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Health & Fitness
CGM Log: Day 14
Shane
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Today, I decided to test all the foods I don’t usually eat but occasionally indulge in, all in one day.
I faced an unexpected challenge as soon as I woke up.
Normally, my blood sugar stays around 80–100 while I sleep, but for some reason, my sensor started warning that my blood sugar was low.
Since my blood sugar couldn’t have dropped that much, please take today’s cheat day and blood sugar log with a grain of salt.
I ate a vague portion of rice cakes.
Someone ate more of the rice cakes I had saved for today, so I scraped together the leftovers and ended up with a half-hearted portion.
Even though the sensor has been tending to report my blood sugar on the low side, it’s good at catching the peaks. I saw my blood sugar hit 200 for the first time—it was quite surprising.
Maybe I ate too much?
Luckily, I didn’t feel too bad or uncomfortable.
My blood sugar was all over the place, rising and dropping like crazy.
When I did a finger prick test to check, the discrepancy wasn’t too bad. Especially for high readings, the sensor seemed reliable.
For a snack, I wanted to buy a baguette and spread some butter on it, but unfortunately, it wasn’t available yet.
So I bought a coffee bun and a cheese bagel instead. Since I don’t react much to flour, my blood sugar didn’t spike much.
For lunch, I went out and bought sushi. I ate 12 pieces of sushi, a roll, and some udon, then walked about 1,500 steps back home.
On the way back, my blood sugar dipped once but peaked again at just 105—not as big a deal as I thought.
But I still had candied fruit skewers (tanghulu) left.
Yes, I bought that infamous tanghulu.
By the way, did you know?
These days, some places make tanghulu with allulose.
Will one allulose tanghulu raise my blood sugar?
Probably not much, right?
That’s why I bought two.
My blood sugar didn’t plummet into the hypoglycemic zone like it was shown in the picture, so it seems to be a sensor error.
I’ve been diligently adding correction values, but I’m losing trust in this sensor.
As I get closer to day 15 of use, the discrepancies seem to get worse.
For dinner, I went out and had jajangmyeon and sweet and sour pork, then walked about 800 steps home.
I said earlier that I don’t react much to flour, right?
It wasn’t too extreme, but my blood sugar didn’t drop easily this time. Maybe it’s because the sauces for jajangmyeon and sweet and sour pork were so sweet.
I was fine after eating rice cakes earlier, but after having jajangmyeon and sweet and sour pork, I got drowsy.
I guess the high blood sugar did have some effect on me. I wasn’t completely exhausted, but I did feel a bit tired.
Looking back, I’m starting to think how ridiculously high those rice cakes spiked my blood glucose.
After two hours, I checked my blood sugar again to reduce the sensor’s error margin.
As long as I’m not in the hypoglycemic range, the error is manageable.
As I’m writing this, it’s been about two and a half hours, and my blood sugar still hasn’t come down.
It’s pretty amazing. In my experience, it usually takes about three hours for it to drop.
At this point, I feel like today's log was a bunch of shits and giggles.
I hope you enjoyed reading.
Starting tomorrow, I’ll be back on my usual low-carb diet.
Have a good night!
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Shane
Debunking the Carbohydrate-Insulin Myth: What Really Makes You Gain Weight?
In recent years, the debate around carbohydrates, insulin, and their role in obesity has taken center stage in the world of nutrition. One popular theory claims that high carbohydrate intake triggers insulin secretion, which leads to fat storage and weight gain—this is known as the Carbohydrate-Insulin Model of Obesity. But how valid is this claim? Today, we'll dive deep into the science behind this controversial topic and explore why the simplistic notion of "insulin makes you fat" may be misleading. The Insulin-Carbohydrate Connection: Myth or Fact? The Carbohydrate-Insulin Model suggests that insulin, a hormone released after consuming carbohydrates, drives fat storage. This theory is based on the fact that insulin is lipogenic (i.e., it encourages the storage of fat) and lowers blood sugar levels, potentially triggering hunger. However, despite some theoretical support, real-world evidence pokes holes in this idea. Theoretical Problems with the Carbohydrate-Insulin Model While insulin does play a role in fat storage, it doesn’t tell the whole story. Insulin’s role is anabolic—it builds up tissues by shuttling nutrients into cells, including muscle and fat. The catch? Insulin can’t lead to weight gain without a calorie surplus. In other words, unless you’re consuming more calories than you’re burning, it’s nearly impossible for insulin to create net body fat gains. Endogenous and exogenous insulin have distinct effects on hunger hormones. Endogenous insulin, produced naturally by the body, tends to help regulate hunger by promoting a feeling of fullness. In most cases, it doesn't lead to a noticeable increase in hunger levels. On the other hand, exogenous insulin, which is injected or administered externally, can cause a sharp drop in blood sugar, triggering a rebound effect that stimulates hunger. This distinction is crucial because many people mistakenly believe that all insulin spikes drive hunger, when in reality, it's primarily the exogenous form that creates this feedback loop. Another problem with the model is that it ignores dietary fats, which are often consumed alongside carbohydrates. Foods like pizza and ice cream are high in both fat and carbs, making them highly lipogenic—yet these are the foods most associated with weight gain, not simple carbohydrates like fruits or whole grains. Real-World Evidence: Carbs vs. Fats In controlled studies, researchers compared high-carbohydrate, low-fat diets to high-fat, low-carbohydrate diets. The results? As long as calorie intake is the same, both diets lead to similar weight loss or gain. This means that insulin spikes from carbohydrates don't result in more fat gain compared to fats themselves. So, what actually causes weight gain? Overeating, especially on highly palatable and calorie-dense foods, regardless of whether they are high in carbs or fats. Most lipogenic foods aren't even high glycemic index (GI) foods! Pizza, ice cream, and cookies are loaded with fat and have moderate or low GI, which means they don’t spike blood sugar as much as people assume. Also, certain foods known to be insulinergic, like yogurt, skim milk, etc., do cause a spike in insulin, but they are unique in that they don’t lead to a subsequent drop in blood sugar. This is because the body counteracts the insulin spike with glucagon secretion. Glucagon, a hormone that raises blood sugar, signals the liver to release stored glucose into the bloodstream. This balancing mechanism ensures that despite the insulin increase, blood sugar remains stable. As a result, these foods do not trigger the hunger rebound often associated with sharp drops in blood sugar, making them less likely to contribute to overeating. The Role of Palatability and Overeating Perhaps the biggest driver of obesity is food palatability. Junk foods, which are typically high in both fat and sugar, are designed to taste good, making it easy to overeat. Foods like cookies, pizza, and ice cream stimulate the brain’s reward system, causing us to eat more even when we’re not hungry. This overeating leads to excess calorie intake, which is the real culprit behind fat gain. The insulin-carbohydrate model doesn’t explain why people get fat on junk food, but the "palatability-reward hypothesis" does. According to this model, we gain weight because calorie-dense, highly palatable foods encourage overconsumption. Blaming insulin alone oversimplifies a much more complex issue. Conclusion: Insulin Is Not the Villain
Shane
Weightloss Diet Guide for Nerds
Weight loss fundamentally relies on maintaining a energy balance deficit, which means consuming fewer calories than your body needs. This guide provides an easy-to-follow plan, focusing on macronutrients and calorie control to support fat loss, founded on the energy-balance model of obesity. Step 1: Estimate Your Total Daily Energy Expenditure (TDEE) To manage weight effectively, understanding your Total Daily Energy Expenditure (TDEE) is essential. The equation for calculating changes in energy storage (ΔES) is as follows: ΔES = EI - [BMR + TEF + (EEex + NEAT)] ΔES = Change in body energy storage (calories) EI = Energy intake (calories consumed through food and drink) BMR = Basal Metabolic Rate (energy needed for basic bodily functions at rest) TEF = Thermic Effect of Food (energy used for digestion and metabolism) EEex = Energy expenditure from planned exercise NEAT = Non-Exercise Activity Thermogenesis (energy expended through daily movement and activities) Calculating each component precisely can be complex, so a practical approach is to use online TDEE calculators that estimate your calorie needs based on age, weight, height, and activity level. Note that each calculators will vary slightly, so make sure to use the same TDEE calculator every time. I personally use one from KetoGains. Step 2: Set Caloric Intake for Weight Loss Once you have your TDEE, aim to create a caloric deficit for fat loss. A common recommendation is reducing calorie intake by 10-20% from your TDEE. For example, if your TDEE is 2,500 kcal/day, aiming for 2,000-2,250 kcal/day could support fat loss while minimizing muscle loss. Modifying TDEE Based on Results If you're losing weight: Continue following your current plan. If you're consistently losing weight over time without significant energy loss or hunger issues, your TDEE estimate is likely accurate. Keep doing what you're doing and monitor your progress. If you're gaining weight: Don’t immediately make adjustments if you notice a short-term increase in weight. Weight fluctuations can happen due to factors like water retention or muscle gain. Continue tracking your weight and calorie intake for at least 2 weeks. If you're still gaining weight after this period, it may indicate that your calculated TDEE is higher than your actual metabolism. In this case, reduce your TDEE estimate slightly and adjust your calorie intake accordingly. For women before menopause: Weight tracking can be more complex due to hormonal fluctuations and water retention during the menstrual cycle. These changes can cause temporary increases or decreases in weight, making it harder to assess actual progress. To account for this, track your weight consistently and compare averages across menstrual cycles rather than focusing on short-term changes. This method provides a more accurate picture of weight loss over time and helps avoid unnecessary adjustments to your TDEE based on temporary water retention. Step 3: Macronutrient Breakdown for Fat Loss After determining your daily caloric target, you can plan your macronutrient intake to optimize fat loss. 1. Protein Intake Recommendation: Consume approximately 2.2g of protein per kg of body weight daily.
Shane
CGM Log: Day 15 - Dead End
Yesterday's Efforts vs. Today's Goals Since I worked hard on eating yesterday, I thought I should work hard on exercising today. I focused on a lower-body routine with squats and Romanian deadlifts. After the workout, I could feel how much my muscles were stimulated—my entire body felt sore, so I treated myself to a session with the massage gun for the first time in a while. Post-Workout Incident As I was taking off my workout clothes, I heard a little "pop!" sound, and something dropped to the floor. Upon closer inspection, I realized it was my continuous glucose monitor (CGM) that had been attached to my left forearm. Yes, it had been dangling since yesterday afternoon, and it finally gave way. Still, it hung on well until the morning of day 15, so I think it did its job. Actually, my interest in tracking blood sugar has decreased, and there were a few inconveniences as well, so I was planning to remove the sensor this afternoon instead of tomorrow when it expires. But maybe it worked out for the better. No Glucose Tracking Today Since the CGM is off, there's no glucose data for today. I had an iced Americano in the morning before working out, and afterward, I had a protein shake. For lunch, I ate bulgogi, had a Zero Coke brownie as a snack, and for dinner, I ate 150g of rice with homemade chashu. By my standards, this isn't a meal that would cause a big blood sugar spike. I usually maintain this kind of diet. Since it feels like a shame to end here, let's review some past data. Glucose Tracking Recap Looking at the average blood sugar over the entire period, my fasting glucose stayed in the 80-90 range, and even after meals, my blood sugar didn't rise significantly, so the average came to 97. I'd say that's a pretty healthy number. Excluding days like yesterday when I had cheat meals, there wasn’t much variation in my blood sugar levels. Nothing particularly interesting to note. Personal Conclusions from This Experiment Here are my personal takeaways: I am sensitive to white rice. I can handle about 3/4 of a bowl per meal. My blood sugar doesn't spike much even when I consume liquid carbs after strength training.