I did the same sort of analysis of my last 150 days of Cronometer data that I did for protein and carbs, but compared day-to-day weight change to the amount of fat consumed. Here’s the scatter diagram for that data:
For me, this explodes the myth that to lose more weight you need to eat more fat. To be more accurate it is true from around 60 to 120 grams of fat that the more fat I ate the more weight I lost the following day. But the curve quickly reverses after that and shows a fairly straight rise. Past around 175 g of fat the weigh increases the next day.
Since I’m looking at data, what is the effect of calories one day on weight the next day? Here’s the chart of calories vs weight change the next day.
Some observations about the data.
- The vertical axis is weight change the day after.
- The horizontal axis is calories eaten the day before the change.
- Calories in and weight increase out seems to work.
- My crossover point seems to be around 2450 calories. That’s pretty close to the Cronometer estimate of what I am expending.
- Next day increases are exaggerated versions of calories consumed. I went out to Red Robin last night and had three big plates of the salad bar. This morning I went up 3+ lbs. There’s no way I ate 10,000 calories at the salad bar, but I believe I could have 3 lbs of veggies in my system.
This confirms calories in and calories out on some rough level. It’s not simple and the error bars of uncertainty are huge, but taken together it shows that if I eat more the the 2450 calories I gain weight and if I eat less I lose weight.
One thing I’ve often wondered about since starting this low carb journey is just what my personal sensitivity to net carbs is. In other words, how many grams of net carbs can I eat without gaining weight? I’ve now got a 150 day long data set which gives me an answer. This chart shows how much the grams of carbs I eat one day affects my weight the next day.
About the chart:
- The vertical axis is weight gained the next day.
- The horizontal axis is grams of carbs.
- The red line on the chart is a 3rd order polynomial trendline as determined by EXCEL.
At less than 20 grams of carbs the line is pretty flat. It doesn’t seem like reducing my carbohydrates below 20 grams has much of a payoff in weight loss.
The turnaround point seems to be around 32 grams of net carbs. Past that point my weight gets progressively higher the next day.
From this I would conclude that my personal carbohydrate threshold is around 32 net grams of carbohydrates but that I can tolerate up to around 40 net grams without a large effect.
In my last post I looked at the question of whether eating protein one day causes weight gain the next day (“Protein Makes Me Gain Weight The Next Day”). Turned out protein didn’t make me gain weight all the way up to past 1 grams per pound of body weight.
This post looks at the maintenance macros I got from Ted Naiman’s website as described here (Maintenance Macros – Dr Ted Naiman). I have 150 days of Cronometer data and looked at the Protein to Non-Protein Energy ratio vs day-to-day weight gain.
Ted’s method sets the grams of protein starts to your body weight in lbs. Use the same number of grams of non-protein (carbs and fat) to maintain your weight. For me, that’s 170g of protein, 150g of fat, and 20g of carbs. With this method there’s no need to convert the number of grams to calories.
What does my own data show for Protein to non-protein ratio vs day-to-day ratio?
Here’s what I find interesting in the data:
- The vertical axis is weight change day-to-day. The zero line means that I did not change weight the next day.
- The day-to-day variance is pretty big.
- The horizontal axis is the ratio of Protein to Non-Protein grams. Most of my numbers were 1.0 or greater since I was trying to cut weight most of the time. That means I had more grams of protein than grams of fat+carbs.
- This graph looks at trendlines to generalize out the large day-to-day variances.
- The trendline is a 3rd order polynomial.
- There are only a couple of data points above a ratio of 2.0 to base the swing up after 2.25 on. It may not be a real swing.
- The best ratio for me to have the most loss the next day is around 1.75 grams of protein to grams of fat+carbs. Since I tend to hit my body weight or more in protein that would mean that I am eating relatively low fat on those days.
- There is a near zero crossing around 0.8:1 (which is more fat than protein). Ted’s numbers indicate the zero cross is around 1:1 which isn’t too far off from my numbers.
- Below the 0.8 I have a tendency to increase in weight.
All of this matches Ted’s concept. Here is Ted Naiman’s infographic:
Ted’s numbers for maintenance are pretty close to my actual measurements. I may have to eat a bit more fat to get to my goals of maintenance – which fits my experiences in the past month or so.
[This post replaces an earlier post which had an error in the spreadsheet data].
A common complaint I see on the Internet is
“When I eat more protein my weight goes up the next day.”
I rarely see anyone dig deeper into the question of whether higher consumption of protein actually causes greater weight gain the next day spread across time. A single day doesn’t say much about the effect of protein on weight.
A lot of days of eating protein
I have the last 150 days of data from Cronometer so I looked at how much my weight goes up the day after I eat protein. This is a chart of protein consumption compared to weight change on the following day.
A couple of things to note about this graph:
- The diagram is a scatter diagram.
- The Y axis is weight change between two adjacent days. Day to day weight fluctuations are all over the place.
- The X axis is grams of protein eaten the day before the weight change.
- The data is all over the place.
- The data appears to increase somewhat. More protein should on some level correspond to more weight gain (or less weight loss) since it’s more calories.
- The red line is the trendline that EXCEL determined.
- The trendline is a 3rd order polynomial.
- The deviation from the trendline is really big.
- The trendline shows that under 190 grams of protein (a whole lot of protein) results in weight loss (on the average).
- My weight is currently around 167 lbs.
- About 190 grams of protein results in weight stability (a bit over 1 gram of protein per lb of my weight).
- More protein than 190 grams results in a very small weight increases all the way to over 30 grams of protein.
- Very low protein (less than 100 grams) results in the most weight lost. It is not clear what the nature of this loss is from this chart. Is it more lean body mass lost? Is it just the low calorie amount for the day?
- I don’t have any very low protein data since I think it’s a serious mistake to undereat protein.
Protein, up more than 1 gram per lb of body weight did not result in average day-to-day weight gain.
Your mileage may vary. I am not sure how it could vary by much, but it may.
It’s often claimed that a fat weighs more than muscle. Some even go so far as to claim that a pound of fat weighs more than a pound of muscle. There are even graphics produced which show huge differences in volume such as:
Or the much more ridiculous graphic:
What people really mean is that fat is less dense than muscle. Oil, for instance, floats on top of water. That is because oil is less dense than water.
On average, the density of fat is 0.9 g/mL. The density of muscle is 1.1 g/mL. Using the averages, 1 liter of muscle weighs 1.06 kg, or 2.3 lbs., while 1 liter of fat weighs .9 kg, or 1.98 lbs. (Source)
The difference is less than 20%.
(Image from Bannister Nutrition).
I wrote the following to respond to a post about Jason Fung on Carb Sane (Diabetes Un-Funged). Her central thesis is that exogenous Insulin doesn’t cause Insulin Resistance.
I was a T2DM for 13 years (and probably undiagnosed for 8 years before that).
Two years ago, I went from 100 units a day of Insulin (Medtronics Pump) to zero in two weeks following Fung’s methods (Low Carb and Intermittent Fasting) with great blood sugar levels. I did Low Carb in the past and it helped me get a decent HbA1C but not out of the diabetic range. Fast forward 22 months and I am down 120 lbs (current weight is 165). My HbA1C was 5.2 a few months ago. No longer on HBP meds (I was on them for 20 + years). All of this while following Fung’s methods (Low Carb and Intermittent Fasting).
As to the progression of Insulin and loss of blood sugar control points in your article. In my own case I went from 40 units of Insulin with good control to 100 units with poorer control (higher HbA1C) in 4.5 years. The more I tried to control my blood sugar with Insulin the higher the amount of Insulin I required kept getting.
Worse yet the real surrogate of Insulin Resistance is the ratio of grams of carbs to units of Insulin. Anyone who has been on Insulin for a long time can testify that this ratio degrades with time. At the start, 1 unit of Insulin would cover 15 grams of carbohydrates and 4.5 years later one unit would only cover 4 grams of carbs. Clearly (at least to me) this is evidence of progressive insulin resistance).
Even if you don’t agree with Fung’s reasons his method is essentially the same as yours (Low Carb). Problem for me was that without having an intermittent fasting window I would have just had lower Insulin requirements – not a cure, but a decent treatment. I got to HbA1C of 6.6 with Low Carb and Insulin.
And it wasn’t about weight loss since most of what someone loses in the first week or two is water weight. I think it was more about leaning out the liver and then leaning out the fat around the pancreas than anything else…
Incidentally, this wasn’t about titrating the dosage of Insulin over the four and a half years. The “honeymoon period” is well known among people who start using diabetes meds – including Insulin. It isn’t long until more is required as the body becomes more resistant to the insulin.
Another line of evidence is the studies showing that hyperinsulinemia precedes diabetes and obesity often by decades.
The top rates of fat oxidation (fat burning) are around 1.5 g/min at high intensity levels. At that level an hour would burn 90g of fat or 810 calories. Marathon runners are said to expend about 1,000 calories an hour but that might be largely carbohydrates (around 75%).
Lightly active fat oxidation rates are 31 g/lb of fat mass per day (Hypophagia – How much fat can I lose in a day?). Assuming a 170 lb person with 10% body fat that’s 17 lbs times 31g/lb = 527 cals a day. At that body fat it would take a week to lose a lb. This also means that the diet can’t be at a larger caloric deficit than that amount (exercise as above is the exception).
Assuming that the 170 lb person expends about 12 calories per lb of body weight that’s a daily caloric expenditure of 2040 calories. Cutting calories for a caloric deficit to around 1500 would result in maximum fat loss.
But this is only true if the person gets enough protein. Ideally, that would be around 0.8 g per lb of lean body mass for a lightly active person. This person would need to eat 136g of protein a day.
Eating the protein in four meals of at least 30 grams of protein would spare the most muscle mass while rapidly losing weight.
Macros would then be:
- 136 g protein
- 20 g carbs
- 97 g fat
It might be tempting to drop fat or protein but that would be a mistake since it would not result in larger losses.
Combine that with intense activity (as noted) a greater weight of loss can be achieve.
I have a calculator for this at Keto Calculator.
Contrary to much of the marketing hype, exogenous ketones inhibit fat loss. Ketones generated from the person have the following characteristics (Brianna J. Stubbs, Pete J. Cox, Rhys D. Evans, Peter Santer, Jack J. Miller, Olivia K. Faull, Snapper Magor-Elliott, Satoshi Hiyama,3 Matthew Stirling, and Kieran Clarke. On the Metabolism of Exogenous Ketones in Humans. Front Physiol. 2017; 8: 848.):
The metabolic phenotype of endogenous ketosis is characterized by lowered blood glucose and elevated Free Fatty Acid (FFA) concentrations, whereas both blood glucose and FFA are lowered in exogenous ketosis. During endogenous ketosis, low insulin and elevated cortisol increase adipose tissue lipolysis, with hepatic FFA supply being a key determinant of ketogenesis.
Ketone bodies exert negative feedback on their own production by reducing hepatic FFA supply through βHB-mediated agonism of the PUMA-G receptor in adipose tissue, which suppresses lipolysis (Taggart et al., 2005).
Exogenous ketones have similar effects.
Exogenous ketones from either intravenous infusions (Balasse and Ooms, 1968; Mikkelsen et al., 2015) or ketone drinks, as studied here, inhibit adipose tissue lipolysis by the same mechanism, making the co-existence of low FFA and high βHB unique to exogenous ketosis.
If your goal is weight loss from your body, exogenous ketones are probably a poor choice.
A rat study showed MCT Oil increased liver size (Shannon L. Kesl,corresponding author Angela M. Poff, Nathan P. Ward, Tina N. Fiorelli, Csilla Ari, Ashley J. Van Putten, Jacob W. Sherwood, Patrick Arnold, and Dominic P. D’Agostino. Effects of exogenous ketone supplementation on blood ketone, glucose, triglyceride, and lipoprotein levels in Sprague–Dawley rats. Nutr Metab (Lond). 2016; 13: 9.).
MCT supplemented animals had significantly larger livers compared to their body weight (p < 0.05).
The study offered a possible explanation for the larger liver size.
The ratio of liver to body weight was significantly higher in the MCT supplemented animals (Fig. 5). MCTs are readily absorbed in the intestinal lumen and transported directly to the liver via hepatic portal circulation. When given a large bolus, such as in this study, the amount of MCTs in the liver will likely exceed the β-oxidation rate, causing the MCTs to be deposited in the liver as fat droplets. The accumulated MCT droplets in the liver could explain the higher liver weight to body weight percentage observed with MCT supplemented rats.
The rats were fed a large amount of MCT Oil.
It should be emphasized that the dose in this study is not optimized in humans. We speculate that an optimized human dose would be lower and may not cause hepatomegaly or potential fat accumulation.
Another study indicates positive results when MCT Oil replaces Corn Oil (Ronis MJ, Baumgardner JN, Sharma N, Vantrease J, Ferguson M, Tong Y, Wu X, Cleves MA, Badger TM. Medium chain triglycerides dose-dependently prevent liver pathology in a rat model of non-alcoholic fatty liver disease. Exp Biol Med (Maywood). 2013 Feb; 238(2):151-62.).
These data suggest that replacing unsaturated fats like corn oil with MCT oil in the diet could be utilized as a potential treatment for NAFLD.
This could be something that people who love their Bulletproof Coffee might want to pay attention to.