Monday, January 16, 2012

The China Study II: Wheat’s total effect on mortality is significant, complex, and highlights the negative effects of low animal fat diets

The graph below shows the results of a multivariate nonlinear WarpPLS () analysis including the variables listed below. Each row in the dataset refers to a county in China, from the publicly available China Study II dataset (). As always, I thank Dr. Campbell and his collaborators for making the data publicly available. Other analyses based on the same dataset are also available ().
    - Wheat: wheat flour consumption in g/d.
    - Aprot: animal protein consumption in g/d.
    - PProt: plant protein consumption in g/d.
    - %FatCal: percentage of calories coming from fat.
    - Mor35_69: number of deaths per 1,000 people in the 35-69 age range.
    - Mor70_79: number of deaths per 1,000 people in the 70-79 age range.

Below are the total effects of wheat flour consumption, along with the number of paths used to calculate them, and the respective P values (i.e., probabilities that the effects are due to chance). Total effects are calculated by considering all of the paths connecting two variables. Identifying each path is a bit like solving a maze puzzle; you have to follow the arrows connecting the two variables. Version 3.0 of WarpPLS (soon to be released) does that automatically, and also calculates the corresponding P values.

To the best of my knowledge, this is the first time that total effects are calculated for this dataset. As you can see, the total effects of wheat flour consumption on mortality in the 35-69 and 70-79 age ranges are both significant, and fairly complex in this model, each relying on 7 paths. The P value for mortality in the 35-69 age range is 0.038; in other words, the probability that the effect is “real”, and thus not due to chance, is 96.2 percent (100-3.8=96.2). The P value for mortality in the 70-79 age range is 0.024; a 97.6 percent probability that the effect is “real”.

Note that in the model the effects of wheat flour consumption on mortality in both age ranges are hypothesized to be mediated by animal protein consumption, plant protein consumption, and fat consumption. These mediating effects have been suggested by previous analyses discussed on this blog (). The strongest individual paths are between wheat flour consumption and plant protein consumption, plant protein consumption and animal protein consumption, as well as animal protein consumption and fat consumption.

So wheat flour consumption contributes to plant protein consumption, probably by being a main source of plant protein (through gluten). Plant protein consumption in turn decreases animal protein consumption, which significantly decreases fat consumption. From this latter connection we can tell that most of the fat consumed likely came from animal sources.

How much fat and protein are we talking about? The graphs below tell us how much, and these graphs are quite interesting. They suggest that, in this dataset, daily protein consumption tended to be on average 60 g, whatever the source. If more protein came from plant foods, the proportion from animal foods went down, and vice-versa.

The more animal protein consumed, the more fat is also consumed in this dataset. And that is animal fat, which comes mostly in the form of saturated and monounsaturated fats, in roughly equal amounts. How do I know that it is animal fat? Because of the strong association with animal protein. By the way, with a few exceptions (e.g., some species of fatty fish) animal foods in general provide only small amounts of polyunsaturated fats – omega-3 and omega-6.

Individually, animal protein and wheat flour consumption have the strongest direct effects on mortality in both age ranges. Animal protein consumption is protective, and wheat flour consumption detrimental.

Does the connection between animal protein, animal fat, and longevity mean that a diet high in saturated and monounsaturated fats is healthy for most people? Not necessarily, at least without extrapolation, although the results do not suggest otherwise. Look at the amounts of fat consumed per day. They range from a little less than 20 g/d to a little over 90 g/d. By comparison, one steak of top sirloin (about 380 g of meat, cooked) trimmed to almost no visible fat gives you about 37 g of fat.

These results do suggest that consumption of animal fats, primarily saturated and monounsaturated fats, is likely to be particularly healthy in the context of a low fat diet. Or, said in a different way, these results suggest that longevity is decreased by diets that are low in animal fats.

How much fat should one eat? In this dataset, the more fat was consumed together with animal protein (i.e., the more animal fat was consumed), the better in terms of longevity. In other words, in this dataset the lowest levels of mortality were associated with the highest levels of animal fat consumption. The highest level of fat consumption in the dataset was a little over 90 g/d.

What about higher fat intake contexts? Well, we know that men on a high fat diet such as a variation of the Optimal Diet can consume on average a little over 170 g/d of animal fat (130 g/d for women), and their health markers remain generally good ().

One of the critical limiting factors, in terms of health, seems to be the amount of animal fat that one can eat and still remain relatively lean. Dietary saturated and monounsaturated fats are healthy. But when accumulated as excess body fat, beyond a certain level, they become pro-inflammatory.


Anonymous said...

Ned - interesting stuff, though your description of p-values is slightly misleading: " in other words, the probability that the effect is “real”, and thus not due to chance, is 96.2 percent (100-3.8=96.2)". The p-value is NOT the probability that the effect is real, it's the probability that one would find an effect as big as the observed one if there was not truly an effect. To find the probability that the effect is real you would need to use Bayesian statistics to obtain a posterior probability.

Anonymous said...

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LeonRover said...

@Anon II


Should Ned consider himself in the same boat as Denise and slapped down?

Ned Kock said...

Hi Anon(1). I often try to use language that is more understandable to the non-technical reader – e.g., insignificant vs. non-significant etc.

I am not sure you can use the term “real” more reliably with prior definitions of hyperparameters and such. Bayesian stats are definitely very interesting though.

Ned Kock said...

I’ve never attacked Dr. Campbell on this blog. In fact, I usually go out of my way to thank him and his collaborators for the data that I use in posts such as this.

Still, his response to Denise is not very convincing.

I don’t believe in attacking the messenger, one way or another. It is a distraction.

The message, and the ideas underlying it, are much more important.

Ned Kock said...

For some of the more technical readers: the software, WarpPLS, does not make any assumptions about multivariate normality in the calculation of P values. It uses resampling (e.g., bootstrapping) for that.

Gretchen said...

I think one should keep in mind that the cited steak with 37 g fat was 13 oz. Maybe some people eat 13 oz of meat per meal, but many eat far less.

David Isaak said...

Slick software!

The variance in daily protein intake is interesting, and the average is somewhat higher than I would have expected from anecdotes about China. I wonder where the numbers would have been 30 years ago.

I still have a hard time teasing out causality here. Are we to assume that consuming wheat is damaging because of its metabolic effects, or because it pushes out the consumption of other, more beneficial foods? (Or, as Gary Taubes puts it, the problem with dietary studies is that you have to eat something, and eating less of something usually means eating more of something else.)

Ned Kock said...

Good question David. The answer is in part here, but more clearly when we also consider a different post, which looks at the moderating effect that consumption of animal foods has on the effect of wheat on mortality:

Wheat flour intake increases mortality significantly in both age ranges, and the strengths of the effects do not go down so much here (in this post), when we control for animal protein, plant protein, and fat consumption. This is suggested by the direct effects shown on the graph here.

From that other post, we can see that animal food intake significantly reduces the negative effect of wheat flour consumption on mortality in the 70 to 79 age range.

What these results seem to be telling us is that wheat flour consumption contributes to early death for several people, perhaps those who are most sensitive or intolerant to wheat, regardless of its displacement of animal foods. These people are represented in the variable measuring mortality in the 35 to 69 age range, and not in the 70 to 79 age range, since they died before reaching the age of 70.

Those in the 70 to 79 age range may be the least sensitive ones, and for whom animal food intake seems to be protective. But only if animal food intake is above a certain level. How much animal food does it take for the protective effect to be observed? In the China Study II sample, it is about 221 g/day or more.

As I said earlier, this is not a ringing endorsement of wheat, but certainly helps explain wheat consumption in long-living groups around the world, including the French.

Ned Kock said...

It should be noted that the variable labeled as “Wheat” refers to wheat flour, and not seitan (a.k.a., “mock duck”), consumption.

Ned Kock said...

Something that is also worth noting is that the effect of wheat flour consumption on mortality is stronger in the 70 to 79 age range, which may suggest that it takes a long time for it to cause health problems (similarly to refined sugar consumption and smoking).

That is worth noting in connection with my comment on seitan above, because seitan was developed in the 1960s, and the China Study II dataset contains data from the 1980s.

David Isaak said...

Interesting stuff.

"Seitan" is a problematic term. It initially was a specific wheat gluten recipe--essentially seasoned wheat gluten. But many people (myself included) now use it to refer to any purified wheat gluten.

While "seitan" is recent, use of purified wheat gluten (mian jin) is ancient, going back to at least the sixth century, and it has long been an important component of cuisine in China--especially among the upper classes.

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Frank said...

Maybe educated gain more money and eat more meat. And they have more healthy lifestyle. Is SES and education level controlled in the study?

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