Treating diabetes: Diets, gyms and scalpels

In the US, 27% of those aged 65 or older have diabetes. Based on fasting blood glucose levels or glycated haemoglobin levels, the estimate of the prevalence of pre-diabetes is 79 million cases. The economic cost has been estimated at around $2,000 per person per annum. The maths aren’t complicated working out at about $22 billion per annum.  Most  cases of type 2 diabetes are treated initially by lifestyle changes and then by drugs to manage blood glucose. In 2009, the American Diabetes Association defined partial remission from diabetes when fasting blood glucose levels were lowered to below the diagnostic norm and complete remission when fasting blood glucose levels returned to normal, in both cases in the absence of drug therapy. Relatively little is really known of the extent to which such partial or complete remission can be achieved with lifestyle interventions. In 2001, a large multicenter study was established in the US known as “Look Ahead”, (Actions for Health in Diabetes)^[1]. The trial, funded by the National Institute of Health, involved 2,262 type 2 diabetics given a basic diabetes lifestyle intervention and a group of 2,241 type 2 diabetics given an intensive lifestyle intervention. The former were given 3 group sessions per year while the latter participated in weekly group and one-on-one counseling for the first 6 months followed by 3 sessions per month for the next 6 months and twice monthly sessions thereafter. For this group, a target caloric intake was set between 1,200 and 1,800 calories per day with an exercise goal of 175 minutes of moderately intensive exercise per week (25 minutes per day).  The Look Ahead trial laid out its hypothesis quite clearly: that there would be a significant reduction in heart disease and stroke in the intensively counseled group compared to the group receiving standard advice on lifestyle. The trial has produced over 80 peer reviewed papers and has shown that intensive lifestyle intervention can significantly improve body-weight, blood pressure, blood glucose control and blood lipid levels.

On October 19th this year, when the trial was well into its 11th year, the NIH announced the end of the trial on foot of recommendations from the trial’s data and safety monitoring board. This independent body of experts noted that despite the above improvements on risk factors for cardiovascular disease, there was no statistically significant difference in cardiovascular events between the two groups which was the central hypothesis. Recently, the trial study group published a paper in the Journal of the American Medical Association showing that intensive lifestyle intervention did indeed lead to a greater rate of remission of type 3 diabetes compared to the standard intervention^[2]. The big disappointment was, however, that the impact of intensive lifestyle was very small. The rate of partial or complete remission in year 1 was 11. 5% in the intensively tutored group, falling to 7.3% at year 4. In contrast, the group receiving standard counseling showed a 2% reduction at both time points. Very clearly, type 2 diabetes is not a reversible condition for the vast majority of subjects. And just as clearly, this low response rate in correcting diabetes pathologies explains why no differences in heart disease were observed between the two treatment groups.

In the same issue of this journal, an editorial looks at the overall evidence for lifestyle and surgical interventions in obesity^[3]. The latter are usually confined to subjects with very severe cases of obesity. The latter leads to type 2 diabetes remission rates, which are 12 to 24 fold greater than intensive lifestyle interventions. The Swedish Obesity Study, also published in this year’s JAMA, reported on the long-term effects of the surgical treatment of obesity. Subjects were morbidly obese at baseline (1987 was the start date) and the average duration of follow up was 14.7 years^[4]. Compared to conventional medical and lifestyle treatment, the surgical intervention reduced fatal heart attacks by 47%, all heart attacks by 52% and stroke by 34%. Surgery is expensive but so too is intensive lifestyle interventions and thus some cost comparisons between the two would be interesting.

Clearly, we are in a mess and we must now live with the mess. But how can we prevent the mess for future generations?. Whilst 79 million Americans have prediabetes and are at risk of developing diabetes, the remaining 233 million don’t. Of those aged over 65 years, 11.2 million have type 2 diabetes while the remaining 30 million over 65s do not. They all live in the same obesogenic US environment. One day, not far from now, we will be able to predict who is likely to to draw the short straw and develop obesity-related type 2 diabetes. Moreover, this genetic information will soon be able to zone in on that aspect of diet and lifestyle, which is most responsible for the development of diabetes. For some, it may be a metabolically based genetic factor. For others, it may be a food choice factor that is the driver and for others it may be a defective satiety system. Understanding personal risk and understanding personalised solutions is the future for nutrition and health. In the meantime, we have a mess.

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^[1] https://www.lookaheadtrial.org

^[2] Gregg et al (2012) JAMA 308,2489

^[3] Arterburn DE & O’Connor PJ (2012) JAMA 308, 2517

^[4] Sjostrom L et al (2012) JAMA 307, 56

Obesity and Nature v Nurture re-visited

In the obesogenic environment that we live in, not everyone becomes obese. To the high priests of nutrition, that variability is put down to variation in self-control and self-discipline and that in turn relates to level of education and social class. The idea that this variation might be genetically based is dismissed with the old reliable falsism that since our genes have not changed during the recent epidemic of obesity, it’s the environment that counts. Well, yet another twin study shows that this is nonsense and this twin study is somewhat special since it pooled data from 23 twin cohorts from four countries: Denmark, Australia, Canada and Sweden involving just over 24,000 children[1]. Moreover, this pooling study was able to provide data on twins from birth through 19 years of age. By comparing variation within and between both identical and non-identical twins, it is possible to distinguish the effect of genes from the effect of the environment and the latter can be split into common and unique environments. At birth, only 8% of variation in weight or body mass index (BMI) could be explained by genetic factors. By 5 months this had increased to 65% and rose into the 70% decile up to 9 years of age. In the early teens the genetic variation had reached into to 80% decile and by late teens it had hit 90%.  As children got older, the environmental explanation of obesity had fallen from 74% at birth, to 25% at 6 years and down to about 10% in late teens. While this study clearly shows the powerful effect of genetic factors on obesity, it does raise the question as to why this genetic dimension increased with age. Clearly, the genetic make up remained constant so most likely, changes in gene expression were the contributory factor. Growth in childhood and especially in adolescence is associated with significant biological adjustments, which could create the environment for altered gene expression.

One of the reasons which I personally think public health nutritionists are wary of the genetic influence on obesity is that the subject is strongly orientated toward basic biology, effectively, the digestion, absorption, transport, distribution and utilisation of calories from fat, carbohydrate, protein and alcohol. However, genetic influences on behaviour are to my mind far more important   than the genetics of basic biological elements. A recent twin study has looked at the heritability of taste[2].  Subjects were given a strawberry jelly with or without the hot spice capsaicin derived from chili peppers. They were also asked questions on their liking or otherwise of spicy foods and spices and of foods that have mild, strong and extremely strong pungency properties. 50% of the variation in preference for spicy foods and spices and 58% of the variation in “pleasantness of strong pungency” was explained by genetic factors. Another twin study looked at food neophobia in a group of children aged 8 to 11 years, comprising 5,390 pairs of identical and non-identical twins[3].  Parents were asked about their children’s attitude to foods with four statements: “My child is constantly sampling new and different foods”, “My child doesn’t trust new foods,” “My child is afraid to eat things/he has never had before.” and “If my child doesn’t know what’s in a food s/he won’t try it.” A food neophobia score was worked out and the highly robust finding of the study was that a staggering 78% of variation in food neophobia was genetic in origin. Only 22% was learned from the environment. These studies show that the genetic component of obesity need not be related to the biochemistry of energy metabolism, but rather to more complex behavioural traits such as food choice.

Twin studies of obesity always raise the question of assortative mating, that is fat partners mating with other fat partners and similarly for slim partners. Assortative mating has been shown to occur in personality type, education, religion, politics, age, smoking habits and anti-social behaviour. Researchers at the Rowett Institute in Aberdeen used DEXA scans to accurately measure body fat levels in 42 couples[4]. Strong evidence for assortative mating in relation to body fat was found. For example, subjects with disproportionately large arms assortatively mated with like partners. Given the high heritability of the propensity to develop obesity, assortative mating will accelerate the incidence of obesity sine the children of such parents are likely to inherit genetic patterns from both parents.  

The high priests of public health nutrition may dislike the implications of a genetic dimension to obesity but they are being increasingly isolated from the scientific truth.

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[1] Dubois et al (2012) PLoS ONE 7, e30153

[2] Tornwall et al (2012) Physiology & Behaviour, 107, 381-389

[3] Cooke et al (2007) Am J Clin Nutr 86, 428-433

[4] Speakman et al(2007) Am J Clin Nutr 86, 316-323