Category Archives: Advanced nutrition

Research studies, hypotheses, data, etc.

Nutrition under attack

Posted on October 4, 2011 | 1 comment

Global nutrition is in a state of emergency

Tax this:

Not this:

 

If you catch a whiff of anyone talking about a dietary fat tax here in the states, attack!  Hold no bars.

Passage of the Danish saturated fat tax confirms the shit hit the fan.  They should’ve taxed people for being fat (to offset the increased medical and healthcare costs associated with obesity), or sugars (for making people fat).  Instead, the food companies, famous for crafting thousands of varieties of Danish pastries, lobbied for the taxes to be levied against dietary fat.  This “inadvertently” encourages people to consume more Danish pastries with only 7 grams of saturated fat yet 39 grams of sugar!  The tax will favor Pop Tarts over eggs, and this is supposed to make people healthier?

A dietary fat tax is particularly troublesome because it strikes an expensive blow against real whole foods like eggs, butter, and meat, while leaving unscathed processed foods like doughnuts, refined grains, and SUGAR.  This disproportionately affects healthy foods that are in no way responsible for the obesity epidemic.

My suggestions:

1)      Leave people alone.

2)      A better target, which would entail markedly less collateral damage, is “added” sugars.  Taxing “added” sugars would hit soda, processed food-like products, snacks, and junk food… lots of bad guys, few good guys

3)      Make a tax based on empty calories: foods with a higher ratio of calories to nutrients get taxed more than nutrient-dense foods… thus, people would be eating fewer calories but more nutrients!  That wasn’t too hard?

4)      Tax food in direct proportion to its shelf-life.

5)      The revenue from any of these alternative options should be put toward nutrition education programs in elementary schools.  And a portion of the money saved in healthcare costs should be redirected into funding research in the nutritional sciences.  And the rest can be used to pay off the National debt.

 

Calories proper

 

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Posted in Advanced nutrition, Dietary fat, empty calories, Fructose, Grains, Sugar, Trans fat

Empty calories V

Posted on September 27, 2011 | Leave a comment

The final horcrux!  Empty calories induce a feed-forward loop that promotes  over-consumption. … the following evidence is indirect, of course, but very compelling.

Food intake measured by an automated food-selection system: relationship to energy expenditure (Rising, Ravussin, et al., 1992 AJCN)

This study was designed to validate a new technique for measuring food intake; it had nothing at all to do with “empty calories.”

10 lean, healthy young men.  During a 4-day run-in period, the amount of calories required to maintain energy balance was measured with extreme precision.  Then for 7 whole days, they lived in a metabolic ward and dined from … wait for it … “vending machines.”

 

The vending machines were loaded with entrees, snacks, and beverages, [sic]: “familiar and preferred foods,” aka a “cafeteria diet.”  And I was delighted to see they also published the menu:

 

This study fit so perfectly because the Empty Calories series’ singular major thesis is: empty calories promote over-consumption.  And this can be tested by examining the two logical extremes: 1) a diet devoid of empty calories is inherently healthier, and any increase in the amount of empty calories consumed is accompanied with a decrease in health outcomes; and 2) eating more empty calories will not be balanced by eating less of something else, because empty calories are nutritionally bankrupt and do not affect satiety proper.  And this menu, oh yes, is almost entirely empty calories.

The researchers purposely filled the vending machine with individually packaged processed foods because of their convenience; it’s a very easy way to measure food intake, which was the focus of their study.

The following figure is absolutely nuts; you couldn’t make this stuff up.  like it was mathematically designed to support the Empty Calories credo.

 

It started immediately on day 1 of “ad libitum intake;” food intake doubled- the food was so nutrient poor that twice as many calories were necessary to satisfy their appetite.

Where did all those excess “empty calories” go?  Some (~17%) were spontaneously burned off (increased 24h EE) but most were invested in the infamous negative-yield* calorie savings banks (i.e., adipose).  [*you don’t get back more than you invested].

 

Side note: check the numbers, an overconsumption of 10975 kJ/d = 2622 kcal.  For 7 days = 18,353 kcal; which is approximately the amount of energy in 5.2 pounds (2.4 kg) of fat tissue.  They gained 2.3 kg, just a hair less than mathematically predicted (so much for spontaneously burning off 17% of the excess).  Body composition was not measured, but given the huge increase in carbohydrate intake, I imagine insulin levels were through the roof driving all of the excess energy into fat mass.

This has been confirmed numerous times.  For example, Larsen et al. (1995):

 

When fed the “cafeteria diet” from vending machines, these women almost doubled their food intake and gained a full pound of fat in under a week.  But I digresss.

“And this can be tested by examining the two logical extremes: 1) a diet devoid of empty calories is inherently healthier, and any increase in the amount of empty calories consumed is accompanied with a decrease in health outcomes; and 2) eating more empty calories will not be balanced by eating less of something else, because empty calories are nutritionally bankrupt and do not affect satiety proper.”

The second postulate has been addressed and sufficiently supported by Ravussin’s vending machine study (above).  Fortunately for us a study that addressed the first postulate was blogged on previously.

 

Remember now?

(Hashim and Van Itallie, circa 1965)

 

When fed a bland yet nutritionally complete diet, obese subjects spontaneously and drastically reduced their food intake, and body weight plummeted for EIGHT STRAIGHT MONTHS.  Although this was confirmed a decade later by Cabanac and Rabe (1976), it only indirectly supports the first postulate because it was not real food.  But it proves the point that nutrient sufficiency supports satiety, and this can be dissociated from total calorie intake.  IOW, if the diet provides the essential nutrition, then the remaining daily energy requirement can be met by burning excess fat mass stored in adipose tissue.

avoid ‘empty calories’ and cash out

 

calories proper

 

 

 

 

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Posted in Advanced nutrition, Dietary fat, empty calories, Protein, Sugar, Uncategorized

Empty calories IV

Posted on September 20, 2011 | Leave a comment

Welcome to the fourth installment, empty calories in everyday life

on feeling “full”

fullness can be manipulated by a variety of things, but never truly fooled.  Try drinking a fiber-rich beverage (e.g., Metamucil) right before mealtime and then eat slowly… you will feel full much sooner.  This may even cause you to eat less, but it won’t last … it’s not an effective long-term weight loss or weight maintenance strategy.  and it might even do harm… fiber makes you feel fuller faster by expanding (absorbs water) in your GI tract- it will stretch out your stomach a bit.  When you run out of it, or decide enough is enough, your stomach will feel emptier than usual, which will increase the amount of food necessary to make you feel “full.”

In the example above, that fiber drink would be considered to have a very low energy density.

on energy density

“Energy density” is bunk.  Ha!

But really, advising someone to consume a “low energy density” diet is wrong.  The rationale underlying “low energy density” diets is that fat, the macronutrient, contains 9 calories per gram, whereas carbohydrates only have 4, less than half.  Thus, there is >2x the amount of energy contained in a gram of fat than in a gram of carbs, i.e., fat is more energy dense.  However, when it comes to real food (food, not macronutrients), things change.  E.g., crackers are promoted as a healthy snack for low energy density dieters because crackers are very low fat (4% by weight) and thus low energy dense.  Red meat, on the other hand, has a high energy density (fat content 20-30% by weight)…  but wait, are those statistics referring to macronutrients … or food?

100 grams of crackers can have anywhere from 393 (Saltines) to 492 (Ritz) kilocalories, but 100 grams of red meat has 258 (Porterhouse) – 332 (ground beef) kcal.  Since things like water content vary widely among different foods, the energy density of macronutrients is not the same as that of the foods we actually eat.

on snacking

Think of a meat-eater you know.  Regardless of how much they love steak, they couldn’t eat it until they were sick.  But watch a little kid eating snacks, for example.  especially kids, who are more vulnerable than adults to obesogenic foods.

Most non-animal food sources (rice, pasta, beans, potatoes, etc.), including snacks, lack one or more nutrient or essential amino acid and are therefore considered nutritionally inadequate.  WRT to nutritional deficiencies: for practically every nutrient, the “at-risk for deficiency group” is almost always vegetarians (and/or alcoholics).

Snacks and plant-based foods are nutritionally incomplete; we might overeat them because of this.  Perhaps protein, EFA, & nutrient sufficiency is detected by the satiety systems in our brain.

It is difficult but not impossible to eat a nutritionally adequate vegetarian diet (sans industrial fortification), but it’s practically impossible to be nutritionally insufficient if a small variety animal foods are included in the diet (eggs, red meat, salmon, chicken, etc.)… low chance of success in the former vs. low chance of failure in the latter?

A can of Pringles has more calories than a dozen eggs (900 vs. 852 kcal).  But it’s virtually impossible to eat a dozen whole eggs, partially because that’s gross, but also possibly because just a few eggs provide more than enough nutrition to signal into the satiety system.  IOW, it’s much easier to overeat empty calories.

Snacks make people fat, in part, because they are designed to be tasty but provide little nutrition.  If snack foods provided adequate nutrition, they would satisfy our hunger and we’d eat [and buy] less.  The tasty flavors make us want and like them, and the lack of nutrition prevents us from becoming satiated.

Nutrient density FTW.

 

calories proper

 

 

 

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Posted in Advanced nutrition, Dietary fat, empty calories, Protein

Empty calories III

Posted on September 12, 2011 | 1 comment

Empty calories.  Nutrient density.  Empty calories.  The ANDI score?

With the advent of the ANDI, it is safe to say the phrase, school of thought, and cult following to “a calorie is a calorie” is fading.  All calories were not created equal; some make you fat, others make you strong.  Cantankerous old biochemists and low-fat diet proponents will likely remain loyal, however, with the former citing heat production in a bomb calorimeter (mumbo), and the latter citing the equivalency of nutrient density and animal fat scarcity (jumbo).

But for the rest of us, there is gravitas in this concept       empty calories.

A good place to start might be a critical view of Fuhrman’s  Aggregate Nutrient Density Index (ANDI).  In brief, ANDI is an index of healthiness and is calculated by dividing the amount of nutrients in a given whole food by the calories.

Pro’s and con’s

1)      it only applies to whole foods.  This is convenient because most processed foods would score miserably low unless they’ve been industrially fortified with synthetic vitamin-like chemicals.  Perhaps Fuhrman restricted ANDI to whole foods because something like Diet Coke Plus would score about a million (lots of vitamins, few if any calories), rendering ANDI utterly meaningless to the masses and downright offensive to people like me.

 

2)       “nutrients per calorie” is a far more biologically meaningful and physiologically relevant concept than “calories per gram.”

  1. “Calories per gram” can be too easily manipulated.  E.g., one ounce (~28 grams) of soybean oil has 248 kilocalories: 248 kilocalories / 28 grams ? 9 kcal/g.  Add it to an ounce of water and you get 248 / 56 ? 4.4 kcal/g.  It’s still the same nutritionally, but the “caloric density” was halved by trickery.
  2. “Nutrients per calorie” is relatively unchangeable.  Let’s say there are 14 grams of omega-6 fatty acids in an ounce of soybean oil; that would be 14 grams per 248 kcal.  Add it to an ounce of water and it’s still true.  Drink it on the moon and it’s still true (relatively).

However,

1)      ANDI selectively quantifies only one aspect of a food’s nutritional value.  It is an important aspect, but please note that a diet based on high ANDI foods would be nutritionally inadequate.  Furthermore, there are highly relevant health parameters that ANDI completely ignores.  More questions:

  1. Shouldn’t more important nutrients be given a higher score?
  2. Shouldn’t excess amounts of a nutrient detract from the score?
  3. What about other non-nutritive health-promoting properties of a food?  E.g., foods that are healthier than indicated by their ANDI score:
    1. i.      foods that have some as-of-yet undiscovered nutrients
    2. ii.      foods that indirectly promote health (like pre- or pro-biotics)

2)      Furthermore, ANDI is fundamentally flawed in its application to foods whose value is based at least partially on the actual calories themselves.

  1. Fuhrman uses the ANDI score on fats, which score dismally low because they contain few “nutrients” and a lot of calories.  Thus, industrially-modified, partially-hydrogenated trans fat-rich soybean oil has the same ANDI score as olive oil.
  2. Animal proteins, including grass-fed beef, wild salmon, and pastured eggs, also score incredibly low.  These foods are far more healthful than many most others, essential for life (unlike kale, which is the highest-scoring ANDI food), and much of their value is contained in the quality of their calories.
    1. i.      the fatty acids in salmon are healthy in and of themselves; they don’t contain any nutrients per se; they ARE the nutrient.  But ANDI doesn’t take this into account; it views all fatty acids as empty calories, a grave mistake.
    2. ii.      the same goes for animal proteins.  Eggs, for example, are higher in protein quality than any other food on the ANDI scale yet they score quite low.  And getting a bio-equivalent amount of protein from lower quality plant proteins would require consuming many more calories.

The failure of ANDI to incorporate any measure of fat or protein quality is its demise; why it is unable to stand alone as an indicator of healthiness… a diet consisting exclusively of high ANDI foods is incompatible with life.  A protein deficiency would be vastly more severe than a low ANDI diet, and on a lighter note, the fish oil fatty acids would provide much greater benefits than a high ANDI diet.  These nutritional factors play too big a role in determining healthspan and quality of life to be ignored.

BUT, ANDI is nice in its simplicity, and it works very well for most plant-based foods.  E.g., spinach and cabbage have very high ANDI scores; rice, grains, and pasta have very low ANDI scores.

The diets of many cultures are based almost exclusively on low-ANDI foods.  This is largely because it is much easier to produce enough calories to feed a village than to produce enough nutrients.  Starvation is deadlier than dermatitis.  In the Western world, however, we are fighting a different battle: you need to eat a LOT of empty calories in order to get enough nutrients, but then you get fat.

 

calories proper

 

 

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Posted in Advanced nutrition, Grains, Protein, Sugar, Trans fat, Uncategorized

Empty calories, II

Posted on September 6, 2011 | 1 comment

You should be ashamed of yourself!

Foods, fortificants, and supplements: where do Americans get their nutrients? (Fulgoni et al., 2011 Journal of Nutrition)

The Journal of Nutrition just published an analysis of micronutrient intake in healthy Americans.  The dataset came from the National Health and Nutrition Examination Survey (NHANES), which is run by the Centers for Disease Control (CDC)  and the National Center for Health Statistics (NCHS).

The USDA database was their primary source for nutrient information, but the Food and Nutrient Database for Dietary Studies (FNDSS) and Nutrient Database for Standard Reference (SR)  were also consulted when appropriate values were unavailable.  As the authors faithfully noted in the methods section, these registries are not perfect, but they really did do a lot of footwork to get accurate, up-to-date data.

Importantly, intake from whole foods, processed foods, and supplements was differentiated.  AND bioavailability was taken into account!   Kudos.

Shamefulness: over half of you are not getting enough vitamins D and E, and many are not getting enough vitamins A and C, and magnesium and calcium.

And if it weren’t for processed foods, too many of you would be consuming too little thiamin, niacin, riboflavin, and folate!  Why are you dependent on processed foods for vitamin sufficiency!?!

In the graph below, the higher the solid bars, the more people are vitamin insufficient if only whole foods are considered.  Notice that when processed foods are taken into consideration, the values are much lower for thiamin, niacin, riboflavin, and folate (open bars).  And supplements don’t add a whole lot to the picture (shaded bars).

Supplements don’t change the big picture very much because, well, who takes supplements?  Healthy people.  Healthy people who are probably already getting enough vitamins and minerals from the whole foods in their diet.  Someone who lives on fast food, soda, and crisps probably doesn’t care enough about their health to swallow a multivitamin every morning.  However, their intake is not suboptimal because they don’t take a multivitamin pill, it’s suboptimal because their diet contains too many empty calories!

TO DO: from whole food sources (i.e., not empty calories), get more:

Magnesium: spinach

Vitamin A: red meat, chicken, spinach, kale

Vitamin C: berries, broccoli, kale, peppers

Vitamin D: salmon/fish, whole eggs, red meat, liver

Vitamin E: spinach, nuts, fish

Potassium: spinach, tomatoes, beans

 

And while “adequate is adequate,” stop relying on processed foods and start eating more whole foods for:

Folate: foliage (leafy vegetables like spinach), also high in turkey, chicken, beans, etc.

Thiamin: pork, and lesser amounts in liver, whole eggs, nuts

Iron: red meat

 

processed foods are empty calories.  a processed food that has been chemically fortified with a synthetic vitamin cocktail is still “empty calories” in my book.  And although frank toxicity is rare, processed foods are close to providing too much of certain nutrients, e.g., niacin, vitamin A, folate, and zinc.  Stick to whole foods, and don’t overdo it with your kids- they were more likely than adults to be getting too much zinc, niacin, vitamin A, and folate, and the overage was largely due to processed foods.

 

Calories proper

 

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Posted in Advanced nutrition, TPMC

an elusive rogue criminal mastermind

Posted on August 14, 2011 | Leave a comment

Hyperinsulinemia.  Whether it’s caused by insulin resistance, too many carbs, or industrial insulin secretagogues found in processed foods, high insulin levels are problematic.

Octreotide is a synthetic version of somatostatin and it inhibits the secretion of a variety of hormones, namely insulin.  A group of researchers set out to determine the effects on obesity of pharmacologically lowering insulin via octreotide.  In this setting, it doesn’t matter how insulin became elevated in the first place, only whether reducing it has any impact on obesity.

A multicenter, randomized, double-blind, placebo-controlled, dose-finding trial of a long-acting formulation of octreotide in promoting weight loss in obese adults with insulin hypersecretion (Lustig et al., 2006 International Journal of Obesity)

Octreotide dosing is surprisingly convenient, monthly injections, and there were no other dietary or behavioral interventions.  Lustig’s hypothesis was simply that high insulin levels were making things worse, like causing weight gain and hunger, preventing weight loss, etc.  The intervention was only octreotide; no dietary or behavioral interventions…. Another way of thinking about this hypothesis is: if dietary or behavioral factors were contributing to the obesity phenotype, then perhaps high insulin levels were in part causing those very same dietary or behavioral factors (?).  That seems backward, like an enigma wrapped in a riddle surrounded by a mystery, but this study addressed the possibility by also assessing a variety of psychological and dietary/behavioral factors (whether these could be caused by reduced insulin levels, per se, as opposed to some other effect of octreotide would be difficult to determine, but this study demonstrates the possibility).

This was a population of relatively young (~40-ish), fairly heavy (~240 lbs), but otherwise healthy subjects.  And most of them stayed in the study for the entire duration (which means, in part, that octreotide isn’t an unpleasant therapy).

To make a long story short, octreotide worked, but not very well…

 

In the table above, the “mean percent change from baseline” was less than 2%, which amounts to about 4 pounds (in 6 months).  As a graph (note the ordinate):

 

But the treatment was well-tolerated, and a variety of quality of life measurements were significantly improved, such as physical function, self-esteem, and sex life.  And interestingly, “carbohydrate cravings” were significantly reduced, which suggests the possibility that high insulin levels may in part be self-promoting.

Although a more selective drug would have been preferable to the pan-inhibitor octreotide, another interpretation of the modest weight loss results presents itself.  A recent study by Willett, which I previously blogged about showed that in general, people gain about a pound a year and some of the largest contributors to that weight gain are potatoes, potato chips, and French fries.  All three elicit a robust insulin response, and the latter two most likely contribute to other metabolic abnormalities which also lead to elevated insulin levels (insulin resistance, insulin hypersecretion, etc).  The current study demonstrated the possibility that high insulin levels, per se, might be an important cause of weight gain or the maintenance of an obese state.  AND carbohydrate craving was reduced by octreotide.  Willet’s study showed that foods like potatoes, which cause high insulin levels, are associated with weight gain.  Lustig’s study showed octreotide reduces insulin levels, which reduces carbohydrate cravings and leads to weight loss.  Abandon carbs?  Monthly octreotide injections?  Going on the Atkins diet would cause a much more rapid weight loss than octreotide, but octreotide therapy would cause literally zero lifestyle disruption… and the speed of weight loss would be closer to the how fast the weight came on in the first place.

On a more philosophical note, there is a subtle continuity between the magnitude of weight change and the foods implicated in Lustig’s and Willet’s studies.  On one hand, the most influential foods associated with age-dependent weight gain were starchy carbs (which induce insulin secretion); on the other hand, lowering insulin via octreotide reduced carbohydrate cravings and caused weight loss.  It’s difficult to clearly connect these observations with eloquence, but they seem to suggest a strong correlation.  The rate of weight gain associated with ‘potatoes, et al.’ was slow, similar to the rate of weight loss with octreotide…

So if you likened the cause of obesity to an elusive rogue criminal mastermind, and the cure to a cunning stealth superhero, then you’d be unimpressed with “potatoes” and “a few pounds gained or lost.”  …  obesity doesn’t happen overnight.

 

Calories proper

 

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Posted in Advanced nutrition

the boob tube

Posted on August 3, 2011 | Leave a comment

it’ll kill you!  (too much, i.e.)

OK, FTR I don’t think any amount of TV watching will kill you, and I think that any study showing otherwise is under the control of some major food company , big pharma, or downright statistical sorcery.

Playing in traffic? Perhaps.  Watching TV? No.

Without further ado, some recent studies showing I’m wrong.

Television viewing and risk of type 2 diabetes, cardiovascular disease, and all-cause mortality (Grontved and Hu, 2011 JAMA)

First, a meta-analysis.  Not good.  The first paragraph in the intro starts out with [sic]: “40% of daily free time is occupied by TV viewing within several European countries.”  At first, 40% seems like a lot; how much “free time” do we really have?  Sleep 8 hours, work 8 hours, commuting to and from work, chores, eating, showering, etc… so maybe 3 hours of free time?  40% of 3 hours = 1.2 hours.  But the authors cite “4 hours” of TV viewing which means these people have almost 7 hours of free time per day… which means commuting to and from work, chores, cooking & eating, showering, etc. only takes about 1 hour (unless they either don’t work or don’t sleep.  IOW 7 hours seems like a horrendous overestimate.  There are a few other inconsistencies in the intro, but rather than spend more time nit-picking, on to the data:

To make a long story short, every additional 2 hours of TV viewing per day increased the risk for:

Type II diabetes by 0.0176%

Fatal CVD by 0.0038%

All-cause mortality by 0.0104%

And just to be clear: yes, those are very very small numbers.

The authors searched relevant databases for every study on the topic, excluded the ones that didn’t support their hypothesis (jk… kind of*), and then independently analyzed the resulting studies.  Any disagreements were “resolved by consensus,”  which I’m not exactly clear how is accomplished when there are only 2 authors (rock, paper, scissors?).  In their favor, whenever possible the data were analyzed with and without diet and body weight in their multivariable-adjusted models.

*out of 1,655 relevant studies, 8 (agreed with their hypothesis [jk… kind of]) were included.

Divide and conquer

As seen above, increasing hours of TV viewing is associated with increasing risks for diabetes, CVD, and all-cause mortality.  Yikes!

The risk for diabetes was linearly related with TV viewing, but the risk was modestly attenuated by controlling for diet, and greatly reduced by controlling for body weight… IOW a poor diet is bad but excess body weight is worse (lean people can watch more TV than obese people).

Risk for all-cause mortality was less than CVD and diabetes and wasn’t affected by diet or body weight.  The inflection was around 3 hours…  which means that the risk dying isn’t appreciably increased by TV viewing if you watch less than 3 hours per day.  Phew!  (the applies to adults only).  In sum, 3 hours seems to be a safe amount of TV for lean healthy people; less if obese or pre-disposed to diabetes.

Something similar was found in an EPIC study.

Television viewing time independently predicts all-cause and cardiovascular mortality: the EPIC Norfolk Study (Wijndaele et al., 2011 International Journal of Epidemiology)

 

Although the overall risk for all-cause mortality associated with increased TV was about a third less than in Hu’s meta-analysis, it was 1) statistically significant, and 2) unaffected by diet or body weight (similar to Hu’s findings).

 

The relationship between TV viewing and all-cause mortality was attenuated after controlling for a variety of confounding factors (HR Model A = 1.08, p<0.001; HR Model B = 1.05, p=0.01), which means that someone who watches a lot of TV also has other risk factors which contribute to their risk of dying that have nothing to do with TV (like smoking, for example… unless they smoke because of the show their watching [?]).

Interestingly, the relationship was unaffected by controlling for physical activity (compare HR in Model B to Model C), which seems to imply that sitting too much (watching TV) is not necessarily equal to exercising too little… and in this population, ‘exercising too little’ was statistically unhealthier than ‘sitting too much.’

one from down under:

Television viewing time and mortality.  The Australian diabetes, obesity and lifestyle study (AusDiab) (Dunstan et al., 2010 Circulation)

In AusDiab, TV increased the risk for all-cause mortality slightly moreso than EPIC-Norfolk, but was similarly attenuated by controlling for other risk factors:

 

Oddly, there is a blip at 4 hours in both AusDiab and EPIC-Norfolk.  I have no idea what this means, but it is very interesting that in both England and Australia, people who watch 4 hours of TV per day have a higher risk for all-cause mortality than those who watch for 3 or 5 hours… if you find that you’ve spent 4 hours watching TV one day, throw on a pot of coffee and watch another hour.  Food for thought.

WRT health outcomes, excessive daily TV viewing seems to be a marker for other risk factors such as obesity, smoking, etc (may even be an indirect marker for ‘family history of CVD, diabetes, etc.).  TV watching per se is not the problem, nor is I suspect the TV.  Eat less, move more?

calories proper

 

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Posted in Advanced nutrition, Exercise

n = 1,570,808

Posted on July 27, 2011 | 1 comment

the correlation between time spent watching TV and body weight may have nothing to do with the common thought that if kids aren’t watching TV, they’re out playing.  No, it turns out that kids who watch less TV eat healthier.  They sit around just as much … just not watching TV.  Is there something about mindless sitcoms and cartoons that make us want to eat junk food … or snack … wait a minute … subliminal commercial advertising?

Is any of this true?  probably not.  But if I were to test it, I’d like an intervention study with a couple randomized groups including: one whose TV commercials were strategically replaced with equally fun commercials that don’t promote snack foods; a group of kids who don’t watch TV; and maybe a group who doesn’t watch TV but is exposed to subliminal snack-promoting advertisements…   food for thought.

Changes in diet and lifestyle and long-term weight gain in women and men (Mozaffarian, Hao, Rimm, Willett, and Hu, 2011 NEJM)

This is one of the biggest and longest running prospective studies on diet and lifestyle behaviors.  That’s not to say it’s the best study; epidemiological, observational, and prospective studies are subject to a variety of crippling limitations; but this one is big.

It is a compilation of three big studies that I’ve blogged about in the past:

The Nurses’ Health Study (NHS, n=121,701, est. 1976)

The Nurses’ Health Study II (NHS II, n=116,686, est. 1989)

The Health Professionals Follow-up Study (HPFS, n=51,529, est. 1986)

All in all, a total of 1,570,808 person-years were analyzed (person-years: 16 people x 2 years = 32 person-years).  The biggest finding?  everybody gains weight, about 0.835 pounds per year.  It doesn’t sound like much but after 20 years it means you’re 15 pounds fatter.

The second biggest finding?  Drumroll please…

First, to set the mood: people don’t gain weight magically.  This study was unique in that there were multiple dietary assessments, performed over a very long period of time, in the same group of people.  And one way people gain weight is by eating more.  So these authors were able to see which foods, when increased in the diet, correlated with weight gain.

And the winner was, somewhat surprisingly, potatoes!  Actually number 1 was potato chips, and number 2 was potatoes and French fries or crisps.  The surprise, IMHO, was that soda and junk food was much further down the list.  Furthermore, I might have thought potato chips could be number 1 because of their high trans-fat content, but the presence of potatoes (which lack trans-fats) at number 2 means that trans-fats are not the obesogenic component of potato chips.

The figure (kudos for data presentation):

To quote the study [sic]: “Strong positive associations with weight change were seen for starches, refined grains, and processed foods.”  WRT study design, such conclusions cannot be interpreted to mean: eating less “starches, refined grains, and processed foods” will prevent weight gain.  It means body weight was determined by changes in the amount of “starches, refined grains, and processed foods” were in the diet… if any of those foods were increased, body weight increased; and if any of those foods decreased, body weight decreased. (note: this study was not designed to determine causation).

Exercise was also included in their analysis.  Another good-looking figure, albeit a little more complicated:

Think of the bottom left (front?) as the sum of good dietary changes (associated with weight loss [or less weight gain]).  People in the first “Quintile of Dietary Change” increased their consumption of “starches, refined grains, and processed foods” and gained the most weight, while those in the fifth quintile ate less and lost weight or stayed the same.  A similar trend for physical activity is displayed on the bottom right part of the figure.  People in the first quintile increased their physical activity, while those in the fifth quintile reduced their physical activity.  If you compare the amount of weight gain from the fifth to the first quintiles of dietary change (all the purple bars, for example), the amount of weight gained is highly dependent on diet.   However, within any given quintile of dietary change, not much weight is gained or lost by changing the amount of exercise (follow any set of bars from gray to purple to yellow to green to blue).  IOW, at any given quintile of physical activity change, diet predicts much larger changes in body weight.  Heck, people in the second quintile of dietary change actually gained weight by increasing physical activity … that’s a bit convoluted, but it demonstrates the case that in this enormous data set, diet was a better predictor of weight gain than physical activity (which in some cases didn’t matter at all).

Eat less and move more?

Calories proper

 

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Posted in Advanced nutrition, Grains, Sugar, Trans fat

fat skinny people

Posted on July 15, 2011 | 36 comments

The metabolically obese normal weight phenomenon
or
Fat skinny people.

In general, type II diabetes is preceded and possibly even caused by obesity.  However, there is a marked variation in the amount of excess fat mass that individuals accumulate prior to developing frank diabetes.  IOW, some people are morbidly obese for over 10 years before succumbing to diabetes while others become diabetic much sooner.  In fact, some people, known as “metabolically obese normal weight” (MONW), are technically lean (BMI < 25) when they develop the metabolic syndrome.

While genetics and environmental exposures play a role in determining the amount of fat mass an individual can ‘safely’ accumulate, nutrition is probably the most important factor.

The BMI scale was developed, in part, to specify these ‘safe,’ or more appropriately ‘healthy’ ranges of adiposity.  That is why there are sex and even international variations.  For example, a healthy BMI for people in East Asia is lower than that of Americans.  This is not because of the difference in average body weight between the two populations, but rather due to the observation than people in East Asia develop obesity-related health problems at lower levels of adiposity than Americans.

This is, in part, mediated by diet.

Characteristics of diet patterns in metabolically obese, normal weight adults (Korean National Health and Nutrition Examination Survey III, 2005) (Choi et al., 2010 Nutrition, Metabolism & Cardiovascular Diseases)

This is essentially the Korean equivalent to the United States’ NHANES

In brief, the authors of this study collected data from ~3,000 normal weight Koreans and divided them into two groups: ‘metabolically healthy normal weight (MHNW)’ and ‘metabolically obese normal weight (MONW)’ (remember everyone in both groups had a ‘healthy’ BMI; overweight and obese people were specifically excluded).  MONW was defined as having a waist circumference > 90cm (35″) for men or >80cm (31″) for women and at least 3 out of the next 4 criteria: elevated triacylglycerols, low HDL, hypertension, and impaired fasting glucose.  Basically, MONW is the Metabolic Syndrome for skinny people.

Disclaimer: The MONW population differs from MHNW in more ways than their diet and metabolic profile, and these differences probably have a lot to do with why they eat what they eat.  For example, MONW are less educated and makeless money than MHNW.  But for the purposes of this blog post, it is not why they eat what they eat, but rather what they eat.  And as seen in the table below, MONW eats fewer calories per day and a higher proportion of carbohydrates than MHNW (at the expense of protein and fat).

Divide and conquer

 

MONW ingests less protein (78 vs. 67 g/d) on an absolute basis, which is most likely why they have more fat mass at the same body weight (lower protein intake accommodates less muscle mass).  And it is this lower protein intake that most closely correlates with being metabolically obese:

 

Importantly, these odds ratios were controlled for confounding variables such as age and gender.  The last analysis is probably the most interesting, and it breaks down the risk of being metabolically obese by the intake of each macronutrient (in quartiles) for the entire population.

 

Increasing intakes of total energy, protein, or fat do not increase the risk of being metabolically obese.  Only carbohydrates significantly increased the risk across all 4 quartiles of intake.  The tolerable upper limit of carbohydrate intake was statistically extrapolated to be 59.9% of calories… which is within the recommended range of 55% – 70%.  IOW, by following the government’s dietary recommendations you will be significantly increasing your risk of metabolic derangement.  A prudent recommendation, based on these data, would be more like “less than 50%” (since no lower limit or deficiency was established).

Last but not least, and I’m not sure why, but the metabolic derangements associated with a low protein high carbohydrate diet were far more severe in women than men.

So the take-home message?  A low protein, high carbohydrate diet was significantly associated with metabolic deterioration, and this was most likely not simply correlative.  No, I contend this dietary pattern caused metabolic obesity.

One final note before moving on:  this study was specifically not looking at causes of obesity.  Obese and overweight people were excluded and this study focused solely on lean individuals.  Therefore we can’t conclude that any of the variables that cause metabolic obesity also cause weight gain… although they might (and probably do), the study was simply not designed that way.

…

Dear Drs Choi and Park,

If you’re reading this, please re-assess diet, blood parameters, insulin sensitivity, and body composition in these subjects in 5-10 years and report your findings.  I am very curious to see how metabolic obesity affects health outcomes.

Sincerely,

Bill Lagakos

 

In a similar study on the NHANES III data (United States), Zhu and colleagues analyzed risk factors for the metabolic syndrome across a wide range of BMIs.  In order to be more directly comparable to Choi’s findings, we’ll only consider the subjects with a health BMI (less than 25).

Lifestyle behaviors associated with lower risk of having the metabolic syndrome (Zhu et al., 2004 Metabolism)

The table below is divided by gender, regression analysis (Model 1 is the most direct correlation, while Models 2 and 3 control for a variety of confounding factors), and carbohydrate intake (less than 30% of total calories, 30-60%, and greater than 60%).

 

The correlation between MONW and a high carb intake is stronger for men than women, but present in both.  For men, the association is not weakened by controlling for confounding factors (age, race, education, and income).  For women, the association is present in the general population (Model 1) but no longer exists in Models 2 and 3.  In both men and women, a high-fat diet was associated with lower risk of MONW in Model 1 but not 2 or 3.

In Choi’s study on a Korean population, a high carb and low protein diet was associated with MONW, with a smaller influence of low fat.  In Zhu’s study on an American population, high carb and low fat were associated with MONW and protein intake wasn’t analyzed.  Collectively, these results suggest that lean people eating a diet high in carbs but low in protein and fat are the most likely to have metabolic abnormalities and possibly may be unwittingly diabetic.  Skinny on the outside, fat on the inside.  A carbohydrate intake greater than 60% of total calories significantly increased the risk of MONW in Choi’s population, while an intake of less than 30% significantly decreased the risk in Zhu’s study.  Greater than 60% = bad.  Less than 30% = good.

 

Calories proper

 

 

 

 

 

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Posted in Advanced nutrition, Dietary fat, Protein

Trans fats, take III

Posted on July 2, 2011 | Leave a comment

Man vs. ape     Or
Postmenopausal women vs. Africa green monkeys

 

Two good and potentially somewhat contradicting studies on our good old friends, trans fats.

Trans fat diet induces abdominal obesity and changes in insulin sensitivity in monkeys. (Kavanagh et al., 2007 Obesity)

In this study, Kavanaugh and colleagues fed either a control diet or one fortified with trans fatty acids to a group of African green monkeys for 6 years.  Two immediate strengths of this study are 1) the use of primates, who respond to dietary intervention much more similarly to humans than rodents, and 2) the duration is long enough to model what would be seen in a human population.  Furthermore, to prevent differences in food intake from affecting the outcome, all of the animals were fed 70 kcal/kg of their initial body weight.  This feeding regimen was chosen specifically to prevent an energy imbalance, i.e., the monkeys were to be “weight stable” for the entire study.  This method is superior to pair feeding, where one group is fed ad libitum and the other group is given the same amount of calories as the first group, but instead of grazing all day (normal behavior) they get it all in one sitting.  Pair feeding is stressful for the animals and causes a whole host of other problems.  Both groups in this study received exactly the same amount of food (70 kcal/kg of initial body weight) every day for 6 years.

At the beginning of the study, the monkeys weighed ~6.5 kg (14.3 pounds); thus, for the rest of the study they were fed 455 kilocalories every day.  The diet consisted of 35% fat, 17% protein, and 48% carbohydrates.

The diet for half of the monkeys was supplemented with 8%, or ~4 grams, of trans fatty acids.  The average intake for humans is 3%, or ~7 grams per day.  An intake level of 8% for humans is around 18 grams, which could be accomplished by eating fast food or microwave popcorn a few times per week.  So besides being informative and shedding a new light on energy balance, this study is also of practical relevance.

Furthermore, the trans fat they chose was similar to the most abundant trans fat found in human diets (processed foods): partially hydrogenated soybean oil.

The diet:

 

TRANS refers to trans fatty acids, and CIS is the opposite of trans.  Cis fatty acids are the form of most natural fatty acids.  People don’t usually call regular fatty acids “cis” because it is assumed; this is how most unsaturated fatty acids are found in nature.

To the data.

 

divide and conquer.

 

Body weight was roughly similar in CIS (closed circles) and TRANS (open circles) but started to diverge toward the end of the study.

The control group (CIS) weighed 6.41 kg at baseline and 6.55 kg at follow-up, an increase of less than 2%.  This was expected because at baseline, 70 kcal/kg per day was precisely enough food to keep them weight stable, so essentially nothing changed in these monkeys.  More specifically, since food intake and body weight didn’t change, we can say that there were probably no major perturbations in energy balance in this group.

 

TRANS, on the other hand, gained almost 3 times more weight despite eating exactly the same amount of food as the control group, which was exactly the same amount of food they were eating when they were weight stable at baseline.  Energy balance was clearly perturbed by trans fats.

As seen below, the excess weight in the TRANS group was primarily in the form of increased visceral fat:

 

An abdominal CT scan.  The lighter areas represent fat tissue.  Both pictures depict roughly similar amounts of fat in the outer region (subcutaneous fat), whereas the TRANS group had significantly more fat tissue within the viscera.

For reference:

 

In all, TRANS had 27% more fat mass.  Fasting glucose and insulin levels were unchanged but postprandial insulin levels were markedly elevated in TRANS (see below), suggesting that dietary trans fats indeed caused insulin resistance.  I boldly use the term “caused” because this was a fairly well-controlled intervention study; the only thing different between the groups was the diet.

 

The TRANS group gained a significant amount of fat mass despite an absence of excess calories.  This was most likely caused by the trans fat-induced insulin resistance and subsequent postprandial hyperinsulinemia.

It would appear as though trans fatty acids defied the laws of energy balance.  The TRANS group gained fat mass despite an absence of excess calories.  Even the most practical explanation bodes poorly for trans fatty acids… it would appear as though trans fats were capable of inducing nutrient anti-partitioning independent of food intake.

I can see two ways to interpret these data.

  1. Trans fatty acids have an independent effect on energy balance.  That is, they specifically reduce energy expenditure, which would make the initial 70 kcal/kg*day excessive.  This would account for the excess fat mass, compared to controls, but not necessarily the increased body weight.  455 kilocalories (70kcal/kg*d) should be sufficient to support a specific amount of body weight; it is difficult to imagine a scenario whereby muscle mass declined enough to significantly reduce metabolic rate to the point where 455 kilocalories was so excessive that fat mass increased significantly more than the amount of muscle lost.  IOW, if this possibility were true, I would have expected, at most, a similar body weight but more fat and less muscle, not simply way more fat.

Of course, these processes would occur simultaneously and discreetly in vivo, but for simplicity’s sake I’ve broken it down.

6.6 kg monkey, x 70 kcal/kg*d = 462 kcal/d

Loses 0.022 kilograms of muscle, new body weight = 6.578 kg… since FFM is reduced, BMR should be reduced.  It was a 0.33% loss of body weight which was entirely from muscle (in this theoretical example), so perhaps BMR declines proportionately 460.46 kcal/d (? there are more accurate formulas in the literature, but this approximation is sufficient for our purpose)

all of those excess calories formerly burned in the lost muscle are now available for storage in fat.

462 – 460.46 = 1.54 excess kcal/day.  1.54 excess kcal every day for 6 years = 3,372.6  total excess kcal, which translates to ~0.438 kg fat mass.

0.438 kg new fat mass – 0.022 kg muscle lost = 0.416 kg overall weight gain.

6.6 kg + 0.416 = 7.016 kg.  Actual final body weight was 7 kg.  Pretty darn close.

Wow, can the loss of less than one ounce of muscle really cause such a drastic change in fatness?!? I don’t know for sure, but exchanging the microwave popcorn for a little resistance exercise seems prudent.

(in case you were wondering, no. I didn’t guess 22 grams. I did a ton calculations to quantify the metabolic rate reduction necessary to cause an energy surplus big enough to lay down enough fat mass to compensate for the reduction in muscle [which theoretically declined in proportion to the reduction in metabolic rate] and end up as close to 7 kg as possible… it could be calculated exactly but this has taken up 30 minutes already, and I think the point has been made)

2. Alternatively:  Energy expenditure varies day-to-day, hour-to-hour, second-to-second.  When we eat, we are transiently in positive energy balance, which reverses after a few hours, especially at night when a negative energy balance ensues and the fuel stored during the positive energy balance is utilized.  During those stints of positive energy balance, some of the excess energy is stored as fat tissue, while the rest is used to fuel the body.  Somehow, trans fatty acids shift the balance in favor of fat storage.

2a.  can there exist a positive energy balance selectively in adipose tissue?

2b. more likely, trans fatty acids reduce some component of energy expenditure, possibly basal metabolic rate, or perhaps the thermic effect of feeding.  Neither of these was measured, but I firmly believe energy balance was maintained.  It’s always maintained.

But the frightful conclusion remains the same: the TRANS group got fatter without eating more.  They didn’t eat more than they were supposed to but got fatter anyway.  Sad but true.

What about in humans?

Effect of trans-fatty acid intake on insulin sensitivity and intramuscular lipids-a randomized trial in overweight postmenopausal women. (Bendsen et al., 2011 Metabolism)

This study gave a group of 52 overweight but otherwise healthy postmenopausal women 16 grams of trans fatty acids in pumpkin muffins.  The control group received olive & palm oil-enriched pumpkin muffins.  In terms of the dosing, this study is almost directly comparable to Kavanaugh’s study.  However, this study only lasted 16 weeks (probably due to ethical reasons).  They also included a lean control group (for good measure?), baseline subject characteristics are below:

 

Nothing out of the ordinary.

And the investigators measured compliance empirically.  You are what you eat.  When a specific type of fat is consumed, its constituent fatty acids accumulate in body tissues like adipose and red blood cells.  So the researchers measured red blood cell trans fatty acid content.  Kudos!  (biomarkers are superior to almost any other measurement of compliance to a dietary intervention in humans)

 

Indeed, the women ate their muffins.  But no effect on body weight!

 

Body weight increased by about 2% in both groups.  If you want to get nit-picky, then we can make a few verrry long stretches concerning the body composition data:

 

The increase in fat mass was 33% greater in TFA compared to controls!  (fat mass increased by 3% in the control group and 4% in TFA).  The increase in percent body fat was twice as big in TFA compared to controls!  (body fat percent increased by 1% in the control group and 2% in TFA).  IOW, the changes in body composition were nil.  This does not necessarily refute Kavanaugh’s African green monkeys because that study lasted 6 years; the insignificant changes in fat mass in Bendsen’s women over the course of 16 weeks could very well add up to significant changes after 6 years.  Actually, if the endpoint was indeed a 6% weight gain after 6 years (like the monkeys) (78.7 * 1.06 = 83.422 -78.7 = 4.722 / 6 years = 2.156 grams per day x 16 weeks = 241 grams) we might have expected these women to gain less than they actually did (~ 241 grams in 16 weeks compared to 1,200 grams).  In truth, however, these numbers are well beneath what can actually be measured accurately even in a laboratory setting.  So it is bona fide nit-picking.

Maybe it’s time to throw in the towel and confess that trans fats are significantly worse for African green monkeys than for overweight but otherwise healthy postmenopausal women.  There was no change in visceral adipose between the groups:

 

Potential confounding?  I’m really grasping at straws… but here it goes anyway:

 

The TFA group reduced their carbohydrate consumption over the course of the study.  Carbohydrate consumption is directly correlated with liver fat accumulation.  But as per the trans fat study, trans fat consumption is inversely correlated with liver fat.  So we might expect trans fat-induced increase in liver fat to be cancelled out by the carb reduction-induced decrease in liver fat.  And this is exactly what happens!

 

Furthermore, liver fat didn’t change in the control group because 1) their carbohydrate intake didn’t decline, and 2) they weren’t eating a ton of trans fats.  IOW, neither of the major dietary determinants were altered.

So, according to these colorful explanations, trans fats may have been just as harmful to Bendsen’s women as they were to Kavanaugh’s monkeys.  The reason why the results differ can be at least partially explained by the inferior dietary intervention utilized by Bendsen.  IOW, Kavanaugh’s dietary intervention was perfect; the subjects (monkeys) ate their prescribed diet exactly, no cheating, no sneaking in any snacks.  The diet changed markedly in Bendsen’s study; all women gained weight meaning that the test foods were probably not isocalorically substituted for foods in their normal diet.  Perhaps they just ate the foods in addition to their normal foods (unlikely considering the marked changes in macronutrient consumption).

Some more data from Bendsen’s overweight but otherwise healthy postmenopausal women were reported in another paper, and hints of trans fat-induced insulin resistance were revealed…

Here are the results from an oral glucose tolerance test:

 

Glucose:  Just like Kavanaugh’s monkeys, there was no change in the glycemic response to a glucose load.

On the right, insulin levels.

 

Insulin:  The open triangles are the control group, solid squares are the TFA group..  The dashed lines indicate insulin responses at baseline and the solid lines represent insulin responses at 16 weeks. In a randomized controlled intervention study, ALL changes in the intervention group must be compared not only to baseline measurements (pre-treatment), but more importantly they must be compared to the changes in the control group.  Over the 16 weeks, insulin response declined very slightly in the control group (see the little red arrow around the 45 minute mark).  However, insulin response increased slightly in the TFA group.  Take either of these changes individually and they would amount to nil.  But when you consider the change in control vs that in TFA, a modest trend appears.  The TFA group is beginning to show a hint of peripheral insulin resistance.  Maybe I’m seeing something where there is nothing, but the Kavanaugh’s study lasted 6 years and Bendsen’s study was only 16 weeks.  We must expect the changes to be ~20 times smaller in the Bendsen study.

OK, perhaps I got lost in the minutiae, or lost sight of the forest for the trees, but that doesn’t mean I’ll be eating microwave popcorn any time soon.  And on the bright side, creating this post was a great brain exercise

calories proper

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Posted in Advanced nutrition, Dietary fat, pair-feeding, Trans fat, Uncategorized