Transaction data for population health

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Digital technology opens up a new era in the understanding of human behaviour and lifestyle choices, with people's daily activities and habits leaving 'footprints' in their digital records. For example, when we buy goods in supermarkets and use loyalty cards to obtain benefits (e.g., future discounts), the supermarket records our purchases and creates a representation of our habits and preferences. Until now the use of 'digital footprint' data has mostly been limited to private companies. Companies have been using aggregates of these data to track sales of their products, to understand the factors that impact sales levels, and to target marketing and promotions. Changes in Data Protection law in the UK, i.e. General Data Protection Regulation, mean the public can now access and donate their data for academic research. Shopping history data, recorded through loyalty cards by retailers, are an extremely useful source of information for population health research as it can provide granular, objective data on real world choices and behaviours (e.g. painkillers, food) and other behaviours (e.g., pain and weight, wellbeing management). This information is often hard to obtain in the health research domain. Links between lifestyle choices and health outcomes are commonly studied through self-report questionnaires that ask people to remember their everyday choices and behaviours, which can bias results: responses about behaviours do not always reflect the reality of what people actually do. If and when shopping history data are used in a privacy preserving and ethical manner, these data can be utilised for public good, benefiting health research (e.g., helping to understand how everyday behaviours and lifestyle choices impact health and social outcomes). For example, what are the exact levels of alcohol consumption that lead to irreversible health damage for unborn babies accounting for moderating factors (e.g., age, gender, genetic makeup, etc.)? Under which conditions do different types of ready meals contribute to obesity? Do chemicals in household products lead to higher risks of cancer and other adverse health outcomes in children? The Transaction Data for Population Health research programme utilises commercially collected datasets for privacy-preserving, ethical research to benefit the public good. This program questions whether shopping history data can be used in a positive way to support health research and the development of new interventions. The fellowship will establish the feasibility of novel ways of assessing both health outcomes and associated lifestyle choices through objective measures of real world behaviours reflected in retail shopping history data recorded through loyalty cards. At the same time it will build a framework that can be used by future researchers. My research programme in Yrs 1-4 will unfold in three stages. First, it will use commercially collected datasets to identify and study reproductive health outcomes through patterns in the shopping data. Second, it will validate patterns in the data which are associated with health outcomes using established Longitudinal Population Studies such as the Avon Longitudinal Study of Parents And Children (aka Children of the 90s). Third, I will use the linked datasets to research questions of population health importance in the domain of reproductive health, such as what are the true rates of miscarriages, how do women manage postpartum health and wellbeing, whether breastfeeding is better in the long run for children's mental health, and others. This will be done through studies with Children of the 90s participants and the general public helping to validate the results. The impact of the project will realised in Yrs 5-7 and include a conceptual change in techniques for studying population health, making it possible to identify lifestyle causes of diseases, assess the impact of national policies, and provide recommendations for health interventions.