How Much Of The Confusion In Childhood Obesity Studies Is Simply Regression To The Mean?
When it comes to childhood obesity interventions, there is much confusion as to what works and what doesn’t. Thus, for every study showing that a given “intervention” (e.g. school intervention programs, exercise programs, removing vending machines, etc. ) changes weight measures, there is at least another study showing that it doesn’t. Although this problem is by no means specific to research in childhood obesity, for reasons stated below, research in this area appear to be particularly prone to this problem. Now, a paper by Cockrell Skinner Asheley and colleagues, published in Childhood Obesity, suggests that much of this confusion may simply be due to the statistical phenomenon of “regression to the mean” (RTM). As readers may be well aware, regression to the mean refers to the well-described phenomenon that “outliers” (up or down) tend to “regress” towards the mean on repeated measures. Or as the authors explain, “Today, RTM is often conceptualized primarily in the context of measurement error or repeated measures. Blood pressure provides a reasonable example. If one measure of blood pressure is obtained and is either much higher or lower than the mean, a second measure will likely be closer to the mean. If conceptualized as measurement error, then an average of multiple measures is often used to reduce measurement error, thereby also reducing regression to the mean.” Repeated measures however do not solve the problem when the measured values actually do change over time (as in a child’s body weight). As the authors note, “However, this does not address changes in the true value of the variable over time, which are not due to measurement error. Whenever two variables are not perfectly correlated (such as blood pressure at two time points), there will always be RTM when measured in terms of standardized variables. This occurs regardless of measurement error, the order of measurement, and whether the two variables are repeated measures of the same construct. Additionally, as noted by Barnette et al., regression to the mean can occur in nonnormal distributions and those that are not continuous. For example, RTM can occur in binary data and cause subjects to change categories without a change in their actual status.” While this issue tends to affect all types of research, which is why every experiment would ideally have rigorous controls and the most robust research methods generally use some form of randomisation, this is particularly difficult in studies in childhood obesity.… Read More »
The Highs and Lows of BMI and Mortality
Almost all biological variables are detrimental to health at the extremes. A blood pressure that is too high can kill you – so can a blood pressure that is too low. A blood sugar that is too high can kill you – so can a blood sugar that is too low. It turns out that BMI is no different – too high and too low both carry a risk – a risk, however, that is substantially confounded by actual body fat%, which is not reliably measured by BMI. This is basically the message in a paper by my colleagues Raj Padwal and co from the University of Alberta in a paper published in the Annals of Internal Medicine. The researchers looked at data from about 50,000 women and 5,000 men (mean age, 63.5 years; mean BMI, 27.0 kg/m2) referred for bone mineral density (BMD) testing with dual-energy x-ray absorptiometry (DXA), which they linked to administrative databases. Given the size and demographics of the cohort, death occurred in almost 5000 women over a median of 6.7 years and 1000 men over a median of 4.5 years. Women in the lowest BMI and body fat% quintiles had a 40% higher risk of dying (compared to quintile 3). Risk of dying were also about 20% greater in the highest body fat% quintile for women. Similarly in men, both low BMI (HR, 1.45 for quintile 1) and high body fat percentage (HR, 1.59 for quintile 5) were associated with increased mortality. The exciting bit about this study is that the researchers had both BMI and body fat% available to them and were able to show that both variables independently of each other contribute to mortality risk. Thus, the worst possible combination in both men and women was low BMI and high body fat%. Or, as the authors put it, “Low BMI and high body fat percentage were both associated with increased all-cause mortality. Mortality increased as BMI decreased and body fat percentage increased…..Thus, our results suggest that BMI may be an inappropriate surrogate for adiposity, and this limitation may explain the presence of the obesity paradox in many studies.” As the authors discuss, these finding should have clinical implications as they clearly demonstrate the limitations of BMI as a measure of health risk. “..our findings underscore that the risk for all-cause mortality increases with both increasing adiposity and decreasing BMI in a general population of middle-aged and… Read More »
Obesity Network Facebook Page Gets 3000 Likes
This weekend the Canadian Obesity Network’s new facebook page received its 3,000th like. Now this may not seem like much (my personal facebook page has almost 15,000) – but then again, let’s not forget that the Network’s page has only been up since late last year, when the Canadian Obesity Network launched its public engagement strategy. So why is this remarkable? Because it takes guts to declare your interest and support in an organisation that has the word “obesity” in its name. Suddenly, all your ‘friends’ can see your interest in this topic – not trivial given the shame and stigma attached to this disease. I can hear the taunting from some of your ‘friends’ (even if they would perhaps never say this to your face), “So now that you follow the Canadian Obesity Network, are you going to finally do something about your weight?“ or “Obesity Network? Isn’t that like an “acceptance group” for fat people?“ Yes, it takes real guts to “like” the Canadian Obesity Network page on facebook. But Canadians living with obesity are evidently a brave lot. Take for example the facebook page of the US Obesity Action Coalition (the closest thing to CON’s engagement strategy in the US) – their 12,000 likes seem a lot more that 3,000. But let’s not forget that the US population is 10 times bigger than Canada’s – so that number for the OAC should really be 30,000 to match CON’s 3,000. This is not bragging about size (I’ll leave that to politicians) – it is about reminding ourselves that few conditions share the stigma and discrimination of obesity and that it is far harder to publicly show your support for an obesity organisation than an organsisation that is saving dogs or kittens. So kudos to the 3,000 bold Canadians, who have so far “liked” the Obesity Network’s facebook page – hopefully many more will follow your brave example and show their interest and support for the Network. @DrSharma Edmonton, AB
Senate Report: Bold Policies To Reduce the Number of Demented Canadians
According to a report just released by the Canadian Senate, “In the past three to four decades there has been a drastic increase in the proportion of demented Canadians. Statistics Canada data reveals that almost two thirds of Canadian adults are now demented. Sadly, the increase in dementia rates among children is also dangerously high. About 13% of children between the ages of five and 17 are demented while another 20% are somewhat dull. These numbers reflect at least a two-fold increase in the proportion of demented adults and three-fold increase in the proportion of demented children since 1980.” Just replace the word “demented”with the word “obese” in the above paragraph and you will instantly see what is wrong with this report, which happens to in fact be about obesity, and not about Canadians at risk of or living with dementia. Only when speaking about “obesity crisis”, would an official report composed by professional writers on an important medical condition still use the name of the condition as an adjective. Indeed, the use of “people-first language” to describe someone living with a condition rather than being defined by that condition has long been accepted in the case of virtually every other condition. Thus, we speak of people living with addictions rather than of addicts, of people living with diabetes rather than of diabetics, of people living with psychosis rather than of psychotics, of people with arthritis rather than of arthritics, of people living with cancer rather than of the cancerous, you get my drift. Enough has been written on this issue here, here, here, here, here and here. A report that wants to be taken seriously as addressing the concerns and struggles of Canadian adults and children living with overweight or obesity could perhaps begin by ensuring that it uses the proper language. This is not to say that the report does not indeed make bold and important policy recommendations – it does, from taxing sugar-sweetened beverages to limiting advertising to children, to rewriting Canada’a Food Guide to food labeling to tax benefits to promote physical activity (and more). It even addresses (although in passing) the need to provide better treatments to people living with overweight or obesity. Just which of these policy recommendations will actually find their way into legislation and how much difference they’ll actually make remains to be seen especially as the recommendations come with no actual funding… Read More »
Why There Is So Much Confusion About Obesity And Mortality
Any follower of media reports or even research papers on the relationship between obesity and mortality should be righty confused by now. Not only are there publications suggesting that the relationship between obesity and mortality isn’t that strong after all and that perhaps the BMI levels associated with the longest survival are somewhere around 30 (and not below 25) but then there is the issue of the obesity paradox, or the finding that among people with chronic (and some acute illnesses), a higher BMI is associated with better survival than being of “normal” weight. On the other hand, there is overwhelming evidence that higher BMI’s are associated with an increased risk of a wide range of health problems – from diabetes to cancer. This is not to say that everyone with a higher BMI is sick – they are not! But there is no doubt that the risk of illness does increase with higher BMIs. In our own study on the Edmonton Obesity Staging System (EOSS), which classifies individuals based on their actual health rather on their BMI, we found that while about 50% of individual in the BMI 25-30 range can be considered healthy (EOSS Stage 0 or 1), this number drops to below 15% for individuals in the BMI 40+ range. So, if obesity is such a risk factor for disease, why do epidemiological studies struggle to consistently show an effect of obesity on mortality? Now, a paper by Andrew Stokes and Samuel Preston, published in the Proceedings of the US National Academy of Science, suggests that it is not current weight (as used in many studies) but rather the highest lifetime weight that is most clearly associated with mortality. Their reasoning is as follows. “Intentional” weight loss in the population is rare (very few people in the general population ever consciously manage to lose a significant amount of weight and keep it off) In contrast, “unintentional” weight loss, when it occurs is generally a bad sign. Indeed, one of the best indicators of poor prognosis (for almost any health condition) is when someone loses weight. In many cases, this “spontaneous” weight loss can precede overt illness or death by many years. Thus, the authors argue that most of the literature on this issue is simply confounded by the confusion caused by all the people who have unintentionally lost weight due to an underlying health problem (diagnosed or undiagnosed). As these people would… Read More »
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