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Adiposity-based Chronic Disease—Obesity Re-worked

US Endocrinology, 2016;12(2):102–4 DOI:


Obesity is a complex, chronic disease with a high prevalence rate that has been resistant to current preventive and therapeutic efforts. A new definition of obesity is proposed in the context of emerging information and the need for de-stigmatization. Adiposity-based chronic disease (ABCD) addresses the amount, distribution, and function of body fat. An ABCD model is best approached using structured lifestyle medicine and a focus on health promotion, rather than exclusively disease management. Future care models for ABCD will likely involve gene/genomic analyses and advanced body imaging technologies.
Keywords: Obesity, adiposity, chronic disease, insulin resistance, type 2 diabetes, lifestyle medicine, body imaging
Disclosure: Jeffrey I Mechanick has received honoraria for lectures and program development from Abbott Nutrition International. No funding was received for the publication of this article.
Compliance with Ethics Guidelines: This study involves a review of the literature and did not involve any studies with human or animal subjects performed by any of the authors.
Authorship: All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship of this manuscript, take responsibility for the integrity of the work as a whole, and have given final approval to the version to be published.
Open Access: This article is published under the Creative Commons Attribution Noncommercial License, which permits any noncommercial use, distribution, adaptation, and reproduction provided the original author(s) and source are given appropriate credit.
Received: September 27, 2016 Accepted: November 15, 2016
Correspondence: Jeffrey I Mechanick, 1192 Park Avenue, New York, NY 10128, US. E:

Obesity has been declared a chronic disease by many organizations, with multiple complex drivers and adverse biological sequelae, commonly regarded as complications (see Figure 1).1,2 For most clinicians and the informed public, overweight and obesity are defined exclusively by a body mass index (BMI; weight [kg]/height [m]2) ≥25 and 30, respectively. However, there are many flaws in this definition (see Table 1). The prevalence rate for obesity in the US remains essentially unchanged, with troublesome increases in certain population subsets, such as children, several ethnicities (particularly those in lower socio-economic strata), women over 60 years old, and more severe forms of obesity (for example, those with a BMI ≥35).3,4 However, with all the knowledge that has been learned, and advances in obesity research, education, and clinical practice, why is the problem, at least from an epidemiological standpoint, not really improving? One answer may be the need for greater governmental intervention (for example, behavioral economics and obesity-related legislation).5 But even this may be quite unrealistic. A better option for now may be to use a new term and approach. The word ‘obesity’ is antiquated, does not reflect the basic underlying pathophysiology, and carries a stigma that resists any conciliatory political correctness. On the other hand, ‘adiposity’ and ‘chronic disease’ are two medical concepts that, when joined together as ‘adiposity-based chronic disease’ (ABCD) transmit a clear message.1,6

What is adiposity and how does it lead to chronic disease?
There are many terms in the medical literature referring to body fat and related clinical conditions, but these terms generally lack specificity and detail. Though obesity is the most popular, others include ‘adiposopathy’, ‘fatness’, and ‘adiposity’. Adiposopathy refers to the premise that the key pathological mediators of abnormal body fat that lead to adiposity-based complications (particularly cardiometabolic) are secreted factors: hormones, cytokines, adipokines, etc.7 Fatness is a non-specific, generic term typically used to describe an increased amount of fat, but this term also confers stigma, as does any word with the root ‘fat’.8

Adiposity refers to body fat in general terms but includes, not only increased quantity and/or abnormal function, but also the impact of various distributions of fat (see Table 2).9 For instance, visceral (intra-abdominal) adipose tissue is associated with higher cardiometabolic risks than subcutaneous abdominal adipose tissue.9 Intracellular fat can also occur in bone marrow, perivascular, epi/pericardial, and subcutaneous gluteal/femoral adipose tissue, as well as ectopic lipids in non-adipose tissue, such as skeletal muscle, cardiac muscle, kidney, pancreas, and liver.10,11 In fact, it has been postulated that ectopic lipid deposition occurs when two necessary pre-conditions exist: first, over-nutrition and second, inability of eutopic adipose tissue to accommodate excess energy storage needs.12 It is further hypothesized that it is the ectopic lipid that principally contributes to cardiometabolic risk, or the metabolic syndrome (MetS), explaining in a somewhat simplistic fashion why many patients with obesity (but minimal ectopic fat) can be healthy (with no or minimal MetS

components).12 Additionally, in some ethnicities, it is the relatively low amounts of fat and muscle mass that contribute to cardiometabolic risk: Asian-Indians have a specific diabetes and obesity phenotype described by Mohan et al.13 that is associated with sarcopenia (low muscle mass and therefore relatively high fat-to-muscle mass even with normal adjusted BMI). Long regarded as a medical curiosity, ‘lipodystrophy’ (complete or partial loss or absence of adipose tissue) has found new relevance in the context of increased cardiometabolic risk.14 The decreased capacity of lipodystrophic adipose tissue stores can promote increased ectopic lipid stores.15 For the sake of clarity, adiposity and ABCD refer to intracellular fat molecules, whereas extracellular fat molecules are relevant in the context of dyslipidemias and lipid-based chronic disease.

Overall, a re-working of obesity into an ABCD model provides the granularity and robustness to better account for the human phenotype and expression of disease. Consequently, one can foresee a shift in the diagnostic work-up from conventional anthropometrics (BMI, waist circumference [WC], etc.) to advanced body imaging and molecular biology studies. High-resolution imaging can provide not only anatomic description of the disease process, but also information about function, such as inflammation and metabolism. Interestingly, Lee et al.16 demonstrated that adipose tissue volume and attenuation by computed tomography (CT) was associated with cardiovascular disease (CVD) risk, independent of anthropometrics (BMI and WC).

An accurate analysis of the adipocyte secretome, as well as secretory products in ectopic lipid, can provide important information to guide decision-making, including emergent properties from network analysis for research hypothesis generation. For example, a preliminary network analysis of an adipokine-cardiovascular-lifestyle network is presented by Mechanick et al.17

The second part of ABCD is chronic disease. This is defined as a pathophysiological state persisting for at least three months and characterized by adaptive and maladaptive processes that may or may not achieve a steady state, but nevertheless evolve and develop biological complexity.18 The implication is that, unlike relatively direct and expeditious treatments for acute or sub-acute illnesses that target

1. Garvey WT, Mechanick JI, Brett EM, et al., American Association of Clinical Endocrinologists and American College of Endocrinology comprehensive clinical practice guidelines for medical care of patients with obesity, Endocr Pract, 2016; 2(Suppl 3):1–205.
2. Mechanick JI, “What if” being overweight was good for you?, Endocr Pract, 2013;19:166–8.
3. Ogden CL, Carroll MD, Kit BK, Flegal KM, Prevalence of childhood and adult obesity in the United States, 2011-2012, JAMA, 2014;311:806–14.
4. Centers for Disease Control and Prevention. Adult obesity facts. Available at: (accessed September 25, 2016).
5. Trivedi NJ, Fields J, Mechanick CH, et al., Lack of correlation between antiobesity policy and obesity growth rates: review and analysis, Endocri Pract, 2012;18:737–44.
6. Garvey WT, Garber AJ, Mechanick JI, et al., American Association of Clinical Endocrinologists and American College of Endocrinology position statement on the 2014 advanced framework for a new diagnosis of obesity as a chronic disease, Endocr Pract, 2014;20:977–89.
7. Bays HE, Adiposopathy. Is “sick fat” a cardiovascular disease?, J Am Coll Cardiol, 2011;57:2461–73.
8. Previte J, Gurrieri L, Who is the biggest loser?, Fat news coverage is a barrier to healthy lifestyle promotion, Health Marketing Quarterly, 2015;32:330–49.
9. Neeland IJ, de Lemos JA, Time to retire the BMI?, J Am Coll Cardiol, 2016;68:1522–4.
10. Devlin M, Rosen CJ, The bone fat interface: basic and clinical implications of marrow adiposity, Lancet Diabetes Endocrinol, 2015;3:141–7.
11. Poirier P, Exploring the spectrum of diseases influenced by excess adiposity, Translat Res, 2014;164:278–83.
12. Grundy SM, Overnutrition, ectopic lipid and the metabolic syndrome, J Investig Med, 2016;64:1082–6.
13. Mohan V, Sandeep S, Deepa R, et al., Epidemiology of type 2 diabetes: Indian scenario, Indian J Med Res, 2007;125:217–30.
14. Handelsman Y, Bloomgarden ZT, Brown RJ, et al., The clinical to the detection of lipodystrophy – an AACE consensus statement, Endocr Pract, 2013;19:107–16.
15. Grundy SM, Adipose tissue and metabolic syndrome: too much, too little or neither, Eur J Clin Invest, 2015;45:1209–17.
16. Lee JJ, Pedley A, Hoffmann U, et al., Associations of changes in abdominal fat quantity and quality with incident cardiovascular disease risk factors, J Am Coll Cardiol, 2016; 68:1509–21.
17. Mechanick JI, Zhao S, Garvey WT, The adipokine-cardiovascularlifestyle network, J Am Coll Cardiol, 2016;68:1785–803.
18. Mechanick JI, Kushner RF, Why lifestyle medicine? In: Mechanick JI, Kushner RF (eds.). Lifestyle Medicine, Springer, New York, 2016, pp. 1–8.
19. James GD, Human evolution and chronic diseases: genes, Allostasis, and cut-points, Anthropol, 2014; 2: e123. doi:10.4172/2332-0915.1000e122.
20. Zhao S, Mechanick JI, Targeting foodome-metabolome interactions: a combined modeling approach. In: Mechanick JI, Via MA, Zhou S (eds.). Molecular Nutrition: The Practical Guide, Endocrine Press, Washington, DC, 2015, pp. 182–205.
21. Nordstrom P, Pedersen NL, Gustafson Y, et al., Risks of myocardial infarction, death, and diabetes in identical twin pairs with different body mass indexes, JAMA Intern Med, 2016. doi:10.1001/ jamainternmed.2016.4104.
22. Castellano JM, Penalvo JL, Bansilal S, et al., Promotion of cardiovascular health at three stages of life: never too soon, never too late, Rev Esp Cardiol, 2014;67:731–7.
23. Mechanick JI, Kushner RF, Appendix: lifestyle medicine checklist. In: Mechanick JI, Kushner RF (eds.), Lifestyle Medicine, Springer, New York, 2016, p. 357.
Keywords: Obesity, adiposity, chronic disease, insulin resistance, type 2 diabetes, lifestyle medicine, body imaging