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BACKGROUND

Unhealthy diets are a major cause of ill health. Unsustainable diets are also contributing to the climate and nature emergencies. Food labelling policies could improve both the healthiness and environmental impact of diets through influencing consumer choice, food availability decisions by retailers, new product development and reformulation by manufacturers, etc.

Sustainability claims (one aspect of food labelling) are messages or representations, which, in any form, state, suggest or imply that a food has particular characteristics related to its impact on human health, animal welfare, the environment or social wellbeing, 

In previous research we have found that health-related sustainability claims (HRSCs) (e.g. ‘low fat’, ‘good for the heart) have a significant impact on dietary choices but that foods with HRSCs only have a marginally better nutritional profile than foods without such claims. However, this research used 2013 data collected from packets by hand.

As well as HSRCs for foods, there seems to be a growing number of environment-related sustainability claims (ERSCs) (e.g. ‘low-carbon’, ‘eco-friendly’). It is unclear what impact ERSCs have on the healthiness and sustainability of diets and whether regulation of such claims is necessary to prevent so called ‘green washing’. (NB there are already fairly strict regulations for HRSCs). 

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The proposed project will start by estimating the prevalence of HRSCs and ERSCs in the UK and the composition of foods carrying such claims. This will involve using data from the foodDB database developed by NDPH researchers. The foodDB database contains data (and metadata) on all foods and drinks available in nine UK online supermarkets collected weekly since November 2017.

The project will then involve exploring the health and environmental impacts of HRSCs and ERSCs firstly by comparing foods with and without such claims using validated scores of the healthiness and environmental impact of foods and secondly by modelling impact of consuming foods with and without claims.   This last stage of the project will involve models developed by NDPH researchers such as the Preventable Risk Integrated Model (PRIME) The project could well involve other ways of assessing the impact of claims such as discrete choice experiments.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING

The student will be mainly based at NDPH. NDPH researchers have considerable experience of working with foodDB data and appropriate impact models such as PRIME.  The department also makes available a range of training courses in quantitative research.

PROSPECTIVE STUDENT

The ideal candidate will have a Masters degree in a relevant area and will have experience working with large datasets, strong quantitative analysis skills, and an interest in diet and public health.

Supervisors

  • Mike Rayner
    Mike Rayner

    Professor of Population Health and Director of the World Health Organization Collaborating Centre on Population Approaches for Non-Communicable Disease Prevention (CC PNP)

  • Asha Kaur
    Asha Kaur

    Intermediate Research Fellow

  • Jessica Renzella
    Jessica Renzella

    Lecturer in Population Health