Micro Trends in Health and Wellness

Thursday 7th September

By Chris Fung

Chris is the former CEO of Crussh Fit Food & Juice Bars, the UK’s leading juice, smoothie and healthy eating chain with over 30 sites in London. Having led Crussh for 13 years, he is now a non-exec board advisor investing in and guiding a number of businesses with a specific focus on the Food Tech space.

In the run-up to London Food Tech Week this October, Chris will be sharing his perspectives on each of the week’s key Day Themes. This week he explores our day focussed on the The Hyper (R)Evolution of Eating; where he deep dives into some of the trends and technologies in health and wellness and asks when and how we'll be moving towards hyper-personalised nutrition.

The global wellness industry, which includes the health, nutrition and fitness sectors, is now worth over $3.7 trillion and growing at 11% per annum. There is technology for everything from fitness tracking, nutrition apps and wearables, to connected IoT (Internet of Things) measuring devices and meditation and sleep optimisation apps.

Yet despite all this, the global workforce is becoming increasingly unwell. Obesity rates continue to rise as an ever greater proportion of the population is overweight. We are becoming less resilient, more stressed out and suffering from increasingly poorer quality rest – why is it not working?

Right now, we have solved most of the health tracking feedback loop – fitness trackers monitor our every movement, sleep sensors work well enough, wi-fi enabled digital scales and fat percentage monitors measure and send our results updating apps automatically. Fitness tracking is getting more advanced and activity-specific by the day. Wearables like the Fitbit, and Apple watch, while not perfect, can track our relative movements sufficiently to be useful. Sleep tracking has also come along in leaps and bounds.

Fitbit wearer - yfood

However one key link still remains at large: nutrition tracking. We haven’t quite figured out how to automatically keep tabs on what we eat and drink accurately.

The key thing holding back widespread uptake is that we still need to manually enter what we eat and drink in order to track our dietary habits and nutrition. Even with all the tech available from apps like MyFitnessPal and Lifesum amongst dozens of others – the tracking of what we eat falls down simply due to human behaviour. It is too cumbersome and manual input requires effort!

Our friends at healthy lifestyle app giant Lifesum, recently commented that they cannot measure and track what is not logged or measured. For all but the most dedicated of fitness fanatics, people tend to neglect logging correctly what they actually eat. We forget, we don’t enter the full amount, or we don’t have all the right information; and outside of short bursts of time, we find it difficult, if not impractical to track everything we consume.

Until we can solve this problem with automation or find an alternative way to measure the impact in real time of what we have just eaten, we are effectively treading water and there won’t be the step change required for health tracking to become truly ubiquitous. This is part of a wider set of reasons why the Apple Watch hasn’t been as successful as it promised to be.

There are a number of companies looking at solving the problem of understanding the nutritional impact of what we eat using the 3 B’s – Bloodwork, Breath, and Bodily fluids (saliva, sweat, tears, etc). In essence, overriding the need to manually track what we eat by going straight to measuring the impact of our diet on glucose levels and other metabolic markers. The challenge with bloodwork in particular, is that no one wants to subject themselves to pin pricks on a regular basis and we are not quite ready yet to have RFID chips or smart stents implanted subcutaneously en masse. Contact lenses (Google X has been working on it since before 2014), saliva and sweat patches show promise as does breath analysis and we probably aren’t too far away from being able to commercialise it in a convenient way. E-skin tattoos might also be a faster way forward too.

While the missing link to automating nutritional input data remains, we won’t be reaching the fully Quantified Self just yet. All the other pieces of the health tracking feedback loop are available but without this key input none of the data sets generated will be sufficiently accurate nor useable. Despite this flaw, there are still many ways to use the data generated by fitness trackers and nutrition apps to reveal insights and trends that might lead to better health outcomes.

Lifesum, for example, now has lifestyle data on over 20 million customers. With their big data and AI capabilities, they can start mapping these data sets. Such large and rich data pools from millions of users can start to reveal patterns of behaviours and measured outcomes as insights are drawn from research findings in ways much quicker than traditional methods of scientific testing.

If there is something good that comes out of this then it would be to pass on the most up to date nutritional knowledge to the general population and drive significantly better health outcomes for all.

For example – the current wave of veganism, plant-based diet movement, HFLC (High Fat Low Carb) plans for losing weight and ketogenic diets can be analysed against historically calorie-controlled style diets to compare outcomes and results.


This information is not only useful at the aggregate and total population levels but the information can now be fed into personalised nutrition programmes.

Once you can combine this information with personalised genetic testing along with individual movement and nutrition data, truly personalised nutrition programmes can be devised. Companies like Vitl and Pure Genetic Lifestyle are already taking genetics into account to personalise their supplements to better match individual nutrition needs.

Further opportunities then arise from using big data and AI at aggregate levels to roll down to personalised nutrition programmes aimed at preventative rather than curative options. We can more evenly distribute the health wealth once we are able to meet the first challenge of knowing how to improve health outcomes.

For instance, rather than taking the Amazon model of selling based on purchase history to give us more of what we don’t need nor want, it might be a better use of the data available to offer people suggestions based on product choices that lead to healthier outcomes.

Companies have started to think about these possibilities including Swedish company Fudigo and health app Nutrifix. Rather than looking at simple repetitive meal plans, they recommend options that steer you towards better eating choices that match your health goals rather than reinforcing current habits.

So here’s to longer, healthier and fitter lives. As to happiness and fulfilment, AI and tech can only take you so far. The rest is still up to you!


Hospitality tech expert and YFood contributor Chris Fung will be exploring each of the five London Food Tech Week Day Themes in turn. You can find out more about each Day Theme and the rest of the week here.

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