The Evolving Landscape of Continuous Glucose Monitoring (CGM) in Everyday Life
Daily life takes on new dimensions when you start tracking glucose levels. A little over a year ago, I was preparing for a conference; my bags were packed, and the Uber was on its way. Yet, before I could head to the airport, there was one last thing to do: tearing open a small isopropyl alcohol wipe, I cleaned the skin on the back of my arm and applied a small applicator, ignoring the visible needle inside. I squeezed my eyes shut and pressed a button, which made a distinct ka-thunk. I repeated the process on the other arm.
The Transition From Medical Necessity to Everyday Tech
Now, I had a Dexcom Stelo in my right arm and an Abbott Lingo in my left—over-the-counter continuous glucose monitors (CGMs) that would track the fluctuations in my glucose levels. I opened my phone to check both apps to ensure they were transmitting data. I even made a mental note to consider how altitude might affect these readings. To my surprise, I felt no pain during the application process.
It’s important to note that there was no urgent medical necessity for me to track my glucose; I’m not diabetic, and my A1C levels—indicative of long-term blood sugar—have always been normal. The growing trend of glucose tracking isn’t just confined to those with diabetes anymore; wellness influencers, biohackers, and athletes have started to discuss the benefits of CGMs. As a health tech tester, I decided to try this technology for a few weeks and evaluate its usefulness for someone who isn’t diabetic.
A Year of Discoveries
What began as a few weeks of testing extended into a year, during which I experimented with various devices, delved into scientific studies, consulted researchers, and navigated through a maze of medical professionals, trying to decipher if any underlying issues were at play or if it was the devices themselves. Applying CGMs has become second nature over this period.
While the first professional CGM was approved by the FDA in 1999, many people misunderstand that these devices measure blood sugar. In actuality, they offer real-time glucose readings from interstitial fluid located just beneath your skin. Compared to traditional finger-stick tests that directly measure blood sugar, CGMs provide prolonged tracking of glucose trends.
Historically, CGMs required a prescription and were primarily designated for Type 1 diabetics—individuals with minimal to no insulin production. However, recent advancements have led to both Dexcom and Abbott offering retail CGMs targeted towards non-diabetics and prediabetics.
The Potential Benefits of CGMs for Non-Diabetics
The advantages of using CGMs for prediabetics and Type 2 diabetics are evident, given that these conditions can develop gradually due to insulin resistance. Identifying these issues early on enables individuals to reverse their conditions through lifestyle changes. As of 2021, Type 2 diabetics comprised about 95 percent of the estimated 38.4 million Americans living with diabetes, while prediabetes affected an estimated 98 million. Hence, a significant demographic could discover valuable insights regarding how their dietary choices relate to actual health outcomes through CGMs.
However, the utility of CGMs for non-diabetics remains ambiguous. This hasn’t deterred CGM manufacturers and certain government officials from championing their use. If Health Secretary RFK Jr. has his way, we might see widespread adoption of CGMs among the general populace. The Surgeon General’s nomination of Casey Means—a co-founder of a CGM startup called Levels—reiterates the growing belief that this technology can rectify metabolic dysfunction often seen as a precursor to chronic illnesses. Although numerous healthcare experts contest this notion, suggesting that robust research on the topic is still lacking.
The Complexities of Data Interpretation in CGMs
As we transition into a new era of wearable technology, the potential for optimization of personal health data becomes increasingly vivid. This tech can serve as a means to flag potential health issues and simultaneously facilitate personal growth through enhanced self-awareness. However, it also amplifies the complexities involved in contextualizing data.
Many individuals are now resorting to meticulously logging their food intake while utilizing CGMs. Companies like January AI initially focused on CGMs but pivoted towards providing predictive insights on glucose spikes through meal logging apps. The rising trend of optimizing metabolic health necessitates the integration of data acquired from both CGMs and traditional meal tracking.
A major conundrum that arises is how to navigate the extensive data generated. As identified in studies, interpreting this data without sufficient context can lead to stress and anxiety. CGM apps, like Dexcom Stelo, often provide alerts for glucose spikes after a certain duration, while Abbott’s Lingo offers a simplified scoring system. Yet the subjective nature of these readings and the differences in data presentation creates confusion, especially when using multiple devices simultaneously, as I did.
The Psychological Impacts of CGM Usage
The psychological toll that using these devices can impose on one’s eating and exercise habits is notable. As I focused obsessively on the food I consumed, interactions at social events became stressful. For instance, during a family Thanksgiving gathering, I found myself bargaining with myself about the acceptable food choices based on CGM data. Ultimately, the anxiety surrounding perceived deviations in glucose responses became overwhelming.
This area—particularly among those with pre-existing conditions—has shown a concerning potential for disordered eating patterns. While there’s no definitive evidence linking CGM use to an onset of eating disorders, numerous healthcare professionals express caution regarding the psychological ramifications of such close monitoring.
The Real Impact of Medical Intervention
Ultimately, my journey transitioning into a CGM user culminated in newfound insights about my health. After extensive monitoring, additional tests revealed elevated liver enzymes and cholesterol levels I hadn’t noticed before. Though I didn’t exhibit diabetes, elevated liver enzymes pointed toward non-alcoholic fatty liver disease, a common condition affiliated with polycystic ovary syndrome. Traditional methods of managing these conditions through diet and exercise proved insufficient.
During the last year of observing these changes, I found a new doctor and — after adjusting my medical treatment plan — started to see improvements in my CGM data and overall health metrics. After about four months on medication designed specifically for my unique health profile, I found that my long-term testing played a pivotal role in my treatment strategy.
In summary, while I initially approached CGMs as tools for self-optimization, I learned that underlying medical issues required attention beyond what lifestyle adjustments could provide. I find value in CGMs for specific contexts, but caution others about relying on them as all-encompassing solutions. Users need to be aware of data limitations and the psychological impact of extended monitoring for optimal health management.
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