The Blind Men and an Elephant: The Real Solution to the Obesity Epidemic


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Note from Armi: This is a guest article from my friends Jeff Thiboutot and Matt Schoeneberger, who run the website They are two of the most evidence-based weight loss experts I know, and they were kind enough to let me share this article of theirs with you.

The numbers are not good.

The percentage of people who are obese (a BMI of 30 or greater) has steadily increased for a few decades. Additionally, it’s becoming even harder for these people to then lose, and maintain their weight.

Most weight loss programs do not produce long-term results (Bray et al; Douketis et al). We feel this is due to most weight loss recommendations being overly simplistic and not addressing the many contributing factors.

In this article, we will not be laying out a bunch of specific things to do, such as eat this food, avoid that food, do this exercise, eat every X hours, blah, blah, blah.

Rather, we are highlighting a meta-concept to weight management. Weight management is a complex phenomenon (Bray et al; Friedman; Palou et al; Woods et al; Yang et al) influenced by three interconnected factors, (1) biological, (2) psychological, and (3) sociological, referred to as the Bio-Psycho-Social (BPS) Model (Borrell-Carrio et al; Kaplan).

We feel the solution to this problem is a comprehensive approach that addresses the many aspects that impact body weight regulation. The following diagrams help highlight the overarching concept before discussing a few details.

How to Lose Weight Figure 1


Schematic diagram showing the major factors determining neural control of appetite and regulation of energy balance
 The brain monitors the internal milieu through a number of hormonal- and neural nutrient-sensing mechanisms and is under constant influence of the environment and lifestyle through the senses and mainly the cognitive and emotional brain. The two streams of information are integrated to generate adaptive behavioral (food intake) and autonomic/endocrine responses determining nutrient partitioning, energy expenditure, and overall energy balance. Any of the peripheral and central signaling steps are subject to individual predisposition through either genetic, epigenetic, or non-genetic early life imprinting mechanisms. (p.76; From Zheng, H & Berthoud, H.N. (2008). Neural Systems Controlling the Drive to Eat: Mind Versus Metabolism. Physiology 23: 75-83.)


From; Michie, S. et al (2011). The behavior change wheel: A new method for characterizing and designing behavior change interventions. Implementation Science; 6:42.

Retrieved from


Humans have innate drives for sloth and gluttony (Laham; Heshmat), meaning that we are hardwired to find ways to move less and eat more. However, this does not mean that we can’t override these tendencies.

Only about 40% of the population is able to maintain a healthy weight[1], so clearly a lot of people can find a way to balance their energy intake and expenditure. Of course, that means about 60% of the population is struggling with balancing how many calories they eat with how many they burn. Why do so many people struggle with their weight?

As depicted in the diagrams above, there are many contributing factors that determine what we eat, how much we eat, and how much we move. Eating and physical activity arecomplex behaviors.

Eating behavior, in particular, is difficult to manage, because we haveto eat in order to live, unlike most other behaviors, including exercise. Therefore, balancing the needs of the body with the many biological and non-biological drives to consume food is no easy task.

The evidence is clear that for many people, maintaining a healthy weight is very challenging,. This is true with many other important behaviors that contribute to our ability to stay healthy, like being consistent with exercise, not smoking, and sleeping enough. But because something is hard to do does not mean it should not be pursued, particularly when the rewards of such efforts are likely to outweigh the risks, costs, and effort. Which leads to the point of this piece; what should you do?

Because body weight regulation is clearly influenced by biological, psychological, and social (BPS) drives, interventions to prevent and reverse excess body fat stores must include all of these.

This concept is fairly common in the scientific literature (Anderson et al; Berthound et al; Bray et al; Cohen; Finegfood et al; Hafekost et al; Maclean et al; Skelton et al; Thompson et al; Ulijaszek et al). However, even though it is known that these aspects each play an important role, they are rarely studied in a comprehensive manner. Additionally, the BPS concept is often missing in the lay literature regarding weight management.

We contend this is the reason most weight loss programs don’t work in the long-term. We feel that the BPS concept is not more widely discussed in the lay literature because it is not simple or sexy.

It doesn’t lend itself well to short slogans and seemingly simple solutions. This does not mean that a BPS intervention will be excessively complex and unmanageable by many of the people struggling with their weight. Although there are many factors that contribute to body weight regulation there are often just a handful of evidence-based interventions that can address the majority of them.

The current trend seems to be an unnecessary and distracting focus on diet and exercise, particularly the trivial or specious aspects, resulting in a waste of time, effort, and money. To be clear, diet and exercise, in general, are very important, but our precious and limited resources of time, money, and effort are lost to trying to find thesupplement, thefood, thefood plan, theexercise or theexercise routine that will be thething that makes weight loss easy and sustainable. This is foolish, but not surprising as the weight loss industry’s job is to sell you theanswer.

There is NO single nutrient, food, exercise, behavioral technique, and so on, that can circumvent the multiple biological, psychological, and social drives, such as the following… 

Ghrelin, leptin, inflammation, protein, palatability, liquid calories, stress, hyperbolic discounting, autonomy, relatedness, serving size, non-starchy vegetables, sleep, situational cues, priming, social norming, social network, exercise, NEAT, fiber, habits, microbiome, public policies, taxes, food costs, availability, pre-frontal cortex, limbic system, CCK, insulin, glucagon, willpower, personality, education, socioeconomic status, intrauterine environment, pollutant exposure, liquid fats, delay of gratification, dopamine, serotonin, medications, knowledge, calories, coping skills, variety of foods, marketing, emotions, impulsivity, volume, for example (Anderson et al; Berthound et al; Bray et al; Cohen; Finegfood et al; Hafekost et al; Heshmat; Keith et al; Maclean et al; Palou et al;  Ramon et al; Skelton et al; Thompson et al; Ulijaszek et al).

… that cause us to eat more and move less. We need a comprehensive approach to produce lasting change for most people struggling with their weight. A framework for such an approach will be outlined in future articles.

Jeff and Matt are currently working on a new project they are very excited about: Please go to the site to learn more about whom they are and what they are doing.

### References

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Berthoud, HR. & Morrison, C. (2008). The brain, appetite, and obesity. Annu Rev Psychol; 59: 55-92.

Borrell-Carrió et al. The biopsychosocial model 25 years later: principles, practice, and scientific inquiry. Annals Family Med 2004; 2(6): 576-582.

Bray, G. & Champagne, C. Beyond energy balance: There is more to obesity than kilocalories. J  American Dietetic Association 2005; 105: S17-S23.

Cohen, D. (2008). Neurophysiological pathways to obesity: Below awareness and beyond individual control. Diabetes; 57: 1768-1773.

Douketis, JD et al. Systematic review of long-term weight loss studies in obese adults: clinical significance and applicability to clinical practice. Inter J Obesity 2005; 29: 1153-1167.

Flegal, K. et al (2013). Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis.JAMA; 309(1):71-82

Finegood, D. et al (2010). Implications of the Foresight Obesity System Map for solutions to childhood obesity. Obesity; 18(1): S13-S16.

Friedman, J. Modern science versus the stigma of obesity. Nature Med 2004; 10(6): 563-569.

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Hafekost, K. et al (2013). Tackling overweight and obesity: does the public health message match the science? BMC Medicine; 11:41.

Heshmat, S. (2011). Eating behavior and obesity: Behavioral economics strategies for health professionals. Springer. New York.

Janssen, I. (2007). Morbidity and Mortality Risk Associated With an Overweight BMI in Older Men and Women. Obesity; 15(7): 1827-1840.

Kaplan, D. The next advancement in counseling: The bio-psycho-social model. (n.d.); Retrieved March 15, 2014; from

Keith, SW. et al. Putative contributors to the secular increase in obesity: exploring the roads less traveled. Inter J Obesity 2006; 30: 1585-1594.

Laham, S. (2012). The science of sin. The psychology of the seven deadlies (and why they are so good for you). Three Rivers Press. New York.

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Michie, S. et al (2011). The behavior change wheel: A new method for characterizing and designing behavior change interventions. Implementation Science; 6:42.

Orpana, H. et al (2010). BMI and mortality: results from a national longitudinal study of Canadian adults. Obesity; 18(1):214-8

Palou, A. et al. Obesity: molecular bases of a multifactorial problem. Eur J Nutrition 2000; 39: 127-144.

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Raman, J. et al (2013). The clinical obesity maintenance model: An integration of psychological constructs including mood, emotional regulation, disordered overeating, habitual cluster behaviors, health literacy and cognitive function. J Obesity; 240128.

Skelton, J. et al (2006). Obesity and its therapy: From genes to community action. Pediatr Clin North Am; 53(4): 777-794.

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Thompson, W. et al (2007). Treatment of obesity. Mayo Clin Proc; 82(1): 93-102

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Woods, SC. & Seeley, RJ. Understanding the physiology of obesity: review of recent developments in obesity research. Inter J Obesity 2002; 26 (Suppl 4): S8-S10.

Yang, W et al. Genetic epidemiology of obesity. Epidemiologic Reviews 2007; 29(1): 49-61.

[1] using the common guidelines of a BMI of 19 to 25, which is, in our opinion, a bit restrictive on the upper end when it comes to determining a healthy weight (Flegal et al; Janssen, I.; Orpana, H. et al)

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