Healthy obesity

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This editable Main Article is under development and subject to a disclaimer.

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## Contents

* 1 What is Healthy Obesity?
* 2 The Cause of Healthy Obesity?
* 3 Does Healthy Obesity need to be treated?
* 4 The evidence base for the healthy obesity phenotype
* 5 References

## What is Healthy Obesity?[edit]

Although obesity is a major risk factor for cardiovascular disease and type 2 diabetes mellitus, about a third of obese individuals maintain healthy cardiometabolic profiles; this phenotype of healthy obesity may be linked to the location of adipose tissue and the metabolic characteristics of the fat. Some data also suggest that weight loss by healthy obese subjects may have an adverse impact on their favorable cardiometabolic profile. [1] [2]

Despite excess adipose tissue, this subset of obese individuals appears to be protected from the obesity-related abnormalities that promote insulin resistance, atherosclerosis and Type 2 Diabetes Mellitus. This phenotype is termed ‘Metabolically Healthy but Obese’ (MHO)[3]. There has been great difficulty in adequately standardising MHO identification in both research and clinical settings [4]. Presently, there is no definitive consensus as to the characterisation of the MHO phenotype. Figure 1 is a summary of the current understanding of the features associated with the MHO phenotype. It is important to note this figure does not state the respective ranges of concentrations that distinguish MHO from obese individuals; this is due to the fact that exact numerical parameters have not yet been determined e.g. plasma concentrations of ferritin in MHO compared with obese [4].

Figure 1. Comparison of Healthy, Normal Weight with Obese and Obese but Metabolically Healthy (MHO) Phenotypes [2][5][4][6].

Healthy, Normal Weight Phenotype  | Obese Phenotype  | Obese but Metabolically Healthy (MHO) Phenotype

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• BMI <25

• High insulin sensitivity

• Favourable cardiovascular profile

• Normal inflammation, hormonal and immune profiles

• No hypertension

• Plasma Triglyceride levels Less than 150 mg/dL

• Healthy Apolipoprotein B levels

• Fasting insulin levels suggestive of high insulin sensitivity

• Healthy ferritin levels

• Triglyceride/ HDL ratio of 2 or less

• BMI >30

• Increased insulin resistance

• Inflammatory and cardiovascular profiles associated with Type 2 Diabetes Mellitus and cardiovascular disease

• Altered immune profiles

• Often altered hormonal profiles

• Often hypertension

• Plasma triglyceride levels 200 - 499 mg/dL or above

• Adiponectin levels lower than MHO phenotype

• Apolipoprotein B levels higher than MHO

• Ferritin levels higher than MHO

• Increased fasting insulin levels, suggestive of insulin resistance

• Triglyceride/ HDL ratio of 4+

• BMI >30

• High insulin sensitivity

• Inflammation, hormonal and immune profiles similar to that of healthy normal weight phenotype

• No hypertension

• Plasma triglyceride levels lower than obese phenotype

• Adiponectin levels higher than obese phenotype

• Apolipoprotein B levels lower than obese phenotype

• Lower ferritin levels than obese phenotype

• Fasting insulin levels suggestive of insulin sensitivity

• Triglyceride/ HDL ratio of lower than obese phenotype

• Compared to obese: lower risk of atherosclerosis due to decreased carotid IMT levels

Identification of an MHO Individual

In both clinical and research environments, quick, efficient and non-invasive methods of MHO individual identification are highly important but, as of yet, such a methods remain elusive.

Although a reasonable determinant between obese and normal weight individuals, waist size has been proven an ineffective MHO distinguishing feature, since both MHO and obese phenotypes have similar waist sizes [1]. Stefan et al. found MHO individuals had lower amounts of ectopic fat around the liver and muscle tissue compared to those who are unhealthily obese, suggesting this could be utilised as a distinguishing feature between these two phenotypes [7] Unfortunately, these findings were not concurrent with further studies and therefore may not be an accurate determinant across all obese populations [2]. Higher plasma triglyceride levels, a higher triglyceride/HDL ratio, along with increased Apolipoprotein B and ferritin levels have all been associated with the unhealthy obese phenotype, but not with MHO. Consequently, measurements of these features have been proposed by Messier et al. as techniques to distinguish MHO from obese, and appear promising throughout this study. However, by the author’s own admission, further investigation must be conducted to determine standardised quantitative values for this molecules by which obese and MHO can be accurately distinguished [4].

Liam Jon Carr 00:14, 10 November 2011 (UTC)

## The Cause of Healthy Obesity?[edit]

Proposed Mechanistic Determinants of the Healthy Obese Phenotype

Adipose tissue is an endocrine organ, releasing several inflammatory cytokines and expressing endocrine hormone receptors. The location of adipose tissue, the histological characteristics of adipose tissue and its metabolic activity may be more relevant than its total mass with regards to the healthy obese phenotype, and they may play a role in determining the cardiometabolic health of obese individuals [2].

Adiponectin and Healthy Obesity

Adiponectin is a protein hormone which is secreted into the bloodstream from adipose tissue and modulates several metabolic processes, including fatty acid catabolism and glucose regulation. The level of adiponectin in the bloodstream is inversely correlated to the percentage of body fat in adults. It is associated with the suppression of metabolic processes that can lead to obesity, type 2 diabetes mellitus and non-alcoholic fatty liver disease (NAFLD). Diabetics tend to have reduced levels of the hormone and levels of adiponectin are significantly increased with weight loss. Other metabolic effects of adiponectin are: decreased gluconeogenesis and increased glucose uptake; lipid catabolism; protection from endothelial dysfunction; insulin sensitivity, and control of energy metabolism. Hypoadiponectinaemia, therefore, is an independent risk factor for metabolic syndrome and type 2 diabetes mellitus– two conditions associated with an unhealthy metabolic profile of obese individuals.

There is an inverse relationship between body mass index (BMI) and concentrations of adiponectin in both humans and animals. However, in ob/ob mice - mutant mice that eat excessively and become obese - overexpression of adiponectin in adipose tissue increased plasma adiponectin concentrations, keeping them in a physiological range. This increase resulted in significant weight gain and reduced hyperglycaemia and amended metabolic abnormalities. These findings suggest a role of variable plasma adiponectin concentrations in the pathophysiology of the healthy obese phenotype. Data from one recent study shows that lack of suppression of adiponectin concentrations is independently associated with the metabolically healthy profile of certain obese individuals [8].

One study found that 20% of individuals with a BMI greater than 40kg/m2 had adiponectin concentrations on average higher than those of subjects with a normal BMI. Obese women and men with adiponectin concentrations >12.49mg/l and >8.07mg/l respectively, were more likely to be metabolically healthy. These results were proven to be significant in a logistic regression model after controlling the effect of insulin, age, and waist circumference. Thus, some obese individuals have plasma adiponectin concentrations similar to those of normal BMI subjects, and this may contribute to the metabolically healthy obese phenotype [8].

Location of Adipose Tissue

Both central adiposity and ectopic fat (fat found in lean tissue) are thought to be associated with the role of fat location in healthy obesity. Some studies have found that healthy obese individuals have smaller waist circumferences or lower levels of abdominal visceral fat (VAT) than metabolically unhealthy individuals. This is not surprising as central visceral fat is drained into the portal circulation and contributes to insulin resistance and dyslipidaemia, two factors associated with cardiovascular risk and metabolic disturbances [2]. However, other studies produced data suggesting otherwise, and found that there were no differences in central obesity between healthy and at-risk obese individuals.

High levels of subcutaneous adipose tissue (SAT) have been found in some studies to be protective against atherosclerosis, independent of levels of VAT, suggesting a role for SAT in the healthy obese phenotype. However, other studies have found that high levels of SAT and VAT contribute to elevated CVD risk factors, and no differences in SAT levels were found between healthy and at-risk obese individuals. This could be due to the suggested modifying effects of VAT on SAT's effects on metabolic profile; high levels on SAT contribute to development of the metbolic syndrome when paired with loe VAT levels, but seem to be protective when paired with high levels of VAT [2].

Victoria Catherine Pickard 19:57, 31 October 2011 (UTC)

## Does Healthy Obesity need to be treated?[edit]

Having been characterised as ‘Healthily Obese’ using the above criteria, what treatment strategy, if any, should be used? The widely accepted intervention for all obese people is weight loss (National Institutes of Health, 1998), however is this an appropriate and efficacious option for this minority phenotype of the obese population? If so, what impact would this have in their health in general, but more specifically on their cardio-metabolic risk factors?

Evidence for interventions

A variety of studies have been carried out to ascertain whether Metabolically Healthy Obese (MHO) subjects gain any benefit from weight loss. There are three principle strategies for reducing body mass: increasing exercise levels, hypoenergetic diets and surgery (e.g. Laproscopic Adjustable Gastric Banding [LAGB]). Studies have been carried out recently to see the impact of these methods on the MHO. In a 2008 study (Karelis et al, 2008), when participants were put on an energy-restricted diet for a 6 month period (with physical activity levels limited), both the MHO and at-risk groups showed a significant increase in insulin sensitivity, prompting the paper to call for a ‘one size fits all’ approach to obesity intervention. It has been shown that the use of an energy-restricted diet causes a significant increase in insulin sensitivity in MHO subjects, whilst the same study also highlighted signs of sub-clinical vascular disease, which if left untreated could lead to consequences in later life (Janiszewski et al, 2010). An interesting recent study (Sesti et al, 2011) into the impact of gastric banding and a hypocaloric diet on both MHO and at risk obese populations concluded that some significant factors were higher in the at risk group, such as, waist circumference, 2hr OGTT and insulin levels. There was no difference in other significant measurements such as total and HDL cholesterol.

Evidence against interventions

However other recent published literature contradicts some of this evidence. When lifestyle was modified by varying the level of exercise programme the participants were submitted to, there was no significant difference in insulin sensitivity or any other major markers. There was no improvement in cardio-vascular risk profile in the MHO group (Kantartzis et al, 2011). Other studies back up these findings, showing that there is at best a moderate increase in insulin sensitivity with a hypocaloric diet. There is increasing evidence that the method by which weight is lost may be crucial to the outcome for the patient. Weight loss by diet modification and surgery has been proven to be overall beneficial, whilst the use of a exercise programmes has shown less efficacy (Perseghin, 2008). Healthy obesity treatment is a targeted area of current research, with larger trials necessary to improve reliability and distinguish the true impact of various strategies on the patient.

The healthy obese phenotype makes up a reputed 30% of all obese people (McLaughlin et al, 2007). Since an estimated 9% of the NHS annual budget is spent on treating obesity and its effects, whether or not an intervention is necessary for this subset of high adiposity individuals is a pressing issue. Surely for such a proven heterogeneous obese population, the current ‘one size fits all’ approach cannot be the most economical and patient-centred option.

Keith Charles Allen 15:09, 3 November 2011 (UTC)

## The evidence base for the healthy obesity phenotype[edit]

The mainstream literature on obesity focuses on its negative consequences on mortality. This may be due to a landmark meta-analysis published in the New England Journal of Medicine (NEJM) in 1999 which assessed the risk of mortality compared with BMI in over 1 million Americans.[10] It concluded that the risk of death from all causes (including cardiovascular disease and cancer) increased throughout the moderate and severe overweight and obese categories. It may be argued that a weakness of the study is that it used BMI to classify obesity but despite its relative simplicity, BMI has been shown to be a good indicator of overall adiposity, rather than being confounded by other weight factors such as high muscle mass. A recent systematic review by Okorodudu et al.(2010)[12] investigated the diagnostic utility of BMI in identifying obesity due to adiposity and found that there was a strong correlation, particularly between adiposity and high BMI values.

However, other methodological flaws may account for the failure to detect a healthily obese phenotype in the NEJM study. While the study controlled for factors such as age, race, smoking status, and disease history, it made only slight adjustments for fitness. This comprised of only one question, asking for self-reported levels of physical activity in the categories none, slight, moderate or heavy. Fitness has appears to be an important factor, as shown by a study by Johnson et al. (2008)[9] which assessed all-cause mortality and found that in subjects with high BMI and high exercise capacity there was an inverse relationship to mortality. This suggests that overweight and obese individuals with a high level of fitness are in fact healthy. The NEJM meta-analysis has been cited over 2000 times, while by contrast two analyses also published in 1999 which investigated fitness levels and mortality in the obese have been cited only 835 times combined.[11][13] This may represent a Semmelweis reflex present in the scientific literature which results in an under appreciation of the evidence base for the healthy obesity phenotype. Tijmen van Slageren 01:30, 15 November 2011 (UTC)

## References[edit]

1. ↑ 1.0 1.1 Lee CM et al. (2008) Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: a meta-analysis J Clin Epidemiol 61:646-53 PMID 18359190
2. ↑ 2.0 2.1 2.2 2.3 2.4 2.5 Wildman RP (2009) Healthy obesity Curr Opin Clin Nutr Metab Care 12:438-43 PMID 19474713
3. ↑ Marini M.A. et al. (2007) Metabolically Healthy but Obese Women Have an Intermediate Cardiovascular Risk Factor Profile Between Healhty Nonobese Women and Obese Insulin-Resistant Women. Diabetes Care 30(8). 2145-2147 PMID 17507694
4. ↑ 4.0 4.1 4.2 4.3 Messier V et al. (2010) Identifying Metabolically Healthy but Obese Individuals in Sedentary Postmenopausal Women Obesity 18 5, 911–917. doi:10.1038/oby.2009.364. PMID 19851302
5. ↑ Gaziano MJ et al. (1997) Fasting Triglycerides, High-Density Lipoprotein, and Risk of Myocardial Infarction Circulation Circulation. 1997;96:2520-2525 doi: 10.1161/01.CIR.96.8.2520. PMID 9355888
6. ↑ National Cholesterol Education Program (NCEP)(2001). Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA. 2001;285(19):2486-2497.PMID 12485966
7. ↑ Stefan, N et al. (2008). Identification and Characterization of Metabolically Benign Obesity in Humans. Archives of Internal Medicine 168(15). 1609-1616. PMID 18695074
8. ↑ 8.0 8.1 (Aguillar-Salinas et al. 2008)