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<\/a><\/p>\nApplying CGMs has become second nature over the past year. They don\u2019t hurt, but I am hyper aware of the types of sleeves I wear while testing.<\/p>\n
The first \u201cprofessional use\u201d CGM was cleared by the Food and Drug Administration in 1999. Most people think these devices are used to track blood sugar, but that\u2019s not entirely correct. Technically, they provide real-time glucose measurements from the interstitial fluid between your cells, just underneath your skin. Compared to traditional finger-stick tests, which directly measure blood sugar, CGMs can track glucose trends over an extended period of time.<\/p>\n
Until 2024, CGMs required a prescription and were devices primarily used by Type 1 diabetics \u2014 people who produce little to no insulin. Now, both Dexcom and Abbott sell CGMs targeted at non-diabetics, prediabetics, and Type 2 diabetics who don\u2019t rely on insulin. To differentiate, sometimes you\u2019ll see companies market over-the-counter devices as \u201cglucose biosensors.\u201d<\/p>\n
The benefits of using CGMs for prediabetics and Type 2 diabetics are clear. Unlike Type 1 diabetes, prediabetes and Type 2 tend to develop over time as the body becomes more resistant to insulin. If caught early enough, it can be \u201creversed\u201d with lifestyle interventions like changes to diet and exercise. People with pre- and Type 2 diabetes also make up the overwhelming majority of cases in the US. According to the American Diabetes Association<\/a>, as of 2021, Type 2 diabetics make up about 95 percent \u2014 or roughly 36 million \u2014 of the estimated 38.4 million Americans with diabetes. Meanwhile, about 98 million were estimated to have prediabetes. Put all that together, and a significant number of people could potentially learn a lot from using CGMs about how their dietary habits impact a legitimate metabolic condition.<\/p>\n Less clear is whether this technology is useful for non-diabetics. But that hasn\u2019t stopped the push for this tech, from both the CGM makers and the government. If Health Secretary RFK Jr. has his way, in four years, everyone might be wearing one of these<\/a>. Underscoring this, President Donald Trump\u2019s controversial surgeon general nominee Casey Means is also the cofounder of Levels, a CGM startup aimed at non-diabetics. In her book Good Energy, she calls out the technology as a useful tool in fixing metabolic dysfunction \u2014 something she claims is at the root of every possible chronic ailment today<\/a>. However, several medical experts have publicly questioned this logic, stating the evidence for non-diabetics simply isn\u2019t there<\/a>.<\/p>\n But we\u2019ve now entered a new era where wearable technology offers a tantalizing promise. It\u2019s not just about flagging potential illnesses. It\u2019s about optimizing your body\u2019s biometric data to live the longest, healthiest life possible. In the context of the US\u2019s terribly flawed healthcare system, this tech has often been positioned as giving back a degree of control to the average person. Wear this device, track your health, learn more about yourself, and subsequently make better choices.<\/p>\n Optimization of metabolic health has been a rising trend for years. Most commonly, this has come in the form of food logging. However, CGM-related metabolism tracking has gained traction due to the extra layer of data it provides. January AI<\/a> was originally a CGM startup that then pivoted to providing glucose spike prediction within a meal logging app based on the data it collected. Meanwhile, Oura has since partnered with Dexcom<\/a> to provide glucose readings, meal logging, and AI interpretations inside its own smart ring app. Abbott also recently partnered with Withings<\/a>, another wearables maker, for a similar integration. When you factor in that GLP-1 use is increasing, alongside the return of 2000s-era, ultra-skinny diet culture<\/a>, it seems like CGM use is being positioned as the next evolution of fitness tracking.<\/p>\n Why not try biohacking my nutrition to manage my diabetes risk, gain insight into PCOS, and be a better athlete? <\/p>\n \u201cIt\u2019s predicted one in two Americans will have obesity by the year 2030,\u201d says Dr. Thomas Grace, a diabetes clinician with Type 1 diabetes who consulted with Dexcom on the Stelo CGM. \u201cI think the most exciting thing for myself, for my patients, and for people using Stelo is the instant reward they get from understanding how food, activity, stress, and sleep affect their overall glucose health.\u201d<\/p>\n I\u2019m the exact sort of non-diabetic that Dexcom, Abbott, and other CGM startups are targeting. I\u2019ve got a family history of Type 2 diabetes and high cholesterol. I\u2019ve been diagnosed with polycystic ovary syndrome (PCOS) \u2014 a chronic condition that numerous doctors have told me means I likely either have insulin resistance or chronic inflammation that makes me predisposed to diabetes. As a runner, I\u2019ve struggled with energy levels while training for long-distance races despite following standard fueling practices and carb loading. Why not try biohacking my nutrition to manage my diabetes risk, gain insight into PCOS, and be a better athlete?<\/p>\n Even if you apply a CGM perfectly, they can still fail for one reason or another. The CGM pictured mysteriously failed after only 48 hours of testing. This happened a few times in the last year of testing.<\/p>\n Wearing a CGM 24\/7 is invisible until it isn\u2019t. I went days without remembering they were in my arms. Then, they\u2019d inevitably snag on my shirt sleeve, or I\u2019d brush into a doorframe, the contact popping the CGM out of my arm. Now, even when I don\u2019t wear CGMs, I\u2019m aware of the back of my arms and the cut of all my shirts. That hypervigilance comes with being constantly monitored \u2014 even if you\u2019re the one doing the monitoring.<\/p>\n At first, I\u2019d review my data every morning, after each workout, and a few hours after each meal. Most of what I saw was pretty normal. A bowl of pasta? Glucose spike. Roasted salmon and a side salad? Minimal increase. Carb loading before a long run? Mondo spike, followed by a sharp decrease. (I found CGM use too cumbersome for mid-run fueling, as there\u2019s a five-minute delay between readings.)<\/p>\n Nevertheless, reviewing my data multiple times a day began spiking my anxiety. Both Dexcom and Abbott\u2019s apps have educational articles about what the ideal glucose range is for healthy nondiabetics \u2014 70 to 140mg\/dL. Fasting glucose levels \u2014 like when you\u2019re sleeping \u2014 ought to sit in the range of 70 to 99mg\/dL. Those first few months, I woke up well beyond 100mg\/dL every day, even without late-night snacks. Sometimes, I\u2019d wake up to see the Dexcom app had alerted me to glucose spikes while I slept. (Abbott doesn\u2019t send spike notifications for Lingo.)<\/p>\n A year prior, I had tested Nutrisense<\/a> \u2014 which also makes use of CGMs \u2014 for two weeks and never had elevated morning glucose levels. Clearly, diabetes had finally come for me.<\/p>\n Elevated morning glucose is a concern because of the Dawn Phenomenon<\/a>. To help prepare your body to wake up, you produce hormones like cortisol and growth hormone. That signals to your liver to release glucose, giving you energy for the day. In diabetics and insulin-resistant people, however, it leads to overly high blood sugar levels during the morning. Something, perhaps, like what I was seeing.<\/p>\n I spent many mornings puzzling over high overnight glucose readings and what that could possibly mean. <\/p>\n Cue anxiety, scheduling a flurry of doctors\u2019 appointments, and hyperfixating on my diet and exercise. At the doctor\u2019s office, I got shrugs, quizzical brow raises, and a reluctant acquiescence to run blood tests. (\u201cDo they really have non-diabetics wearing those?\u201d a nurse asked while taking my blood pressure.) My A1C, a gauge for your average glucose levels over two to three months, was perfectly normal. No diabetes here. I did, however, have elevated liver enzymes and cholesterol levels.<\/p>\n Out of an abundance of caution, my doctor ordered an ultrasound. I had to wait several weeks for an appointment. Later, once the goo was slathered over my abdomen, I watched nervously out of the corner of my eye as an ultrasound technician muttered to herself. After another few days, I got a call from the doctor. I was diagnosed with a \u201cnothing to worry about right now\u201d case of non-alcoholic fatty liver \u2014 a condition that commonly occurs alongside PCOS. Maybe, my doctor suggested, I should cut out all alcohol (I rarely drink) and lose body fat (I\u2019ve been trying for 10 years). Come back in about a year, they said, and we\u2019ll see where you\u2019re at.<\/p>\n Read one way, this could be a success story for CGMs. The devices flagged something had changed, and though it wasn\u2019t diabetes, I had at least one new official diagnosis. Glass half full: Control over my health had been handed back to me.<\/p>\n A more skeptical take is that elevated liver enzymes and high cholesterol had been present in previous blood work. A former doctor had also suspected fatty liver disease, but said an ultrasound wasn\u2019t necessary unless my levels worsened. Were my levels worse at this CGM-inspired blood test? Not particularly. The advice I\u2019d been given was the same as it had been in years past. Glass half empty: I learned nothing new.<\/p>\n It wasn\u2019t until much later, after consulting with Dexcom and Abbott, that I learned side sleeping could lead to inaccurate overnight glucose readings. When you\u2019re on your side, the CGM can get compressed. That, in turn, could lead to readings lower or higher than your actual glucose levels. I tried swapping arms for the Lingo and Stelo to test for this, but it was impossible to account for how I shifted positions each night. Either way, I continued getting high overnight and morning glucose readings from both sensors for months.<\/p>\n The worst part was that I couldn\u2019t tell whether the data was inaccurate or my doctor had missed something.<\/p>\n I started running into issues after the first month of continuous wear. For starters, it can be pricey. Dexcom and Abbott both gave me several test units, but for the average person, it can cost around $100 a month. A single sensor lasts about 15 days if everything goes well. Sometimes, they malfunction or get ripped out after getting caught on clothing and other objects. The adhesive also leaves stubborn residue that takes weeks of showering to fully remove. Partly to stretch out my supply, partly to give my skin a break, I started testing two weeks of every month. After six months, I pared down to once a quarter.<\/p>\n But regardless of how often a person uses CGMs, every body is different. Foods that cause a spike for me may do nothing for you. The only way to know for sure is through diligent logging and experimentation. The conundrum is that this creates a mountain of data, and as I learned, interpreting that data without adequate context can lead to unnecessary anxiety.<\/p>\n Compounding the issue? CGM makers have differing approaches on how to present that data. The Dexcom Stelo app, for example, will give you spike alerts after about an hour or two. Abbott\u2019s Lingo CGM eschews such alerts altogether. Instead, Abbott opts for a Lingo Score that tries to simplify raw data into a digestible number that signifies how well you did on average at keeping your glucose within a healthy range of 70 to 140mg\/dL.<\/p>\n If you wear two CGMs simultaneously, as I did, it\u2019s possible to get different numbers and not know which one is truly correct<\/p>\n Using a CGM to stay within that range sounds relatively simple and easy. In reality, it\u2019s complicated.<\/p>\n \u201cThe one study that did look at follow-up outcomes found that people who spent more time above that range were more likely to get diabetes, but this was in a pretty small population,\u201d says Nicole Spartano, assistant professor at Boston University\u2019s Chobanian and Avedisian School of Medicine. \u201cThey may have already had prediabetes and are sort of on their way already. I think we\u2019re really at a point where we don\u2019t have a lot of information from a research standpoint.\u201d<\/p>\n For example, Spartano notes that there\u2019s often a lack of context for how CGM numbers could relate to an individual\u2019s health. On the one hand, doctors often see a fasting blood glucose level of over 100mg\/dL as a cause for concern. CGMs, however, do not measure blood glucose. They measure interstitial glucose, which can, at times, be higher than blood glucose. Spartano says more research is needed to determine what the differences between blood and interstitial glucose could be, both broadly and on an individual level.<\/p>\n My glucose has improved since starting new medication. However, what caused these overnight spikes? A bad dream? Side sleeping? Temperature shifts? I\u2019ll never really know. Screenshot: Abbott<\/p>\n \u201cWe assume that they\u2019re completely accurate, but they\u2019re not exactly accurate. There\u2019s a certain level of accuracy that the FDA requires, but that still leaves some wiggle room,\u201d says Dr. David Klonoff, medical director at the Diabetes Research Institute at Mills-Peninsula Medical Center and editor-in-chief of the Journal of Diabetes Science and Technology. <\/p>\n Basically, if you wear two CGMs simultaneously, as I did, it\u2019s possible to get different numbers and not know which one is truly correct. And while most people would only wear one at a time, there could also be a difference between one CGM you wear and the next, based on whether they were applied correctly and several other factors.<\/p>\n But say everything is assumed to be accurate. What is the best way to interpret CGM data for non-diabetics? To try and find out, Spartano ran a clinical study<\/a> in which 18 endocrinologists were asked to evaluate data from non-diabetics.<\/p>\n \u201cWe gave them 20 different glucose monitor reports and asked them, \u2018If someone came in with this report, would you suggest they have a follow-up screening for this?\u2019\u201d says Spartano. She says some experts viewed peaks as a normal part of physiology. Others saw elevated levels as a sign someone might need further testing.<\/p>\n \u201cEssentially, there was no consensus. Even clinicians who read CGM data all day, every day don\u2019t know what to do with this data,\u201d says Spartano.<\/p>\n \u201cOne of the problems is we don\u2019t have an ideal way of analyzing the information yet. We know if someone is doing really poorly or completely normally, but the people that seem to be headed for trouble? We can only say, \u2018It doesn\u2019t look normal, but it\u2019s not abnormal. It\u2019s something in the middle,\u2019\u201d agrees Klonoff.<\/p>\n \u201cEssentially, there was no consensus. Even clinicians who read CGM data all day, every day don\u2019t know what to do with this data.\u201d<\/p>\n According to Klonoff and Spartano, there isn\u2019t a reference set of data that\u2019s been vetted and agreed upon by a group of experts. The data that\u2019s coming in from different subgroups of people using over-the-counter CGMs is all so new that it\u2019ll take years before that\u2019s even possible.<\/p>\n So, say you, a non-diabetic, needed help interpreting your CGM data. It\u2019s very possible that if you were to present your data to 10 different doctors, you might get 10 different recommendations.<\/p>\n During my research, multiple doctors and diabetes experts told me I was fine given that my A1C remained optimal and my CGM data \u2014 for the most part \u2014 stayed within a healthy range. Spikes, they assured me, are a normal part of my metabolism functioning as it should.<\/p>\n However, that\u2019s technically not optimizing. Take Means. While her credentials are questionable (she thinks you can prevent cancer with \u201cgood energy\u201d<\/a> habits), in her New York Times bestseller Good Energy, she advises, \u201cWe want to minimize spikes because they are associated with worse outcomes.\u201d She advocates for stricter criteria. Post-meal glucose levels shouldn\u2019t rise above 115mg\/dL, no spike should be above 30mg\/dL, and \u201coptimal\u201d morning fasting glucose should be between 75 and 80mg\/dL. I\u2019ve seen other influencers recommend similar advice, albeit with slightly different numbers.<\/p>\n By those standards, you could be in a healthy range 100 percent of the time but still have a \u201csuboptimal\u201d metabolism. Never mind that experts have said there\u2019s not enough consensus to define what warrants \u201cgood\u201d or \u201cbad\u201d CGM data in non-diabetics. Many CGM apps will give you scores and additional metrics to aim for. If you\u2019re a perfectionist like me, that can be a recipe for disaster.<\/p>\n I experimented with protein bagels to see if they\u2019d lower glucose spikes while giving me enough energy for longer runs.<\/p>\n I started measuring every single bit of food I ate, including this homemade protein jello.<\/p>\n Inspector Petey the cat was not a fan of my glucose experimentation over the last year.<\/p>\n The longer I wore CGMs, the more obsessed I became with the food on my plate. A slice of pizza at a gathering would make me break out in a cold sweat. Common sense says a single slice of pizza once in a while is not the end of the world. But the thought of a spike alert or a bad score was enough to convince me that I should forgo eating meals or snacks entirely, even if my stomach was growling. Likewise, I began overexercising. I\u2019d feel good if my fasting glucose was below 85mg\/dL, and stressed if it was anything over 100 \u2014 even if there was a logical, temporary, good reason for that. I began to feel stressed about being stressed. At a certain point, I became incapable of enjoying social events and started avoiding them. The worst moment came early on in testing at a family Thanksgiving dinner<\/a>. I started negotiating with myself about what I could eat based on how it was showing up in a CGM app. After six months, it became bad enough that people close to me felt the need to intervene. I had been too fixated on successfully \u201coptimizing my metabolism\u201d to notice.<\/p>\n This is often forgotten in the narrative to optimize metabolism. Studies<\/a> have found<\/a> that it\u2019s difficult to conclude that wearables, diet, or fitness apps have a definitive link to disordered eating or eating disorders \u2014 though the risk is there, and they have been associated with exacerbating symptoms<\/a> in those who already have experienced them. For some people, CGM use won\u2019t come with this kind of dark side. For me, it absolutely did.<\/p>\n I now opt to use CGMs only to test new features.<\/p>\n After about a year, I decided to conduct one final test. Once again, my data was wonky. Morning glucose was elevated. Post-meal spikes were prolonged. And my daily average glucose was higher than it\u2019d ever been. I was consistently exhausted. I kept gaining weight despite vigilantly monitoring my nutrition and exercise. I found a new doctor and got some more blood work done. Still no diabetes or prediabetes. But my bad cholesterol had worsened, and two liver enzymes had more than tripled from the previous year. An ultrasound showed my fatty liver had progressed from mild to moderate. For the first time, I had my insulin resistance tested and was found to be on the \u201chigh side of normal.\u201d<\/p>\n My new doctor concluded that my non-medicated efforts to rein in my chaotic metabolism, while admirable, weren\u2019t cutting it. Prescriptions were written, a plan was formed, and four months into treatment, my CGM data and blood work have dramatically improved. For the first time in a decade, my bad cholesterol is normal. I\u2019ve lost 15 of the 25 pounds I gained, and my liver enzymes have dropped by roughly 65 percent. My morning glucose levels are no longer elevated.<\/p>\n My biomarkers have dramatically improved thanks to new medications, but the hardest thing to measure was how this affected my mental health.<\/p>\n Proponents of non-diabetic CGM use might frame this as an outright win. In many ways, it is. Even so, I\u2019m hesitant to characterize it that way. I was often stumped by my data, anxious when consulting doctors, and for a time, wrecked my hard-fought relationship with food and exercise. Overall, it took 13 months from starting CGM testing to finding a satisfactory treatment for my metabolic issues and 17 months to finally see improvement. Along the way, I shed many tears of frustration, and I\u2019m still adjusting to the side effects of my new medications.<\/p>\n I\u2019m grateful to see my health improve. My long-term testing of CGMs undeniably played a role in that. But arguably, medication \u2014 not CGM use and definitely not \u201ctaking control of my health\u201d through lifestyle changes alone \u2014 is what\u2019s ultimately helping me feel better. I\u2019m all for non-diabetics having access to these sensors, so long as they\u2019re aware of the limitations. 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