Eight Sleep & Span are joining forces – read the announcement

Deep dive into glucose variability for non-diabetics

Adam Bataineh, MD

Longevity MD


Quick read

  • Traditional measures of blood glucose do not capture fluctuations in blood glucose over time or glucose variability.
  • Glucose variability is the fluctuations in glucose over a period of time from its baseline level and is best measured by a CGM.
  • Increased glucose variability is an independent risk factor for worse outcomes in people with metabolic syndrome and diabetes even with normal HbA1c
  • Increased glucose variability has been shown to damage blood vessels and increased oxidative stress in cells.
  • Steeper dips in blood glucose are associated with feeling more hungry and eating more.
  • Glucose variability might be a tool to catch metabolic dysfunction before it's too late.
  • Key metrics to follow are average blood glucose, variation from that average, frequency and amplitude of blood glucose peaks.

The current gold standard for measuring blood glucose (sugar) levels is a test called HbA1c (glycated hemoglobin) along with fasting blood glucose and glucose tolerance tests or GTT (how fast blood glucose rises after ingesting a certain amount of sugar). HbA1c reflects average blood glucose levels over the previous two to three months. Blood glucose chemically links to hemoglobin producing glycated hemoglobin, therefore, the higher the average blood glucose the higher HbA1c.

These tests are limited to providing us with either a snapshot of blood glucose or an overall average. This is why glucose variability has recently emerged as a new and interesting metric for blood glucose monitoring. This is not only true in individuals with diabetes but also in people who may have impairment ifi glucose metabolism or even if those who simply want to avoid developing these conditions. A 2018 study, measured glucose variability in participants with normal blood glucose levels by standard measurements. 15% of them showed severe glucose variability reaching pre-diabetic ranges while 2% reached diabetic ranges despite normal HbA1c levels.

HbA1c and traditional measures of blood glucose might catch metabolic issues too late.

What is glucose variability?

Glucose variability represents fluctuations in glucose over a period of time from its baseline. Glucose variability is difficult to measure but the advent of continuous glucose monitoring or CGM has made it much easier.

There are two types of glucose variability: 

  • Visit-to-visit or long term: the variability in fasting blood glucose or HbA1c from baseline and subsequent clinic visits. This measures long term variability usually in years. 
  • Short term variability: within-day (intra-day) or day-to-day (inter-day) variations. Measured by using a CGM. This is the type I focus on in this article.

There are multiple proposed ways of measuring glucose variability. A popular measure is Standard deviation (SD) which represents how much glucose levels fluctuate over time from a given average. SD is often reflected in research and in practice by %CV or coefficient of variation (which is SD divided by the mean). The more stable the levels are over time, the lower CV is and therefore, glucose variability. 

Glucose variability is obviously increased mostly after meals. The amount of carbohydrates in a food and its glycaemic index play the biggest role. Glucose variability can also be influenced by hormonal function, stress, illness and exercise. I will be writing a separate article on the relationship between glucose and exercise.

What is normal glucose variability?

There is no consensus on what a good target for glucose variability should be. A normal %CV in healthy individuals is below 20. This means aiming for an SD that is less than 20% of the mean glucose. For instance, for someone with a mean glucose of 140 mg/dl, the target SD is 28 mg/dl or less.

Why is increased glucose variability bad for us?

Increased risk of metabolic dysfunction

Individuals with diabetes show increased glucose variability when compared to individuals without the disease. We also observe increased glucose variability with age even in individuals without diabetes. Increased glucose variability has also been found to be an independent predictor of increased complications in diabetics and all cause mortality. It has also been linked to insulin resistance and increased levels of inflammation. 

Furthermore, individuals who end up developing diabetes, show an increased risk of cardiovascular disease even before the appearance of diabetes. This is not surprising as diabetes and increased risk of cardiovascular disease are part of the same picture of metabolic syndrome which is a term used to describe a cluster of conditions often seen together. These include impaired glucose metabolism, deranged cardiac risk markers, central obesity and high blood pressure. A study looking at glucose variability using a continuous glucose monitor (CGM) in three groups: subjects with metabolic syndrome, subjects with both diabetes and metabolic syndrome and subjects with neither.

There was a clear increase in glucose variability between the group with no medical conditions and the group with metabolic syndrome. There was a greater increase among the group with both diabetes and metabolic syndrome. This was true despite there being no similar difference in average glucose between the groups. Interestingly, some of the participants with metabolic syndrome showed a higher glucose variability than the diabetes plus metabolic syndrome group. This clearly suggests that there is a continuum of increased glucose variability which gets worse with higher degrees of  metabolic dysregulation.

Intermittent glucose spikes can cause damage to cells and tissues

Intermittent exposure to high blood glucose, in comparison to constant exposure, has been shown to have deleterious effects on cells and tissues in experimental studies. Rapid fluctuations in glucose levels increase the production of superoxide radicals by mitochondria in cells. This increases oxidative stress and mitochondrial damage which have been linked to many age-related diseases. Studies measuring the effect of glucose infusions into otherwise healthy individuals showed that rapid rises in glucose can directly damage blood vessels by increasing adhesion of inflammatory molecules and immune cells to the lining of blood vessels. This is one of the mechanisms underlying atherosclerosis; the main cause of heart disease.

Steep dips in blood glucose make us more hungry

Studies have suggested that glucose variability can be used as a predictor of dips in blood glucose levels. In individuals with diabetes, episodes of hypoglycemia often follow fluctuations in blood glucose. A recent study published in Nature metabolism looked at glucose dips after meals in otherwise healthy individuals using CGMs. Interestingly, dips in blood glucose levels were found to be a strong predictor of subsequent hunger levels and increased energy intake 2-3 hours after the dip. The steeper the dip the more hungry we are afterwards. This was a stronger predictor than peak glucose level or overall glucose levels (area under the curve).

An early warning sign

Although It is normal to have some excursions in blood glucose after meals, worsening glucose variability may be an early sign of metabolic dysfunction. There are no large trials of CGM use in non-diabetic individuals looking at long term health outcomes but the evidence does suggest that even in non-diabetics, it may be useful to control the following three metrics of blood glucose if we want to maintain our metabolic health in the long run:

  • Average blood glucose?
  • How much does it vary from the average over time?
  • How high are the peaks in blood glucose?
  • How often do you have them?

Nathan DM, Genuth S, Lachin J, Cleary P, Crofford O, Davis M, et al. The effect of intensive treatment of diabetes on the development and progression of  long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993 Sep;329(14):977–86. 

Hall H, Perelman D, Breschi A, Limcaoco P, Kellogg R, McLaughlin T, et al. Glucotypes reveal new patterns of glucose dysregulation. PLoS Biol. 2018 Jul;16(7):e2005143. 

DeVries JH. Glucose variability: where it is important and how to measure it. Diabetes. 2013 May;62(5):1405–8. 

Gorst C, Kwok CS, Aslam S, Buchan I, Kontopantelis E, Myint PK, et al. Long-term Glycemic Variability and Risk of Adverse Outcomes: A Systematic Review and Meta-analysis. Diabetes Care [Internet]. 2015 Dec 1;38(12):2354 LP – 2369. Available from: http://care.diabetesjournals.org/content/38/12/2354.abstract

Brownlee M. The pathobiology of diabetic complications: a unifying mechanism. Vol. 54, Diabetes. United States; 2005. p. 1615–25. 

Glycaemic variability and inflammation in subjects with metabolic syndrome

Silvio Buscemi et al Acta Diabetol 2009 Mar;46(1):55-61. doi: 10.1007/s00592-008-0061-8. Epub 2008 Sep 26.

Buscemi, S., Verga, S., Cottone, S. et al. Glycaemic variability and inflammation in subjects with metabolic syndrome. Acta Diabetol 46, 55–61 (2009). https://doi.org/10.1007/s00592-008-0061-8

Wyatt, P., Berry, S.E., Finlayson, G. et al. Postprandial glycaemic dips predict appetite and energy intake in healthy individuals. Nat Metab 3, 523–529 (2021).

Esposito K, Nappo F, Marfella R, Giugliano G, Giugliano F, Ciotola M, et al. Inflammatory cytokine concentrations are acutely increased by hyperglycemia in  humans: role of oxidative stress. Circulation. 2002 Oct;106(16):2067–72. 

Ceriello A, Ihnat MA. “Glycaemic variability”: a new therapeutic challenge in diabetes and the critical  care setting. Diabet Med. 2010 Aug;27(8):862–7. 

Cox DJ, Kovatchev BP, Julian DM, Gonder-Frederick LA, Polonsky WH, Schlundt DG, et al. Frequency of severe hypoglycemia in insulin-dependent diabetes mellitus can be  predicted from self-monitoring blood glucose data. J Clin Endocrinol Metab. 1994 Dec;79(6):1659–62. 

Bancks MP, Carnethon MR, Jacobs DRJ, Launer LJ, Reis JP, Schreiner PJ, et al. Fasting Glucose Variability in Young Adulthood and Cognitive Function in Middle Age:  The Coronary Artery Risk Development in Young Adults (CARDIA) Study. Diabetes Care. 2018 Dec;41(12):2579–85. 

November 15, 2021
Explore Span in...
Span app