• Apr 2024

Why wear a continuous glucose monitor if you don’t have diabetes?

Why wear a continuous glucose monitor if you don’t have diabetes?
  • Continuous glucose monitors (CGMs) have historically been used by people with diabetes to help monitor and manage their glucose (blood sugar) levels. 
  • Emerging research has shown a number of health benefits of limiting glucose spikes, which can be monitored by using a CGM, even if you don't live with diabetes. 
  • A CGM like Lingo can help you glean insights into your personalised glucose response to food, activities, and other lifestyle habits to help you make the best choices for your health and overall well-being. 

Continuous glucose monitors (CGMs) are wearable, minimally invasive devices that measure glucose levels for days at a time. Historically, these devices have been used by people with diabetes to help monitor and manage their glucose (blood sugar) levels. Since CGMs have revolutionised the management of diabetes, health practitioners have started to utilise CGMs to better understand the glucose response and wider metabolic health of individuals without diabetes.

Data from CGMs allows users to know their glucose in near real time as well as view glucose fluctuations over time. A 2023 paper co-authored by Abbott’s medical research team and published in the scientific journal Metabolism found that CGMs like Lingo can be used to improve the metabolic health of people who do not live with diabetes. The research found that managing glucose spikes and keeping blood sugar in a stable, healthy range can have a positive impact on metabolic health.

Health benefits of CGMs and limiting glucose spikes

Compelling published research shows that using a CGM and limiting glucose spikes, both in the short term and over time, have a number of health benefits for people who don’t have diabetes, including:

  • Being proactive about future health: While both average and fasting glucose levels are important markers for health, glucose extremes and post-meal spikes might matter more. These specific metrics are risk factors for chronic health conditions such as insulin resistance, metabolic disease, and heart disease. (1, 2, 3, 4, 5)

  • Managing weight: With insights from a CGM, individuals had better success adhering to low-glycaemic and low-carb diets, (6) both of which are effective approaches for weight loss — even without intentional calorie restriction. (6, 7, 8, 9) While using a CGM, you can know your glucose in real time, learn how you uniquely respond to foods and habits, and make dietary changes that support steady glucose and lead to improvements in metabolic health and weight. (6, 10)

  • Identifying cravings vs. true hunger: If you just ate but feel hungrier than before, it could be due to a glucose crash. These crashes, which often follow glucose spikes, will convince you that you need to refuel ASAP. (11, 12) Research shows that using a CGM can identify which eating pattern will keep you on track for having steady energy, such as a low-glycaemic diet. CGMs can also help you differentiate cravings from true hunger, all of which can help with weight loss efforts. (6, 13)

  • Improving sleep: Low-glycaemic diets that nourish steady glucose have been shown to improve both sleep quality and length of sleep. (14, 15) And better sleep supports steady glucose the following day, (16) empowering you to make better choices and continue to stay steady. Using a CGM can highlight food choices that minimise glucose spikes, helping to keep you on track and better understand your glucose patterns while you sleep. (6, 10, 17, 18)

  • Bettering your mood: Research shows that a high-protein, low-glycaemic diet, which helps stabilise glucose, improves mood and can even lessen symptoms of depression. (19, 20) Using a CGM like Lingo can help you understand your individual glucose responses to food and encourage adherence to a low-glycaemic diet, which may provide mental health benefits. (20)

A final note from Lingo

Published research has shown that there are a number of benefits of limiting glucose spikes, which can be monitored by using a CGM, even if you don’t have diabetes. A CGM like Lingo provides personalised insights into your unique glucose response to food, activity, and other lifestyle choices.  

With Lingo, you can quickly see the impact of your habits displayed on your glucose graph and know if your glucose is steady, spiking, or crashing. Using this data can help you make healthier choices for your overall well-being. 


  1. Wolosowicz M, et al. Recent Advances in the Treatment of Insulin Resistance Targeting Molecular and Metabolic Pathways: Fighting a Losing Battle? Medicina (Kaunas). 2022 Mar 25;58(4):472. https://pubmed.ncbi.nlm.nih.gov/35454311/ 

  2. Balkau B, et al. High blood glucose concentration is a risk factor for mortality in middle-aged nondiabetic men. 20-year follow-up in the Whitehall Study, the Paris Prospective Study, and the Helsinki Policemen Study. Diabetes Care. 1998 Mar;21(3):360-7. https://pubmed.ncbi.nlm.nih.gov/9540016/ 

  3. Blaak EE, et al. Impact of postprandial glycaemia on health and prevention of disease. Obes Rev. 2012 Oct;13(10):923-84. https://pubmed.ncbi.nlm.nih.gov/22780564/ 

  4. Node K, et al. Postprandial hyperglycemia as an etiological factor in vascular failure. Cardiovasc Diabetol. 2009 Apr 29;8:23. https://pubmed.ncbi.nlm.nih.gov/19402896/ 

  5. Vaccaro O, et al. Relationship of postload plasma glucose to mortality with 19-yr follow-up. Comparison of one versus two plasma glucose measurements in the Chicago Peoples Gas Company Study. Diabetes Care. 1992 Oct;15(10):1328-34. https://pubmed.ncbi.nlm.nih.gov/1425098/ 

  6. Chekima K, at al. Utilising a Real-Time Continuous Glucose Monitor as Part of a Low Glycaemic Index and Load Diet and Determining Its Effect on Improving Dietary Intake, Body Composition and Metabolic Parameters of Overweight and Obese Young Adults: A Randomised Controlled Trial. Foods. 2022 Jun 15;11(12):1754. https://pubmed.ncbi.nlm.nih.gov/35741952/ 

  7. Juanola-Falgarona M, et al. Effect of the glycemic index of the diet on weight loss, modulation of satiety, inflammation, and other metabolic risk factors: a randomized controlled trial. Am J Clin Nutr. 2014 Jul;100(1):27-35. https://pubmed.ncbi.nlm.nih.gov/24787494/ 

  8. Yancy WS Jr, et al. A low-carbohydrate, ketogenic diet versus a low-fat diet to treat obesity and hyperlipidemia: a randomized, controlled trial. Ann Intern Med. 2004 May 18;140(10):769-77. doi: 10.7326/0003-4819-140-10-200405180-00006. PMID: 15148063. https://pubmed.ncbi.nlm.nih.gov/15148063/ 

  9. Bueno NB, et al. Very-low-carbohydrate ketogenic diet v. low-fat diet for long-term weight loss: a meta-analysis of randomised controlled trials. Br J Nutr. 2013 Oct;110(7):1178-87. https://pubmed.ncbi.nlm.nih.gov/23651522/

  10. Chekima K, et al. Use of a Continuous Glucose Monitor to Determine the Glycaemic Index of Rice-Based Mixed Meals, Their Effect on a 24 h Glucose Profile and Its Influence on Overweight and Obese Young Adults' Meal Preferences. Foods. 2022 Mar 28;11(7):983. https://pubmed.ncbi.nlm.nih.gov/35407070/ 

  11. Wyatt P, et al. Postprandial glycaemic dips predict appetite and energy intake in healthy individuals. Nat Metab. 2021 Apr;3(4):523-529. doi: 10.1038/s42255-021-00383-x. Epub 2021 Apr 12. Erratum in: Nat Metab. 2021 Jul;3(7):1032. https://pubmed.ncbi.nlm.nih.gov/33846643/ 

  12. Altuntaş Y. Postprandial Reactive Hypoglycemia. Sisli Etfal Hastan Tip Bul. 2019 Aug 28;53(3):215-220.  https://pubmed.ncbi.nlm.nih.gov/32377086/ 

  13. Jospe MR, et al. Teaching people to eat according to appetite - Does the method of glucose measurement matter? Appetite. 2020 Aug 1;151:104691. https://pubmed.ncbi.nlm.nih.gov/32246953/ 

  14. Gangwisch JE, et al. High glycemic index and glycemic load diets as risk factors for insomnia: analyses from the Women's Health Initiative. Am J Clin Nutr. 2020 Feb 1;111(2):429-439. https://pubmed.ncbi.nlm.nih.gov/31828298/ 

  15. Yoda K, et al. Association between poor glycemic control, impaired sleep quality, and increased arterial thickening in type 2 diabetic patients. PLoS One. 2015 Apr 14;10(4):e0122521. https://pubmed.ncbi.nlm.nih.gov/25875738/ 

  16. Tsereteli N, et al. Impact of insufficient sleep on dysregulated blood glucose control under standardised meal conditions. Diabetologia. 2022 Feb;65(2):356-365.  https://pubmed.ncbi.nlm.nih.gov/34845532/ 

  17. Dehghani Zahedani A, et al. 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. https://pubmed.ncbi.nlm.nih.gov/34047962/ 

  18. Mendes-Soares H, et al. Assessment of a Personalized Approach to Predicting Postprandial Glycemic Responses to Food Among Individuals Without Diabetes. JAMA Netw Open. 2019 Feb 1;2(2):e188102. https://pubmed.ncbi.nlm.nih.gov/30735238/ 

  19. McConnon A, et al. Experience and acceptability of diets of varying protein content and glycemic index in an obese cohort: results from the Diogenes trial. Eur J Clin Nutr. 2013 Sep;67(9):990-5. https://pubmed.ncbi.nlm.nih.gov/23778783/ 

  20. Breymeyer KL, et al. Subjective mood and energy levels of healthy weight and overweight/obese healthy adults on high-and low-glycemic load experimental diets. Appetite. 2016 Dec 1;107:253-259. https://pubmed.ncbi.nlm.nih.gov/27507131/

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