Providing independent clinical excellence since 2005
Posted on Sunday April 21, 2024 in Health Screening
An article by Dr Edward Leatham, Consultant Cardiologist. The opinions expressed in this article are entirely mine and not those of SCVC or the consensus view.
First published April 2024, updated Sept 2024, with the addition of Current Glucose Profile (CGP) and some clarification on how we assess ‘Glucotype’.
In today’s data-driven world, especially in the realm of healthcare, the more data patients receive and understand, the better their health outcomes tend to be. For individuals conscious about their health, having access to various health metrics such as blood pressure, heart rate, body weight, body fat percentage, and notably, continuous glucose monitor (CGM) results, empowers them to make informed decisions toward healthy living and diet choices.
Continuous glucose monitors have seen a sharp increase in usage, with devices now available even in supermarkets. This accessibility underscores the importance for both physicians and patients to grasp the patterns these devices reveal, which can differentiate between healthy and potentially unhealthy conditions.
Just as a car’s tachometer displays varying revolutions per minute (RPMs) based on the incline and the desired speed, a glucose monitor provides detailed data on blood sugar levels in real time. It may be completely normal for glucose to bounce around, within certain limits. These data, while they may be within a normal range most of the time probably requires interpretation to identify when it may indicate a health issue. This point is crucial for non diabetic patients who use CGMs — especially as these individuals typically represent the largest group of CGM users.
Emerging research suggests that high variability in glucose levels, marked by rapid increases or decreases, could indicate an unhealthy metabolism. This variability may signal attenuated insulin regulation and uptake, which could lead to insulin resistance and increase the risk of developing diabetes. Though high glucose variability has been associated with a greater risk of cardiovascular events, there are currently no long-term studies specifically using CGMs to confirm this in non-diabetic patients.
Between 2011 and 2018, researchers at Stanford University observed that more than half of non-diabetics who consumed standard breakfast cereal experienced significant variations in blood glucose levels when monitored by continuous glucose monitors (CGMs) [1,2]. This discovery led to the introduction of the term *glucotype*, used to describe subtypes of blood glucose patterns based on variability rather than focusing solely on spikes outside the normal range. While the term has gained traction, no universally accepted definition of *glucotype* exists yet. This makes it important to define various glucose profiles, providing both patients and healthcare providers with a better understanding of how an individual’s glucose response compares to others.
At SCVC, based on our initial six months of metabolic function tests, we observed a wide range of glucose profiles among patients. During a 1-2 week metabolic health assessment, we monitored food intake, sleep, and physical activity through diaries, along with laboratory tests, such as HbA1c, fasting blood glucose, and glucose tolerance tests. Each patient was placed into one of three groups, referred to as *current glucose profiles* (CGP), based on their glucose curve. These profiles helped us classify patients into one of five glucotypes (I-V), with each patient’s position on the glucose response spectrum determined by their response to dietary carbohydrates.
The primary factor we observed was the frequency and duration of glucose spikes above the widely accepted range of 3.9-7.8 mmol/L. Glucose variability metrics also showed minor differences. We assigned each individual’s *current glucose profile* based on their CGM results at the time of testing, and their glucotype was determined by the extent and duration of glucose excursions (spikes) in response to food, especially carbohydrates. To further assess potential impact of dysregulated glucose, we calculated a new, unpublished metric called the *oxidative stress index*. This index is similar to the well-established *time out of range* metric but instead measures the average percentage of time an individual’s blood glucose exceeds 7.8 and 10 mmol/L.
While an individual’s glucotype seems to be largely influenced by genetic factors, the *current glucose profile* is more modifiable through lifestyle changes and dietary choices. For instance, using CGM results, we can describe the glucose patterns of a person’s everyday life with the term *current glucose profile*. However, *glucotype* is typically determined after observing how an individual responds to high-glycaemic foods, a method also used in tools like the Zoe Health App, where responses to a standardised high-carb food (e.g., a muffin) are monitored. This approach is especially relevant for patients who are pre-diabetic or have dysregulated glucose levels (glucotypes III-V) and have already adjusted their diet and lifestyle. For example, a patient with glucotype III or IV—who would typically have large glucose spikes after consuming high-glycaemic foods like white bread—could show an intermediate or even healthy CGP during testing if they were following a low-carbohydrate diet.
It remains unclear whether glucotype is an innate, genetically determined trait that is difficult to change through lifestyle alone. However, some evidence suggests that certain individuals are genetically predisposed to high glucose responses when consuming carbohydrates, while others have genes that allow them to better manage glucose levels, avoiding spikes above 7.8 mmol/L regardless of what they eat. This genetic predisposition can influence a person’s ability to maintain healthy glucose levels, and understanding these differences could help tailor individual dietary recommendations more effectively.
In summary, while *glucotype* may reflect an individual’s genetically determined response to carbohydrates, their *current glucose profile* is a dynamic measure that can change with lifestyle modifications, such as diet and physical activity. By differentiating between the two, medical teams can offer more personalised advice and treatment, helping patients manage their blood sugar more effectively based on both inherent factors and modifiable behaviours.
Table to show 3 current glucose profiles (CGP).
| Type | Status | CGM | Clinician Comment |
| A | Healthy CGP | Most glucose measurements (apart from exercise induced peaks) are below 7.8 mmol/L (<140 mg/dL). Some hypoglycaemic readings below 3.9 mmol/L can be seen. | The healthiest CGP to shoot for, whichever glucotype ‘hand’ you have been dealt. |
| B | Intermediate | Most glucose measurements are below 7.8 mmol/L (<140 mg/dL). There are, on average, less than 2 glucose excursions above these limits (lasting <30 min) each day. These appear as ‘spikes’ on the weekly graph. HbA1c is typically normal. There may also be high glucose variability with rapid movements of glucose both up or down. | Believed to be healthier than Type C, but not yet decisively proven to be ‘unhealthy’; there is a consensus that lifestyle changes and dietary interventions are indicated to improve long term health. |
| C | Potentially or actually Pre-diabetic | Multiple (on average >2) glucose levels transiently (ie ‘spiking’) exceeding 7.8 mmol/L (140 mg/dL) each day and regularly exceeding 10 mmol/L. There may also be high glucose variability with rapid movements of glucose both up or down. Baseline daytime, sleep and fasting glucose may also be raised. | This CGP is likely to lead onto pre-diabetes and or Type 2 Diabetes and there is more evidence that interventions to prevent glucose highs are worthwhile. |
Table to show the spectrum of individual ‘glucotypes’ as a guide to how patients respond to intake of carbohydrates.
| Glucose Type | Status | CGM | Clinician Comment |
| I | Carbohydrate Adapted | Following carbohydrate intake, all glucose measurements (apart from exercise induced peaks) are below 7.8 mmol/L (<140 mg/dL). Some hypoglycaemic readings below 3.9 mmol/L can be seen. | This glucotype is unlikely to progress to pre diabetic stage or type 2 diabetes anytime soon. Most people under 20 years of age and a proportion aged 20-40 are probably in this group, presumably due to metabolic processes and genes, adapted to higher carbohydrate food intake. It should be noted that there may be a tendency for some people in this group to convert glucose to adipose more efficiently – so any surplus in carbohydrate leads to prompt weight gain from central adipose -triggered by genetic adaptations that occured during bygone eras of famine and ice age. |
| II | Mildly dysregulated glucose axis | After high glycaemic food intake, most glucose measurements are still below 7.8 mmol/L (<140 mg/dL) and do not exceed 10 mmol/L. Occasional excursions >7.8 mmol/L in response to high glycaemic foods are observed, eg during stress. | It is not known whether this glucotype is truly abnormal- it may be a variant of normal and it is usually associated with HbA1c in the normal range. Changes to dietary intake to avoid foods that trigger glucose excursions over 7.8 mmol/L might be a sensible option, particularly if coronary artery disease or raised BMI are present, until more is known about this group. |
| III | Moderately dysregulated glucose axis | After intake of high glycaemic food or drinks, glucose measurements surge over 7.8 mmol/L (140 mg/dL) and sometimes exceed 10 mmol/L (>180 mg/dL). These appear as ‘spikes’ on the weekly graph. HbA1c is typically normal. There may also be high glucose variability with rapid movements of glucose both up or down. | It is not known how damaging this glucotype is. It is possible that glucose highs may produce oxidative stress and inflammation, and high glucose variability is associated with future cardiovascular disease. Changes to dietary intake to avoid foods that trigger glucose excursions over 7.8 mmol/L seems a sensible recommendation, particularly if coronary artery disease or raised BMI are present, until more is known about this group. |
| IV | Dysregulated glucose axis | After even low glycaemic index food intake, glucose measurements transiently (ie ‘spiking’) exceed 7.8 mmol/L (140 mg/dL) and/or occasionally exceed 10 mmol/L. There may also be high glucose variability with rapid movements of glucose both up or down. | Associated with ‘prediabetes’ and patient has a higher risk of developing ‘prediabetes’ or full blown type 2 diabetes mellitus. Lifestyle and dietary changes recommended with consideration of medication, particularly if coronary artery disease is present. |
| V | Highly dysregulated glucose axis | After intake of any carbohydrate food or drink, glucose levels exceed 7.8 mmol/L (140 mg/dL) each day and regularly exceeding 10 mmol/L. There may also be high glucose variability with rapid movements of glucose both up or down. Baseline daytime, sleep and fasting glucose may also be raised. | Usually associated with raised HbA1c ‘re-diabetes’ and higher risk of developing ‘pre-diabetes’ or full blown type 2 diabetes mellitis; lifestyle and dietary changes are recommended with consideration of medication, particularly if coronary artery disease has been detected. |
Glucose type weight and adipose status
As glucotype seems to be largely ‘innate’ and independent to BMI and distribution of adipose, which are both important modifiable risk factors for heart disease, we found it helpful for referring physicians to sub-classify each glucose type according to BMI and extent /distribution of body fat, measured by hip: waist ratio, waist dimension, neck circumference and UK collar size (in men). Our objective was to ensure we did not overlook the negative health impact of high adipose levels that can be present in those patients with healthy looking glucose profiles.
BMI and adipose distribution subtypes
We assess adipose distribution and extent using standard anthropology measures such as BMI, Hip and height to waist Ratio (HWR), neck circumference.
| Subtype | Description | Associated features | Clinician Comment |
| A | Underweight | Low BMI with or without unexplained weight loss | Large population studies have shown that people below their ideal weight have worse outcomes than those in healthy range. It is not known whether low body weight is linked to disease processes or whether low weight is a risk factor for developing diseases. |
| B | Healthy |
| Large population studies have shown that people who are in the ideal weight and BMI zone have better outcomes than those in higher or lower weight/BMI categories. |
| C | Overweight |
| People who are in overweight BMI zone have worse outcomes than those in healthy BMI range . |
| D | Obese |
| Obese patients do not always have high coronary risk however do have greatly increased risk of atrial fibrillation, raised blood pressure and non cardiac issues including pulmonary embolism, cancer and arthritis. |
While awaiting more definitive trials, it’s valuable to observe and analyse the range of CGM results seen in various patient groups. In some individuals, a relatively narrow glucose range—typically between 3.9 and 7.8 mmol/L (72 to 140 mg/dL)—is seen. This range seems to indicate healthy responses to foods, including those high in glycaemic index. We observed non diabetic patients with either early or advanced coronary heart disease often have glucose spikes exceeding 7.8 mmol/L, potentially presenting a different metabolic health profile that requires closer medical attention. For those patients with coronary artery disease or raised coronary fat attenuation index, it raises the intriguing possibility that these glucose spikes and/ or high glucose variability may be contributing to their coronary inflammation. Due to widespread use of CGMs in lifestyle apps such as Zoe and Veri there are many reports that people with glucose spikes on CGM in response to food intake can lose significant amounts of body fat, by altering their food intake to minimise glucose spikes. However the long term effectiveness of CGM-guided food choices has yet to be confirmed.
Until we see long term trials to justify more definite answers to this question, we simply cannot know for sure, however it is known that there is an optimum BMI range – below and above which health issues are more likely to arise, and we also have evolving data suggesting that glucose variability and glycaemic responses exceeding 7.8 mmol / lit are unhealthy, so it seems reasonable to assume that the healthiest glycotype/ subtype is IB (ie flat glucose curve with healthy BMI) and the best CGP to shoot for is type A – where CGM measurements show glucose excursions between 3.9 and 7.8 mmol/L, with infrequent glucose values exceeding 7.8 mmol/L per day and none over 10 mmol/L.
Currently, the absence of rigorous, controlled trials limits the ability of physicians to recommend specific interventions for patients with “unhealthy” CGM profiles. Until more is known, it’s advisable for patients to adjust their lifestyles and dietary habits to help manage and potentially reduce high glucose levels.
To aid patients in navigating their CGM results, it’s helpful to see examples of different glucose patterns. To act as a guide here are 5 examples of glucose monitor results presented in a standardised graphical format- where the glucose levels that are believed to be important are shown as coloured lines, the implication being that the ideal profile and CGP might be where glucose values excursions fall between the green (7.8 mmol/L) and red (3.9 mmol/L) lines. In these time/glucose plots, individual glucose measurements are shown as coloured dots- healthy values depicted by green dots and high values in red, yellow or amber.
Type 1: Carbohydrate Adapted’ glucose type – a healthy or Type A CGP: whatever food or sugars are consumed, the blood glucose does not rise above 7.8 mmol/L.
Type II: potentially unhealthy profile: an occasional excursion over 7.8 mmol/L: less than 1 transient glucose excursion over 7.8mmol/L each day
Type III: moderately unhealthy, (and an intermediate / Type B CGP): in this example a patient with know coronary heart disease who is not aware of any glucose issues, has a normal HbA1c, however has dysregulated glucose with 2 or more excursions in blood glucose over 7.8 mmol/L each day ( referred to as ‘unhealthy spikes’). NB colour coding is different in this older graph – as with red depicts those in range 7.8-10 mmol/L.
Glucotype IV/ Type C CGP – a patient with prior stents taking statins for 5 years required more stents despite a low LDL taking statins. His glucose is very dysregulated with rapid movements (creating high glucose variability). NB colour coding is different in this older graph – as red depicts those values in range 7.8-10 mmol/L. His HbA1c was found to be in the prediabetic range, however the patient and his GP were not aware of the importance of glycaemic control in secondary prevention.
Glucotype V: an example of pre diabetic patient where blood sugar is raised over 10 mmol/L for a significant proportion of a week. The baseline or fasting glucose is also raised.
It’s important to note that occasional glucose spikes are not necessarily harmful. Moderation remains key, and for those with frequent spikes—particularly those with early signs of heart disease—avoiding high glycaemic foods and mitigating spikes through dietary strategies like consuming high-fiber, water-rich, or acidic foods before meals, may be beneficial.
Continuous glucose monitors are a powerful tool for managing health, offering real-time insights into glucose levels that can help guide dietary and lifestyle decisions. As technology advances and more research becomes available, the potential of CGMs to support disease prevention and management will likely become even more significant. Until then, a balanced approach to diet and health, informed by CGM data, appears to be a prudent strategy for those seeking to optimize their well-being.
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