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Background

Excess salt consumption increases blood pressure and is a risk factor for cardiovascular diseases. Although salt is added during cooking and at the table, the majority of salt consumed in the UK comes from purchased foods. The UK Government set salt reduction targets for different food categories in 2017, and salt consumption is regularly measured in the National Diet and Nutrition Survey. Since November 2017, data on the nutritional quality of all food and drinks available in major UK online supermarkets have been collected on a weekly basis and saved in a database called foodDB – the primary objectives of this project will be to use foodDB to evaluate whether the 2017 salt reduction targets have been met, track trends in salt levels in food, and to update estimates of salt consumption from the National Diet and Nutrition Survey by linking consumption data with nutrient composition data from foodDB. Secondary objectives will be to conduct correlational analyses to assess the relationship between salt levels in foods and marketing techniques including price, promotions and packaging. Further work could include monitoring salt levels in foods from the fast food sector; a systematic review on attitudes towards adding salt during cooking and at the table; a qualitative study of attitudes towards low-salt alternatives; or a modelling study estimating the health impact of reductions in salt due to the salt reduction strategy.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The core element of this project will be extensive analyses of foodDB: a database that collects data on all foods available on all major UK online supermarkets on a weekly basis and has been collecting data since November 2017. Additionally, the student will receive support and training in conducting quantitative research, systematic reviewing, and scenario modelling.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING 

For the core element of the thesis, the student will need to be able to conduct analyses on very large datasets that will need a considerable amount of data cleaning and curation. If necessary, training on analytical packages such as R and Stata may be necessary. Other training on systematic review methodology and qualitative data analysis may also be required. Such training courses are readily available. The named supervisors have extensive experience and expertise in disease modelling and data harvesting techniques.

PROSPECTIVE CANDIDATE

A suitable candidate for this project will have the following characteristics: a strong interest in population-level approaches to improving health; quantitative analysis skills. Additionally, the following characteristics would be desirable: experience of qualitative research; knowledge of systematic review methods; knowledge of disease modelling methods. A suitable candidate would have completed a Masters degree in public health or a related subject, or would be an outstanding student with an undergraduate degree related to public health.

Supervisors

  • Peter Scarborough
    Peter Scarborough

    Associate Professor and University Research Lecturer

  • Richard Harrington
    Richard Harrington

    Senior Research Data Scientist

  • Mike Rayner
    Mike Rayner

    Professor of Population Health and Director of the Centre on Population Approaches for Non-Communicable Disease Prevention (CPNP)