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Thursday, May 28, 2015

Obesity, poverty and convenient myths



Policy makers don’t read tabloid newspapers. They read more serious broadsheets from the London Times to Figaro to the Washington Post. And these broadsheets often perpetuate the beliefs that make the upper social echelons happy or indeed smug. And among these beliefs is that which argues that the present epidemic in obesity is primarily a problem of the lower socio-economic groups. One cannot argue against the line that obesity rates are higher among the socially disadvantaged. Neither can one argue against comparably higher rates of suicide, homicide, drug abuse, violent crimes, indebtedness, heart disease, cancer and anything you care to mention but which you’d rather do without, thank you very much.

The fact that obesity, like suicide and homicide, is higher in those who are socially disadvantaged doesn’t mean it is absent in the socially advantaged. The differences in obesity rates are in high fractions such as 0.8 or thereabouts such that for every 5 obese persons who are socially disadvantaged, there are 4 obese persons among the economic elite. Think of the Clintons, Hilary in recent times and Bill, a while back. However, as I’ve already said, obesity is higher among the socially deprived. The question is why so and what to do about it.

A recent paper in the American Journal of Public Health[1] looked at residence mobility in relation to social status and the economic deprivation of the areas of residency in the city of Dallas. The study was part of an on-going study on heart disease and followed subjects (about 1,800) over the period 2000 to 2009. Weight was monitored at baseline, at various intervals and at follow up. Half the subjects moved from one neighbourhood to another and of these, 600 subjects moved to a neighbourhood with a higher ‘Neighbourhood Disadvantage Index’ (NDI: ~ perceived neighbourhood violence, poor physical environment, and low social cohesion). Compared to those who moved to a neighbourhood with a lower NDI or who remained where they originally resided, those moving to a higher ranked NDI suburb gained significantly more weight and the longer the residence in the higher NDI suburb, the greater the weight gain.

Well of course, the answer is simple. These people moved to “food deserts”, the trendy middle class quasi left wing term to describe regions which are so poor, its not worth anyone’s time and money in building them a supermarket. Consequently, the creed goes, they cannot get access to affordable and varied food supplies but are forced to shop in local stores that don’t sell fruit and vegetables at a reasonable price and which prefer to stock their shelves with cheap and, of course, high fat, high sugar and high salt foods (Credo in unum dieta!). Enter a governmental initiative that subsidised the building of a brand new supermarket in the suburb of Morrisania in the New York borough of the Bronx with a ‘control’ suburb of Highbridge where no such investment was made. A research paper just published[2] examined food choice 5 weeks and 52 weeks after the supermarket was opened. The authors concluded as follows: “The introduction of a government-subsidized supermarket into an underserved neighbourhood in the Bronx did not result in significant changes in household food availability or childrens dietary intake. Given the lack of healthful food options in underserved neighbourhoods and need for programmes that promote access, further research is needed to determine whether healthy food retail expansion, alone or with other strategies, can improve food choices of children and their families”. So, access to healthy food options is not the issue. It is most likely lifestyle choice arising from a particular educational stance.


Now enter the ultimate holy grail of the urban middle class food priests, the Farmers Market. What can be more morally upright than buying wholesome food directly from the farmer who toiled the land to produce such heavenly fare? Well, a recent study[3], also in the Bronx, paints a different picture. Following a comprehensive study of farmers markets (FMs) in this region, they conclude as follows:  (1) FMs operate overwhelming fewer months, days, and hours than nearby stores, (2) FMs carry less-varied, less-common, more-expensive produce than nearby stores. (3) FMs offer many items not optimal for good health (e.g., jams, pies, juice drinks) and OMG, (4) FMs might provide little net benefit to food environments in urban communities.

Social inequality lies at the heart of many patterns of chronic disease. Tackling it is outside my expertise but I’ll vote for it








[1] Tiffany M. Powell-Wiley et al (2015) Am J Public Health, in press
[2] Ebel B et al (2015) Public Health Nutrition, Feb 26:1-10.

[3] Lucan SC et al (201)  Appetite 90, 1 July 2015, Pages 2330

Sunday, April 19, 2015

Personalised Nutrition: A look into the future

Personalised nutrition is the future. When the sequence of the human genome was first announced, it was believed that human biology had set a new boundary around its research challenges. It was believed to herald a new dawn in cancer prevention when President Bill Clinton and Prime Minister Tony Blair launched the human genome sequence project in June 2000. Clinton commented: “In fact it is now conceivable that our children’s children will know the term ‘cancer’ only as a constellation of stars” to which Blair added the this heralded: “a breakthrough that opens the way for massive advances in the treatment of cancer”. The era of personalised medicine had arrived and the road ahead was envisaged thus: You doctor would have your genome scanned to check some conditions such as blood pressure where your measurements were marginally high. She or he might find you had a genetic predisposition too high blood pressure and based on your genetic information, the ideal pharmaceutical treatment to stave off hypertension would be identified. Armed with a prescription from your doctor you would go to your high street pharmacist and buy the prescribed drugs and maybe what today is called a ‘companion diagnostic’, a home blood pressure monitoring machine.

The temptation to translate this model to human nutrition was very attractive and so genetic testing companies were set up where for about  €200 a pop, you could be screened for genetic variants associated with diet related diseases. The industry flopped for two reasons. Firstly, when someone is told to eat more fish oil because they have some genetic variant indicative of declining cognitive function in which fish oil fatty acids might play a protective role, it has to be borne in mind that those same fish oil fats influence blood clotting, blood lipids, inflammation, vision and so on. So how could they be sure that what was good for treating cognitive function was maybe bad for your vision or inflammation? Drugs have one single point of action. Nutrients have multiple points of action. The second is that it’s not good enough to tell Homer Simpson he has a genetic variant which influences his cardiac electrophysiology and thus he needs to “watch” his lipids and salt. No, Homer wants a solution, not a problem. There is no wonder drug and no pharmacist to help him. He has to go to the supermarket and start making choices as to the foods that will help balance his lipids and salt. So, he needs customised solutions.

Enter Food4Me, a €9m EU funded project, which looked at all aspects of personalised nutrition: Consumer attitudes, business opportunities, legal and ethical issues, new emerging technologies which give biofeedback and most importantly, an internet based proof-of-principle study of the value of fully internet delivered personalised nutrition which involved providing genetic information, blood analysis and a personalised dietary analysis with feedback and coaching. The latter was the biggest hit with the 1,300 subjects who too part in the 7-centre pan EU study. Subjects entered their data on habitual food intake following a simple template across the Internet. That food intake data was translated into actual weekly nutrient intake and these data were compared to established international standards. The feedback was graphic. If the little cartoon man was in red for calcium you had a major problem to tackle, if it was in amber, it was in need of addressing soon and if in green, it was ok. The subject then was told why they had the problem they had with each nutrient based on their habitual food choice. A high intake of cheese might put calcium in green but saturates in red. A high intake of soup might put energy in green but salt in red. So for the three most urgent nutrients, they received detailed coaching on how to change their food choice to optimise their diet. Unlike Homer walking into the supermarket knowing his problem but not his solution, our subjects went to the supermarket knowing exactly, for them, what foods to chose to optimise their diet. Did it work? Yes it did when compared to a control group who were not given personalised dietary analysis but generalised population healthy eating guidelines.

So the future is thus. Whether by smart phone or a home computer, food choice is inputted and nutrient intake calculated by the service provider who then tells the used the top three problems to solve and what food choices to make to improve things. In fact, the advice won’t be at food level but at a weekly menu level taking into account data on personal taste, access to food, allergies and intolerances and price. This data will be shared with three other players: your smart fridge, a range of supermarkets and your work canteen. The supermarkets will translate the weekly menu into a shopping list and give you a price whereupon you will make your choice and the groceries will be delivered to your door. The smart fridge knows what’s ay home and expects you to interact with the touch screen on the door to indicate what you’ve taken out. I log on: “Good morning Mick” it says and I press a button marked ‘the usual so it deducts a bowl of porridge with milk and sugar, a glass of orange juice and tea. The information is shared with my computer, which now builds up my weekly aggregation of nutrients. Now it re-adjusts its record of the food store. In work I pick a soup and roll and using my swipe card at the check out, and both my computer and smart fridge are informed. On Thursday, I choose fish and chips at work and I swipe my card and I now get a text telling me that I have now reached my 90% limit of salt intake and I have a shortfall in fibre intake. When I get home, my smart fridge that now knows this problem and knows what’s in the kitchen offers several menus to boost my fibre with low salt meal recipes. I pick one but don’t know how to cook it so the smart fridge scans You Tube for demo and away I go.  It’s the future. The white goods industry, the IT industry, retailers, caterers and the food sector are hatching it.

In this analysis I have left out genetic based information, which is a long way off and the postal based blood biochemistry, which is presently operational. If you’d like to read about the project click here and if you’re a little lazy, then watch a 15-minute video on the findings here.  






Wednesday, April 15, 2015

Scientific norms and the WHO


In 2007, a paper was published in the medical journal The Lancet that sought to study how the WHO expert panels reach their conclusions, which are profoundly important in shaping global policy on public health [1]. The study, conducted jointly between the Norwegian Centre for Health Services and the Centre for Health Economics at McMaster University in Canada, and funded by the EU concluded systematic reviews were rarely used and the favoured way of developing a report was to use an expert committee or individual experts. One interview among the 29 directors or equivalents commented thus: “There is a tendency to get people around a table and get consensus – everything they do has a scientific part and a political part. This usually means you go to the lowest common denominator or the views of a ‘strong’ person at the table.” This criticism was bad enough but worse was to come. Two papers were published subsequently in the Lancet, one by researchers looking at insecticide treated anti-malarial bed-nets and another looking at child mortality [2]. For the first paper, the authors outline the success of the programme but, importantly, they also outlined some important uncertainties in the data. The WHO received drafts of the data and ahead of the Lancet publication, issued a press release claiming that the data “ends the debate about how to deliver long-lasting insecticidal nets”.  The second paper from researchers at Harvard and Queensland universities reported disappointing progress I the rate of reduction of childhood mortality. UNICEF contacted the Lancet about the paper but after considerable consultation with individual experts the Lancet decided to publish and informed UNICEF of the intended data of the publication. UNICEF then fast tracked the publication of its annual State of the World’s Children Report and made claims contrary to the paper. These two actions by the UN agencies, caused the Lancet to pen an editorial which concluded thus: “But the danger is that by appearing to manipulate science, breach trust, resist competition and reject accountability, WHO and UNICEF are acting contrary to scientific norms that one would have expected UN technical agencies to uphold. Worse, they risk inadvertently corroding their own long-term credibility” Scornful criticism for a top class medical journal!!

The UN moves slowly and thus in 2012, in response to such scathing criticism, it issued a specific handbook for guideline development and they established a Guideline Review Committee to be involved in evaluating all subsequent guidelines. Central to this process was the internationally accepted approach to the development of guidelines called the GRADE (Grading of Recommendations Assessment, Development and Evaluation) process. Grade is used to evaluate confidence in the effect of some action or intervention and classifies this confidence as high, moderate, low or very low. If there is more than on effect possible, the overall grading is based on the weakest measure of confidence. In addition to the strength of evidence on outcomes from actions or interventions, GRADE also rates the overall recommendations as strong or conditional. An international panel set out to examine how guidelines and recommendations of the WHO adhered to the GRADE system since its introduction in 2007 up to the year 2012 [3]. A total of 160 recommendations were found and reviewers worked in pairs to evaluate adherence to GRADE guidelines. Of the guidelines deemed to be strong, 56% were found to have low or very low confidence in estimates. Only 17% had high confidence in estimates. . Turning to the 167 recommendations that were considered weak, 85% were indeed based on low to very low confidence in the estimates of the effect of the action or intervention. Thus for example, 100% of the strong recommendations were found to be based on low to very low effects estimates for guidelines on nutrition and influenza. Half of the recommendations in the area of maternal and reproductive health, child health, HIV/AIDS and TB were deemed to be strong recommendations based on low to very low confidence in the outcome effects.
The same set of researchers went one step further in a follow up paper. Sometimes, expert committees have to make judgments [4]. The confidence in the true significance effect estimate might not be as strong as they’d like but the expert committee feels that a strong recommendation is warranted for whatever reason. These are called discordant recommendations and GRADE recognised 5 situations where a discordant recommendation is warranted. Given the very high number of strong recommendations with weak effect evidence observed in the previous study, the researchers set out to see how many of these met any one of the five situations, which GRADE allows a discordant recommendation. Only 16% of the discordant recommendations met any one of the 5 situations where GRADE accepts a discordant recommendation. In all, 84% of the discordant recommendations did not meet the GRADE guidelines. 46% of the discordant recommendations (strong recommendation but low supporting evidence) should have been classified as simply conditional recommendations. These two papers show that the WHO still has a long way to go to meet reasonable levels of scientific integrity. It may well be that expert panels make strong recommendation based on weak evidence of effect because otherwise their recommendations will be ignored. The problem is that in many countries, a strong recommendation from the WHO is the first step in the development of national policies and such is the respect that many national public health agencies have in the WHO and their guidelines that they go unquestioned. Anyone who has had dealings with large UN agencies knows that they are frequently short of resources and given that they answer to multiple national governments and to multiple non-governmental organisations, it is correct to have some level of understanding of their constraints. However, failure to rigorously embed their guidelines in the highest quality of science and the repeated issuing of strong recommendations based on weak to very weak evidence based outcomes, means that they cannot be excused. They may keep most non-governmental activists happy but in the long term, global trust is more important. It is hard won and easily lost.



[1] Oxman AD et al (2007) Lancet, 369, 1883-1889
[2] Lancet editorial (2007) Lancet, 370, 1007
[3] Alexander PE ((2014) J Clin Epidemiology 67, 629-634
[4] Alexander PE (2015) J Clin Epidemiology e pub ahead of print

Tuesday, March 17, 2015

Getting old and fat ~ no problem!

Growing old and fat ~ no problem


In today’s obesocentric (a new word I’ve coined) world, there are certain things that are given. These are the immutable facts about obesity. One of them is that the link between obesity, as measured by Body Mass Index (BMI = kg/m2), is U shaped. Over the range corresponding to desirable weight (BMI =20 to 24.99), there is no relationship between BMI and mortality or morbidity. Below 20, there is a rise in the risk of mortality as one gets skinnier. Above 24.99, mortality rises as BMI increases and it soars when obesity exceeds 30. No matter where you look, this is a given. It’s on the WHO website. It’s in your pharmacy window. It’s in schools, in textbooks and its like the boiling point of water, a given, never to be challenged.

Recently, in writing my new book on obesity, I re-discovered a set of data that was 30 years old. The data were published in a Working Party Report of the Royal College of Physicians of London in 1983[1]. It looked at the association between mortality and BMI over decades of age. Among 20 and 30 year olds, the rise in mortality with increasing BMI was quite dramatic above25. So far so good. Among 40 and 50 year olds, we begin to see the emergence of a U shaped curve, rising at both low and high BMI values. However, among 60 year olds, whereas BMI cause rising mortality at very low values, there was no relationship between BMI and mortality above a BMI value of 20. Of course, death rates rose with age but the pattern of mortality with BMI was very much influenced by age.

The subject has recently been revisited through a systematic review and a meta-analysis[2]. A total of 564 publications were identified in the literature based on key words of which 394 were rejected because of a focus on specific patient groups or non-human studies. Of the remaining 170 papers, a further 150 were excluded because they did not provide two or more age comparisons. That left 20 papers of which 13 were US based, 2 were Finland and Taiwan based and 1 each were from Germany, India and Japan. The increase in the risk of mortality with a BMI greater than 24.9 kg/m2   was assessed for decades of age. Averaging the values for men and women, the increased mortality risk with elevated BMI was 60% among those aged less than 35. That figure the fell progressively: 40% among thev35-45 year olds, 355 for 45-55 year olds, 28% among 55-65 year olds, 20% among the 65 to 75 year olds and a mere 11% in those aged above 75 years. The studies all controlled for the possibility of smoking or a pre-existing illness (e.g. high blood pressure or diabetes) being statistically confounding factors. However, the paper reports that this statistical control had no effect on the outcome. Basically, each increasing decade of life above 35 years of age reduced BMI related mortality by 10%.

Writing as a pensioner, a grandfather and a 67 year old, I say YIPPEE. But my GP doesn’t know this nor does my friends cardiologist and so we grey-heads are demonized unnecessarily by medics into being of adequate BMI. Of course, we do benefit from cardiovascular fitness so a good walk during the day when all the younger folk who kindly earn our pension, work away in a stress-filled environment increasing their BMI mortality risk, is a good idea.

Why does this obesocentric world choose to ignore such data? The answer, it seems to me, is that the simpler the message, the easier is the public health communication. So, they don’t complicate it by absolving older folk from the curse of BMI related mortality. And of course there is the other issue of the obesity paradox[3]. It gets even messier but I love it, the truth, that is!!!



[1] Royal College of Physicians Working Group on Obesity (1983) Journal of the Royal College of Physicians London 17:3-58
[2] Wang Z (2015) Obesity Research & Clinical Practice, 9:1-11
[3] BMI, Obesity & mortality: three grand challenges. Gibneyonfood, December 15th, 2014