Monthly Archives: October 2011

Grains III

Grains, gluten, and kids.  And I go WAY overboard on Table 4.

This topic has special relevance because grains provide more calories (31%) than any other food group.  And they are probably the most detrimental.

Higher intakes of energy and grain products at 4 years of age are associated with being overweight at 6 years of age (Dubois, Porcherie et al., 2011 Journal of Nutrition)

The Quebec Longitudinal Study of Child Development (QLSCD) assessed food intake and lifestyle variables in ~1,000 Canadian kids born in 1998 for 2 years.  The data came primarily from mothers but also daycare attendants when necessary, and their method for assessing food intake was pretty good- “multiple-pass” 24-h dietary recall interviews conducted in the home, and they double-checked by re-questioning a huge subgroup (~50%!, kudos).

Methodological peculiarities:

1)      Food groups consisted of

  1. Grains (e.g., breads, pastas, cereals, rice, etc.)
  2. Fruits and vegetables
  3. Dairy
  4. Meat and alternatives (e.g., meat [duh], lentils, tofu, and peanut butter)

What is the rationale for grouping lentils, tofu, and peanut butter 1) together, and 2) with meat?  IOW, data regarding the consumption of “meat and alternatives” will be difficult to interpret.

2)      Divisions between underweight, normal weight, and overweight were based on percentiles as opposed to absolute values.  For adults, BMI<20 = underweight, 20-25 = normal weight, 25-30 = overweight, and >30 = obese, regardless of the weight of their friends, colleagues, and neighbors.  By using percentiles: if the entire cohort is heavier than average, then overweight kids will be classified as normal weight because they are “normal” relative to the rest of the kids in the study, who are heavier than average.  So it’s not a debilitating methodological peculiarity, it just changes the definitions with which we are accustomed… so when they start out their results by stating [sic]: “20% of the children were overweight,” it doesn’t mean they have an unusually lean cohort, it actually tells us nothing.

Divide and conquer

Here’s what these kids were eating, in total and broken down by body weight groups:

 

Heavier kids ate more carbohydrates and less fat, and protein intake was relatively constant.  No big surprises, except that none of this reached statistical significance despite being true across all three quintiles… the lack of statistical significance is most likely due to the small sample size, and I suppose we’ve been spoiled lately with studies that included much larger subjects.  FTR, the carbs and fat data are probably the most relevant finding WRT feeding your kids.

Table 2 showed macronutrients and total energy, while Table 3 shows the breakdown by food groups (see Methodological Pecularity #2 above).

 

THIS is troubling.  Grain consumption is highly adherent to the guidelines, but the more the guidelines were adhered to, the fatter the kids got.  Combined with the amount of calories grains contribute to overall energy intake, this provides a fairly clear explanation for the childhood obesity epidemic.  IOW, these data strongly suggest the guidelines are wrong.

The long-awaited Table 4.  (did you feel the suspense?)

 

This table shows the odds for being overweight in increasing quintiles of total calorie intake.  The first and second columns show what everyone normally expects: more calories consumed = more chance of being overweight.  And it’s highly statistically significant.  But here’s the kicker: the third column adjusts for body weight at 4 years of age and the association is abolished.  !!!  That means being fat at 4 years old was a more important predictor of being fat at 6 years old than calorie intake.  Chubby 6 year olds were overweight because they were chubby when they 4 years old, NOT because they ate too much !  Excessive inactivity is ruled out because these data were adjusted for physical activity.

“Eating less and moving more” is not the answer.  Nutrition matters.  Don’t feed your kids grains, regardless of the guidelines.

 

calories proper

 

really?

REALLY??

REALLY?

 

Glycemic index revisited, again, etc.

The glycemic index (GI) ranks foods based on how high 100 grams (~3.5 oz.) of them make go your blood sugar.  Dietary simple sugars like sucrose (table sugar) and glucose (e.g., Gatorade) have high GI’s because they are quickly digested and absorbed.  Fats and proteins register low on the GI because, well, they don’t provide any glucose.  Complex carbohydrates and fibres are intermediate.  And most important, mixed meals have a low to intermediate GI.  It was once dogma that only high GI foods caused weight gain, but a plethora of somewhat disappointing studies have shown that 1) a low GI diet doesn’t protect lean people from weight gain, and 2) switching from a high to a low GI diet doesn’t facilitate weight loss.  Glycemic load (GL) was then introduced which incorporates the amount of the food consumed, such that low GI foods could have a high GL if enough was eaten at once.  This fared slightly better than GI, but in the end, the total amount of carbohydrates turned out to be more important than the type of carbohydrates. IOW, WRT glycemia and body weight, quantity outweighs quality.  But that doesn’t stop the researchers from testing it … over and over again (on the taxpayers dime!).  In their defense, epidemiological studies have demonstrated a very modest relationship between GI/GL and disease risk, just not with body weight, adiposity, etc.

For example,

Substituting white rice with brown rice for 16 weeks does not substantially affect metabolic risk factors in middle-aged Chinese men and women with diabetes or a high risk for diabetes (Zhang et al., 2011 Journal of Nutrition)

I like this study for its practicality.  It is a real-life, highly “do-able” intervention, which is usually a critical concept in interpreting and applying the results from dietary intervention studies.  Switching out white rice for brown rice, easy enough!  The entire population was Chinese, who ingest phenomenal amounts of rice anyway (>30% of total calories… daily!), so attrition was not a problem.  And as wonderfully illustrated in the chart below, making the switch for 4 months had no effect whatsoever (see the P-values in the far right column).

 

 

LDL cholesterol went down slightly more in the white rice group, but this is biologically insignificant.  All other metabolic parameters were unchanged.  For those who like to nit-pick, BMI went down slightly more in the brown rice group while waist circumference went down slightly more in the white rice group, meaning that body composition may have been more favorably affected by white rice :/

This study is reminiscent of a much larger and more important one by none other than Willett and his Harvard cronies in a population of Brazilian women:

An 18-mo randomized trial of a low-glycemic-index diet and weight change in Brazilian women (Sichieri, Hu, Willett et al., 2001 AJCN)

This study was of a similar design; although they targeted both GI and GL.  The intervention was more robust; there were much bigger dietary differences between the groups, probably because Willet’s crew has virtually unlimited resources, but this didn’t change the outcome.  Total carbohydrate (60% of kcal), fat (27%), and protein (13%) intakes were the same but GI and GL were almost 3 times greater in the high GI (HGI) group compared to the low GI (LGI) group.  FTR, “3 times” is a really big difference… IOW, if GI or GL had any effect whatsoever, they would have detected it from a mile away.

For those who were wondering what exactly comprises a low or high GI diet, a sample menu was provided:

As seen in the table below, there were no dietary differences other than GI & GL between the groups (meaning it was a well-controlled intervention; kudos):

And as illustrated in the figure below, GI and GL had no effect on body weight:

N.B. the scale of the abscissa- it encompasses one kilogram (2.2 pounds); thus, it should look more like this:

Anyway, it looks like both groups lost a LOT of weight, but really their body weight declined very slightly by about 1-2 pounds, then slowly creeped back up (over the course of 18 months).  AND for those nit-pickers, it looks like the low GI group ended up slightly heavier! (not really, as the difference was very small and statistically insignificant). IMHO, WRT GI & GL, the Willet study is compelling.  It was of the highest quality study design: a randomized, controlled, intervention (as opposed to less conclusive or meaningful epidemiological, observational, cross-sectional, etc., studies).  So what was the rationale to re-test GI & GL in a much smaller study with a weaker intervention (brown vs. white rice)?  Beats me!  But the notion that a low GI or GL favorably affects body weight will not go away.  Carbohydrate quantity not quality is the major determining factor.

AND as blogged extensively on HERE, potato chips were the most obesogenic foods in one hyooge study.  potato chips have a relatively low GI, around 55.

 

calories proper

 

 

 

 

 

 

 

 

 

 

 

 

Nutrition under attack

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