The following peer-reviewed research articled was published in the ACNEM Journal in December 2024, and was written by Dr Michelle Woolhouse, the Medical Director of Vively.

Abstract

Continuous Glucose Monitors (CGMs) have traditionally been used to manage type-1 and type-2 diabetes by providing real-time glucose data, allowing for better control of blood sugar levels. However, recent research highlights the expanding role of CGMs beyond diabetes, offering significant potential for improving metabolic health, athletic performance, and preventive healthcare in non-diabetic populations. This literature review examines the latest findings on CGM technology, emphasising its use in enhancing metabolic flexibility, reducing glucose variability, and fostering behavioural changes that promote healthier lifestyles. Special attention is given to the Vively app, an Australian digital health platform that leverages CGM data to provide personalised insights and recommendations to users. By integrating real-time glucose monitoring with tailored feedback, Vively helps individuals optimise diet, exercise, and recovery, and supports the prevention of metabolic diseases. The review also addresses the challenges associated with CGM use, including data interpretation, cost barriers, and accessibility issues, while exploring future directions for integrating CGM technology into personalised and preventive healthcare. The findings suggest that CGMs, supported by platforms like Vively, hold significant promise for transforming health management and improving long-term health outcomes in both diabetic and non-diabetic populations.

Introduction

Continuous Glucose Monitors (CGMs) have transformed the management of both type- 1 and type- 2 Diabetes, offering real-time insights into lifestyle behaviours and associated blood glucose levels. These devices, however, are now gaining traction among non-diabetic populations. Recent research highlights the potential benefits and applications of CGMs in these groups, from prevention to enhancing metabolic health and for facilitating lifestyle changes. This article explores the latest findings on the use of CGMs in both diabetic and non-diabetic individuals, based on recent studies and data.

Methodology

This literature review synthesises information from peer-reviewedjournals and digital health applications, including Nature Digital Medicine,Metabolism Clinical and Experimental, and data analysis from the Vivelyapp. The review aims to explore the evolving use of CGMs in non-diabeticpopulations and evaluate the benefits of integrating digital tools like Vivelyin supporting health outcomes.

Results

Understanding Continuous Glucose Monitors

CGMs are wearable devices that provide continuous, real-time glucose readings by measuring interstitial glucose levels through a sensor inserted under the skin. These readings are transmitted to a smartphone app, which enable the user to watch their glucose trends and fluctuations throughout the day and night.

The Shift Towards Metabolic Flexibility

1. Metabolic syndrome, obesity, type- 2 diabetes (T2D) and insulin resistance are on the rise over the past half a century, due to rapid and dramatic changes in dietary habits, movement patterns, sedentary past-times, increasing mental and work-related stress and poor sleep. These commons conditions which were previously referred to as western maladies, but now are becoming prevalent in developing countries as well. A diagnosis of metabolic syndrome brings with it, a 5 times greater chance of developing T2D and cardiovascular diseaseⁱ.
2. Metabolic in-flexibility is a broad term which is used to define a person’s reduced ability to respond to or adapt to changing metabolic demands and is commonly seen in people who are obese, insulin resistant, pre-diabetic and who have metabolic syndrome. The increasing prevalence of these conditions has spurred interest in using CGMs for non-diabetic individuals to help enhance education, insights, behaviour change and understanding of these conditions at an earlier stage. A study published in Nature Digital Medicine explored the use of CGMs in overweight and obese individuals, finding that real-time glucose monitoring can help identify dietary triggers and optimise meal timing to improve metabolic outcomesⁱⁱ. By providing immediate feedback on glucose levels, CGMs helped to guide the users towards healthier eating habits, potentially aiding weight loss and preventing metabolic diseases.
3. Glucose Variability (GV) is emerging as a key metric for oxidative stress triggers and cardiovascular disease (CVD) riskⁱⁱⁱ. It refers to the swings in blood glucose, including hypoglycaemic excursions and post-prandial increases. Although it is normal to have a level of glucose variability due to our innate circadian rhythms, excessive highs and lows of glucose trigger mitochondrial oxidative stress mechanisms, which put pressure on inflammatory pathways and nutritional reserves^v. High GV is associated with various micro and macro vascular complications in diabetes. It is also associated with increased mortality, independent of Hba1c . CGM technology is currently the only way to assess GV and add depth to the current gold standard metric of Hba1c.
   High GV is also associated with reduced patient psychological well-being and quality of life scores. Although the mechanism is not completely understood, there is increasing evidence to suggest that it is due to endothelial dysfunction, inflammation, and oxidative stress, which leads to vascular damage and atherosclerosis^vi.
4. CGM technology is emerging as a powerful tool for improving glucose control by providing real-time, continuous data on glucose levels. The Australian-based Vively app, has been developed to help a user to understand and improve their glucose control by providing interpreted insights based on their lifestyle choices and glucose fluctuations. The app offers a range of features, including data visualisation, personalised recommendations, educational resources and gamification to help the user understand their glucose patterns and make positive changes to their eating habits, their physical activity levels and other lifestyle variables.
5. Another use of CGMs is in understanding and optimising an athlete’s performance and fitness. By monitoring glucose levels during training and recovery, athletes can gain valuable insights into energy utilisation and nutritional needs. According to research published in Metabolism Clinical and Experimental, CGMs can help athletes modify their diet and training regimens to support optimal glucose levels, thereby enhancing performance and recovery^vii.
6. With nearly half ( 46.6%) of Australians suffering from at least one chronic disease^viii, facilitating lifestyle changes is at the core of  prevention and treatment. Real-time, personalised glucose insights have been shown to be a powerful motivator for lifestyle changes. One study highlighted in JMIR MHealth and UHealth showed that non-diabetic individuals using CGMs experienced increased awareness of their body's response to different foods and activities, which they were previously oblivious to^ix. This heightened awareness commonly led to healthier dietary choices and more consistent physical activity since they could see the immediate impact of their behaviours on their glucose levels.
7. Using a CGM can help the user to understand and manage glucose spikes. Research shows that both high levels and low glucose levels are associated with increased hunger, mood lability, fatigue and sleep impairment^x. Understanding which foods, exercise patterns and behaviours increase the risks of glucose irregularity, offers a person previously hidden insights into what personalised changes they could try, to support more regular glucose levels. This level of nuanced data has been previously unachievable until CGM.

Using a comprehensive program

Zahedani et al (2023) looked into the effectiveness of a digital health application integrating wearable data and behavioural patterns to improve metabolic health^xi. The study enrolled 2,217 people with varying glucose levels, including those within the normal range, those with pre-diabetes and T2D. The participants used the program for 28 days, logged food data, their physical activity and body weight via a smart-phone app and received personalised recommendation based on their goals, their preferences and their glycaemic patterns, as identified in the program. Users could interact with the app for an additional 2 months after the CGM stopped collecting data. The results showed an increase in healthy eating habits, reduced caloric intake, a decrease in body weight, especially in those who were over-weight or obese, an increase in protein and a reduction in simple carbohydrates to calorie ratio, an increase in fibre intake and healthy fats. It was deduced that using this technology can be a valuable tool for T2D prevention and treatment and in the optimisation of healthy lifestyle.

The Vively app, as designed in Australia, follows similar principles to the smart-phone app used in this research. A recent study analysed data from Vively app users, including those with T2D, pre-diabetes and normal glucose levels^xii. Participants were given a CGM every 3 months and the option to buy additional sensors. The Vively app provided support and guidance on the use of CGM as well as offering the user’s health care providers access to their data.

The analysed data came from 4,332 users, using 8,783 sensors over the study time. The metrics assessed were estimated HbA1c, time in target range, number of spikes, glucose variability and BMI.

The analysis revealed:

1. Improved Glucose Control: Across users with diabetes and prediabetes, there were significant improvements in key glucose control metrics, including reductions in average blood glucose, HbA1c levels, glucose variability, and an increase in time in range (TIR).
2. Reduction in Glucose Spikes: CGM use was effective in reducing glucose spikes across all users, including those with normal glucose levels, highlighting its role in helping users maintain more stable blood sugar levels.
3. Greater Improvement with Extended CGM Use: Users with diabetes who used CGM for over six months showed more substantial improvements in glucose metrics, especially HbA1c, demonstrating the long-term benefits of consistent CGM usage.
4. Positive BMI Changes: There were improvements in BMI for users with diabetes, prediabetes, and normal glucose levels, showcasing the system’s potential to aid in weight management as part of overall metabolic health improvement.
5. Impact of Practitioner Support: Users who worked with healthcare professionals experienced a higher rate of improvement (55.83%), suggesting that professional support enhances the effectiveness of CGM technology and the Vively app in managing metabolic health. The study did highlight some potential improvements to the Vively app. The data showed the predominate users to be both aged between 31-60 years with a significant predominance of females. The reasons for this are not fully understood, but it may lead to opportunities to look to engage older people, and help them become familiar with the technology. The female predominance may have to do with health-seeking behaviour, body-image pressure, diet culture or marketing. The reasons for this may also require further investigation.

Mental Health and Behavioural Insights

Sub-acute inflammation is now a recognised causative and or additive factor in some people with chronic depression, one of the reasons for this is often due to poor diet, poor lifestyle habits and glucose dysregulation driving inflammation, oxidative stress and mitochondrial dysfunction.  Emerging research suggests a link between glucose fluctuations and mental health issues such as depression. A recent study in Frontiers in Psychiatry investigated the relationship between glucose levels and mood in non-diabetic individuals, finding that significant glucose variability was associated with a higher risk of negative mood and poor cognitive function^xiii. By using CGMs, individuals can gain insights into glucose variability and potentially also gain access an understanding into how their glucose levels correlate with their emotional well-being, lifestyle habits, dietary choices, sleep and stress. The latter, consequently, may provide insights and opportunities into better lifestyle choices and exercise activities.

Early Detection of Pre-diabetes

Currently, a CGM is not a diagnostic tool; however, a study published in June 2023 could change all that. A group of mathematicians have teamed up to investigate the accuracy of a new homeostatic model that could be used alongside the data of a CGM to increase the accuracy of early detection of pre-diabetes, a common condition which often goes un-diagnosed. The CGM data of 380 participants was compared to regular medical classifications. When applying the homeostatic mathematical model, they found it to have equal sensitivity and specificity to the gold standard Hba1c and better than the oral glucose tolerance test, paving the way for a whole new metric of dysfunctional glycemic control^xiv.

Long-Term Health Implications

Insulin resistance tends to precede glucose impairment by about 10-15 years, but it is not routinely looked for in modern general practice and is rarely highlighted by doctors.  Addressing hyper-insulinemia, before glucose becomes impaired, is ideal and optimal when it comes to prevention. PubMedZhedani et al. analysed the long-term health implications of using CGMs in non-diabetic individuals^xv. Their research found that consistent use of CGMs can help detect early signs of insulin resistance and other metabolic irregularities, allowing for early intervention and prevention of more serious conditions like T2D^xvi. Of the 665 participants, 15% had glucose excursions into the diabetic range and 36% of them into the pre-diabetic range. It also showed a significant number of users positively increase their time within normal range, by changing their lifestyle patterns, whilst using the CGM. Putting in place behaviour changes when identifying glucose excursions shows great potential for using a CGM as part of a comprehensive prevention plan; however, more research is needed to evaluate the longer-term impacts of preventative measures such as these.

Technological Advances and Accessibility

The expansion of CGM use among non-diabetics is also driven by technological advancements and increased accessibility. Modern CGMs are more user-friendly, affordable, and integrated with smartphone apps, making them appealing to a broader audience. Additionally, the data generated by CGMs can be shared with healthcare providers, such as through The Vively App, enabling more personalised and proactive health management and eliminating the risk of information overload, confusion and health anxiety.

The ease and cost effectiveness of continuous glucose monitoring applications such as Vively opens the opportunity for use in more novel scenarios, such as in women with gestational diabetes, menopausal women who are at increased risk of metabolic syndrome, those on high dose steroids who are at risk of developing diabetic changes, and those in hospital with stress induced hyperglycaemic changes. Use of a CGM during these challenging times may provide a deeper understanding on how to implement safe and effective lifestyle advice and treatments which are targeted, personalised and adaptable.

Research shows that even intermittent use can provide actionable glucose insights to not only the user but to their health care providers and paves the way for regular intermittent use, alongside medication reviews, lifestyle coaching and other preventative measures^xvii.

Potential Challenges and Considerations

While the benefits of CGMs for non-diabetic individuals are promising, several challenges and considerations remain:

1. Data Interpretation: Interpreting CGM data requires a certain level of knowledge and understanding. Without proper guidance, users may misinterpret glucose fluctuations and make suboptimal health decisions. This highlights the importance of sharing the data, education and support from trained healthcare professionals.
2. Cost and Accessibility: Although CGMs are becoming more affordable, cost can still be a barrier for some individuals, as out-of-pocket expenses may deter potential users. We know that there is a health divide in our country, and those in the lower socio-economic group have proportionately higher rates of metabolic disease and T2D^xviii. Until CGMs are government funded, we run the risk of further exacerbating this health divide.
3. Technology Accessibility and Targeted Groups: The recent Vively user data study revealed a gender disparity, with a higher proportion of female users as compared to males^xix. Such differences may be due to differences in health seeking behaviour, awareness of technology, use of medical consultations and body-image pressures. The data also showed a predominance in younger age groups, with the majority falling into the 31-64 year age group, this suggests there may be a need for more targeted features. Older Australians may face barriers to adopting CGM technology, be less familiar, more timid or less comfortable with mobile apps and wearable data. The learning curve associated with these newer technologies may be worth considering when designing new technological features and accessibility.
4. Privacy and Data Security: The continuous data collection by CGMs raises concerns about privacy and data security. Ensuring that user data is protected and used ethically is crucial as CGM usage expansion.

Discussion

The potential of CGMs in non-diabetic populations looks promising, with ongoing research and technological innovations paving the way for broader applications, especially for prevention and more novel treatment groups.

Potential future directions include:

1. Personalised Nutrition: CGMs could play a central role in personalised nutrition plans, helping individuals optimise their diets based on real-time glucose data. This approach could help to prevent metabolic disorders, cardio-vascular disease, unhealthy weight gain, depression and promote overall health and well-being.
2. Integration with Other Health Metrics: by combining CGM data with other health metrics, such as heart rate, heart-rate variability, waist measurement, blood pressure, sleep assessments and activity levels, could provide health care professionals with a more comprehensive and actionable view of an individual's health. This integrated approach could enhance personalised health recommendations and interventions, increase health literacy and support a more empowered and prevention orientated health care approach.
3. Preventive Healthcare: By identifying early signs of glucose dysregulation, insulin resistance, pre-diabetes and glucose variability: CGMs could become a valuable tool in preventive healthcare. Early intervention based on CGM data might prevent the progression of metabolic diseases, cardiovascular disease and improve long-term health outcomes and health-span.

Conclusion

The use of CGMs is fast expanding beyond the realm of diabetes management, offering numerous benefits for non-diabetic individuals. From enhancing metabolic health and athletic performance to facilitating lifestyle changes, fitness and improving mental well-being, CGMs have the potential to transform how we approach health and wellness. As technology advances and accessibility improves, CGMs may become an integral part of preventive healthcare and personalised medicine, helping people lead healthier, more informed lives.

ⁱ Regufe VMG, Pinto CMCB, Perez PMVHC. Metabolic syndrome in type 2 diabetic patients: a review of current evidence. Porto Biomed J. 2020 Dec 3;5(6):e101.

ⁱⁱ Zahedani, A.D., McLaughlin, T., Veluvali, A. et al. Digital health application integrating wearable data and behavioral patterns improves metabolic health. npj Digit. Med. 6, 216 (2023).

ⁱⁱⁱ Suh S, Kim JH. Glycemic Variability: How Do We Measure It and Why Is It Important? Diabetes Metab J. 2015 Aug;39(4):273-82.

^iv Zhang Z, Huang Q, Zhao D, Lian F, Li X, Qi W. The impact of oxidative stress-induced mitochondrial dysfunction on diabetic microvascular complications. Front Endocrinol (Lausanne). 2023 Feb 7;14:1112363. doi: 10.3389/fendo.2023.1112363. PMID: 36824356; PMCID: PMC9941188

^v Martinez M, Santamarina J, Pavesi A, Musso C, Umpierrez GE. Glycemic variability and cardiovascular disease in patients with type 2 diabetes. BMJ Open Diabetes Res Care. 2021 Mar;9(1):e002032.

^vi Martinez M, Santamarina J, Pavesi A, Musso C, Umpierrez GE. Glycemic variability and cardiovascular disease in patients with type 2 diabetes. BMJ Open Diabetes Res Care. 2021 Mar;9(1):e002032.

^vii Jarvis, Paul R.E. et al. Continuous glucose monitoring in a healthy population: understanding the post-prandial glycemic response in individuals without diabetes mellitus. 2023 Sep. Metabolism - Clinical and Experimental, Volume 146, 155640

^viii Australian Bureau of Statistics (ABS). Health Conditions Prevalence for 2020-2. 2022 Mar. https://www.abs.gov.au/statistics/health/health-conditions-and-risks/health-conditions-prevalence/latest-release

^ix Ehrhardt N, Al Zaghal E. Continuous Glucose Monitoring As a Behavior Modification Tool. Clin Diabetes. 2020 Apr;38(2):126-131.

^x Fritschi C, Park C, Quinn L, Collins EG. Real-Time Associations Between Glucose Levels and Fatigue in Type 2 Diabetes: Sex and Time Effects. Biol Res Nurs. 2020 Apr;22(2):197-204.

^xi Zahedani, A.D., McLaughlin, T., Veluvali, A. et al. Digital health application integrating wearable data and behavioral patterns improves metabolic health. npj Digit. Med. 6, 216 (2023).

^xii Vively Health. Enhancing Glucose Management with Machine Learning: An Analysis of Vively’s Comprehensive Metabolic Health Solution. 2024 Oct. https://www.vively.com.au/post/enhancing-glucose-management-with-machine-learning-an-analysis-of-vivelys-comprehensive-metabolic-health-solution

^xiii Mishra S, Singh A, Rajotiya S, Singh P et al. Exploring the risk of glycemic variability in non-diabetic depressive individuals: a cross-sectional GlyDep pilot study. 2023. doi: 10.3389/fpsyt.2023.1196866

^xiv Jaycee M. Kaufman, Lennaert van Veen, Yan Fossat, Screening for Impaired Glucose Homeostasis: A Novel Metric of Glycemic Control, Mayo Clinic Proceedings: Digital Health, Volume 1, Issue 2, 2023, ISSN 2949-7612

^xv Zahedani, A.D., McLaughlin, T., Veluvali, A. et al. Digital health application integrating wearable data and behavioral patterns improves metabolic health. npj Digit. Med. 6, 216 (2023). https://doi.org/10.1038/s41746-023-00956-y

^xvi Dehghani Zahedani A, Shariat Torbaghan S, Rahili S, Karlin K, Scilley D, Thakkar R, Saberi M, Hashemi N, Perelman D, Aghaeepour N, McLaughlin T, Snyder MP. Improvement in Glucose Regulation Using a Digital Tracker and Continuous Glucose Monitoring in Healthy Adults and Those with Type 2 Diabetes. Diabetes Ther. 2021 Jul;12(7):1871-1886.

^xvii Klupa T, Czupryniak L, Dzida G, Fichna P, Jarosz-Chobot P, Gumprecht J, Mysliwiec M, Szadkowska A, Bomba-Opon D, Czajkowski K, Malecki MT, Zozulinska-Ziolkiewicz DA. Expanding the Role of Continuous Glucose Monitoring in Modern Diabetes Care Beyond Type 1 Disease. Diabetes Ther. 2023 Aug;14(8):1241-1266. doi: 10.1007/s13300-023-01431-3. Epub 2023 Jun 16.

^xviii Carroll SJ, Dale MJ, Niyonsenga T, Taylor AW, Daniel M. Associations between area socioeconomic status, individual mental health, physical activity, diet and change in cardiometabolic risk amongst a cohort of Australian adults: A longitudinal path analysis. PLoS One. 2020 May 29;15(5):e0233793.

^xix Vively Health. Enhancing Glucose Management with Machine Learning: An Analysis of Vively’s Comprehensive Metabolic Health Solution. 2024 Oct. https://www.vively.com.au/post/enhancing-glucose-management-with-machine-learning-an-analysis-of-vivelys-comprehensive-metabolic-health-solution