Boring is another word for satiating

Satiety is a common topic of discussion on this blog. In the last few posts it came up several times in the comments’ sections. Also, in my interview with Jimmy Moore, we did talk a bit about satiety. I told him what has been my perception and that of many people I know, which is that the least satiating foods tend to be foods engineered by humans.

(Source: Wellnessuncovered.com)

There is another component to satiety, which applies to natural foods, or foods that are not man-made. That other component is the nutrition value of those foods, and whether they meet our nutrition needs at a given point in time. If our body needs certain essential amino acids for tissue repair, subconscious mechanisms will make us crave those foods from which those amino acids can be extracted. In this context, eating is generally a good idea.

The problem is that we have not evolved mechanisms to differentiate “true” from “fake” nutrient starvation; one example of the latter would be fat starvation due to transient hyperinsulinemia induced by refined carbohydrate-rich foods.

Foods engineered by humans tend to lead to overeating because humans are good engineers. In modern society, business drives everything. Food business is predicated on consumption, so engineered foods are designed so that one person will want to consume many units of a food item – typically something that will come in a box or a plastic bag. There is no conspiracy involved; the underlying reason is profit maximization.

When we look at nature, we typically see the opposite. Prey animals do not want to be eaten; often they fight back. Eggs have to be stolen. Plants do not want their various parts, such as leaves and roots, to be eaten. Much less their seeds; so they have developed various defense mechanisms, including toxins. Fruits are exceptions to this rule; they are the only natural foods that are designed to be eaten by animals.

Plants want animals to eat their fruits so that they can disperse the plants’ seeds. So they must be somewhat alluring to animals. Sugar plays a role here, but it certainly is not the only factor. The chemical composition of fruits is quite complex, and they usually contain a number of health-promoting substances, such as vitamins. For example, most fruits contain vitamin C, which happens to be a powerful antioxidant, and also has the ability to reversibly bind to proteins at the sites where sugar-induced glycation would occur.

Many modern fruits have been bred to be resistant to diseases, more palatable, and larger (usually due to more water retention). But, fundamentally, fruits are products of evolution. So how come we don’t see fruits that are pure sugar? Watermelons, for example, are often referred to as “bags of sugar”, but they are only 6 percent sugar. Ice cream is 25 percent sugar.

Two things must be kept in mind regarding fruits and their evolution. One is that dead animals do not eat fruit, and thus cannot disperse seeds. Sick animals would probably not be good candidates for fruit dispersion either. So the co-evolution of fruits and animals must have led fruits to incorporate many health-promoting attributes. The other is that seed dispersion success is correlated with the number of different animals that consume fruits from a plant. In other words, plants do not want all of their fruits to be eaten by one single animal, which must have led fruits to incorporate satiety-promoting attributes.

Often combining foods, adding spices, and so on, is perceived as making those foods exciting. That is so even with natural foods. If you read the descriptions of the foods consumed by healthy isolated populations in Weston Price’s Nutrition and Physical Degeneration, you will probably find them a bit boring. A few very nutritious food items, consumed day in and day out, frequently without heavy preparation. Exciting foods, requiring elaborate and time-consuming preparation, were consumed in special occasions. They were not eaten regularly.

The members of those healthy isolated populations were generally thin and yet lacked no important nutrients in their diet. They were generally free from degenerative diseases. Their teeth were normally strong and healthy.

Just before writing this post, I took six whole sardines out of the freezer to thaw. I will prepare them as discussed on this post, and eat them with a side of steamed vegetables for lunch. (I tend to eat fruits only on the days I exercise; typically 3 days out of 7.) This lunch will be very nutrient-dense. I will be very hungry before lunch, since I’ll have been fasting for 16 hours, and after I’ll not be hungry until dinner. Frankly, eating the sardines will not be very exciting, since I’ve been doing this for years.

Boring is another word for satiating.

"Friends Don't Let Friends Drive Drunk": How Soon is too Soon to Find the Teachable Moment in the Death of Ryan Dunn?

"Friends Don't Let Friends Drive Drunk". A memorable tag line from the 1990s, found in many drunk driving prevention public service announcements (PSAs).

Early Monday morning, June 20, 2011, Ryan Dunn and a passenger were killed in a car accident in Pennsylvania. Ryan appeared in all three seasons of "Jackass" on MTV, as well as their movies.

Shortly after the news of Ryan's death broke (along with preliminary reports of speeding and photos of him drinking at the bar hours before the accident), Roger Ebert tweeted "Friends Don't Let Jackasses Drink and Drive". Although Roger did not "intend to be cruel"- he "intended to be true", there was a lot of backlash to his play on the old PSA tagline. Ryan's friends and colleagues from "Jackass" tweeted their anger in response and popular celebrity blogger Perez Hilton posted that Roger responded insensitively to Ryan's death. All felt that it was too soon to hold Ryan up as an example of the dangers of drinking and driving.

So the question I pose is: How soon is too soon to capitalize on a "teachable moment"?

Teachable moments are important in public health. They let us identify a time when our audiences will be more open to prevention education/intervention because they will see its relevance to their lives. Often the identification and sustainability of teachable moments are supported by media reports on the health/lives of celebrities.

As this week has moved along, more information has been released about the accident that killed Ryan Dunn and his passenger. His alcohol level was approximately twice the legal limit in Pennsylvania (0.196%) and he was traveling at a very high rate of speed (estimated at 132-140 mph) at the time of collision. Therefore, there is clearly a lesson to be learned here- about speeding and about drinking and driving. But much of these lessons our audience already knows. If you drink and drive- you could die (and/or kill someone else). If you speed- you could die (and/or kill someone else).

So maybe the lessons have to be broader. Apparently Ryan had a history of speeding and driving under the influence. These factors put him at risk. What could he, his friends, his family, the courts, the bar done to prevent this tragedy? What about the bystanders? His friends at the bar...employees at the bar...his friend who ultimately got into the car...could someone have stopped him from driving? What are the lessons you find in this story and how/when should they be communicated?

Maybe you should stop trying to be someone you are not

Many people struggle to lose body fat, and never quite make it to their optimal. Fewer people manage to do so successfully, and, as soon as they do, they want more. It is human nature. Often they will start trying to become someone they are not, or cannot be. That may lead to a lot of stress and frustration, and also health problems.

Some women have an idealized look in mind, and keep losing weight well beyond their ideal, down to anorexic levels. That leads to a number of health problems. For example, hormones approach starvation levels, causing fatigue and mood swings; susceptibility to infectious diseases increases significantly; and the low weight leads to osteopenia, which is a precursor to osteoporosis.

In men, often what happens is the opposite. Guys who are successful getting body fat to healthy levels next want to become very muscular, and fast. They have an idealized look in mind, and think they know how much they should weigh to get there. Sometimes they want to keep losing body fat and gaining muscle at the same time.

I frequently see men who already look very healthy, but who think that they should weigh more than they do. Since muscle gain is typically very slow, they start eating more and simply gain body fat. The reality is that people have different body frames, and their muscles are built slightly differently; these are things that influence body weight.

There are many other things that also influence body weight, such as the length of arms and legs, bone density, organ mass, as well as the amount of glycogen and water stored throughout the body. As a result, you can weigh a lot less than you think you should weigh, and look very good. The photo below (from MMAjunkie.com) is of Donald Cerrone, weighing in at 145 lbs. He is 6 ft (183 cm) tall.

Mr. Cerrone is a professional mixed martial arts (MMA) fighter from Texas; one of the best in professional MMA at the moment. Yes, he is a bit dehydrated on the photo above. But also keep in mind that his bone density is probably well above that of the average person, like that of most MMA fighters, which pushes his weight up.

A man can be 6 ft tall, weigh 145 lbs, and be very healthy and look very good. That may well be his ideal weight. A woman may be 5’5”, weigh 145 lbs, and also be very healthy and look very good. Figuring out the optimal is not easy, but trying to be someone you are not will probably be a losing battle.

Alcohol intake increases LDL cholesterol, in some people

Occasionally I get emails from people experiencing odd fluctuations in health markers, and trying to figure out what is causing those fluctuations. Spikes in LDL cholesterol without any change in diet seem to be a common occurrence, especially in men.

LDL cholesterol is a reflection of many things. It is one of the least useful measures in standard lipid profiles, as a predictor of future health problems. Nevertheless, if one’s diet is not changing, whether it is high or low in fat, significant fluctuations in LDL cholesterol may signal a change in inflammatory status. Generally speaking, the more systemic inflammation, the higher is the measured LDL cholesterol.

Corella and colleagues (2001) looked into alcohol consumption and its effect on LDL cholesterol, as part of the Framingham Offspring Study. They split the data into three genotypes, which are allele combinations. Alleles are genes variations; that is, they are variations in the sections of DNA that have been identified as coding for observable traits. The table below summarizes what they have found. Take a look at the last two columns on the right.

As you can see, for men with the E2 genotype, alcohol consumption significantly decreases LDL cholesterol. For men with the E4 genotype, alcohol consumption significantly increases LDL cholesterol. No significant effects were observed in women. The figure below illustrates the magnitude of the effects observed in men.

On average, alcohol consumption was moderate, around 15 g per day, and did not vary significantly based on genotype. This is important. Otherwise one could argue that a particular genotype predisposed individuals to drink more, which would be a major confounder in this study. Other confounders were also ruled out through multivariate controls - e.g., fat and calorie intake, and smoking.

Alcohol consumption in moderation seems, on average, to be beneficial. But for some individuals, particularly men with a certain genotype, it may be advisable to completely abstain from alcohol consumption. Who are those folks? They are the ones for whom LDL cholesterol goes up significantly following moderate alcohol consumption.

What is a good low carbohydrate diet? It is a low calorie one

My interview with Jimmy Moore should be up on the day that this post becomes available. (I usually write my posts on weekends and schedule them for release at the beginning of the following weeks.) So the time is opportune for me to try to aswer this question: What is a good low carbohydrate diet?

For me, and many people I know, the answer is: a low calorie one. What this means, in simple terms, is that a good low carbohydrate diet is one with plenty of seafood and organ meats in it, and also plenty of veggies. These are low carbohydrate foods that are also naturally low in calories. Conversely, a low carbohydrate diet of mostly beef and eggs would be a high calorie one.

Seafood and organ meats provide essential fatty acids and are typically packed with nutrients. Because of that, they tend to be satiating. In fact, certain organ meats, such as beef liver, are so packed with nutrients that it is a good idea to limit their consumption. I suggest eating beef liver once or twice a week only. As for seafood, it seems like a good idea to me to get half of one’s protein from them.

Does this mean that the calories-in-calories-out idea is correct? No, and there is no need to resort to complicated and somewhat questionable feedback-loop arguments to prove that calories-in-calories-out is wrong. Just consider this hypothetical scenario; a thought experiment. Take two men, one 25 years of age and the other 65, both with the same weight. Put them on the same exact diet, on the same exact weight training regime, and keep everything else the same.

What will happen? Typically the 65-year-old will put on more body fat than the 25-year-old, and the latter will put on more lean body mass. This will happen in spite of the same exact calories-in-calories-out profile. Why? Because their hormonal mixes are different. The 65-year-old will typically have lower levels of circulating growth hormone and testosterone, both of which significantly affect body composition.

As you can see, it is not all about insulin, as has been argued many times before. In fact, average and/or fasting insulin may be the same for the 65- and 25-year-old men. And, still, the 65-year-old will have trouble keeping his body fat low and gaining muscle. There are other hormones involved, such as leptin and adiponectin, and probably several that we don’t know about yet.

A low carbohydrate diet appears to be ideal for many people, whether that is due to a particular health condition (e.g., diabetes) or simply due to a genetic makeup that favors this type of diet. By adopting a low carbohydrate diet with plenty of seafood, organ meats, and veggies, you will make it a low calorie diet. If that leads to a calorie deficit that is too large, you can always add a bit more of fat to it. For example, by cooking fish with butter and adding bacon to beef liver.

One scenario where I don’t see the above working well is if you are a competitive athlete who depletes a significant amount of muscle glycogen on a daily basis – e.g., 250 g or more. In this case, it will be very difficult to replenish glycogen only with protein, so the person will need more carbohydrates. He or she would need a protein intake in excess of 500 g per day for replenishing 250 g of glycogen only with protein.

Google Continues to Use its Power for Public Health Good

Yesterday, Google announced its new surveillance system for Dengue Fever. Dengue Fever is a disease caused by four related viruses spread by a particular species of mosquito. It can cause high fever, rash, muscle and joint pain, and in severe cases- bleeding, a sudden drop in blood pressure (shock) and death. Millions of cases of Dengue infection occur worldwide each year. Most often, dengue fever occurs in urban areas of tropical and subtropical regions.

The system is similar to that which was previously released as their Google Flu Trends program. These systems use search queries within Google (for example those that enter the disease's name and/or symptoms) to identify trends. The Dengue system also takes advantage of a new feature called Google Correlate, which shows previously unknown correlations between search terms. These correlations allow researchers to model real world behaviors by examining internet search trends. For those who may be skeptical of this model, you should check out a publication (co-authored by Google and the Centers for Disease Control and Prevention-CDC) in the 2009 Nature Journal . The article reports that "because relative frequencies of certain queries were highly correlated with the percentage of physician visits in which a patient presents with influenza-like symptoms, we can accurately estimate the current level of weekly influenza activity in each region of the United States, with a reporting lag of about one day."

This is a pretty exciting addition to public health surveillance (where the goal is systematic, ongoing, data collection that is used to monitor trends, identify priorities, direct resources, identify emerging hazards, and evaluate interventions).

This is not the first time that Google has jumped into the public health field with an impressive contribution. In 2010, Google searches related to suicide started appearing with a message guiding users to the toll-free number for the National Suicide Prevention Lifeline. The number is 1-800-273-8255. Triggered by searches such as "I want to die" or "ways to commit suicide," the number is listed next to an icon of a red telephone, at the top of the search results.

The addition of the Lifeline number came shortly after (at the suggestion of a Google user), the company started displaying the hotline for the American Association of Poison Control Centers after searches for "poison emergency."

These cases of Google's work in public health are great examples of effective health communication and public health principles:

• Identifying the primary channels through which your audience searches for health information (more and more are utilizing the internet) and delivering accurate and effective information and/or interventions via those channels.

• Maximizing data driven surveillance systems- using existing data (e.g., internet searches) to identify public health trends.

• Building strong partnerships (as evidenced by the publication by Google and CDC) CDC has partnered with a company with specific expertise and resources in an area that can be invaluable to their work.
  

The China Study II: Wheat may not be so bad if you eat 221 g or more of animal food daily

In previous posts on this blog covering the China Study II data we’ve looked at the competing effects of various foods, including wheat and animal foods. Unfortunately we have had to stick to the broad group categories available from the specific data subset used; e.g., animal foods, instead of categories of animal foods such as dairy, seafood, and beef. This is still a problem, until I can find the time to get more of the China Study II data in a format that can be reliably used for multivariate analyses.

What we haven’t done yet, however, is to look at moderating effects. And that is something we can do now.  A moderating effect is the effect of a variable on the effect of another variable on a third. Sounds complicated, but WarpPLS makes it very easy to test moderating effects. All you have to do is to make a variable (e.g., animal food intake) point at a direct link (e.g., between wheat flour intake and mortality). The moderating effect is shown on the graph as a dashed arrow going from a variable to a link between two variables.

The graph below shows the results of an analysis where animal food intake (Afoods) is hypothesized to moderate the effects of wheat flour intake (Wheat) on mortality in the 35 to 69 age range (Mor35_69) and mortality in the 70 to 79 age range (Mor70_79). A basic linear algorithm was used, whereby standardized partial regression coefficients, both moderating and direct, are calculated based on the equations of best-fitting lines.

From the graph above we can tell that wheat flour intake increases mortality significantly in both age ranges; in the 35 to 69 age range (beta=0.17, P=0.05), and in the 70 to 79 age range (beta=0.24, P=0.01). This is a finding that we have seen before on previous posts, and that has been one of the main findings of Denise Minger’s analysis of the China Study data. Denise and I used different data subsets and analysis methods, and reached essentially the same results.

But here is what is interesting about the moderating effects analysis results summarized on the graph above. They suggest that animal food intake significantly reduces the negative effect of wheat flour consumption on mortality in the 70 to 79 age range (beta=-0.22, P<0.01). This is a relatively strong moderating effect. The moderating effect of animal food intake is not significant for the 35 to 69 age range (beta=-0.00, P=0.50); the beta here is negative but very low, suggesting a very weak protective effect.

Below are two standardized plots showing the relationships between wheat flour intake and mortality in the 70 to 79 age range when animal food intake is low (left plot) and high (right plot). As you can see, the best-fitting line is flat on the right plot, meaning that wheat flour intake has no effect on mortality in the 70 to 79 age range when animal food intake is high. When animal food intake is low (left plot), the effect of wheat flour intake on mortality in this range is significant; its strength is indicated by the upward slope of the best-fitting line.

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

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. That is approximately the intake level above which the relationship between wheat flour intake and mortality in the 70 to 79 age range becomes statistically indistinguishable from zero. That is a little less than ½ lb, or 7.9 oz, of animal food intake per day.