Childhood obesity and new technologies
11 September 2016
The publication of the Government’s Strategy on Childhood Obesity has drawn criticism for not seizing the opportunity to do something more radical to curb one of the biggest threats to the nation’s health.
The statistics are well known: 1 in 3 primary school age children are overweight or obese, and the links between this and ill health in later life are well established.
Overweight and obesity are multifactorial conditions, and encompass areas of our lives which can be very difficult to ‘unpick’ from the outside. Attempts to tackle this problem are more likely to yield results if we include several different perspectives in our thinking - weaving innovative approaches and new technology into traditional public health approaches.
The Government strategy did describe a multifaceted approach, but stopped short in terms of depth of analysis. As part of the strategy’s ‘shopping list’ of measures, there was reference to two areas which might give cause for optimism, as mentioned in our recent blog. The strategy describes a need to ‘harness the best technology’ and to ‘support health professionals in developing the kinds of skills needed to offer personalised advice, and influence behaviour change’ but doesn’t set out in detail a vision of what this might entail.
As part of our healthcare futures work we have been looking at the latest developments in the field of nutrigenomics which aims to harness insights from our genomes to offer more personalised nutritional guidance. So how might personalised nutritional and lifestyle advice, guided by genomics and other biomarkers be formulated and delivered, how could technology be used and how might this help obesity in childhood?
Personalising the message
One of the aims (as yet unrealised) of nutrigenomics is to identify genomic markers which could be used to stratify individuals in terms of the most effective nutritional advice to ensure they maintain a healthy weight. However this approach is unlikely to succeed on its own. Instead, enabling healthcare professionals (or others?) to deliver the sort of personalised advice referred to in the strategy, will require combining knowledge of an individual’s genetic makeup with other relevant metrics. These might include information about our physiology such as hormone levels at different stages of life or information about our environment or social circumstances e.g. home or work commitments, awareness of which is essential if we are to create truly personalised strategies with the best chance of succeeding. Regardless of the metrics used to formulate this advice, the act of personalisation in itself seems to elicit better responses- it seems we all prefer a bespoke service
Even if we are able to personalise nutritional advice using a biomarker led approach, there remains the challenge of monitoring adherence to that advice and its impact on our health. Digital technologies can help here too. Smartphone apps and personal monitoring devices such as iFit are now widely used to estimate calorie intake, daily steps taken, or sports performance and assist with healthy living, weight loss, or fitness training goals. The data generated by such apps about our diet and activity levels can also be fed back and combined with analysis of our metabolism and genetic makeup to further refine the health advice given either to prevent obesity or to tackle it once it is established.
The increasing availability of portable, low cost digital and biological analysis will also empower individuals to understand the determinants of their health, including weight. Obesity focused apps of the future may be improved through initiatives such as the EU QuaLiFy (Quantify Life feed Yourself) project which helps researchers and small enterprises share data to help develop the next generation of tools to support personalised nutrition. Other projects such as the PRECIOUS (PREventive Care Infrastructure based on Ubiquitous Sensing) project are looking at the possibilities of ‘quantified self’ technology, using sensors to deliver ambient data on food intake, sleep and exercise, which is then interpreted, with advice fed back, using advanced motivational techniques, such as gamification, and allowing the system to adapt to an individual’s goals and preferences.
This kind of technology has the potential to revolutionise our daily habits and, in its extreme form, turn autonomous behaviours into machine-prompted ‘choices.’ Of course, this kind of intrusive ‘big brother’ style monitoring may not be acceptable to many, but in a more moderate form may bring benefits in the form of ‘nudging’ us towards adopting healthier behaviours
How might this impact on childhood obesity?
There is much evidence that poor diet in the early years of life is linked to a greater risk of being overweight or obese in later childhood and adulthood. It is hard to envisage how digital tools being developed for the monitoring of behaviour and diet in adults could be easily applied to younger children and their carers. For now, at least, general public health messages about weaning and healthy eating as a family are probably still the most appropriate way to tackle obesity in the early years. However, in older children, who have increasing autonomy over food choices outside the home, it’s easier to see how technology, particularly the ever-present smartphone, could be used effectively to ‘nudge’ their behaviours. With this in mind, gamification - working on the fact that individuals exhibit increased motivation when there is a desire to ‘master’ or improve ratings - might be particularly useful. Applying these approaches in children or young adults, however, does raise ethical questions about autonomy and responsibility that will need to be addressed.
In thinking how best to provide a healthy future for children, we can argue about the shortcomings of top-down measures like reducing sugar in drinks but we must remember to act positively and also invest resources in developing the technological tools and support which have the power to help families, and children, to help themselves.