Why You Should Arm Your Bullshit Alarm Before Reading Diet News.

In the fight over best diet for health and weight loss, it's protein lovers vs. vegetarian zealots. So far, a clear winner has not emerged. Only one loser: you, the victim of biased research. Here is an example of why you should keep your bullshit alarm on high alert when reading about weight loss diets.  

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Ellen M. Evans and colleagues wanted to know whether overweight men and women differ in their body composition responses to different weight loss diets [1]. So they enrolled 58 men and 72 women with a BMI greater than 26, and randomized them into two diet groups.
One group was instructed to follow a high-protein low-carbohydrate diet, which delivered 1.6 g of protein per kg bodyweight per day. The high-carb group  received only half that amount of protein, and both groups' fat intake was capped at 30% of total energy intake. Both diets contained the same amount of fiber. Women received a daily total of 1700 calories, men 1900 calories. The intervention lasted for 4 months, followed by an 8-months weight maintenance period. Fast forward to the 12-months results:

Both diet groups and both genders lost about 10% of their body weight. But expressing weight loss in kilos of body weight can be a deceptive thing. Ideally we want that loss to be fat loss rather than loss of lean mass, that is, muscle mass. In the study at hand, for men on the high-carb diet, a little over one third of their weight loss came from lean body mass. Meaning, of the 14 kilos, which they lost on average, 5 Kilos came from a reduction in muscle tissue. The high-protein guys maintained their muscle mass to a greater extent: only 20% of their weight loss came from wasted muscle. For the women the picture looked almost identical: muscle mass contributed 37% to the weight loss of the high-carb women, compared to 23% in the high-protein group. 

You would be forgiven if you now agreed with the authors' statement that the high-protein diet "...was more effective in reducing percent body fat...". Or in other words, a high-protein diet is superior to a high-carb alternative, as losing lean mass isn't a good thing in weight loss. I'll get to that point shortly in a little more detail. 

Before we go there, let me state, that, being a firm supporter of the high-protein low-carb dietary philosophy, I loved to read this study. But I'm an equally firm supporter of proper scientific methods. And they have been prostituted in this case, which is why I love this study a lot less than its results. 

Here is why: When I read the tables in which the authors present the results, I was impressed by the fact that both groups not only managed to rescue the 4-months weight loss to the 12-months finish line, but even increased this weight loss a little. When you have read literally hundreds of studies on weight loss interventions, as I have done, you'll find this observation to be in stark contrast to what we typically see: a reversal of weight loss. That is, at least a partial post-intervention regain of the weight lost during the dietary period. 

We find the explanation for this miraculous exception in the number of participants. Or rather in the number of disappearing participants. Of the 66 participants who started in the high-carb group, only 30 made it to the finish line 12 months later. That's a drop-out rate of more than 50%!  And of the 64 participants in the high-protein group 23, or 36%, had dropped out by month 12. 

High drop-out rates are nothing unusual in weight loss trials, but it is good practice for researchers to tell their readers, how they accounted for these drop outs in the statistics, with which they interpret the data. Nothing of that in this paper. So, we don't know whether the drop-outs simply did not show up for their measurements, or whether the researchers did not consider the data of those participants, who failed to achieve some arbitrary weight loss threshold. The latter is an absolute no-no. It enables researchers to skew the results every which way they want. And the former is reason to investigate whether the drop-outs differed in some way significantly from the adherent participants. Such differences often affect the interpretation of the results. 

One interpretation emerges right away, when checking the differences of relative fat loss while considering the drop-out rates:  the smaller relative loss of muscle mass in the high-protein diet is not significantly different from the loss observed in the high-carb group. That does not mean, there is no difference between these two diet types. It only means, the study was underpowered to detect such difference, if there was any. And if it was underpowered to detect the difference between diet groups, it was certainly underpowered to differentiate between men and women in this respect. 

If you still want the final verdict on high-carb vs. high-protein, I'm afraid I can't give it to you, even though I'm heavily leaning in favor of the high-protein version. I base my judgment on a 2009 systematic review of all randomized controlled trials, which were performed between 2000 and 2007, and which had pitted high-carb vs. high-protein strategies [2]. This review demonstrated that high-protein diets are more effective with respect to weight loss and probably with respect to cardiovascular risk factors than high-carb diets. At least over observation periods of 6 to 12 months. 

Only long-term observations, comparing hard endpoints, can decide which diet may be better. Those studies are a long way off. To complicate matters, we might find that different people react differently to the same type of dietary strategy. Until we know better, we need to go with what we know: 

The preservation of lean body mass certainly is a key aspect. Muscle tissue is an important endocrine organ, which, when exercised, produces potent anti-inflammatory substrates and hormones. These are the key elements of physical activity's protection against the initiating step of heart disease: atherosclerosis. Muscle tissue is also the body's primary site to store dietary carbohydrate in the form of glucose. The other site being the liver. With a high-carb diet, these storage sites are easily overwhelmed, which leads to conversion of carbs to fat. When, ironically, a high-carb diet nibbles away at the body's carb storage sites, you can imagine what this means to the body's relative fat content. Another aspect is that muscle tissue consumes energy, even at rest. The loss of this "burner" during weight loss makes weight rebound more likely.

So, if all these matters are known and understood, why perform a study, which is underpowered and fraud with questionable interpretations? Why produce the food equivalent of a scientology propaganda piece?  

Beats me. Maybe because part of the study's funding came from the National Cattlemen's Beef Association and The Beef Board. Both of which are, of course, entirely neutral to the outcome of research funded by them, and unbiased to its interpretation. 

It also beats me, why a respected journal and its peer reviewers facilitate the publication of such a study. Maybe because its senior author, Professor DK Layman, is a leading researcher in nutrition science, and... 

...the Egg Nutrition Center's director of research. 

As much as my dietary preferences place me in the protein camp of this contest, my bullshit alarm is set to high-sensitivity. And so should yours be. 

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1. Evans, E., et al., Effects of protein intake and gender on body composition changes: a randomized clinical weight loss trial. Nutrition and Metabolism, 2012. 9(1): p. 55.

2. Hession, M., et al., Systematic review of randomized controlled trials of low-carbohydrate vs. low-fat/low-calorie diets in the management of obesity and its comorbidities. Obesity Reviews, 2009. 10(1): p. 36-50.

Evans, Ellen, Mojtahedi, Mina, Thorpe, Matthew, Valentine, Rudy, Kris-Etherton, Penny, & Layman, Donald (2012). Effects of protein intake and gender on body composition changes: a randomized clinical weight loss trial Nutrition and Metabolism : doi:10.1186/1743-7075-9-55

Hession, M., Rolland, C., Kulkarni, U., Wise, A., & Broom, J. (2009). Systematic review of randomized controlled trials of low-carbohydrate vs. low-fat/low-calorie diets in the management of obesity and its comorbidities Obesity Reviews, 10 (1), 36-50 DOI: 10.1111/j.1467-789X.2008.00518.x

Individualized Medicine, Ignorant Medics And An Invitation To Lose Weight.

In my previous post I promised to talk about your individualized way to achieving optimal health. If that made you think about personalized medicine, you were right. Almost. Because personalized medicine is still light-years away from us. That's the bad news. The good news, personalized prevention is an emerging reality. At least in my lab. Which is why I would like to invite you to become a part of it. No strings attached. But before we get to this let's first get on the same page about the personalization of medicine.

Two questions we need to ask ourselves: What is personalized medicine and why would we want it?

Professor Jeremy K Nicholson of the Imperial College, London, defined personalized medicine as "effective therapies that are tailored to the exact biology or biological state of an individual" [1]. Such tailoring of a treatment, say for your high blood pressure, would require your doctor to evaluate your biochemical and metabolic profile in order to prescribe you the most effective drug or treatment at the most effective dose, with the least possibility of side effects.

Now, why would we want this?
Simply because we don't have it. Because our current drugs do not work optimally in most people [2]. But don't just take my word for it. Take that of Dr. Allen D. Roses, head of the Drug Discovery Institute at Duke University School of Medicine. In an interview he told a UK newspaper, The Independent, that more than 90% of modern drugs work, at best, in 30-50% of the people. He said that in 2003. At the time, Roses was also senior vice president for genetics research and pharmacogenetics at GlaxoSmithKline. 

Contrary to what you might think, Roses did not reveal any nasty industry secret. What he said is plainly visible for everyone who can read the results of clinical trials through the lens of statistics. I simply quote Roses for effect. After all, he knows what he is talking about. Contrary to many medical doctors, who have an amusingly limited grasp of the basic statistics used to interpret and present the results of clinical trials. Just how limited, that has been recently demonstrated for the case of cancer screening in a mock-up trial investigating the understanding of practicing physicians [3].

Before I tell you the results of this trial, let me make you understand what it was about. One big question in cancer screening is whether screening helps to reduce the number of people dying from cancer. Let's take a hypothetical example, and here I reuse the one which the study's authors used to explain statistical outcomes. Let's say, cancer was detected in a group of people at age 67. All of them died of their cancer at age 70. The 5-year survival rate from diagnosis would stand at 0% (they all died before 5 years were over). Now imagine that all those cancer cases would have been detected at age 60 with a screening test. And also imagine that all of them still died at age 70. In this case the 5-year survival rate would have been 100% (they were all still alive at 65). You see the issue: the survival rate was better with screening, but the rate of dying remained the same. In epidemiology we call this sort of thing lead-time bias. That is, simply detecting a disease earlier might lead to an improved survival rate which has, in fact, nothing to do with improved survival. Such lead time bias is rarely an all-or-nothing thing as in this hypothetical case. Most of the time it comes in degrees. But in any case, it would help you as a patient, if your doctor was able to see through the reporting, and to question the clinical relevance of the results so presented. Your doctor should look for the mortality rate, the rate of dying, not the survival rate.

Back to the results of the mock-up trial about physicians' interpretive skills of clinical research publications. If the results of this mock-up trial are representative of the population of your doctors, then you should be worried. Of the over 200 practicing physicians enrolled in this trial, fully 76% would recommend you this useless screening test. They considered an improved 5-year survival rate as prove for the test's efficacy! These were not undereducated physicians of a third world country, mind you. They were randomly selected from the Harris Interactive Physician Panel, which is representative of the general U.S. physician population.

OK, you may say that this was a test related to cancer screening. What has it got to do with understanding the efficiency of a drug, which your doctor prescribes you? Well, maybe your doctor aces the statistics test on drug trials after he has flunked the one on cancer screening. If you believe that, you probably also believe in the tooth fairy and in Santa Claus.  But you may have another question: Can trial results be presented in such misleading ways? Aren't researchers supposed to report their results honestly and correctly? And what use is the peer-review process which every published paper has to go through?

With 70% of all medical research being financed by the private sector, data are a commodity. So, whether you develop a screening test, a drug or a treatment, you will want to dress it up as a magic bullet. Because when you have the magic bullet for, say high blood pressure or high cholesterol, it will make it into every physician's armory. That's where the money is. It's certainly not in personalized medicine, which may find your competitors' drugs as more suitable solutions for a variety of cases. 

Which brings us back to personalized medicine. I have told you in my previous posthow much it costs to develop a drug. Which is why Big Pharma would love to concentrate its research on the areas where the probability of success is high and the potential risk of failure is low. That's the area of follow-up drugs, drugs of the same class as established drugs, but with incremental improvements over the older version. Ironically, our health care system discourages this type of pharmacological research. Incrementally improved drugs are typically reimbursed at the same rate as older drugs. Not much profit potential there. Particularly when competition is fierce.   

Which is why Big Pharma looks for new grounds, that is new therapeutic classes, for which, of course, there need to exist a large market [4]. Again, individualization is certainly not desirable, as it would fragment any market. There is another draw-back: when you break new grounds, it takes a lot longer to get off that ground with some new product. Which is what we see in the FDA's records of drug approvals over the past 10-15 years [5]. Ten years ago the FDA approved on average 90-100 new drugs every year. For the past few years this number has dwindled to 20-30 drugs per year, with the average development period for a drug increasing from 10 years to 14 years. Seven of those years are locked up in the clinical trials required by the FDA. Faced with these risks and costs, how eager, do you think, is Big Pharma to develop niche products for individualized medicine?

Even if we didn't have all those economic issues, individualizing medicine is not as easy as making some genetic test and reading the right drug combo and dosage for your ailment from it. True, genetic testing has become possible and prices are coming down. But to know your organism's blueprint doesn't mean to know what your organism does with this blueprint. In my earlier post I have explained about epigenetics, and how environmental and behavioral factors have a great influence on how your genes play out in the final version of "you". I'm afraid, without this knowledge we can't get individualized medicine off the ground. Not to the extent it exists in most people's fantasy.       

How about personalized prevention? What's the big difference to personalized medicine? Well, for one, we don't need to develop a drug. When I talk about prevention, I talk about preventing what kills most of us today: heart disease, stroke, cancer, and diabetes. Actually, diabetes per se does not kill us, it's those cardiovascular diseases which ride on it. Anyway, to prevent them and diabetes and many cancers takes only some modifications to your lifestyle, chiefly not smoking, not being overweight, being physically active and eating a healthy diet. Any of these comes without undesirable side effects. And for all of them an incredibly large number of studies has investigated their effects under virtually all possible combinations of risk factors, biomarkers and population characteristics.

What doesn't exist is the knowledge of what will work best for you. For two reasons: First, most of this research has been correlated with our classical risk factors. In an earlier post I suggested why these risk factors really suck when it comes to predicting your risk for disease or your health career. Second, there is no knowing how you will react to any intervention even if a research paper tells you that this-and-this exercise routine has cut blood pressure in the participants from 140 to 120 mmHg. Each participant will have experienced a different effect on his blood pressure, ranging from a lot more to no effect at all. The 20-mmHg reduction is merely an average value. We would need to know how similar you are to which participant to tell you exactly what you might expect.

These are the two issues which we work on in my lab: getting away from inconclusive risk factors to what really predicts health, disease and longevity. And making this trial-and-error approach a systematic one. Instead of working with risk factors we have identified key organic functions which predict health and disease much more accurately than risk factors do. And instead of dishing out the generic "spend-150-minutes-per-week-on-exercise" advice we are building a database of biomedical knowledge which will match your profile with the most promising exercise and dietary interventions to help you achieve your personal goals with the least possible effort. And to monitor the effects of your efforts on your organic functions, we are developing tools for you to precisely measure them. For convenience's sake, preferably at home, or at least in your fitness center, at your office or your doctor's practice. 

We do walk entirely new ways to achieve all this, but we never stray from the scientific method. I will, in the twice-weekly postings of this blog, report occasionally on the progress we make. I can't hold my tongue, simply because this work is so fascinating and exciting, at least to me. Of course, I do know that most people are obviously not interested in their health. Judging by the fact that less than 2% of Americans achieve ideal health metrics [6]. But for those who really want to achieve chronic health and functional longevity, we will have something to offer. In fact, I have something right now:

With overweight being one of the biggest issues, we have developed a little tool with which you train what we call a 6th sense for your calorie balance. We have tested this tool in a successful proof-of-concept study. Which is why I would like to invite you to use it. Free of charge, no strings attached. Except for the following three:

First, bear with us for the design of this web-based tool. It can't compete with what you are used to from the design gods of Apple. Second, give me your feedback and suggestions. And third, use it as it is intended to be used: daily. You'll see what I mean when you get there. 

You can find it on facebook. Just type the name "adiphea" into the search bar and click on the app. Or call it up directly from here. It doesn't cost anything, and there is no advertisement other than what facebook puts on all our pages. The tool itself is described in all details on its app-page on facebook. Most of the explanations come in the form of short videos. Which is why I'm not going into details right here. Only one thing I need to mention: Ideally, you should have a body-fat scale instead of the regular bathroom scale. Body fat scales calculate your body water, too.  And the app works best when you enter body water together with your weight daily.

We have set aside a limited contingent for users who are truly interested to work on their health and on their weight in an entirely new way. For those who are determined enough to use our tool properly and thereby help us to perfect it, it will remain accessible free of charge. For all others, utilization will be terminated after one month.

If you are a coach, operate a fitness center, run a company or a medical practice, and you want the app for a group of your clients, staff or patients, talk to me. You'll find my email on my lab's website (www.adiphea.com) . I will arrange for you to get administrative functions, so that you can manage your clients. And not to worry, the tool is built on top of an electronic patient data file, which meets the strictest data security and privacy requirements.We also do not use your email address for anything else than responding to your inquiry.

Let's see whether we can make personalized prevention fly. Big Pharma certainly wouldn't like it. They can't make money from chronically healthy people. But you could be on your way to NOT become one of the 50-70% of people in whom Big Pharma's drugs don't work so well. Now, is that an inducement or what ?

1.           Nicholson, J.K., Global systems biology, personalized medicine and molecular epidemiology. Mol Syst Biol, 2006. 2: p. 52.

2.           Nicholson, J.K. and E. Holmes, Global systems biology and personalized healthcare solutions. Discov Med, 2006. 6(32): p. 63-70.

3.           Wegwarth, O., et al., Do physicians understand cancer screening statistics? A national survey of primary care physicians in the United States. Annals of Internal Medicine, 2012. 156(5): p. 340-9.

4.           Pammolli, F., L. Magazzini, and M. Riccaboni, The productivity crisis in pharmaceutical R&D. Nat Rev Drug Discov, 2011. 10(6): p. 428-38.

5.           Loscalzo, J., Personalized Cardiovascular Medicine and Drug Development. Circulation, 2012. 125(4): p. 638-645.

6.           Yang, Q., et al., Trends in Cardiovascular Health Metrics and Associations With All-Cause and CVD Mortality Among US Adults. JAMA: The Journal of the American Medical Association, 2012.

Nicholson, J. (2006). Global systems biology, personalized medicine and molecular epidemiology Molecular Systems Biology, 2 DOI: 10.1038/msb4100095

Wegwarth O, Schwartz LM, Woloshin S, Gaissmaier W, & Gigerenzer G (2012). Do physicians understand cancer screening statistics? A national survey of primary care physicians in the United States. Annals of internal medicine, 156 (5), 340-9 PMID: 22393129

Pammolli, F., Magazzini, L., & Riccaboni, M. (2011). The productivity crisis in pharmaceutical R&D Nature Reviews Drug Discovery, 10 (6), 428-438 DOI: 10.1038/nrd3405

Loscalzo, J. (2012). Personalized Cardiovascular Medicine and Drug Development: Time for a New Paradigm Circulation, 125 (4), 638-645 DOI: 10.1161/CIRCULATIONAHA.111.089243

Yang, Q. (2012). Trends in Cardiovascular Health Metrics and Associations With All-Cause and CVD Mortality Among US Adults JAMA: The Journal of the American Medical Association, 307 (12) DOI: 10.1001/jama.2012.339

Yang Q, Cogswell ME, Flanders WD, Hong Y, Zhang Z, Loustalot F, Gillespie C, Merritt R, & Hu FB (2012). Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults. JAMA : the journal of the American Medical Association, 307 (12), 1273-83 PMID: 22427615

The one way to make you slim, fit and healthy?

That your fattening lifestyle drives health insurance costs up is nothing but a fat lie. That much I have told you in the previous post. With Marlboro Man and Ronald McDonald doing better for your health insurer's balance sheet than Healthy Living, you might think that public health should look beyond economics as an argument for health.  In this post I will tell you why they shouldn't. 

 And why economics may well turn out to be the one and only way to getting you to exercise and reduce your weight. And, no, with economics I don't mean punishing you with penalty premiums on your health insurance and punitive taxes on your fast food. Let's leave such uninspired nonsense to the politicians. We can do better than that. Before I get to that point, let's pick up the thread from where we left it in the previous post. 

There I introduced you to the fact that the amazing arithmetic of sicker-equals-cheaper has been introduced by economists working in the employment of public health agencies. They are interested in the financial health of their government, not of a health insurance company. From that point of view, convincing smokers to quit and obese people to slim down doesn't seem to make much sense either. Here is why:

When smokers quit, their near-term health care costs may go down, but in the long run they will be offset by higher medical bills for causes unrelated to smoking but related to a longer life [1]. This longer life hurts the government twice. First, when smokers stop lighting up they also stop paying tobacco taxes to the government. Second, with longer lives come longer pension payments. In fact, if all smokers would quit today, we would have very unhappy finance ministers. Ours, here in Germany, would have his tax revenues reduced by € 14.5 Billion per annum. 

What goes for smoking goes for obesity, too. So, how sincere are our politicians with their professed concerns for our health? Is this a pretext for soon taxing your consumption of sugar and fast food? Well, they certainly have the backing of the World Health Organization. The WHO recommended the introduction of punitive taxes in their 2010 Global status report on noncommunicable diseases. What our politicians apparently don't have is the ingenuity to come up with a more innovative solution, for once. Which is why we have to find it. By looking a little closer at the economics of health.  

So, I'm asking you: aside from you personally, who benefits from your health so much, that promoting it makes economic sense? Your employer, for instance. Not only is a healthy employee less often absent from work, he is also more productive while he is at work. The costs related to work absence have been appropriately termed absenteeism, which makes you immediately understand what is meant with its twin, presenteeism. It describes the costs of being less productive while at work. 

As it turns out, presenteeism clobbers companies' profits much more than absenteeism. In fact, for cardiovascular disease and diabetes, the costs of reduced productivity, while at work, exceed those of absenteeism by a factor of 10 [2]. Admittedly, the calculation of presenteeism is not an exact science. But all available evidence points to a substantial return on employers' investments into preventing those chronic diseases, which produce chronically less productive workers. Across companies and nations, the overall cost:benefit ratio has been found to be in the region of 1:2.2 [3]. Which means, for every dollar spent on corporate health promotion, 2.2 dollars are gained. Not bad. But it could be a lot better if you really did prevent those chronic diseases.

Only, you don't. How do I know? By looking at the trends for the 7 metrics used by the American Heart Association (AHA) as the Strategic Impact Goals for improving cardiovascular health. By 2020 cardiovascular health shall be improved by 20%. That doesn't sound very ambitious. But in all likelihood it is way too ambitious. Here is why: Let's look at obesity, which the IOM has just branded a "catastrophic" problem in the U.S.
Instead of falling, the percentage of obese people has been on the rise, again, over the past 10 years, with now 34% of women and 32% of men being obese [4]. Physical activity levels have not improved significantly, neither did dietary habits. Blood sugar control has actually worsened, and blood pressure control has only slightly improved in men. Based on these data the improvements of cardiovascular health in 2020 will be around 6%, not 20%.

That's how I know that you aren't following your employer's corporate health program. Why would you when you don't follow public health's promotions and recommendations in the first place? Unless, of course, your employer makes you an offer you can't refuse. What would you do if your employer rewarded your participation in his health promotion program with hard cash, additional leave, or a tangible good you desire? What if he tied those benefits to your effort (e.g. your participation rate), or your measurable outcome (e.g. kgs of weight lost, or weight maintenance), or any mixture of effort and result? Would that entice you to pick up healthier habits?

As I have pointed out before, the argument that people who live healthy generate less health care costs than their unhealthily living peers is unsubstantiated. But that should not make us eliminate economics as a metric when it comes to promoting health. On the contrary. By making health an economic good we bring to the table what motivates people most: tangible rewards. The question is, would it get you to pick up exercise, if you didn't do it already, and would it get you to lose weight, if you needed to?

The reason why I'm asking you is, because as a public health scientist, I'm utterly disillusioned with the success rate of our preventive efforts. On one hand, we have this wonderfully simple and enormously effective preventive tool called exercise and weight loss. And on the other hand we have 4 out of 5 people not using this tool. On one hand, we have the new guidelines for the treatment of diabetes [5] and for the prevention of cardiovascular disease  [6], both of which have been released over the past few weeks. Both guidelines acknowledge lifestyle change as the first line of defense against those diseases. But on the other hand we have less than 2% of the population achieving the 7 simple health metrics of the AHA. Guidelines won't change that. So, how can we make the remaining 98% of the population achieve the 7 metrics? Obviously not with the same song and dance that didn't get the job done in the past.

Which is why we need to explore new ways. Taxing your consumption of the foods you enjoy isn't new. Making health an investment good, that's new. But without attracting those people who we haven't reached in the past, it won't work either. Now what do you think?

Will tangible rewards make employees exercise and lose weight?

1.          Temple, N.J., Why prevention can increase health-care spending. The European Journal of Public Health, 2011.

2.          Collins, J.J., et al., The assessment of chronic health conditions on work performance, absence, and total economic impact for employers. J Occup Environ Med, 2005. 47(6): p. 547-57.

3.          Dietmar Bräunig and T. Kohstall, The return on prevention: Calculating the costs and benefits of investments in occupational safety and health in companies, 2012, ISSA: Geneva, Switzerland.

4.          Huffman, M.D., et al., Cardiovascular Health Behavior and Health Factor Changes (1988-2008) and Projections to 2020: Results from the National Health and Nutrition Examination Surveys (NHANES).Circulation, 2012.

5.           Inzucchi, S.E., et al., Management of hyperglycaemia in type 2 diabetes: a patient-centered approach. Position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diab tologia, 2012.

6.           Perk, J., et al., European Guidelines on cardiovascular disease prevention in clinical practice (version 2012): The Fifth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of nine societies and by invited experts) * Developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR). European Heart Journal, 2012.

Temple, N. (2011). Why prevention can increase health-care spending The European Journal of Public Health DOI: 10.1093/eurpub/ckr139
 
Collins, J., Baase, C., Sharda, C., Ozminkowski, R., Nicholson, S., Billotti, G., Turpin, R., Olson, M., & Berger, M. (2005). The Assessment of Chronic Health Conditions on Work Performance, Absence, and Total Economic Impact for Employers Journal of Occupational and Environmental Medicine, 47 (6), 547-557 DOI: 10.1097/01.jom.0000166864.58664.29
 
Huffman MD, Capewell S, Ning H, Shay CM, Ford ES, & Lloyd-Jones DM (2012). Cardiovascular Health Behavior and Health Factor Changes (1988-2008) and Projections to 2020: Results from the National Health and Nutrition Examination Surveys (NHANES). Circulation PMID: 22547667
Inzucchi SE, Bergenstal RM, Buse JB, Diamant M, Ferrannini E, Nauck M, Peters AL, Tsapas A, Wender R, & Matthews DR (2012). Management of hyperglycaemia in type 2 diabetes: a patient-centered approach. Position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia, 55 (6), 1577-96 PMID: 22526604
 
Authors/Task Force Members:, Perk J, De Backer G, Gohlke H, Graham I, Reiner Z, Verschuren M, Albus C, Benlian P, Boysen G, Cifkova R, Deaton C, Ebrahim S, Fisher M, Germano G, Hobbs R, Hoes A, Karadeniz S, Mezzani A, Prescott E, Ryden L, Scherer M, Syvänne M, Scholte Op Reimer WJ, Vrints C, Wood D, Zamorano JL, Zannad F, Other experts who contributed to parts of the guidelines:, Cooney MT, ESC Committee for Practice Guidelines (CPG):, Bax J, Baumgartner H, Ceconi C, Dean V, Deaton C, Fagard R, Funck-Brentano C, Hasdai D, Hoes A, Kirchhof P, Knuuti J, Kolh P, McDonagh T, Moulin C, Popescu BA, Reiner Z, Sechtem U, Sirnes PA, Tendera M, Torbicki A, Vahanian A, Windecker S, Document Reviewers:, Funck-Brentano C, Sirnes PA, Aboyans V, Ezquerra EA, Baigent C, Brotons C, Burell G, Ceriello A, De Sutter J, Deckers J, Del Prato S, Diener HC, Fitzsimons D, Fras Z, Hambrecht R, Jankowski P, Keil U, Kirby M, Larsen ML, Mancia G, Manolis AJ, McMurray J, Pajak A, Parkhomenko A, Rallidis L, Rigo F, Rocha E, Ruilope LM, van der Velde E, Vanuzzo D, Viigimaa M, Volpe M, Wiklund O, & Wolpert C (2012). European Guidelines on cardiovascular disease prevention in clinical practice (version 2012): The Fifth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by re European heart journal PMID: 22555213

Am I shittin' you? Learn to be a skeptic!

Learn to be a skeptic!

Why you cannot believe what you read about medical studies.

In my last blog post I promised to tell you why you shouldn't trust any study results, particularly when you didn't read the study yourself. It has to do with the methods of biomedical research. To make my point, I'll take the gold standard research method, the double blinded randomized controlled trial, or RCT. 

Let's say we want to test a drug, which is supposed to lower blood pressure in those who suffer from hypertension. The researchers have decided to enroll, say, 100 "subjects". That's what we typically call the people who are kind enough to play guinea pig in our studies.   

The researchers will first do a randomization of subjects into one of two groups (very often it is more than one group, but to keep it simple we will assume just two groups). What we mean with randomization is that we randomly assign each subject to one of the two groups. One group - the intervention group - will receive the drug, the other group - the control group - won't. What they get instead is a sugar pill, a placebo. 

With the randomization we want to make sure that, at the start, or baseline, both groups are indistinguishable from each other with respect to their average vital parameters. For example, if we were to calculate the mean age, blood pressure and any other variable for each group, these mean values would be not different between groups. That's important, because we want to isolate the effect of the drug. We don't want to worry at the end whether the effect, or lack thereof, was maybe due to some significant difference between the groups at baseline. 

Once the randomization is done, we organize the trial in such a way that neither the "subjects" nor their physicians and nurses know whether they get the placebo or the active drug. Both sides are blind to what they get and give, which is why this set-up is called double-blinded. That's an important feature, because a researcher often goes into a study with a certain expectation of its outcome. Either that outcome supports his hypothesis, or it doesn't. To eliminate the risk of, more or less subconsciously, influencing the study towards a desired outcome, double-blinding is very effective tool.

Fast forward to the end of our trial. We have now all the data in hand to compare the two groups. After unblinding, the researchers will compare the two groups with each other. In our example, they will compare the average, or mean, of the blood pressure values of all the individuals for each group. If the intervention group's mean value is lower than that of the control group, then it is plausible to reject the null-hypothesis, that is to REJECT the idea that the drug is NOT as ineffective as the placebo (we are, of course, assuming here that the sugar pill didn't lower the blood pressure of the control group). 

There are statistical tools to determine whether the difference between the groups may just be a chance event, or whether chance is a very unlikely explanation. We can never rule out chance completely. Now, when we are confident that it is the drug and not pure chance, which has lowered the mean blood pressure in the intervention group, we write our paper to present it in one of the medical journals. 

If the subject is a little more sexy, than just lowering blood pressure, there will sure be some journalists who pick it up and report to their readers that, say, eating chocolate makes you slimmer. I'm not kidding. This headline very conveniently went through the media shortly before Easter this year [1]. Good for Hershey who are running it of course on their webpage. And in the media it reads like it did in the Irish Times: "Good news for chocoholics this Easter. Medical Matters: No need for guilt over all those Easter eggs."    

I'm not going to comment on the media geniuses, because it's their job to put an angle on every story, so that YOU find it interesting and read their stuff. But since I'm sure you'll follow these links, just let me warn you: the chocolate study was an observational study, not an RCT. And one thing we MUST NOT do with the results of observational studies is to confuse association with causation. Only when we conduct an RCT, where the intervention group eats chocolate and the control group doesn't, might we be able to determine whether there is a causal link. And for obvious reasons we can't blind the subjects, to whether they eat chocolate or not. But I'm digressing.

Back to our blood pressure study. When we compare the group averages, everything looks very convincing. And sure enough, as researchers we are happy with the results, and we are perfectly correct, when we conclude, that this medicine does its job. 

But will it do it for you? When you are hypertensive? You might be wrong if you say "Yes". And you will be wrong more often than we, as researchers, or your doctors care to admit. For one simple reason: The variability of effect within the group. You give 50 people the same drug, and I bet with you, and I'm not the betting type, that you'll have 50 different results. 

The mean value of the entire group glosses over these inter-individual differences. Let me give you an example from a study performed on 35 overweight men, who were studied in a supervised and carefully calculated 12-weeks exercise program, with the intention of reducing body weight. The mean weight loss was 3.7 kg. That was almost exactly the amount of weight loss which the researchers had expected from the additional energy expenditure of the exercise program. But when they looked at each individual, it became clear that the group mean doesn't tell you anything about how YOU would fare in that program. 

First of all, the standard deviation was 3.6 kg. Now, a standard deviation of 3.6 kg simply tells you that approximately two thirds of the participants experienced a weight loss anywhere between 3,7 kg (the mean) minus 3.6 kg and 3.7kg + 3.6 kg, that is between 0.1 kg and 7.3 kg! That's a lot of kilos. And what about the remaining one third of those participants? They are even further from these values. In this case the greatest loser went down by 14 kg, and the biggest "winner" gained almost 2 kg. A spread of 16 kilos!

Here is the graph which shows you the change on body weight and fat for each individual participant. Which one would you be?

This effect is what you do not see when you don't read the studies. And in most studies, it isn't made obvious either. 

Which is why, you shouldn't be surprised to learn that most major drugs are effective only in 25-60% of their users [2]. The same goes for weight loss drugs and interventions, for almost everything we study in biomedicine. 

That's not a problem for us in public health. Because a drug, which works in 60% of the patients, helps us reduce the burden of disease in our population. Public health is not interested whether you are one of the 60% or not. But you are. And that's why I believe not only medicine, but also prevention must be individualized.

 Which is why the GPS to chronic health, which I currently develop, is all about helping you find your individual path to your health objectives.

Why not have a look at it, and maybe even try it out? 

References

1.           Golomb, B.A., S. Koperski, and H.L. White, Association Between More Frequent Chocolate Consumption and Lower Body Mass Index.Archives of Internal Medicine, 2012. 172(6): p. 519-521.

2.           Wilkinson, G.R., Drug Metabolism and Variability among Patients in Drug Response. N Engl J Med, 2005. 352(21): p. 2211-2221.

Are fat people just lazy?

Are fat people just lazy? Or is it in their genes?

Let's look at an unlikely place for the answer: an AA meeting. If you get up and say "My name is Jane, and I'm not really an alcoholic, I don't drink that much..." they throw you out. They welcome you back, once you say "My name is Jane and I'm an alcoholic". The same should be true for fat people. And I'm using this politically incorrect term deliberately. Because unless you wake up to the reality, you won't be able to change that reality.

 AA have long ago realized that fact. And they have a 50% long-term success rate. That is, half the alcoholics who join AA stay dry for the rest of their lives. That's way more than what public health, clinical and commercial weight loss programs achieve with obese participants. We are happy if 10% of those who enter these programs achieve a 10% weight loss AND keep it for more than 2 years. It's that bad. Is it because of the genes? A study published recently in Nature Genetics, might supply another excuse to some overweight people. But before we look at this study, let's look at some other facts first.

One thing we all know for sure: if you are overweight, you obviously have taken in more calories than you have expended. Over quite some time, because it takes a while to accumulate all those energy reserves on your waist and hips. Boils down to one of the tenets of a universal law of physics that says: Energy can neither be destroyed nor miraculously created. Not even on your hips.

Now I know all the objections raised by so many overweight people, like "But, I hardly eat anything. How can I be fat? Even my friends say, from what you eat nobody can get fat." Believe me, I've heard them all.  And my heart sinks, when I do, because I know there goes the hopeless case. The Jane who goes to AA and tells them she is different. The study published in Nature Genetics might just deliver her the next excuse. Not because the researchers tell her so, but because some media genius might just read it the wrong way. As they often do. So, let's look a what the researchers say.

The researchers conducted a meta-analysis of some 14 genome wide association studies involving altogether 14,000 children, one third of which were obese. They found 7 genetic markers which correlated with obesity and which also turned out to correlate with obesity in adults. The beauty of looking at genetics in kids is, that they haven't been exposed to decades of lifestyles which may obscure such links. 

So, the results clearly point into the direction of some genetic signature predisposing a person to become obese. But having this signature doesn't mean you'll inevitably become obese. Because most kids who have the signature are not obese. It's only that this signature shows up a little more often in the obese kids than in their non-obese peers.  And there is one more thing, you need to keep in mind. Over the past 20 years the human genetic make-up hasn't changed at all. But the obesity rate in US kids has. In fact it has tripled during that period. And health behavior has changed, too. And so did our environment.

What makes me always frustrated in all this debate about genes vs. environment vs. behavior is my scientist colleagues' and the media's inability to educate their audience about the complete picture. Genes make up the blueprint to your organism. True. But they don't make that organism. Genes make proteins, but whether they make them or whether they are silenced into not making them, that depends on epigenetics, on the interaction with your environment, and on your behavior, which again is influenced by all the others. It is a very complex relationship, and I'm afraid, genetics will not help us, to solve the obesity epidemic. But neither will the stigmatization of the obese. 

What we need, is a way to help those who recognize their fatness as a resolvable reality, resolve it. That's why I'm working on the GPS tochronic health, because I know that once the health behaviors put you on track to chronic health and longevity, your overweight problem will resolve automatically. As a side effect. But only if the obese person works with us. 

So did that answer the question? You decide for yourself.   

How to get to chronic health. With three steps into the age of chronic health and longevity.

Into the age of chronic health.

My yesterday's post was all about what's holding us back from achieving chronic health for everybody. Today I want to look at the three important steps we can do right now to enter the age of chronic health and longevity. 

Incentivize health! 

Earlier this year Standard & Poor's told the G20 economies:  Get prevention to work or we will downgrade your triple A rating by latest 2018. Because your economies won't be able to deal with the costs for treating your sick, demented and frail population. Of course Standard & Poor's phrased it more politely but the message was all the same.  Why is that so important? Because it's the first step to making everybody realize that your chronic health is not just this often proclaimed "higher good", it is an economic asset. It makes you more productive for your employer, and less costly for your health and life insurer. Once your health shows up in the shareholder value universe, employers have an incentive to invest into it. And they have an incentive to share with you in the form of a health dividend. The keyword here is incentive. The lack of it is what ails our current health care strategies. Because until now we have failed to incentivize people's prevention efforts. Think about it: Whether it's status or money or anything else that turns your neighbors green with envy, the driving force behind all human endeavors is the prospect of incentives. It's hardwired into our brains. It's why everybody's efforts to achieve chronic health needs incentives, too. As we have seen, the prospect of being healthy in a distant future can't beat the siren call of a humble tiramisu, or of the drag on a cigarette, or of staying on the sofa instead of jogging through the Park. So, if the phenomenon of hyperbolic discounting has taught us anything, it is the need for incentives with which to beat those that lure us into unhealthy behaviors.

What holds our companies and insurers back from incentivizing health big time? Certainly it is not unwillingness, and rarely is it uncertainty about the size of the returns on investment. It is rather the lack of a tool with which to direct incentives to where they are deserved and to withhold them from where they are not. A tool which helps you to express, in objectively measurable terms, not only your health but also your efforts and achievements of preserving it. We are currently testing the first prototype of such a tool. We started to develop it with this and two more goals in mind. The first is to help you to...  

Outfox your brain!

As you have learned above, the evolutionary ape in us is well protected against any interference of free will and reason, the two things that make us human. But whether human or ape, we all have the ability to develop a 6th sense for mastering any skill which improves our chance of survival, makes our life easier or more enjoyable. In your case, think swimming, think cycling, think keeping your in-laws out of your hair. So we thought, how about a 6th sense for your daily calorie balance? We thought, if you knew it intuitively, at any moment, and before it shows on your bathroom scale, you would effectively know your metabolic state. With that knowledge you will be able to correct and to keep that balance always in line with your weight targets. This intuitive knowledge does not eliminate the craving for the tiramisu. But it enables you to recognize the need for taking some compensatory measure and to select the appropriate size of that measure.  This idea was borne out of the results of a new web-assisted intervention which we developed and tested in Germany with the aim to institute lasting behavior change in adults at elevated risk for chronic disease. Once the participants of our clinical trial showed signs of mastering this 6th sense, they also started to drop their dress sizes. And they still keep those dress sizes down.

Now, I can hear your question: Even if, say, my employer pays me a monthly or quarterly health dividend, in the form of money or annual leave or whatever floats my boat, how can you be so sure that my new lifestyle of eating right and exercising right will bring me chronic health and longevity? Which brings me to the last point. 

Take Biomedicine's most powerful tools!

Let's just look at how your chances play out. If, at age 45, you are free of any risk factors, you stand a 97% chance of making it through to your 80th birthday in good health. If, however, you already have 2 risk factors, such as hypertension and elevated blood sugar, for example, those chances shrink to a mere fifty-fifty. And even if you are among the lucky half, who will see those 80 candles on their cakes, chances are that you won't blow them out under your own steam. Because one of those nasty chronic diseases will have taken that last piece of strength and dignity away from you. The good news is that simple health behaviors - physical activity, dietary and smoking behaviors - determine which version of the party, if any, will apply to you. In fact, biomedicine currently knows no intervention which prevents disease and promotes longevity better than physical activity and dietary behaviors. There is one caveat, though: these simple behaviors need to be tailored to your individual health profile, which also means to your genotype AND your phenotype. 

Which is why my colleagues and I are building an intervention matching feature into the tool I mentioned earlier. It will give you the means to match your individual health and risk profile with the physical activity and dietary strategies most suitable for your profile. We call this tool the GPS to chronic health and longevity. It takes its coordinates on the landscape of health from your vital functions and keeps you right on track towards your health goals.

It is the engine which we hope will give you the power of mapping and following your personal path into the age of chronic health and longevity. After all, nobody deserves the indignity of a stroke or a heart attack and the disabilities that come as a consequence. 

I firmly believe we are only a tiny step away from the age of chronic health and longevity. To that tiny step you can contribute.  Just visit me at indiegogo until 31st of May. 

I'm looking forward to meeting you there.