add tiny bit of detail

_posts/2020-06-11-biohacking-lite.markdown

@@ -83,14 +83,14 @@ Since I am a computer scientist it is hard to avoid a comparison of this "energy
 
 > So... a few textbooks later we see that to lose weight one should eat less and move more.
 
-**Experiment section**. So how big of a deficit should one introduce? I did not want the deficit to be so large that it would stress me out, make me hangry and impact my work. In addition, with greater deficit your body will increasingly begin to sacrifice lean body mass ([paper](https://www.ncbi.nlm.nih.gov/pubmed/15615615)). To keep things simple, I aimed to lose about 1lb/week, which is consistent with a few recommendations I found in a few [papers](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4033492/). Since 1lb = 454g, 1g of fat is estimated at approx. 9 kcal, and adipose tissue is ~87% lipids, some (very rough) napkin math suggests that 3500 kcal = 1lb of fat. The precise details of this are [much more complicated](https://www.ncbi.nlm.nih.gov/pubmed/21872751), but this would suggest a target deficit of about 500 kcal/day. I found that it was hard to reach this deficit with calorie restriction alone, and psychologically it was much easier to eat near the break even point and create most of the deficit with cardio. I started the experiment in June 2019 at about 195lb (day 120 on the chart below), and 1 year later I am at 165lb, giving an overall empirical rate of 0.58lb/week:
+**Experiment section**. So how big of a deficit should one introduce? I did not want the deficit to be so large that it would stress me out, make me hangry and impact my work. In addition, with greater deficit your body will increasingly begin to sacrifice lean body mass ([paper](https://www.ncbi.nlm.nih.gov/pubmed/15615615)). To keep things simple, I aimed to lose about 1lb/week, which is consistent with a few recommendations I found in a few [papers](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4033492/). Since 1lb = 454g, 1g of fat is estimated at approx. 9 kcal, and adipose tissue is ~87% lipids, some (very rough) napkin math suggests that 3500 kcal = 1lb of fat. The precise details of this are [much more complicated](https://www.ncbi.nlm.nih.gov/pubmed/21872751), but this would suggest a target deficit of about 500 kcal/day. I found that it was hard to reach this deficit with calorie restriction alone, and psychologically it was much easier to eat near the break even point and create most of the deficit with cardio. It also helped a lot to adopt a 12-8 intermittent fasting schedule (i.e. "skip breakfast") which helps control appetite and dramatically reduces snacking. I started the experiment in June 2019 at about 195lb (day 120 on the chart below), and 1 year later I am at 165lb, giving an overall empirical rate of 0.58lb/week:
 
 <div class="imgcap">
 <img src="/assets/bio/weight.png">
 <div class="thecap">My weight (lb) over time (days). The first 120 days were "control" where I was at my regular maintenance eating whatever until I felt full. From there I maintained an average 500kcal deficit per day. Some cheating and a few water fasts are discernable.</div>
 </div>
 
-**Other stuff**. I should mention that despite the focus of this post the experiment was of course much broader for me than weight loss alone, as I tried to improve many other variables I started to understand were linked to longevity and general well-being. I went on a relatively low carbohydrate mostly Pescetarian diet, I stopped eating nearly all forms of sugar (except for berries) and processed foods, I dramatically reduced alcohol consumption to just a few events/gatherings, I started regular cardio a few times a week (first running then cycling), I started regular resistance training, etc. I am not militant about any of these and have cheated a number of times on all of it because I think sticking to it 90% of the time produces 90% of the benefit. As a result I've improved a number of biomarkers (e.g. resting heart rate, resting blood glucose, strength, endurance, nutritional deficiencies, etc). I wish I could say I feel significantly better or sharper, but honestly I feel about the same. But the numbers tell me I'm supposed to be on a better path and I think I am content with that 🤷.
+**Other stuff**. I should mention that despite the focus of this post the experiment was of course much broader for me than weight loss alone, as I tried to improve many other variables I started to understand were linked to longevity and general well-being. I went on a relatively low carbohydrate mostly Pescetarian diet, I stopped eating nearly all forms of sugar (except for berries) and processed foods, I stopped drinking calories in any form (soda, orange juice, alcohol, milk), I started regular cardio a few times a week (first running then cycling), I started regular resistance training, etc. I am not militant about any of these and have cheated a number of times on all of it because I think sticking to it 90% of the time produces 90% of the benefit. As a result I've improved a number of biomarkers (e.g. resting heart rate, resting blood glucose, strength, endurance, nutritional deficiencies, etc). I wish I could say I feel significantly better or sharper, but honestly I feel about the same. But the numbers tell me I'm supposed to be on a better path and I think I am content with that 🤷.
 
 **Explicit modeling**. Now, getting back to weight, clearly the overall rate of 0.58lb/week is not our expected 1lb/week. To validate the energy deficit math I spent 100 days around late 2019 very carefully tracking my daily energy input and output. For the input I recorded my total calorie intake - I kept logs in my notes app of everything I ate. When nutrition labels were not available, I did my best to estimate the intake. Luckily, I have a strange obsession with guesstimating calories in any food, I've done so for years for fun, and have gotten quite good at it. Isn't it a ton of fun to always guess calories in some food before checking the answer on the nutrition label and seeing if you fall within 10% correct? No? Alright. For energy output I recorded the number my Apple Watch reports in the "Activity App". TLDR simply subtracting expenditure from intake gives the approximate deficit for that day, which we can use to calculate the expected weight loss, and finally compare to the actual weight loss. As an example, an excerpt of the raw data and the simple calculation looks something like: