A Multi-Modal Approach for A Healthier Weight and More Active Lifestyle

Abstract Background Obesity and overweight has been increasing globally and in the UK over the last few years, bringing along a wide array of challenges in health and wellbeing. Not only do they take a heavy toll on those affected, but obesity and overweight-related ill-health is costing the UK National Health Service £6.1 with projected costs to run up to £9.7 billion in 2050. This project aimed to apply artificial intelligence to identify the predictive indicators for obesity and co-create an intervention with public health practitioners and stakeholders. Methods Using health and wellbeing public health population data from the 2015, 2018 and 2022 from a city in the East Midlands, we applied artificial intelligence that uses machine learning techniques to discover insights, find hidden patterns and discover relationships in the data about engaging in physical activity and a healthy diet. The data on dietary choices and physical activity preferences were further analysed using advanced machine learning techniques. Results The outcomes from our machine learning process revealed patterns of physical activity engagement and diet from specific locations, along with a range of demographic variables that influence individuals’ patterns of physical ability and dietary practices. These findings, which will be presented in detail, have been integrated into a comprehensive city map. This map not only showcases opportunities for engaging in a healthy lifestyle but also aids in prioritising interventions in areas of greatest need. Conclusions The AI technology we employed allowed us to parameterise and generalise our findings with the possibility of scaling up the machine learning approach to other similar datasets. The findings facilitated the development of bespoke training for public health officers working with underserved communities, further demonstrating the impact of applying AI to inform the design of public health interventions. Key messages • Applying Artificial Intelligence to public health data has the potential to inform the development of effective interventions and increase precision. • Using AI in public health data can generate new insights into population health and well-being and inform public health policy.