Arya M. Sharma, MD

Yesterday, the Arthritis Alliance of Canada together with the Canadian Arthritis Network released The Impact of Arthritis in Canada: Today and Over the Next 30 Years, a 50-page report that provides a detailed look at the impact of arthritis in Canada and offers solutions on how to mitigate and manage the situation.

According to this report, there are currently more than 4.4 million people living with osteoarthritis (OA) in Canada. In 30 years, more than 10 million or one in four Canadians is expected to have OA. Within a generation (in 30 years), there will be a new diagnosis of OA every 60 seconds.

Currently OA drives about $10 billion in direct health care costs and about $17 billion in indirect costs (lost wages, lost taxes, etc.) - together with other forms of arthritis (especially rheumatoid arthritis) the total cost of arthritis amounts to an estimated $33 billion annually. These numbers will on only grow.

Recognising that excess weight is one of the prime (modifiable) drivers of the OA epidemic, the report suggests that targeting obesity should be a priority (along with better access to joint replacements and adequate pain management) in reducing the burden of arthritis on Canadians.

As the report points out:

If a prevention program was available to reduce obesity rates by 50% in the Canadian population over the next 10 years:

• 45,000 new cases of OA could be avoided over 10 years and over 200,000 cases of OA could be avoided over 30 years;

• 25,000 workers could avoid OA over 10 years and over 136,000 cases of OA in the labour force could be avoided over 30 years;

• $3.8 billion could be saved in cumulative direct health care costs over 10 years and $48.3 billion over 30 years (2010 dollars); and

• $14.0 billion could be saved in cumulative productivity losses over 10 years and $163.7 billion saved over 30 years (2010 dollars).

(Limitation: Costs attributable to obesity-reduction interventions were unavailable and, therefore, not considered in the model.)

While this conclusion stresses the importance of obesity as a key driver of arthritis costs, this assumption of course is rather optimistic.

To my knowledge, there is no known prevention strategy that comes even close to reducing obesity prevalence by 50% in 10 years. Indeed, for those at the highest risk of OA, namely, those who are already obese, ‘prevention’ strategies come too late - you would actually have to look at ‘treatment’ strategies.

The authors are certainly aware of this as they concede that:

“Further research is needed to improve on current strategies for preventing and treating obesity.”

Fortunately, we’re already on it.

AMS
Edmonton, Alberta

Earlier this week, the Manitoba Centre for Health Policy (MCHP) released a report on Adult Obesity in Manitoba: Prevalence, Associations, and Outcomes.

The document (and especially the summary) makes an interesting read as it describes the rather complex nature of the epidemic and its impact on Manitobans.

While the analysis of about 35,000 Manitoba adults over the age of 18 who took part in one of three surveys between 1989 and 2008, documents the high prevalence of obesity and the fact that many health conditions are indeed more common in people with higher BMI’s, it also shows that these findings do not readily translate into higher healthcare costs till about a BMI of 33.

Thus, as the report summarizes:

“The Obese group almost always used more healthcare services than the other groups. However, the differences were small and often did not come into play until the very highest BMIs….people in the Obese group visited doctors more often than others. However, they only visited about 15% more overall. As well, the rise in visits only occurred from a BMI of 35 for men and 32 for women.
Likewise, costs of prescription drugs went up quite slowly until very high BMIs were reached. Hospitalizations were higher for those in the Obese group, but only for BMIs at or above 33. Home care use did not differ much either.”

This finding is actually not that surprising or unexpected.

Regular readers will by now be quite familiar with the Edmonton Obesity Staging System (EOSS), which was developed exactly because BMI is such an inadequate measure of risk or health.

Thus, I am confident that applying EOSS to this analysis would produce substantially different results than simply looking at BMI.

Thus, for e.g. our recently published analyses show that about 50% of people in the overweight category actually rank as EOSS 2/3. These individuals would considerably amplify the costs of people within the BMI 25-30 range - probably to the same level as EOSS 2/3 in the Obesity categories, while the obese EOSS 0/1 folks (of which there are about 20% in the BMI 30-35 class) would have costs very much like those of the EOSS 0/1 overweight people.

Such overlap in EOSS stages across BMI levels would readily mask any relationship between BMI and healthcare costs till rather extreme levels of BMI, where very few people will remain with EOSS 0/1 and the costs of being EOSS 2/3/4 would be substantially higher.

Thus, the ability of BMI to explore and interpret the cost of ‘obesity’ is limited, as it misses all of the ‘excess-weight-related’ health problems in the Overweight group while diluting the health care costs in the Obese group due to a substantial number of obese EOSS 0/1 people found in the moderately Obese group.

Thus, although I agree with the findings that higher health-care costs are only identifiable in individuals with moderate to severe obesity, I also sense that this report substantially underestimates the true cost of ‘excess-weight-related’ health problems.

The report also looked at ‘risk factors’ for obesity - a topic that I will comment on in tomorrow’s post.

A Summary of the Report is available here

The Complete Report is available here

AMS
Edmonton, Alberta

Today, as I attend the 47th European Association for the Study of Diabetes (EASD) Annual Meeting here in Lisbon, I cannot help but discuss an article by Kenneth E. Thorpe and Zhou Yang, Emory University, Atlanta, Georgia, published in the latest issue of Health Affairs.

Based on their analysis of the significant impact of even modest sustained weight reduction on the incidence of type 2 diabetes, these authors suggest that enrolling overweight and obese pre-diabetic US adults aged 60–64 into a proven, community-based weight loss program nationwide could save Medicare $1.8–$2.3 billion over the following ten years.

Estimated savings would be even higher ($3.0–$3.7 billion) if equally overweight people at risk for cardiovascular disease were also enrolled.

Thus, lifetime Medicare savings could range from approximately $7 billion to $15 billion, depending on how broadly program eligibility was defined and actual levels of program participation, for a single “wave” of eligible people.

A key assumption in their proposal, is that a fully funded sixteen-twenty week community program (perhaps delivered by the YMCA), would deliver about 4% weight loss and replicate the almost 50-70% reduction in progression to diabetes seen in some diabetes prevention studies.

Using our Edmonton Obesity Staging System definitions - this program would target Stage 1 patients (pre-diabetes) or Stage 2 patients (with hypertension or dyslipidemia).

There is no doubt that community based ‘lifestyle’ interventions are the only plausible way in which any program can be delivered to millions of eligible individuals. There is also little doubt that in randomised controlled trials, considerable benefits have been demonstrated.

The question remains, however, whether enough eligible participants will in fact participate and persist with these ‘lifestyle’ changes without continuing and ongoing support (which is generally what the clinical trials have delivered). The notion that an intervention of limited duration (even twenty weeks) will lead to sustainable effects, may be a bit over optimistic, even if 10 year follow-up data from some diabetes preventions studies suggest long-term benefits even after the end of the trials.

It is also worth discussing whether or not success is actually dependent on losing weight (not a behaviour) rather than simply increasing physical activity and eating better (which are behaviours).

Whether or not there is indeed a realistic chance that millions of people can be enrolled in community based interventions programs will remain to be seen, but it is certain that, if feasible, savings would indeed be substantial.

This is why, in the recently announced Alberta Health Services Obesity Initiative, there is a significant emphasis on the importance of community based programs (such as Thr!ve on Wellness, a joint initiative from Alberta Health Services and the Alberta Cancer Foundation, which will soon be expanded to over 100 Alberta communities).

If successfully adopted, these programs should have benefits far beyond diabetes prevention and reduce rates of heart disease, cancers, musculoskeletal problems and hopefully also improve mental health and well being.

Perhaps this is when we can truly claim to be moving towards a ‘health care’ rather than a ’sickness care’ system.

AMS
Lisbon, Portugal

Thorpe KE, & Yang Z (2011). Enrolling people with prediabetes ages 60-64 in a proven weight loss program could save medicare $7 billion or more. Health affairs (Project Hope), 30 (9), 1673-9 PMID: 21900657

Over the last several days I have been examining various aspects and implications of our recent publications showing that the Edmonton Obesity Staging System (EOSS) does a far better job of predicting mortality than does BMI (in fact BMI does almost nothing in this regard).

Not only does EOSS make intuitive sense to clinicians and most patients (especially the ones who are at EOSS 0) it is also a better way to individualize patient management strategies.

But, despite these two publications in three independent samples that included over 20,000 participants, many important questions remain to be addressed:

it is not clear whether all comorbidities should receive the same weight for defining the EOSS stage - for e.g. should chest pain due to reflux disease count the same as chest pain due to ischemic heart disease (probably not)?

What is the natural history of EOSS stage progression? Or in other words, how long does it take for patients to move from Stage 0 to Stage 1 or from Stage 2 to Stage 3? Are there really patients, who never progress? Are there predictors of progression? If yes, can this progression be delayed or prevented?

What does it take to reverse Stages and does reversing the obesity Stage improve prognosis (it probably does)?

How do cost-effectiveness and risk-benefit ratios of obesity treatment for patients look at different EOSS stages? I am guessing that both increase at higher stages, but is this really the case?

Can we develop a simplified version of EOSS (EOSS-lite?) that only counts certain comorbidities or only acknowledges certain dimensions of quality of life?

Is EOSS a concept that health professionals, decision makers, and funders are ready to adopt and will it improve practice and outcomes?

These are all questions that future research will need to address, some of this work is already underway, but I’d be happy to hear from potential collaborators or people wanting to do some of this research on their own.

If nothing else, I at least hope that the EOSS discussion has opened a whole new way of thinking about clinical assessment and definition of obesity and will find its way into clinical care pathways and management guidelines.

From everything I hear, this is already beginning to happen.

AMS
Edmonton, Alberta

Padwal RS, Pajewski NM, Allison DB, & Sharma AM (2011). Using the Edmonton obesity staging system to predict mortality in a population-representative cohort of people with overweight and obesity. CMAJ : Canadian Medical Association journal = journal de l’Association medicale canadienne PMID: 21844111

Kuk JL, Ardern CI, Church TS, Sharma AM, Padwal R, Sui X, & Blair SN (2011). Edmonton Obesity Staging System: association with weight history and mortality risk. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme PMID: 21838602

This may seem like a stupid question - of course, many readers will probably agree, that we need to prevent and better manage childhood obesity, no matter what it costs.

But in the end, someone still has to pay the bills, and so knowing what it may cost, is not an unreasonable question to ask.

The problem, however, is that economic forecasts are highly dependent on all kinds of assumptions and the perspective of what costs count, depends on who is looking - a narrow ‘health-care’ cost perspective is very different from a broader societal perspective of lost income, reduced productivity, and the substantial emotional cost of obesity (much of which has little to do with obesity itself but rather results from the pain caused by the societal bias and discrimination that kids and adults with excess weight have to endure).

Nevertheless, even with a very narrow perspective through the lens of people who pay for health care, these kind of analyses can be enlightening.

Therefore, it is with interest that I read the paper by Sai Ma and Kevin Frick from the Johns Hopkins Bloomberg School of Public Health, published in the latest issue of Academic Pediatrics.

As the authors point out:

“To endorse interventions at the earliest ages, one needs to understand 3 critical details: 1) the persistence of childhood obesity into adulthood, 2) the degree to which interventions are likely to be adopted by the children and their families at different stages in children’s lives, and 3) the potential returns on investment.”

So this study attempts to project at what level of effectiveness and cost a population-based or targeted intervention for childhood obesity would yield a positive net economic benefit.

The analyses is based on data from the National Health and Nutrition Examination Survey, the persistence of obesity from childhood to adulthood from a literature review, and a cost estimate from the 2006 Medical Expenditures Panel Survey.

Simulations were conducted to estimate the break-even point for interventions that take place between ages 0 and 6 years, ages 7 and 12 years, and ages 13 to 18 years, with a range of effectiveness.

The simulations show that, from a pure medical cost perspective, spending approximately $1.4 to $1.7 billion at present value for each birth cohort will break even if 1 percentage point reduction in obesity among children is achieved.

If this 1 percentage point in obesity rates is achieved through population-based interventions, they would break even between $280 and $339 per child at present value.

In contrast, If this 1 percentage point reduction is achieved solely by targeting obese children, one could afford to spend up to $1648 to $2735 per obese child.

In addition, the authors note that:

“…although for population-based interventions, per capita breakeven point for every percentage point reduction is about the same in each age group, to reach 1 percentage point reduction requires a higher effectiveness level of the intervention in the younger age group. For example, for every 2 percentage point reduction in obesity, a 55% effectiveness level is needed among the 0- to 6-years age group, 20% effectiveness level is needed for those aged 7 to 12 years, and approximately 17% is needed for those aged 13 to 18 years. This implies that interventions need to be more effective for younger children than those targeting older children in order to achieve the same economic returns.

The high cost savings of targeted interventions and needed higher effectiveness of interventions for children aged 0 to 6 years implies that providing targeted approaches perhaps makes more economic sense than providing population-based interventions.”

In support to favouring targeted interventions for younger kids, the authors discuss that:

“Limited research has found engaging parents is one single important effective factor among early interventions, which again requires intensive and customized interventions. Additionally, empirical evidence suggests preventions targeting high-risk children, such as children with obese parents or from disadvantaged backgrounds, could achieve better results than those offering service to the whole population of children.

In contrast, a population-based approach could be more applicable for older adolescents because they have a much higher obesity rate (18%), and there are problems such as stigma and feasibility imbedded in targeted interventions.”

As the authors also discuss, these estimates need to be taken with a grain (or rather a teaspoon) of salt, as we do not really know what health problems will actually develop in today’s kids with overweight and obesity (they may well end up far healthier than we think). Also, we don’t really know how health care costs will increase in the future.

Perhaps, even more importantly, while the authors tell us how much one could ‘afford’ to spend on these measures, they also note that data showing that any such interventions would actually work are rather limited - indeed, I am not aware of any strategies that have actually shown sustainable population-level reductions in 1 percentage point in obesity prevalence.

So even if policy makers did make this money available for addressing childhood obesity, it is not readily apparent on what specific interventions (population-wide or targeted) this money would actually be best spent to achieve this result.

In my patients, I always worry about balancing the potential risk of doing nothing against the potential risk of doing the wrong thing.

At a population level such risk-benefit analyses are even more daunting. As with all complex problems, wrong policy decisions (no matter how well-intended), that result in ‘unintended consequences’ (e.g. increasing weight-bias, reinforcing obesity stereotypes, promoting unhealthy weight-obsessions or dieting behaviours, etc.), could potentially harm far more people than they help.

All cost discussions aside, perhaps improving the health of the population by making it easier for all kids and adults to eat healthier, increase their physical fitness, and feel good about themselves (no matter what their weight), may not only reap greater health benefits but also turn out to be far more affordable and feasible than focusing too narrowly on simply reducing obesity percentage points.

Let us save the obesity treatments for the folks, who really need them.

AMS
Toronto, Ontario

Ma S, & Frick KD (2011). A simulation of affordability and effectiveness of childhood obesity interventions. Academic pediatrics, 11 (4), 342-50 PMID: 21764018