How wearables are becoming important for nutrition

Wearable technologies have become ubiquitous in our everyday lives. Not only do they allow us to track our health, they are evolving to provide important data that can inform the creation of personalized recommendations that can improve our health and nutrition. This article covers what wearables are and how they have become an essential tool in digital health

What are Wearables technology and devices?

Wearable technologies, commonly referred to as wearables, are electronic devices that can be worn on the body to measure health-related data. The most popular wearables are wristwear such as a smartwatch, wrist bands, followed by eyewear & headwear, footwear, neckwear, and bodywear.

The wearable technology market has been growing and is forecasted to exceed 186.14 billion USD in revenue by 2030.

Recent reports indicate the 8 out of 10 US consumers (63.4%)  have used apps and wearables to track their health.

According to a recent report by McKinsey, Gen Z as well as Millenials are most likely to spend more on health and nutrition where wearables would fit in. In fact they stated that around 17% of Gen Z's track their nutritional intake and approximately 66% of Gen Z's use wearables to track their health vs only 40% of other generations. Females, people with a college education, and household income exceeding $75 000 are more likely to use wearable devices. According to industry media resource Nutraingredients, this current trends is not about to end soon.

Wearables in Digital health

Wearables are used to monitor chemical, physiological, and biological changes. Therefore, they can give insights into a wide range of health-related data, including but not limited to: blood pressure, pulse and heart rate, glucose, electrolytes, hormones, and physical activity metrics. Access to an individual's data by non-invasive methods such as wearables opens the door for personalized nutrition interventions and real-time recommendation and tracking.

The potential and benefits of wearables in healthcare

Wearables offer a new way to gather data of an individual in the real-world setting. Wearables can be tracking data via user input for example an exercise session or logging nutritional intake or automatically such as sleep.

These data points can be used a way to understand lifestyle behaviours and patterns opening avenues for personalization. Data can be mined using AI and machine learning to unravel patterns or to predict events. Anumber of studies have already leveraged wearables to conduct clinical studies.

The Fitbit heart study  is a good example. More than four hundred fifty-five thousand participants without atrial fibrillation (AF) were enrolled in the study. 1-week ambulatory ECG patch monitors were given to the participants showing irregular rhythms based on the data Fitbit provided.

Results showed that Fitbit wearables displayed high positive predictive value for concurrent AF. However, various wearables use various technologies (sensors) which take measurements from different body parts, which results in a diversity of the data (refer to current challenges of using wearables: data quality), which is only one of the challenges.

 Another clinical study examined the efficacy of self-tracking of physical activity in type 2 patients. Both the intervention and control groups received the usual care. The intervention group was also given Fitbit Zip ( an activity tracker) that connects to an online lifestyle program. After 13 weeks of intervention, patients using the activity tracker showed significantly increased physical activity.

In another study the Apple watch was used as a device to track female menstruation cycle throughout the month to identify any correlation between the data collected and common conditions such as Polycystic Ovary Syndrome (PCOS). 

There are more and more calls for wearable data to be integrated into electronic health records. Companies such as Validic offer a hub of wearable devices which can be connected to EHT using API's.

Wearables as a data source in Personalized nutrition

"Access to an individual's data by non-invasive methods such as wearables open the door for more personalized and real-time nutrition interventions.” Mariette Abrahams

Wearables can act as a source of data which can be combined with others to provide insight into an individuals' lifestyle and behaviour.  A few examples that can provide real-world insight into an individual's lifestyle include:

• Diet tracking/Food logging with apps such as Myfitnesspal can be used to provide insight into how and when an individual eats basd on how they exercise
• Coaching - data collected by wearables can be used as a source of data to provide personalized coaching services
• Sport and fitness – Wearables data can be used to provide personalized recommendations based on when and how to hydrate such as the Gatorade sweat patch
• Shopping – GPS Geolocation can be used to provide nudges and prompts for individuals based on where they are for example restarurant recommendations, gyms, parks or supermarkets
• Remote care - data can be used to provide remote care such as when blood sugars are extremely high or low or when blood pressure is out of range. 
• Self-tracking and resilience - Wearables can be a useful tool to asses how resilient an individual is to stress or specific interventions such as training. This can provide insight into how quickly an individual recovers, or how much sleep is required to restore stress levels.

How Personalized nutrition solutions can leverage data from wearables

New wearables have been developed to monitor, screen, detect and predict health-related outcomes and diseases.

Here are just a few examples of wearables and their importance for personalized nutrition:

• Continues glucose & ketone detection sensors: Blood glucose and ketone detection have great importance for diabetic patients, people who follow ketogenic diets, and athletes. Wearable sensors (patches) give continuous and real-time blood glucose and ketone levels, contrary to conventional methods that give single time data representing measurement time. Continuous blood and ketone detection by non-invasive, user-friendly, low-cost, and accessible methods such as wearables can drastically improve personalized nutrition interventions.
• Sensors monitoring sodium intake: Sodium monitoring is vital for people with cardiovascular diseases, the leading cause of death globally. Patients try to monitor sodium intake by reading labels and using apps that do not provide actual data. These methods demand continuous effort from the patients, which is a real barrier to improving patients' health. Oral sensors monitoring real-time sodium intake are developing. Having the data on sodium intake can shape personalized nutrition interventions, especially for people with increased risk of cardiovascular diseases and patients with cardiovascular diseases.
• Saliva-based sensors: Saliva contains ions, urea, uric acid, cholesterol, creatine, fatty acids, protein, and hormones. Saliva-based sensors such as smart bands, brackets, and pacifiers are on the market.
  Hormone sensors: Hormones regulate the body's functions, including metabolism, weight regulation, appetite, and dietary intake. For example, wearables commonly measure cortisol by sweat, blood, and saliva. The data can help personalized nutrition interventions for weight management since the hormone cortisol is associated with stress, metabolism, and food intake.
• Physical activity trackers: Physical activity metrics are the most common feature of wearables used by consumers. Wearables give data on various physical activity indicators such as daily steps, workouts, cardio fitness estimates, VO2 max (showing maximal aerobic capacity), and recovery time. These data can inform the healthcare professional about a patient's lifestyle, which can improve interventions prescribed to patients because sedentary lifestyles are common among people and contribute to important health problems.
• Breathables: These devices can measure health status such as metabolic flexibility, small intestinal bacterial overgrowth as well as fermentation and glucose

CGM's as a popular wearable to track glucose levels

At present, CGM's have become popular amongst consumers who are interested in tracking their responses to lifestyle changes such as diet, exercise and sleep.

CGM's are wearable medical devices that are inserted at the top (and back) of an individual's arm. Popular devices include Abbott's freestyle sensor as well as Dexcom. Sensors last up to 14 days and transmit levels of interstitial glucose to an app that takes a measurement every 5 minutes or so. These devices can provide data over 24 hours.

The CGM market is expected to balloon to $5.5bn according to recent market reports with the main drivers being a rapid rise in Type II Diabetes diagnoses, an aging population, lowering cost as well as increased adoption and recommendation by healthcare professionals.

The use of CGM's amongst healthy individuals is still highly controversial as it is argued that individuals in good metabolic health will have blood sugar spikes after a meal and will spend around 90% of the time in normal blood sugar range (TIR) according to Shah et al 2021.

Despite this, consumers have become interested in their metabolic health and the adoption amongst lifestyle consumers continues to increase. 

This has driven shifts in the market  in a number of ways:

• The increase in consumer awareness of the role of blood glucose in health as well a rise in the number of online searches for CGM's
• The increase in strategic partnerships between wearable and personalized nutrition startups in the industry to provide enhanced data insights 
• Partnerships between CGM providers and larger retail brands 

Market examples of wearables providing Personalized nutrition and lifestyle advice

• Supersapiens delivers Abbott Libre Sense glucose sport biosensor measuring real-time blood glucose levels. The Supersaphiens app gives personalized guidance to improve fueling efficiency and performance (now closed).
• Apple Watch & InsideTracker partnership allows users to integrate activity tracking features of Apple Watch with the InsideTracker personalized guidance to reach fitness goals and tips for sleep optimization.
• Garmin & Body Kitchen collaborated to provide health monitoring and nutrition coaching for esports teams.
• Royal Dutch Group (DSM) & Huami give users personalized nutrition and physical activity guides based on real-time health data AmazaFit (by Humai) provides.
• Abbott and Weight Watchers are running a study to determine whether wearing a CGM can lower HbA1C levels in Type II Diabetics and Overweight individuals.

Do wearables change behaviour?

Data on it's own cannot drive behaviour change unless you are a biohacker to know what the data means. Owing to it's potential ease of data-collection and leveraging AI and machine learning to make sense of the data, wearables have the potential to enhance personalized nutrition offerings.

According to recent systematic reviews and meta-analyses, the most frequent areas of research where wearable data are used as biofeedback (a behaviour change technique) inclde Diabetes, Weight management and Cardiovascular disease (Richardson et al 2023). Based on the analysis by Villinger et al (2019) they demonstrated that digital health tools such as wearables and apps have a small but significant impact on behaviour change especially when it comes to increasing Fruit and vegetable intake.

Current challenges of using wearables to inform Personalized nutrition solutions

Wearable technologies are continuously getting better at measuring health-related data. However, there are challenges in the use of wearables in digital health and clinical use:

• Overestimation and overprediction are common issues among wearable technologies, as reported by the European Commission.
• Data quality is affected by the variability of sensors. The same biomarkers (take blood oxygen saturation) can be measured from various body parts by various wearables (such as smart watches, rings, and pulse oximeters). In addition, a recent, researchers highlighted that there is high variability of glucose responses to the same meal. This means that the same meal can have different impact on glucose levels depending on time of time. These difference can be as variable as glucose responses to entirely different meals. (Hengist 2024). These variabilities in data create problems in data quality especially if glucose measurements are not taken over a long peiod of time.
• Health equity and representativity of the dataset: Wearables mostly target specific age, social and economic groups more than others, which results in inequity (Lancet)
• Affordability: High price is a big issue for most people willing to use wearables.
• Information security: The consumer's personal data can be stored by wearables in digital clouds to analyze consumer data.
• Regulatory requirements: Regulations that are flexible enough to facilitate innovation and protect public health are needed to expand the use of wearable technologies in healthcare.
• Consumer preferences and habits: Consumers abandoned their wearables for various reasons, including limited functionality, the lack of inbuilt technology, no inbuilt internet connectivity, inaccurate data and information, poor integration with other devices, fast battery drain, and poor design.

Still accumulating research shows that increasing accuracy, reducing noise in the data, and improving heterogeneity and privacy problems can open a door for the use of wearables to help detect cardiovascular diseases in large populations. 

A Wearable future

Wearable technologies have emerged as electronic devices worn on the body to measure health-related data. With the market growing rapidly, businesses have recognized the potential of wearables to improve personalized nutrition interventions. Wearables can monitor chemical, physiological, and biological changes, providing insights into a wide range of health-related data that can inform business strategies.

New wearables have been developed to monitor health-related outcomes and diseases, including continuous glucose & ketone detection sensors, sensors monitoring sodium intake, saliva-based sensors, hormone sensors, and physical activity trackers. Wearables can drastically improve personalized nutrition innovations by providing access to an individual's data through non-invasive methods and informing future solutions such as Digital twins according to a recent article by Vitafoods. 

Our Qina take

We believe that new types of wearables such as hearables and tatoo's will change the face of wearables in the years to come. We also believe the Generative AI presents new oportunities to deliver personalized recommendations in real-time based on wearable data.

However, challenges remain in using wearables in digital health and clinical use, such as overestimation and overprediction, variability of sensors, health equity and representativity of the dataset, affordability, information security, regulatory requirements, and consumer preferences and habits. Despite these challenges, wearables are rapidly becoming essential tools for businesses seeking to improve personalized nutrition interventions for their customers.

At this stage it is clear that our smartphones hold the key to being the gateway between digital and wearable solutions and our behaviour. Our guess is that the future will be increasingly connnected.

For more information on which wearables combine with nutrition and wellness apps to provide personalized recommendations, our comprehensive Qina platform tracks new innovations and industry news.

References

1. The Fitbit Heart study |  URL
2. Moshawrab, M.; Adda, M.; Bouzouane, A.; Ibrahim, H.; Raad, A. Smart Wearables for the Detection of Cardiovascular Diseases: A Systematic Literature Review. Sensors 2023, 23, 828. |  Link
3. Kooiman, Thea J.M. MSc; de Groot, Martijn PhD; Hoogenberg, Klaas MD, PhD; Krijnen, Wim P. PhD; van der Schans, Cees P. PhD, PT, CE; Kooy, Adriaan MD, PhD. Self-tracking of Physical Activity in People With Type 2 Diabetes: A Randomized Controlled Trial. CIN: Computers, Informatics, Nursing 36(7):p 340-349, July 2018. | DOI: 10.1097/CIN.0000000000000443 |  URL
4. Qina reveals ten trends in Personalised nutrition - Nutraingredients
5. Big tech and ChatGPT among main drivers for innovation in 2024 - Vitafoods
6. Nearly two-thirds of US consumers are mobile health app users. Insider intelligence

7. Wearable devices—addressing bias and inequity - Lancet

8. 8. Abbott and Weight watchers CGM trials https://diatribe.org/weightwatchers-and-cgm-new-trial-studies-using-both

      9. Hengist A, Ong JA, McNeel K, Guo J, Hall KD. Imprecision nutrition? Duplicate meals result in unreliable individual glycemic responses measured by continuous glucose monitors across four dietary patterns in adults without diabetes. medRxiv [Preprint]. 2023 Dec 11:2023.06.14.23291406. doi: 10.1101/2023.06.14.23291406. PMID: 37503002; PMCID: PMC10371100.