to which BMI plays a role is variable. Trials of obesity interventions to improve mental health interventions in childhood/adolescence are rare, but improvements in body weight may improve mental health outcomes and associated morbidities. The potential impact of improving body weight on mental health outcomes and inequalities at a population level is unknown.
 

Aim/Objectives
To use longitudinal cohort data to simulate the potential impact of population obesity interventions on prevalence and inequalities in mental health outcomes (problems and skills).

Methods
The thesis should initially commence with a systematic literature review on the topic, and may also involve patient, public involvement activities. The student will be expected to develop their own ideas before commencing data analysis with support of supervisors. Directions of data analysis could include:

The student using a causal mediation approach (e.g., Marginal Structural Models, Interventional Disparity Measures) using longitudinal cohort data (e.g., the Millennium Cohort Study [MCS] comprising young people born around the year 2000), allows measures of exposure to disadvantage, weight status, mental health (and confounding factors) to be modelled temporally.  This will allow options for the thesis development by the student for example:

  • Using a social determinants approach where the exposure is household disadvantage (e.g., income) and weight status mediates the journey to MH outcomes (could be anxiety, depression or holistic view of MH e.g., MH problems (externalising/internalising) or a skills-based conceptualisation of positive mental health).
  • Using body weight as the exposure and MH measures mediate the journey to metabolic health outcomes (blood pressure, lipids, cholesterol, PWV).

There may be other areas to develop during the thesis, including:

  • Exploring ‘weight scarring’, where people who had obesity but lose weight retain a heightened risk of struggling with mental health issues and dying early. 
  • Exploring links between metabolic health and mental health, given that people with obesity but better metabolic health, may be less prone to developing mental health conditions. 
  • Exploring nutrition and mental health, given that poor nutrition may be links to metal health problems regardless of weight status.
     

References
Rajan TM, Menon V. Psychiatric disorders and obesity: A review of association studies. J Postgrad Med. 2017. 63(3):182-190.
Mannan M. et al. Prospective Associations between Depression and Obesity for Adolescent Males and Females- A Systematic Review and Meta-Analysis of Longitudinal Studies. PLoS ONE 2016. 11(6): e0157240. 


Contact
Lee Hudson (l.hudson@ucl.ac.uk)