Back in 2008, when I first proposed what is now widely referred to as the Edmonton Obesity Staging System (EOSS) as a means of classifying the severity of obesity beyond BMI, I could not have imagined how readily this concept would be embraced by those of us interested in clinical obesity management.
A current PubMed search reveals almost 60 published articles on the use of EOSS to determine risk and outcomes in a variety of populations and settings, consistently showing that EOSS does a far better job of predicting morbidity, mortality, surgical complications, fertility rates, occupational function, hospital stay, and even cost than BMI.
But how practical is the application of EOSS to real-world data in primary care?
This is now the topic of a paper by Rukia Swaleh and colleagues from the University of Alberta, published in CMAJ open.
The paper describes the development of a clinical dashboard that calculates and displays the relation between BMI and EOSS and the prevalence of related comorbidities based on cross-sectional data in over 30,000 patients within the Northern Alberta Primary Care Network and the Canadian Primary Care Sentinal Surveillance Network, who were at least 18 years of age with BMI between 30 and 60 and visited a network clinic between July 2016 and July 2019.
This EOSS dashboard provides an interactive tool that readily identifies and characterizes patients based on EOSS stage within a primary care practice, thus prompting better surveillance, prevention, and management of patients with obesity and related complications.
Applying these analyses to the study population revealed several interesting findings.
Firstly, BMI class distribution appeared to be rather similar across EOSS stages, confirming once again that BMI is not a useful or reliable measure of obesity severity.
Secondly, age alone described 31% of the variation in EOSS stages. In contrast, sex and BMI explained very little of the variation in EOSS stages, together accounting for just over 1% of the variation.
Thirdly, hypertension, dyslipidemia and diabetes (and their complications) were the leading drivers of higher EOSS stages.
The EOSS tool provides several useful features that can be used to further characterize and analyse patients down to seeing tests, medical prescriptions, and last date of visit for individual patients based on EOSS stage.
Thus, this paper not only shows that one can develop electronic EOSS tools based on real-world practice data but also shows how these data can be used to better manage patients with obesity and related complications in primary practice.
I have been practicing medicine long enough to remember treating hypertension before there were ACE inhibitors or ARBs. I vividly remember training in a lipid clinic before the introduction of statins. Many will recall managing type 2 diabetes before we had TZDs, DPP4 inhibitors, SGLT2 blockers, or GLP-1 analogues.
In all of these disease areas, prior to the introduction of the currently available effective medications, the focus was on dietary and other behavioural interventions. Thus, I recall giving talks on sodium restriction, physical activity, or the DASH diet for managing hypertension or on the AHA Step I/II diets to manage dyslipidemia. While dietary and other behavioural interventions remain important pillars for managing these conditions, it would be quite uncommon today to see clinicians manage any of these entities with “lifestyle” interventions alone.
However, the latter is still the case for treating obesity, which in itself remains the exception rather than the rule as far as clinical management is concerned.
This may be about to change.
Thus, according to a paper by Timo Müller and colleagues, published in Nature Reviews Drug Discovery, there is much reason for hope that we will soon have a plethora of anti-obesity medications that may well drastically change obesity management.
The paper extensively reviews the rather sketchy past history of anti-obesity medication and provides a brief primer on the complex neuroendocrine systems that govern the energy homeostasis.
The authors also highlight the important challenges in developing effective anti-obesity medications including heterogeneity of the disorder, the complexity of the neuroendocrine system, translating findings from animals to humans, and of course safety aspects.
The authors then go on to discuss the various existing and potential targets with an update on the rather wide range of molecules currently under investigation. Broadly, these can be classified as incretin-based (mono-, dual- and even triple-agonists), leptin, leptin-sensitisers and MC4 receptor agonists, mitochondrial uncouplers, GDF15, amylin, PYY, and a few others.
While no one expects all or even most of these molecules to ultimately meet the rather high bar of efficacy and safety, one would have to be rather pessimistic to think that none of these molecules will make it.
Rather, as we are currently witnessing with the recent regulatory approval of semaglutide for obesity (in the US, UK, EU and Canada), which is promising to deliver weight-loss in the 15-20% range, and the emerging data for the dual agonist tirzepatide or the early data for the combination of semaglutide with the amylin analogue cagrilinitide, it is foreseeable that medical treatment of obesity will one-day routinely involve the use of anti-obesity medications, in the same way that medications are routinely used to manage hypertension, dyslipidemia or type 2 diabetes.
Obviously, much needs to happen before this becomes a reality. Not only do we need long-term outcome studies (some of which are already underway) but we also need payors to help make these medications accessible to those who need them. Finally, we need education of both health care providers and patients to fully understand why these medications are necessary in the first place and how they can be best used to reduce the burden of obesity related complications and impairments in quality of life in people living with obesity.
Obesity is a complex and heterogeneous condition that can occur at any age throughout the lifespan for a myriad of reasons. Furthermore, once established, obesity generally becomes a lifelong problem requiring long-term (often lifelong) management.
Thus, given that almost anyone can be affected (no matter how healthy your lifestyle in the past) and early intervention in high-risk individuals would seem prudent, it would clearly be of great interest to identify those at highest risk of weight gain.
The researchers analysed longitudinal data from 400 primary care practices and included over two million individuals aged 18–74 years who had BMI and weight measurements recorded between Jan 1, 1998, and June 30, 2016, with at least 1 year of follow-up.
Of all the potential factors that one might imagine would predict weight gain, including socioeconomic factors, comorbidities, medications, etc., the only significant predictor of future weight gain turned out to be young age!
Thus, being a young adult between 18-24 years of age carried the highest risk (4 to 5 fold higher than for older adults) of developing obesity or transitioning to a more severe obesity stage (based on BMI).
Other socio-demographic factors including sex and race were only marginally significant.
Not only are these findings surprising but also pose an important challenge to clinicians trying to identify individuals at risk. After all, young age is not much information to go on.
This of course does not mean that predicting obesity is hopeless. It just shows that there are probably myriads of risk factors for future obesity (e.g. adverse life events, comorbidities, medications, etc.) that act throughout the lifespan and can be significant for individuals but not for entire populations.
My advice to clinicians would be to keep a close eye on changes in body weight (especially in younger adults) and try to identify drivers of excess weight gain as early as possible, remembering that an upward weight trajectory can occur in pretty much anyone at any point in life.
Humans are social beings and supporting each other in challenging endeavours is often the best path to success.
Thus, one would imagine that peer support would be one of the key elements that can help nudge, motivate, encourage and ultimately steer someone towards their goals.
Not surprisingly, peer support groups are often mentioned and recommended in the context of weight management and lifestyle change.
But how effective are such groups in actually helping people change their lifestyles and support relevant outcomes (e.g. weight loss)?
This is the topic of a systematic review and meta-analysis by Lim Siew and colleagues from Monash University, Victoria, Australia, published in Obesity Reviews.
The researchers examined data from 65 studies, including over 15,000 participants, looking at the effectiveness of peer intervention in changing body weight, energy intake, and physical activity in adults.
While statistically significant, the overall effects on these parameters were rather minimal – about 1 kg decrease in body weight, an 0.75 cm reduction in waist circumference, and a minute effect on physical activity with no change in energy intake.
Interestingly, adding a health professional to the group appears to have little influence on the outcomes.
As one may expect, there was considerable heterogeneity between studies and given the nature of peer-support groups, it was virtually impossible to pinpoint the source of variations in outcomes.
Thus, while peer-support groups may well provide other benefits to participants, as in social contact and support, they are hardly a reliable means of promoting lifestyle change.
This should not discourage anyone from participating in such groups if they happen to find them helpful – however, there does not appear to be any pressing argument to join such a group if peer-groups are not your thing. .
Bariatric/metabolic surgery has been shown to promote improvements and even remission of type 2 diabetes.
Now, as paper by Lena Oppenländer and her German colleagues, in a paper published in Molecular Metabolism, shows that vertical sleeve gastrectomy (VSG), in contrast to a low-energy diet results in fast ß-cell recovery in diabetic db/db mice, a model of severe obesity and type 2 diabetes.
Using single-cell profiling of islets of Langerhans, the researchers showed that VSG induced distinct, intrinsic changes in the β-cell transcriptome, but not in that of α-, δ-, and PP-cells.
Furthermore, within two weeks of interventions, VSG triggered fast β-cell redifferentiation and functional improvement.
Expansion of β-cell area was attributed to both redifferentiation and by creating a proliferation competent β-cell state.
In addition, the paper presents substantial information on changes in molecular pathways that would in part explain these observations.
Although evidence from animal studies should always be taken with a grain of salt, these studies should lead to further exploration of similar mechanisms resulting in the restoration of ß-cell function in humans following metabolic surgery.