Metabolically Active Fat
Recent evidence suggests that brown adipose tissue (BAT) exists into adult hood and can, when present account for as much as 20% of daily resting energy expenditure. While the exact contribution of BAT (or lack thereof) to obesity remains to be determined, the presence and inducibility of BAT by cold exposure is inversely related to BMI, appears higher in women, and diminishes with aging. Given the role of cold exposure in the expression of BAT, it can be speculated that an increase in ambient temperature may promote weight gain by significantly reducing BAT and, thus, metabolic rate in some individuals. In rodents, increased production of neuropeptide Y in the hypothalamus can not only increase food intake but also reduce energy expenditure via a reduction in non‐shivering thermogenesis in BAT and facilitate triglyceride deposition through increased insulin levels.
A wide range of medications can affect metabolic rate. Notably, the use of beta‐blockers has been shown to significantly reduce thermogenesis, resulting in clinically relevant weight gain 34. Metabolic rates can also be reduced by the discontinuation of drugs that promote thermogenesis such as beta‐adrenergic agents, stimulants (including performance‐enhancing and illicit drugs like crack/cocaine), coffee or nicotine, resulting in weight gain.\
Finally, weight loss can markedly reduce energy requirements with a 5–10% reduction in body weight reducing resting metabolic rate by as much as 20% in some individuals, thereby substantially increasing the susceptibility to weight regain in the post‐obese state.
Commentary: In summary, any of the many factors that can reduce metabolic rate, can result in weight gain even with no change in energy intake or energy expenditure. In a clinical setting, this would apply to the patient, who tells you that they have not changed their food intake or their activity levels and, yet, have gained weight. Rather than simply discarding this information from a patient as being untrue or “delusional”, clinicians should give careful consideration to the factor that there very well may be factors that have led to a significant reduction in metabolic requirements.
The importance of fat-free mass as the key determinant of resting metabolic rate, even in a very obese individual [sic], cannot be over emphasized. Obese individuals [sic] can present with wide variations in lean body mass, almost entirely accounted for by differences in skeletal muscle mass. Thus, any change in muscle mass can markedly affect basal energy requirements. In this context it is important to remember that in ambulatory individuals, the mass of weight‐bearing muscles is directly proportional to BMI, as heavier individuals require a greater skeletal muscle mass to support and move their excess weight. This alone accounts for much of the higher basal and activity‐related energy requirements of larger individuals.
Although inactivity may be the most common cause of decreased skeletal muscle mass and reduced basal metabolic needs in obese individuals [sic], it is important to consider other causes of muscular atrophy that can likewise markedly reduce energy demands. A wide range of nutritional, neuromuscular, endocrine, renal, cardiac, pulmonary, inflammatory, infectious or neoplastic conditions can result in muscular wasting and sarcopenia. Reduced skeletal muscle mass and weight gain is also noted after many cancer treatments, although the mechanisms remain unclear. Any reduction in skeletal muscle mass not accounted for by a decrease in physical activity and ambulation should prompt investigations for other causes of muscular wasting.
Commentary: Sarcopenic obesity is perhaps even more prevalent than most people may think – especially in people who have slight overweight or even moderate obesity. It is particularly common in certain ethnic groups such as South Asians, even at “normal” BMIs. Clinically, this is where body composition studies can be helpful. Although a reduction in muscle mass does reduce resting metabolic rate (RMR), it is important to remember that overall skeletal muscle only accounts for about 15% of RMR. This is why, the notion that building up muscle mass will help with weight loss by burning more calories is not really an effective weight loss strategy.
Across the entire age continuum, a wide range of neuroendocrine factors can not only affect metabolic rate, but also substrate partitioning and utilization, which may directly or indirectly contribute to weight gain. The latter point is of particular significance as low rates of fat oxidation are associated with an increased risk of weight gain.
A wide range of neuroendocrine hormones and biomarkers can affect energy metabolism; sympathetic nervous system activity and thyroid function are two major factors directly influencing resting energy expenditure.
Sympathetic nervous activity is also a major determinant of post‐prandial thermogenesis and the thermogenic response to a glucose load has been shown to be significantly lower in obese [sic] individuals, a finding that persists even with substantial weight loss.
Specific examples of endocrine hormones that affect energy metabolism and substrate partitioning include cortisol, growth hormone (GH) and testosterone.
Catabolism associated with hypercortisolism or Cushing’s syndrome can reduce energy requirements and increase the deposition of truncal fat.
Discontinuation of GH treatment at the end of childhood growth in individuals with GH deficiency markedly increases fat mass and decreases metabolic rate, whereas GH treatment in GH‐deficient adults has beneficial effects on protein metabolism, energy expenditure and thyroid metabolism.
Testosterone deficiency can also result in abnormal energy partitioning, which adversely alters anabolism and reduces metabolic rate.
It is important to note that a careful history and physical examination should precede any endocrine testing for these disorders, as testing should be reserved for patients with an above‐normal pretest probability for one of these conditions.
Commentary: as pointed out in the last paragraph, while all of the above are important considerations, each one is quite rare, which is why it is important to use clinical judgement in recognising these factors, rather than simply ordering a battery of endocrine tests on every patient.
Because heritable factors appear to be responsible for 45–75% of the inter‐individual variation in body mass index (BMI), the potential impact of genetic determinants of metabolic rate upon the predisposition to obesity must be considered. While numerous somatic and mitochondrial genes with potential effects on metabolic rate have been identified, their contribution to human obesity has yet to be defined Likewise, although there is preliminary evidence for intrauterine and perinatal programming of genes involved in energy metabolism, their role in human obesity remain unclear. What is apparent is that the genetic predisposition to obesity (including both energy intake and metabolism) is not explainable on the basis of a small number of common mutations exerting substantial effects on the individual tendency to weight gain. Thus, a great deal of work is still required before investigation into the multitude of genetic determinants of body weight can potentially impact clinical management. Currently, a careful clinical assessment of family history of obesity and related risk factors remains the best measure of genetic risk for obesity.
There is a clear effect of gender [sic] on metabolic requirements, whereby, for the same BMI, women consistently display lower metabolic rates (approximately 20% less) than men, largely accounted for by differences in fat‐free mass (FFM).
Aging is an important determinant of a decline in metabolic rate, with an estimated reduction of around 150 kcal per decade of adult life. Factors that result in the age‐related decline in energy requirements include changes in neuroendocrine factors (e.g. sympathetic activity, thyroid function, etc.) as well as a reduction in skeletal muscle quantity and quality (resulting from reduced physical activity, reduced protein intake and other less‐well‐understood factors).
Additional factors that can affect metabolic rate will be discussed in subsequent posts.
Any assessment of obesity should begin with an estimate of energy requirement – specifically recognizing that any decrease in metabolic rate, without a corresponding decrease in energy intake and/or increase in activity will result in weight gain. Thus, in anyone presenting with weight gain, without any notable change in energy intake or activity levels, it is safe to assume that the only explanation can be a reduction in energy metabolism.
As a rule of thumb: the lower the total energy requirements, the greater the risk of obesity (simply stated: over‐eating is less likely for someone who needs 4000 kcal d−1 than for someone who needs 1500 kcal d−1). In sedentary individuals, resting metabolic rate is responsible for dissipating the vast majority of daily ingested calories (60–75%) and is therefore a key determinant of energy expenditure. Thus, even a small, sustained percentage reduction in resting metabolic rate, without a compensatory adjustment of energy intake or activity, can account for a large cumulative caloric excess over time (e.g. an unbalanced 3% reduction in resting metabolic rate in an individual with a total energy expenditure of 1800 calories can lead to a caloric excess of 32.4 kcal d−1, which can translate into 972 kcal excess per month).
Numerous factors can determine and/or affect metabolic rate. These include genetic and epigenetic factors, gender, aging, neuroendocrine function, sarcopenia, metabolically active fat, certain medications and prior weight loss.
Commentary: of course the numeric relationship between caloric intake and weight gain is not as straightforward as many people may think. This is because changes in caloric balance will in turn change caloric expenditure – remember, we are dealing here with physiology, not physics! Thus, a 20 kcal daily excess will only lead to weight gain until the higher body weight uses up the extra 20 kcal to maintain itself, at which point the 20 kcal are no longer in excess of demands and a new caloric balance is found (weight-gain plateau – the reverse happens with caloric restriction). Thus, to continue gaining weight, one has to continue increasing caloric intake to ensure that they stay above actual requirements. This self-limiting nature on the effect of a change in caloric intake (increase or decrease) on weight gain is often forgotten when people make simplistic assumptions that small increases in caloric intake have large effects on body weight over time – they don’t! Nevertheless, the lower your caloric requirements, the greater your risk of eating too many calories.
In the same manner in which a complete understanding of oedema requires the assessment of the complex physiological systems affecting fluid and sodium homeostasis, understanding obesity requires a comprehensive appreciation of the multitude of factors affecting energy intake and expenditure. Energy expenditure can be further subdivided into non‐activity (= resting metabolic rate + dietary‐induced thermogenesis) and activity thermogenesis (= non‐exercise + exercise activity thermogenesis). For simplicity’s sake, these three elements can be termed diet, metabolism and activity. A change in any one of these elements, if not balanced by corrective changes in the others, will result in a net change in energy balance, which, if positive, will result in caloric ‘retention’ and weight gain.
In subsequent posts, I will discuss the many factors that can affect energy metabolism, food intake, and physical activity and how changes to each (if not balance by corrective changes in the others) can lead to weight gain and often pose barriers to obesity management.
Several years ago, my colleague Raj Padwal and I published a paper in Obesity Reviews, where we outline a rational approach to an aetiological assessment of obesity.
As many readers may not have seen this paper, I will repost several of the key elements we discussed in it. Although some of our thinking has evolved since then, I believe the overall reasoning remain as relevant today, as when we first wrote the paper back in 2010:
Obesity is characterized by the accumulation of excess body fat and can be conceptualized as the physical manifestation of chronic energy excess. Using the analogy of oedema, which is the consequence of positive fluid balance or fluid retention, obesity can be seen as the consequence of positive energy balance or caloric retention. Just as the positive fluid balance of oedema can result from a host of underlying aetiologies including cardiac, hepatic, renal, endocrine, infectious, venous, lymphatic or drug‐related causes, obesity can result from a wide range of aetiologies that promote positive energy balance.
As with oedema, assessment and management of obesity requires an exploration of the root causes and underlying pathologies. To extend the obesity–oedema analogy, addressing all forms of obesity simply with caloric restriction and exercise (‘eat less and move more’) would be akin to addressing all forms of oedema simply with fluid restriction and diuretics. As this narrowly focused approach is not considered standard‐of‐care in managing patients with oedema, why should it be considered as the preferred method of treating obesity?
The classical treatment of obesity, based on increased physical activity and decreased calorie intake, has not been successful. Approximately two‐thirds of the people who lose weight will regain it within 1 year, and almost all of them within 5 years. In our opinion, the lack of efficiency in these therapeutic approaches is likely due to an incomplete understanding of the precise aetiology or aetiologies of obesity and, consequently a failure to address the root causes of energy imbalance.
In this paper, we present a theoretical diagnostic paradigm that provides an aetiological framework for the systematic assessment of obesity and discuss how this framework can enhance our ability to diagnose and manage obesity in clinical practice. The framework considers socio‐cultural, physiological, biomedical, psychological and iatrogenic factors that can determine energy input, metabolism and expenditure.
Comment: In hindsight, I would note that apart from failure to address the underlying pathology and drivers of weight gain, the “failure’ of conventional “eat-less – move-more” approaches to obesity management, relying largely on willpower, primarily fail because these efforts are counteracted by powerful neuroendocrine factors that both defend against continuing weight loss and promote weight regain. At the time we wrote this paper, we had perhaps not given the powerful nature of these effects full consideration. Nevertheless, I still believe that trying to understand exactly why a given person has gained excess weight is a good start to any obesity management endeavour.
More to follow…
There is no doubt that some people gain weight when started on anti-depressant medications. However, it is also true that the increased appetite and listlessness that accompanies “atypical” depression can contribute to weight gain. Finally, there is evidence that weight-gain in turn may decrease mood, which in turn may further exacerbate weight gain.
Trying to cut through all of this is a study by Rafael Gafoor and colleagues from King’s College London, in a paper published in BMJ.
They examined data from the UK Clinical Practice Research Datalink, 2004-14, which included data on 136,762 men and 157,957 women with three or more records for body mass index (BMI).
In the year of study entry, 17,803 (13.0%) men and 35,307 (22.4%) women with a mean age of 51.5 years were prescribed anti-depressants.
While during 1, 836,452 person years of follow-up, the incidence of new episodes of ≥5 weight gain in participants not prescribed anti-depressants was 8.1 per 100 person years, it was slightly higher at 11.2 per 100 person years in those prescribed an anti-depressant.
In the second year of treatment the number of participants treated with antidepressants for one year for one additional episode of ≥5% weight gain was 27.
Thus, there appears to be a slight but discernible increased risk of weight gain associated with the prescription of anti-depressants, which may persist over time and appears highest during the second and third year of treatment.
However, as the authors caution, these associations may not be causal, and residual confounding might contribute to overestimation of associations.
Nevertheless, the notion that there may be a distinct weight-promoting pharmacological effect of some anti-depressants is supported by the finding that certain anti-depressants (e.g. mirtazapine) carry a far greater risk of weight gain than others (e.g. paroxetine).
Given the frequency with which anti-depressants are prescribed, it could be argued that the contribution of anti-depressants to the overall obesity epidemic (particularly in adults) may be greater than previously appreciated.
If nothing else, patients prescribed anti-depressants should be carefully monitored for weight gain and preventive measures may need to be instituted early if weight gain becomes noticeable.