Scientific integrity

Scientific integrity

That a society trusts its scientific community to be truthful in all its manifestations is a given in any civilised society. We are all aware of scandals involving sometimes young and sometimes prominent scientists being disgraced for having falsified scientific data in peer-reviewed scientific publications in scholarly journals. That is the newsworthy end of this thorny issue but beneath that headline-catching level lie some equally challenging issues of scientific integrity. The first of these relates to the belief of many MEPs that scientific advisers to the European Food Safety Agency (EFSA) should be, as George Smiley, would have said “Persil grade”, clean as the driven snow with no links to the food industry.  That pressure has led to several high level confrontations between EFSA and the European Parliament plus a plethora of NGOs in the food area. Now an expert in the biology of the lactating yak is unlikely to be considered as a likely expert for a panel of EFSA but someone with a life’s investment in public health nutrition research is likely to be very attractive. The problem is that the lactating yak expert attracts zero interest from the food industry while the lifetime devotee to public health nutrition cannot be free from food industry links. If their research is world class, everyone will want to talk with them, pay their travel to give talks, co- fund or fund their research and generally get to know such an expert. And if the EU, through its competitive research programme funds this expert, then for sure, there must be industry links because that is an absolute requirement of funding. So the MEPs cannot have it both ways. If they want the best, they will have to accept that both the regulator and the regulated will visit the best. 

Having a link with the food industry appears to suggest to MEPs that there is a higher likelihood that independent scientific thinking is likely to be compromised. However, this does not appear to apply to NGOs. A scientist who is an active member of an environmental NGO could be compromised if he or she were to be a member of an advisory committee of an EU institution if the topic involved GM foods. And would a strict vegan be a truly independent chair of an expert group on some nutrient, which has a strong line with animal based foods like iron or zinc? The simple solution here is to require that such potential conflicts of interest be declared so that anyone reading a report involving such individuals knows the background of the experts. But that doesn’t count for much with MEPs. NGOs are inherently good whether they be environmental NGOs or vegan NGOs. It is only industry that seems to matter to the guardians of scientific integrity. Seems strange to me!

Finally, we burrow down to what is ultimately the most sinister aspect of scientific integrity, namely being honest in interpreting primary (my discovery) or secondary (your discovery) data. In a very important paper published in the International Journal of Obesity {2009-(1-50}, researchers at the University Of Alabama reported a study in which they tracked the manner in which primary data (my discovery for example) is cited in secondary data (your reported discovery citing my original findings in support). They chose a study, which examined the link between the development of obesity and sugar-sweetened beverages (SSBs). The original primary data showed no statistically significant association between SSB intake and obesity. Often, authors of papers, which report “negative” data, grasp at straws of positivity. In this case, a subset analysis showed a suggestion of such a link. However, the subset analysis was always a sideshow while the main event, the true objective of the study, showed zilch evidence linking SSBs and obesity. They then tracked all the studies published in English that cited the paper. Of these, 84% inaccurately reported the primary data. That is, they chose to ignore the main and “true” conclusion of the paper and chose instead to focus on the sideshow, the non-intended analysis, which did suggest that in some sub-groups there was a possible link between SSBs and obesity. This is a minor snapshot of a paper that shows a massive systematic bias of researchers toward that interpretation of data, which suits their agenda.

Just about everybody reading this will recognise this bias in all spheres of human activity. However, for science, which purports to be built on the truth, this is a major problem. If scientists, select from here and there to suit their agenda, the “sayonara” objectivity.

Fitting into your genes

Fitting into your genes

Some years ago, I was given the honour of delivering the opening plenary lecture to the First World Congress of Public Health Nutrition and I had carte blanche as to the content. I chose to talk about nutrition and genetics and when I finished, I was set upon by the doyens of the subject to whom the idea that genes could play a role in such chronic diseases as obesity was verging on sacrilege. The argument was simple but fundamentally flawed. Obesity rates, they argued, have rocketed over the last 50 years[1] during which time the gene pool has remained constant so how could genes be involved.  Recently, I gave a similar talk to the Polish EU Presidency gig and got the same reaction. So here is how it happens. Imagine you could take 1000 extremely muscular Maasai tribesmen from the utterly non-obesogenic Kenyan plains and re-house them with a decent disposable income in any western city awash with obesogenic facilities. Some would resist weight gain. Some would show modest weight gain of which some would do so quickly and others more slowly. Some would become overweight and obese and do so at different rates. When the experiment is finished, I would predict a pattern of body weight among the Maasai broadly similar to the prevailing local pattern.

The evidence dates back 30 odd years when three seminal papers were published in leading medical journals. The first used identical and non-identical children and from this mix it is possible to say what part of obesity is inherited and what part is due to the environment. The non-identical twins share the same environment but not the same genome. In the case of identical twins, they share the same environment and the same genome. Geneticists have used this model in many areas to separate out the effects of the environment and the genome. The outcome was that 70%+ of the variation in obesity was inherited. The next set of data took identical twins that were overfed for several months and later, underfed for several months. In the overfeeding phase of 1000 extra calories per day over normal, all subjects gained weight but to varying degrees. The big variation was between groups of identical twins. However, among identical twins, here was no variation. If one gained weight rapidly, so did the other. If one resisted weight gain, so did the other. And when 1000 calories a day were deducted from their habitual intake, the same happened. All lost weight but some more than others. And identical twins shed weight at exactly the same rate. The final study looked at adoptees and compared their body weights with those of their adopting parents and those of their biological parents. The correlation was much stronger with their biological parents.

All of this data was then buried and forgotten because it was a most inconvenient truth. Even accepting its truth, those charged with the public health nutrition challenge of obesity had a further problem. If the average punter got word that their weight problem was genetic, they would abandon all personal efforts at weight management, throw their hands in the air and declare “Its not my fault, its my genes” as they wolfed into some stylish nosh. One has to have considerable sympathy for this point of view since the struggle to help manage obesity is a truly hard road. For a while, there was an escape clause in that it was argued that “that was then and this is now and thirty + years ago we didn’t have the ubiquitous obesogenic environment of today”.  And that was fine until Professor Jane Wardle of University College London began publishing data on modern twin cohorts followed up over a long period and with quite detailed lifestyle and diet recorded. Everything shown 30+ years ago was shown to be still true today. Moreover, Professor Wardle also showed that the belief that obesity in children has a huge socio-economic dimension is just not true. Twins of lean parents remained thin from aged 4 to 11 years irrespective of social class. However, when children from overweight children were considered, those of low social background did show accelerated weight gain. Thus social class matters in childhood obesity but only if filtered by the genes they inherited.

Studying twins helps us to quantify the true rate of heritability of obesity. It doesn’t tell us which genes are involved and thus it doesn’t allow us to predict which one of us will put on weight faster and more easily than others. Now, new technology allows us look at many hundreds of thousands of points of variation along the human genome to see where this natural variance is most pronounced in the obese as opposed to those of us lucky to remain lean. Each point of variation along a gene is known as an allele and there are certain alleles, which are much more commonly found among the obese. Thus we are now approaching the point where we can predict that a certain individual has a strong genetic tendency toward obesity and maybe, that knowledge could be used to help children and parents to take preventative measures against obesity. The converse is also true. We can now conduct simple genetic tests that will indicate the best calorie reduced diet for individuals to follow in losing weight. Some will do best by shedding fat calories and other will do best shedding carbohydrate calories. For some, either route will be equally effective.

When one mentions the link between genes and obesity, attention always turns to genetic variation influencing how energy rich substrates are handled (digested, transported stored, retrieved, metabolized and so on) in the body. However, this is simply because the people with the biggest interest in genetic research are usually biologists. But a genetic tendency to become obese may relate to our behaviour, our food choice, our satiety, our will power and any one of the many aspects of our lives that govern food intake. That poses an even greater challenge to the study of diet and obesity.

As to the extension of nutrition and genetics to the wider area of personalised nutrition, take a look at the website of an EU funded project that I am coordinator: www.food4me.org.

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[1] Actually the rocketing started in the 1850s but that’s another story

Taxing the fat and sweet

Taxing the fat and sweet

There is at present a considerable media interest in the taxation of both fat and sugar in an attempt to control the epidemic of obesity. In a typical Western diet, fat and sugar combine to contribute about 55% to 65% of our total caloric intake. To contemplate putting a tax on more than half our energy intake is palpably absurd so the target is then moved toward specific foods which merit taxation based on (a) their fat and sugar levels and or (b) their putative contribution to obesity. The problem regarding the latter is a total lack of any evidence linking very specific food groups to obesity.  Across time  (decades of research) and space (all continents) there is no universal single pattern of food choice uniquely associated with obesity. Consider a solid example of how this works. Across time and space, every study that has sought to examine the link between dental caries and diet has found that it is the frequency of sugar consumption, which is important.   When, time after time, in all corners of the globe and under all sorts of different circumstances an observation is found to be simply constant, then it ends up in the “no-brainer” category of knowledge. Not so with obesity. There is no consistent pattern of food intake. Some eat excessively and never eat chips, others eat chips but don’t eat excessively and you can substitute “chips” in that phrase with any food you like. If there were a pattern that every researcher saw every time they looked we’d have done something about it long ago. However, there simply is no consistent pattern of food choice that is uniquely linked to obesity.

Of course that is a great disappointment to those who hold the belief that obesity is directly related to the intake of fast food or to foods with empty calories, high in sugar or fat. Having an identifiable corporate whipping boy makes life easy. Bashing McDonalds might make some concerned citizens feel good but since McDonalds are responsible for the sale of maybe just 10% of all chips consumed, ignoring the main purveyors of chips (ethnic restaurants, fish and chip shops, pubs, works canteens, mobile food vendors etc) means that the real “villains” are getting away “Scot free”. And of course when it comes to the practicality of imposing a fat tax on chips (and other fast foods), the taxing of bars, fish and chip shops and the other suppliers of the nation’s chips poses quite a logistical problem.

In the absence of hard data to identify foods, which are uniquely involved in the development of obesity, the next step is to use the nutritional composition of foods to sort out those that are high in those nutrients for which we should reduce our intake. This is referred to as “nutritional profiling”.  The theory here is that a mathematical formula can be devised into which the nutritional properties of individual foods are entered allowing an output which marks foods into “good”, “bad” and “ok but not great” categories. In the UK the dream is to then assign a colour code to this as per traffic lights. Interestingly, when the mathematical construct gets things wrong, that is to say when it disagrees with the a priori opinion of the users, the formula is changed to make sure that the output meets the opinions of the particular experts who are adherents to this process. In principle, anything that helps consumers to make better choices must be welcome but the problem here in the EU is that the process is doomed to poor science for the simple reason that we do not use portion sizes here but rather units of 100g or 100 ml. The argument is that across the EU, portion sizes differ. For example, it is argued that in Italy, the average intake of pasta is 3 to 4 times higher than in Northern EU. However, this difference is not due to portion size but to the frequency of consumption. A plate of pasta in Rome is the same as a similar plate in any Italian restaurant across the entire EU. Mixing up frequency of consumption (higher for pasta in Italy) with portion size is nonsense but that is at the heart of the EU thinking as regards EU food legislation. In the US there is an agreed RACC (Recognised Amount Commonly Consumed) value for each food. To understand how daft this is, consider the comparison of water biscuits (usually served with cheese) and pizza. A typical 100-gram of pizza will provide about 7 grams of fat while 100 grams of water biscuits provide up to 23 grams of fat. However, a typical serving size of pizza would yield about 20+ grams of fat while a typical serving of water biscuits would contain about 4 grams of fat. Ignoring portion size can penalise foods, which have typically small servings Per 100g, mustard has twice as much fat as full fat milk!!!!!

 Trying to find a single all embracing formula to assign a general nutritional quality index to every food is difficult and will be constantly bothered by obviously “wrong” decisions. An approach used successfully in Scandinavia, uses an agreed compositional target per food category. If there is a move toward a reduction of a given nutrient, then the regulators and the manufacturers of a particular category of food can agree a target that all can work towards. In Scandinavia, foods that reach that target get to display an emblem which consumers can recognise as having met a given standard.

One of the first lessons to be learned in nutrition is that there are no such things as “good foods” or “bad foods” but rather “good diets” and “bad diets”. Sadly, it is a lesson quickly forgotten by those who regard diet and obesity as a simple problem linking certain naughty foods with weight gain. 

Welcome to gibneyonfood

The media is today awash with articles on all aspects of food and health and some are so non-sensical that I thought I'd start my own blog to provide an alternative medium through which an informed view on food and health can be delivered. The blog will be a weekly event coming live every Monday morning, beginning on Monday November the 8th and will cover a wide range of topics.