The 1 Really Important Thing We Didn't Tell You About Losing Weight

The most interesting part of 10 Things You Need to Know about Losing Weight was the segment which focussed on an overweight actor. This lady revealed that she had always been large and that she felt that she had a 'slow metabolic rate'. She also stated that she had given up worrying up about her weight or trying to diet and just concentrated on eating a healthy diet and being active. Clearly, neither was helping her to lose weight.

This idea that you are overweight because you have a body that burns food off more slowly is, of course, a common belief, but it isn't the case. Indeed, as Gary Taubes explains in his book Good Calories, Bad Calories [Alfred A. Knopf, NY, 2007] in the chapter Paradoxes (p. 278):

The most obvious difficulty with the notion that a retarded metabolism ... is that it never had any evidence to support it. ... Magnus-Levy had reported that the metabolism of fat patients seemed to run as fast if not faster than anyone else's. .... The obese tend to expend more energy than lean people of comparable height, sex, and bone structure, which means their metabolism is typically burning off more calories rather than less. When people grow fat, their lean body mass also increases. They put on muscle and connective tissue and fat, and these will increase total metabolism...

For example, from Fitday, I, at 5'4" and 8 stone 3lbs, with a sedentary type of job require 2050 calories per day, whereas if I was 12 stone, I would need 2432 calories. As predicted, the metabolic rate for the subject of this segment came up perfectly normal.

Next came an investigation into how much she was eating. Looking at the lady in question, I guesstimated 3000 calories per day for her. She thought she was eating 1900 calories or less. As most people really have no idea about calories and portion sizes, I don't find this surprising and I don't think it's a deliberate or even an unwitting self-deception. It's just understandable, because humans didn't evolve doing complicated calorie counts before putting food into their mouths.

The test involved a 9-day diet record. Some of this was a video food diary plus a written food diary. The food that we saw looked perfectly reasonable: chicken and vegetables (though, my goodness - a whole head of broccoli?), (a very large) fruit salad, something dipped into a cup of coffee or tea. The guinea pig also drank doubly-labelled water so that the team could monitor her caloric intake. The result given to us was that she had underreported her food intake by 43% and that her actual intake was 3000 calories per day (score one me!)

Two things need commenting on here. Firstly, the underreporting. So what? It is fiendishly difficult to estimate portion sizes. I should know, I do it quite a lot to use Fitday. I try to be quite accurate, occasionally weighing or measuring to try and learn to 'eyeball' - say 30g of cheese or 1 oz of ham. On the other hand, there is a temptation to cheat. In my case, if I see the carbs going too high, there is a definite urge to downsize my estimates, even if this is silly because I'm only denying reality.

Secondly, what we weren't told. We weren't told what her energy expenditure was. We were told that the doubly-labelled water technique told the team that her caloric intake was 43% higher than her food diary records showed. The implied conclusion was that she was overeating - here we go, she thinks she's eating 2000 calories a day and she's actually eating 3000 calories a day and so she's fat. Whereas in fact that's probably not the case. She would probably be in energy balance - most people are, even fat people - they plateau at a certain weight, they don't all keep on getting fatter and fatter and fatter....

Now I thought this at the time, but I didn't know how right I was because then, to write this post I looked up the doubly-labelled water technique to see how it worked and found this :

the term doubly-labeled water test refers to a particular type of test of metabolic rate, in which average metabolic rate of an organism is measured over a period of time.

and:

Energy expenditure measurements are easier to perform since the development and application of the doubly-labelled water technique.*

In other words, to work out that she was eating more calories than she said, they proved that she was using that many calories because the test itself measures energy expenditure not actual energy intake! But they didn't tell us that and they didn't draw the obvious conclusion that she was in energy balance! Certainly, if she ate less than 3000 calories a day she could draw on the stored fat and not starve. But, as she had pointed out herself at the start of the segment, she was not trying to diet and just trying to 'eat healthily'. Possibly to a dietician or nutritionist 'eating healthily' for an overweight person, by definition ought to mean dieting. However, the point is that just eating normally, she was not overeating, she was just eating as much as she needed to maintain her body - including all the extra fat - without discomfort or hunger.

Clearly, if she could only mobilise that fat and burn it up, she could eat less, so what is stopping that? The reason the fat mass isn't simply used as fuel as soon as we restrict calories is to do with the interplay of hormones in the body. In the simplest terms, if you have too much circulating insulin, then it promotes storage of fat in fat tissue and glucose burning in muscle. It does this because its job is to get excess glucose out of your blood because high blood sugar is damaging. Only if your insulin level is low, can your fat tissue release fat into the bloodstream and your muscles burn fatty acids.

The carbohydrate hypothesis of obesity basically says that carbohydrate intake promotes insulin release which promotes fat storage and the conversion of excess glucose (all starch breaks down into glucose) into fat for storage. So a person who eats a 'healthy diet' that would be 50-60% 'healthy' carbohydrates - 6-11 servings a day of cereals anyone? plus lots of fruit but is quite sensitive to this effect of insulin would convert all the excess to fat and store it. If they are unlucky their insulin stays relatively high preventing their body accessing this stored fat. Now they are 'growing' (but outwards) and as long as enough carbohydrates are consumed to keep insulin 'too high' for fat burning, their appetite tells them they need to eat more and so on it goes.

And that is why all nutritionists and dieticians and doctors should read Gary Taubes' book Good Calories, Bad Calories - published as The Diet Delusion in many countries.

*from Invited Commentary, Energy requirements assessed using the doubly-labelled water method, Klaas R. Westerterp, British Journal of Nutrition (1998), 80, 217–218. Available here.

Review of 10 Things You Need to Know About Losing Weight

I managed to watch 10 Things You Need to Know About Losing Weight (BBC 1, 9pm) last night without throwing anything at the screen - click here for a link to the program (may be available in the UK only) or here for a related BBC Magazine article - but this may just have been because my hands were occupied taking notes so that I could blog about it.

Here are the 10 things:

1. Not sure what they called this, seemed to be a variation on: Don't go shopping when you're hungry. The presenter had his brain MRI scanned, firstly on a full stomach, on a second occasion on an empty stomach, and while being shown pictures of food. His brain 'lit up' more in response to 'high calorie' food (chocolate eclairs) than 'low calorie' food (cucumber slices) when he was hungry; whereas when he wasn't hungry the response was the same.

Use of an expensive machine to discover the bleeding obvious: when you are hungry, you are more interested in food and, more than that, more interested in food that your brain knows (from prior experience) is more likely to provide you with calories. Actually, I suppose this kind of research is necessary - we should investigate 'what everybody knows' - and try and disprove it - that is the scientific method. It also raises another interesting point - which wasn't mentioned in the program (although to be fair it isn't strictly relevant). Why doesn't the hungry brain respond to pictures of fruit and vegetables? Perhaps it's because humans didn't evolve chewing their way through bucketloads of plant matter for hours?


2. Use plate size to trick the brain about portion size, i.e. use a smaller plate - less food will look like more.

Personally, I think this works, I've used it with children the other way round - i.e. put the food on a larger plate and it looks like less so they eat it up. However, if you don't eat 'enough', you may end up hungry later on and snack!


3. Count calories - save a few here and a few there e.g. have black coffee instead of cappuccino, and it will add up to fewer calories over the day/month/year, leading to you magically losing weight.

Or maybe you'll just be hungrier? Has there ever been a controlled trial of this idea to see if it actually works?


4. Fat people eat more than they think they do.

Actually this was the most interesting point and worth a separate post of its own.


5. Eat protein because it leads to greater satiety.

This was demonstrated with a small-scale experiment during the programme. It has been shown by studies.


6. Liquid food (as opposed to drinks with food) fill you up for longer. This was also demonstrated with an actual experiment.

This point is different from the preceding one: the mechanism here is one of the physical constraints on digestion, whereas the fullness from protein comes from the release of a hormone (PPY) which interacts with other appetite regulating hormones (leptin, ghrelin). If you use soup to 'trick' your body into eating fewer calories than usual, you will likely eat more at the next meal, once the soup has been digested.


7. Choice causes overeating.

I thought the 'experiment' conducted to show this was quite poor. Two bowls of equal quantities of sweets were left out in an office canteen with a sign Free Sweets: one bowl was obviously smarties, the other bowl held purple smarties only. The smarties all disappeared, the purple ones didn't. A better comparison would have been smarties vs. chocolate buttons (they're all the same). The purple smarties looked vaguely medicinal - how do we know that didn't put people off?


8. Calcium in dairy binds fat which you then excrete: over a month this can save you calories.

In fact, it saved the guinea pig in this experiment slightly more than 5g of fat per day or about 160g per month. (Sounds like a lot? - I eat that much fat every day! I'm not going to quibble about the loss of one day's consumption per month.) Interesting - bad for dairy's image as a source of calcium - how much of the dairy calcium is lost this way? Also, the presenter felt constrained to recommend 'low-fat' dairy for this strategy. Noteworthy that this was the only vestige of 'low-fat' dogma in the programme. On the other hand, if it truly is 'low-fat' dairy then there isn't much point is there - where's it gonna find the fat to bind?


9. Exercise - another interesting one. An experiment with the presenter on a treadmill showed that 90 minutes of fairly fast-paced walking (he was quite breathless after it) only burned about 19g of fat (171 calories).

Given that after 90 minutes of fast-paced walking you've probably built up a bit of an appetite, it isn't going to do much for weight loss is it?
However there is a punchline - an 'afterburn' effect where exercise boosts 'fat-burning' into the next day. So this could work - but there is still that question: why will the greater amount of calorie burning going on, not prompt your body to ask you for more food?
Update: the effect of exercise to promote 'fat burning' is disputed by research - see article here.


10. Small amounts of extra movement during the day e.g. take the stairs instead of the lift, will boost your calorie burning.

Can't argue with this really, but the effect will be small (90 minutes on a treadmill = 171 calories) and once again it ignores the hormonal elephant in the room - which will be tackled in the next post about point 4.

Atherogenesis in Mice

Another day, another plug for the diet-heart hypothesis in BBC Health, even when the study being reported on Scientists pinpoint fats danger is really about molecular genetics(Thorp et al.,Reduced Apoptosis and Plaque Necrosis in Advanced Atherosclerotic Lesions ofApoe and Ldlr Mice Lacking CHOP, Cell Metabolism ,Volume 9, Issue 5, 474-481, 6 May 2009, subscription required). The study showed that mice lacking a gene (CHOP) which helps to trigger cell death (apoptosis) had a 35% smaller area of plaques and 35% less apoptosis and 50% less necrosis (dead tissue) in plaques. To quote the researhers directly (as reported by the BBC):

Lead researcher Dr Ira Tabas said that previous research had suggested that this mechanism might be involvedin plaque rupture, but the magnitude of the effect uncovered in the latest study was a surprise.
He said: "The fact that we were able to isolate one gene encoding one protein with such a profound effect on plaque necrosis (death) was a big surprise."
Dr Tabas said the finding raised hopes of new drugs which could act on the key gene, or the associated mechanism, to cut the risk of dangerous plaques.
"Just about everybody in our society has atherosclerosis (thickening of the arteries) by the time we reach 20," he said.
"So the wave of the future in treating atherosclerosis will be in preventing harmless lesions in young people from becoming dangerous ones, or soothing dangerous plaques so they don't rupture as we age."

Never mind what effect such a treatment might have on necessary cell death (e.g. to deal with emerging cancers) in other parts of the body.

Anyway, what does this have to do with diet and the heart? Well, again from the BBC article:

Scientists have identified a genetic mechanism which appears to determine which fatty deposits in the arteries have the potential to kill us. Most of these plaques pose no risk to health, but a minority burst, forming blood clots, which can cause heart attacks or strokes. .....
Fatty deposits begin to form in the arteries of most people in their teens, but the vast majority are harmless.

Here we see the perpetuation of the myth that fat just floats around in the bloodstream clogging up our arteries like it would a drainage pipe. Plaque formation is a much more complex process than that and its genesis is still not fully understood (see for example, extensive discussion here or here).

But, ah you say, just read on ...

The researchers bred mice prone to develop plaques, and fed them a high-fat diet for 10 weeks.

So what was this high-fat diet? It was the TD.88137 Western Diet (Teklad Lab Animal Diets, Harlan Laboratories, Madison, WI) which consists of:

	g/kg
Casein	195.0
DL-Methionine	3.0
Sucrose	341.46
Corn Starch	150.0
Anhydrous Milkfat	210.0
Cholesterol	1.5
Cellulose	50.0
Mineral Mix, AIN-76 (170915)	35.0
Calcium Carbonate	4.0
Vitamin Mix, Teklad (40060)	10.0
Ethoxyquin, antioxidant	0.04

(Data from this pdf.)

This diet is 17.3% protein, 48.5% carbohydrate and 21.2% fat by weight, but 15.2% protein, 42.7% carbohydrate and 42.0% fat by energy, thus approximating a typical Western-style diet which is high in fat and simultaneously high in carbohydrate. Note that of the carbohydrates 70.4% by weight is sucrose! The mice are eating 30% of calories as sucrose. Now mice are not little people, but what does that kind of intake do to people?

How does this compare to a mouse's real diet?

From The Mouse in biomedical science (James G. Fox, Stephen W. Barthold, Muriel T. Davisson, Christian E. Newcomer, 2nd ed., Academic Press, 2007) p. 28 we learn that it is still debated whether mice are granivores, eating a wide range of cereals, oilseeds, and a variety of grass and plant seeds, or whether they live on a mix of plant and animal sources. However from the evidence presented in this book it appears that in many environments, mice eat small invertebrates for at least part of the year (i.e. when seeds are in short supply) or to supplement plant seed diets.

In short, the typical composition of a diet of invertebrates is high in fat and protein e.g. from p.41 in Marsupial nutrition, (Ian D. Hume, Cambridge University Press, 1999) it can range from 20-60% fat and 10-75% protein (by weight of dry matter) for typical things that a mouse might eat (insects and insect larvae). Cereals are typically 68-79% carbohydrate, around 10-15% protein and 2-7% fat, legumes are as much as 25% protein, typically 50-60% carbohydrate and only 1-2% fat whereas nuts (e.g. hazelnut) and oilseeds (e.g. sunflower) are typically about 15-25% protein, 50-60% fat and 15-20% carbohydrate (from various tables in On Food and Cooking, H. McGee, 1st ed. Unwin Hyman, 1984).

From this we can conclude that a typical wild mouse would for part of the year eat a diet that was mainly protein and fat and for another part of the year eat a diet that was high in carbohydrate - at least if it ate cereals, but not so much if it ate other types of seeds - but low in fat. It would not however be eating a lot of sucrose. The carbohydrate in grains and seeds is starch which is a polymer of glucose and does not contain fructose. As further support of this analysis here Peter of Hyperlipid considered data on what wild-type mice eat when given free choice: about 12% protein, 6% carbohydrate and 82% fat (all as proportions of energy).

A final note about the mice. The mice used in the experiment were either apoe or ldlr mice. Apoe mice lack a particular lipoprotein (apolipoprotein E) which is important in both the HDL and vLDL cholesterol transporters, in particular:

ApoE mediates high affinity binding of chylomicrons and vLDL particles to the LDL receptor, allowing for specific uptake of these particles by the liver, preventing the accumulation of cholesterol rich particles in the plasma
.....
Mice develop normally, but exhibit five times normal serum plasma cholesterol and spontaneous atherosclerotic lesions

Ldlr mice lack a proper LDL receptor and essentially mimic (familial) hypercholesterolaemia with a very high circulating LDL level and an increased propensity to develop atherosclerotic lesions amongst other things.

Does this not indicate that fat is the root cause? Well not necessarily.

vLDL is made in the liver to transport triglycerides (made from excess carbohydrates intake) to the tissues for use and storage. At this stage, it does not contain apoE: it has to pick that up from HDL on the way. ApoE contributes to its recognition and re-uptake by the liver after it has performed its delivery task or it loses its apoE and becomes an LDL particle and is taken up by body cells with an LDL receptor. So, this process will become disrupted in an apoe mouse which does not have a proper apoE protein. No wonder it ends up with excess blood cholesterol (which really means excess circulating lipoproteins). Similarly as ldlr mice lack the LDL receptor, they cannot remove the LDLs left at the end of the described process. On the other hand, after digestion, fat is absorbed either directly into the bloodstream - if the molecule is small - which gets it to the liver (where it may contribute to triglyceride production) or, for larger molecules, as chylomicrons which go via the lymphatic system into the bloodstream and from there directly to fat tissue for storage or to the liver to be used to provide fuel.
So which is more likely to contribute to the problem - the 21.2% of food (by weight) that comes as fat (most of which doesn't go straight to the liver anyway) or the 48.5% of food (by weight) that comes as carbohydrate - three-quarters of which is sucrose and half of that is fructose (i.e. 17% by weight of the total food intake) which goes straight to the liver and comes out as triglycerides.

Mediterranean Diet Score - What else does the model tell us?

A further analysis of the expected (from the model) vs the observed numbers within each diet score category and eating particular amounts of each food group throw up more interesting observations. This doesn't mean that we are claiming that people should behave like the model and that we expected that their food choices would not be internally correlated in some way. In fact, we expected that they would be (so do these researchers which is why they are trying to describe a dietary pattern); this data gives us information on what these correlations are.

We have already noted that meat & poultry intake is actually largely independent of the diet score. So, when researchers claim that a Mediterranean diet is low in meat, we will know that that is not borne out by this data.

Comparison of expected vs actual numbers in the low score (0-3) group shows that there are more people getting a low score because they score 0 for vegetables, fruit & nuts, legumes or fish consumption (i.e. they don't eat 'enough' of these). Conversely, in the high scoring group (6-9) there are more people than expected scoring a 1 in these same categories. There are also more people than expected scoring a 0 for meat & poultry, dairy and cereals in the high scoring group, i.e. they get a high score while still eating 'bad' amounts of these food groups. The suggestion here then is that the diet score is mainly a reflection of vegetable, fruit & nut, legume and fish consumption and is much less related to dairy and cereal consumption as well as being independent of meat consumption.

What about the predicted correlation between meat & poultry, dairy and the monounsaturated/saturated fat ratio? Whether this has any impact is very hard to determine. The main reason for this is that the postulated effect is obscured by the data presentation. To see why consider this thought experiment:

Let's assume our subject has a score of 6 so far and we have meat & poultry, dairy and the fat ratio still to determine. If either meat & poultry or dairy score 0 (i.e. greater than median consumption), this increases the chance that the fat ratio will also be scored 0, giving a final score of 7; if both meat & poultry and dairy score 0, then there is an even greater chance of fat ratio being 0, giving a final score of 6. But, we can't see the difference (i.e. that there are proportionally more scores of 6 and 7 and fewer of 8 than expected) because all scores 6-9 are lumped together. The same argument works in the other direction, making the scores 2 and 3 potentially more frequent than scores of 1, but again this effect is obscured when the low score includes 0-3. Perhaps this is why?

Data Patterns in the Mediterranean Diet Score

The original construction of the edifice known as the Mediterranean Diet began with a paper which used a scoring system to handle the mass of data that results when you give thousands of people food frequency questionnaires. The data manipulation is roughly like this: People say how often and how much they eat of typical dishes and foodstuffs; these quantities and frequencies are converted to daily food group consumption for which a score is given. RESULT massive amounts of data reduced to one number.

Let's recall the basics: the food groups were: vegetables, fruits & nuts, legumes, meat & poultry, fish, dairy products, cereals, monounsaturated to saturated fat intake ratio and alcohol intake. The bad score was 0 for eating more of the bad groups (meat & poultry, dairy, low mono to saturated fat ratio and alcohol) and not enough of the good groups (vegetables, fruit & nuts, legumes, fish, cereals) and the good score was 1 for doing the opposite. When these scores are added up, the lowest possible score (bad) is 0 and the highest (good) is 9.

Now, it turns out that the pattern of scores expected can be modeled by a mathematical probability distribution known as the binomial distribution. Strictly speaking, to adopt this model of the situation we need to make two assumptions about the behaviour of the participants. Firstly, we assume that each participant is operating (i.e. choosing foodstuffs and quantities of these to eat) independently of (i.e. not influenced by) each other participant (this is quite likely) and secondly, we need to assume that a participant's scoring on each food group is independent of (i.e. not influenced by) the score of other food groups. This second assumption is not entirely true, for example, it is clear that there would be some correlation between both dairy products and meat & poultry consumption and the monounsaturated/saturated fat ratio. However, for now, let's make this assumption and then we can check whether the actual data support this view.

With this model for the scoring process, it becomes possible, given the total number of participants, to calculate the expected numbers with different scores. It is quite easy to see that, given the way the scoring system has been constructed, there will be a full spread of scores, because on every food item, there is a 50-50 chance of scoring 0. Another point to consider is that, with the exception of scores 0 and 9, there are multiple ways of obtaining the other scores. For example, a score of 1 may be obtained by being above the median on one and only one of the 9 food groups - which means there are 9 different ways of getting this score. Whereas a score of 2 may be obtained by combining a score of 1 from 2 out of 9 groups: there are 36 ways of doing this. For the most likely scores of 4 and 5, it can be shown that there are 126 different ways to obtain each of these scores.

Table 2 (and you should look at this table while reading the next bit) in the paper shows the individual food group scores versus the Mediterranean diet score. This table is important because it gives some insight into the raw results of the scoring process which is otherwise obscured because score results for the individuals are grouped into three categories: low diet score (0-3), medium (4-5) and high (6-9). This is distinctly unhelpful and does not let us see how many got each individual score. However we can see – within each diet score category – how many people scored 0 or 1 for a particular food group (i.e. how many people ate more than the median amount and how many ate less than it - or vice versa).

Using the binomial distribution and the total number of individuals, it is possible to predict how many people should score 0 or 1 for each food group in the three diet score categories under our assumptions outlined above. (But note that we will get the same prediction for each and every food group because the model makes no distinction between these.) For example, for men in the category of low diet score (0-3), we would expect 2257 individuals and to see only 643 (28%) scoring 1 but 1616 (72%) scoring 0. In the category of medium diet score (4-5) 4378 individuals are expected, with equal numbers scoring 0 and 1 and in the category of high diet score (8-9), we would expect to see 643 of 2257 (28%) scoring 0 and 1616 (72%) scoring 1.

How does the prediction compare to the actual values? Quite well in fact for legumes and fruit & nuts (both 23%/77% and 50/50 in the medium score category) and dairy products (31%/69% in the low and high categories and 50/50 in the medium category) not quite so well for fish, vegetables and fat ratio where the ratios are actually 'more extreme' than predicted (18%/82% or 20%/80% in the low and high score categories). Cereals (36%/64%) and meat & poultry show the worst correspondence where the ratios are 'less extreme' than predicted. Overall we slightly overestimate the number in the medium score category (actual number 3808) and underestimate the numbers in the low and high categories.

There are some foodstuffs included in Table 2 which are not included in the calculation of the Mediterranean diet score: eggs, potatoes and sweets. As they are not used to calculate the score, it can be expected, that any participant in any diet score group would be equally likely to be above as below the median consumption of these items and so there would be approximately a 50%/50% split in the consumption in each diet score category. A sizeable departure from these figures would suggest that the participant's consumption of these non-scoring foodstuffs is in some way dependent on or linked to consumption of a scoring food group. However, this is clearly not the case, except possibly for potatoes, which show about 16% deviation from the expected 50-50 split in favour of (unsurprisingly) vegetables.

This leads to the most notable find in this table - a point which was completely unmentioned in the original article. The distribution of meat and poultry consumption appears to be essentially independent of the Mediterranean diet score. Within each scoring category, the distribution of above and below median consumption for meat and poultry is much more like that of eggs and potatoes and sweets than it is of the other items making up the diet score. Whatever the diet score group, there is close to a 50-50 split in the distribution of individuals' meat consumption. On a Chi-sqared test on the actual versus the expected values, the meat and poultry item shows the strongest result for independence in common with the foodstuffs which are independent of the diet score (e.g. eggs, potatoes, sweets) because they are not used in its calculation. It is interesting that this result is not remarked upon in the paper. In fact, to the contrary, when giving an example based on the link between a 2-point increment in the diet score and improved survival, it is mentioned that such an increment could be achieved by `making a substantial reduction in meat intake' despite the evidence that many high scorers score highly in spite of an above median meat intake!

When epidemiology works

Sometimes epidemiology produces a reasonable result. Take this recent story.

Researchers note that somewhere has a very high rate of a relatively rare condition. In this case a province of Iran with a high rate of oesophageal cancer. The first step in such a situation is often the case control study. This is a study done on the basis of matching people already diagnosed with the condition as closely as possible with controls who do not have the condition and then attempting to find significant ways in which the cases and the controls differ. Case control studies can be problematic because the results can be manipulated by choice of the controls. Also this type of study is purely observational and it is after the fact observation. You are relying on people's recall and what they recall may be influenced by their present condition - particularly when they have a serious disease. However in this study the results were quite striking:

Compared with drinking warm or lukewarm tea (65C or less), drinking hot tea (65-69C) was associated with twice the risk of oesophageal cancer, and drinking very hot tea (70C or more) was associated with an eight-fold increased risk.

The speed with which people drank their tea was also important.

Drinking a cup of tea in under two minutes straight after it was poured was associated with a five-fold higher risk of cancer compared with drinking tea four or more minutes after being poured.

There was no association between the amount of tea consumed and risk of cancer.

Compare this with the purported increase in risk of death from eating red meat (based on the responses to one labyrinthine food frequency questionnaire ten years earlier) of about 0.31 times (men) to 0.36 times (women).

And what was also nice was that having asked people to estimate how hot they drank their tea, they then went and measured the actual temperature.

Calorie Restriction and Memory - Low-Carb wins again, actually...

This study is the latest to make headlines around the world as it is claimed that modest calorie restriction in elderly people can result in an improvement in memory. From the abstract:

Animal studies suggest that diets low in calories and rich in unsaturated fatty acids (UFA) are beneficial for cognitive function in age. Here, we tested in a prospective interventional design whether the same effects can be induced in humans. ......We found a significant increase in verbal memory scores after caloric restriction .... which was correlated with decreases in fasting plasma levels of insulin....No significant memory changes were observed in the other 2 groups. This interventional trial demonstrates beneficial effects of caloric restriction on memory performance in healthy elderly subjects.

However, what caught my eye in reports of the study was this:

However, care was taken to make sure that the volunteers, despite eating a restricted diet in terms of calories, carried on eating the right amount of vitamins and other nutrients.

Now, this is an important point - it was even - implicitly - used as an objection to the approach by an anonymous dietician who said that:

....people, particularly those already at normal or low weight, should be "extremely careful" about attempting such a diet. She said: "There is other evidence that, far from enhancing memory, dieting or removing meals can interfere with memory and brain function.

presumably because it follows that if you just cut calories by 30% you cut nutrition by 30%.

But these people claim they didn't reduce the subjects intake of vital nutrients, how did they manage this?

The truth is revealed in the (rather limited) data in the Table S2 in the supplementary information package.

For individuals in the caloric restriction experimental group the mean calories fell from 1843 to 1630, the mean protein intake went from 77g to 71g (all numbers rounded to nearest whole number), the mean fat intake from 70g to 57g and the mean carbohydrate intake from 192g to 74g!! Converted to percent energy measures, this means the mean values went from 17% protein, 35% fat and 43% carbohydrate to 24% protein, 43% fat and 25% carbohydrate (the values don't add to 100% because alcohol intake was included). In other words caloric restriction was achieved, without compromising nutrition, by restricting carbohydrates (especially one imagines typical nutritionally empty carbohydrates like products made mainly of white flour and white sugar).

Interestingly, the individuals in the second experimental group which increased its unsaturated fat intake (to 68% of total fat intake on average - that's 36% mono-unsaturated fat which didn't actually increase (baseline for that group was 36%) and 32% polyunsaturates (from 15%)) didn't show the memory improvement, although they also appeared to have achieved a conversion to 'low-carb'. However, in their case the standard deviation for carbohydrate intake was bigger than the mean value (and much larger than the baseline value), which suggests a huge variation within the group.

Another caveat is that while taking the mean values of consumption and converting to calories reproduces (to within 40 calories or better) the reported mean caloric intake for the before case in all the groups, it is does not do so for the after case (the discrepancy is as much as 400 calories - and in all cases the mean nutrient data (in grams) result in an under-estimate of the mean calories). A better model - using a normal distribution for each parameter - might give an idea as to why this is so. Another interesting fact related to this is that - apart from the unsaturated to saturated fat ratio for the unsaturated fatty acid experimental group, none of the reported differences in before and after macronutrient mean intakes were reported as significant.

To sum up: the calorie restriction appears to have been mainly achieved by restricting carbohydrates. The researchers claimed that they had achieved calorie restriction without reducing nutrient content of the diet. The only way to do this is by removing or significantly reducing nutritionally empty carbs e.g. see here. Mean dietary data reported from the study lends support to this theory. The results observed in the subjects e.g. reduced insulin levels also support this theory.