Metabolic consequences of overfeeding in humans

Energy Expenditure in Upper Gastrointestinal Cancers: a Scoping Review

Malnutrition is prevalent in people with upper gastrointestinal (GI) cancers and is associated with shorter survival and poor quality of life. In order to effectively prevent or treat malnutrition, nutrition interventions must ensure appropriate energy provision to meet daily metabolic demands. In practice, the energy needs of people with cancer are frequently estimated from predictive equations which are not cancer-specific and are demonstrated to be inaccurate in this population. The purpose of this scoping review was to synthesize the existing evidence regarding energy expenditure in people with upper GI cancer. Three databases (Ovid MEDLINE, Embase via Ovid, CINAHL plus) were systematically searched to identify studies reporting on resting energy expenditure using indirect calorimetry and total energy expenditure using doubly labeled water (DLW) in adults with any stage of upper GI cancer at any point from diagnosis. A total of 57 original research studies involving 2,125 individuals with cancer of the esophagus, stomach, pancreas, biliary tract, or liver were eligible for inclusion. All studies used indirect calorimetry, and one study used DLW to measure energy expenditure, which was reported unadjusted in 42 studies, adjusted for body weight in 32 studies, and adjusted for fat-free mass in 13 studies. Energy expenditure in upper GI cancer was compared with noncancer controls in 19 studies and measured compared with predicted energy expenditure reported in 31 studies. There was heterogeneity in study design and in reporting of important clinical characteristics between studies. There was also substantial variation in energy expenditure between studies and within and between cancer types. Given this heterogeneity and known inaccuracies of predictive equations in patients with cancer, energy expenditure should be measured in practice wherever feasible. Additional research in cohorts defined by cancer type, stage, and treatment is needed to further characterize energy expenditure in upper GI cancer.

Impact of Gut Microbiota on the Risk of Cardiometabolic Diseases Development

Obesity is a multifactorial disease that leads to excessive adipose tissue accumulation, mainly visceral fat. Importance and prevalence of obesity has increased significantly in recent decades all over the world. Until now, the pandemic of obesity has been associated more to lifestyle changes: excessive eating and low physical activity. In recent years, special attention has been paid to studying of composition and functions of intestinal microbiota as major factor in development of obesity and related comorbidities, such as hypertension, cardiac ischemia, heart failure and others. It is proved that gut microbiota affects extraction, accumulation and consumption of energy derived from food, lipid metabolism and immune response. It is also revealed that composition of the microbiota is different in thin and obese people. Thus, study of the relationship between intestinal microbiota composition and risk factors for cardiovascular diseases, in particular obesity, is an actual task. The purpose of this review is analyzing of literature about assessment of relationship between composition and functions of intestinal microbiota in the diagnostics, prevention and treatment of obesity and cardiovascular diseases.

Effects of synbiotic supplement on body weight and fasting blood glucose levels in obesity: A randomized placebo-controlled trial

BACKGROUND

Obesity and diabetes are related. The role of gut microbiota disruption in obesity has been reported as a cause of several metabolic diseases including diabetes.

OBJECTIVES

Evaluate the effects of synbiotic supplementation (a combination of probiotic and prebiotic) on body weight (BW), Body Mass Index (BMI), and Fasting Blood Glucose (FBG) in obese subjects.

METHODS

This study was a randomized, double-blind placebo-controlled. Participants were allocated with randomization into 2 groups: the obese group with synbiotic supplementation and the obese group with placebo; each group consists of 8 participants. BW, BMI, and FBG level were measured at baseline, 8 weeks after supplementation, and 4 weeks after terminating the supplementation.

RESULTS

There were no significant change of body weight and BMI after 8 weeks synbiotics supplementation and 4 weeks after supplement discontinuation, but there were significant increases in body weight by 3.38 kg and BMI by 1.37 kg/m2 in the control group. Fasting blood glucose levels were significantly decreased by 6.125 mg/dL after synbiotic supplementation. FBG did not resume 4 weeks after terminating the supplementation. In contrast, there was a significant increase of FBG in control group on week 8 and was further increased 4 weeks after placebo was discontinued.

CONCLUSIONS

Synbiotic supplementation may prevent increase of body weight and BMI in obesity and this may be related with lower fasting blood glucose levels.

Physiological responses to carbohydrate overfeeding

PURPOSE OF REVIEW

To consider emerging research into the physiological effects of excessive dietary carbohydrate intake, with a particular focus on interactions with physical activity.

RECENT FINDINGS

A single episode of massive carbohydrate overload initiates physiological responses to stimulate additional peptide hormone secretion by the gut and the conversion of carbohydrate into lipid by the intestine, liver and adipose tissue. These acute responses maintain glycaemic control both via increased oxidation of carbohydrate (rather than lipid) and via nonoxidative disposal of surplus carbohydrate into endogenous glycogen and lipid storage depots. Sustained carbohydrate overfeeding therefore results in a chronic accumulation of lipid in the liver, skeletal muscle and adipose tissue, which can impair insulin sensitivity and cardiometabolic health in general. Beyond any direct effect of such lipid deposition on body mass/composition, there is not yet clear evidence of physiologically meaningful metabolic or behavioural adaptations to carbohydrate overfeeding in terms of other components of energy balance. However, regular physical exercise can mitigate the negative health effects of carbohydrate overfeeding, independent of any effect on the net carbohydrate surplus.

SUMMARY

Research in this area has advanced understanding regarding the mechanisms of weight gain and associated health outcomes within the modern context of an abundant supply of dietary carbohydrate.

The biology of human overfeeding: A systematic review

This systematic review has examined more than 300 original papers dealing with the biology of overfeeding. Studies have varied from 1 day to 6 months. Overfeeding produced weight gain in adolescents, adult men and women and in older men. In longer term studies, there was a clear and highly significant relationship between energy ingested and weight gain and fat storage with limited individual differences. There is some evidence for a contribution of a genetic component to this response variability. The response to overfeeding was affected by the baseline state of the groups being compared: those with insulin resistance versus insulin sensitivity; those prone to obesity versus those resistant to obesity; and those with metabolically abnormal obesity versus those with metabolically normal obesity. Dietary components, such as total fat, polyunsaturated fat and carbohydrate influenced the patterns of adipose tissue distribution as did the history of low or normal birth weight. Overfeeding affected the endocrine system with increased circulating concentrations of insulin and triiodothyronine frequently present. Growth hormone, in contrast, was rapidly suppressed. Changes in plasma lipids were influenced by diet, exercise and the magnitude of weight gain. Adipose tissue and skeletal muscle morphology and metabolism are substantially altered by chronic overfeeding.

Metabolic response to fasting predicts weight gain during low-protein overfeeding in lean men: further evidence for spendthrift and thrifty metabolic phenotypes

BACKGROUND

Greater increase in 24-h energy expenditure (24EE) during overfeeding and smaller decrease in 24EE during fasting ("spendthrift" metabolic phenotype) are associated with more weight loss during sustained caloric restriction in overweight subjects.

OBJECTIVES

The aim of this study was to investigate whether these acute metabolic responses can also predict weight gain during sustained overfeeding in lean individuals.

METHODS

Seven lean men participated in this study. Prior to overfeeding, 24EE responses to fasting and 200% normal-protein overfeeding were measured in a whole-room indirect calorimeter. Volunteers underwent 6 wk of 150% low-protein (2%) overfeeding followed by another wk of weight-maintaining diet, during which 24EE was revaluated. Body composition, 24EE, and various hormone concentrations, including fibroblast growth factor 21 (FGF21), were assessed at baseline, at wk 1, 3, and 6 of the overfeeding period, and 1 wk following overfeeding through the use of dual-energy X-ray absorptiometry, indirect calorimetry, and ELISA. Cumulative energy surplus was calculated from 24EE, daily physical activity, and direct measurements of calories of nutrient intake, feces, and urine by bomb calorimetry.

RESULTS

The average weight gain during 6 wk of low-protein overfeeding was 3.8 kg (6.1%, min: +2.5%, max: +8.0%). During 24-h fasting at baseline, 24EE decreased on average (mean ± SD) by 158 ± 81 kcal/d (P = 0.007). Subjects with less 24EE decrease during fasting (more metabolically spendthrift individuals) gained less weight (r = -0.84, P = 0.03), less fat mass (r = -0.81, P = 0.049), and stored less calories (r = -0.91, P = 0.03) during overfeeding. Following overfeeding, increased 24EE above requirements for achieved body size was associated with less weight and fat mass gain (r = -0.78, P = 0.04) and with the increase in 24EE during 200% normal-protein overfeeding measured at baseline (r = 0.91, P = 0.005). Serum FGF21 concentrations increased up to 44-fold during overfeeding (P <  0.0001).

CONCLUSIONS

Low-protein overfeeding may be an important tool to identify metabolic phenotypes (spendthrift compared with thrifty) that characterize susceptibility to weight gain. This trial was registered at clinicaltrials.gov as NCT00687115.

Molecular adaptation in adipose tissue in response to overfeeding with a high-fat diet under sedentary conditions in South Asian and Caucasian men

For the same BMI, South Asians have a higher body fat percentage than Caucasians. There might be differences in the fatty acid (FA) handling in adipose tissue when both ethnicities are exposed to high-fat overfeeding. The objective of the present study was to investigate the molecular adaptation in relation to FA metabolism in response to overfeeding with a high-fat diet (OHFD) in South Asian and Caucasian men. Ten South Asian men (BMI 18-29 kg/m2) and ten Caucasian men (BMI 22-33 kg/m2), matched for body fat percentage, aged 20-40 years were included. A weight-maintenance diet (30 % fat, 55 % carbohydrate and 15 % protein) was given for 3 d followed by 3 d of overfeeding (150 % energy requirement) with a high-fat diet (60 % fat, 25 % carbohydrate and 15 % protein) while staying in a respiration chamber. Before and after overfeeding, abdominal subcutaneous fat biopsies were taken. Proteins were isolated, analysed and quantified for short-chain 3-hydroxyacyl-CoA dehydrogenase (HADH), carnitine palmitoyl-transferase 1α (CPT1a), adipose TAG lipase, perilipin A (PLINA), perilipin B, lipoprotein lipase and fatty acid binding protein 4 using Western blotting. OHFD decreased the HADH level (P < 0·05) in Caucasians more than in Asians (P < 0·05), but the baseline and after intervention HADH level was relatively higher in Caucasians. The level of CPT1a decreased in South Asians and increased in Caucasians (P < 0·05). PLINA did not change with diet but the level was higher in South Asians (P < 0·05). The observed differences in HADH and PLINA levels as well as in CPT1a response may be important for differences in the long-term regulation of energy (fat) metabolism in these populations.

Physiology of energy homeostasis: Models, actors, challenges and the glucoadipostatic loop

The aim of this review is to discuss the physiology of energy homeostasis (EH), which is a debated concept. Thus, we will see that the set-point theory is highly challenged and that other models integrating an anticipative component, such as energy allostasis, seem more relevant to experimental reports and life preservation. Moreover, the current obesity epidemic suggests that EH is poorly efficient in the modern human dietary environment. Non-homeostatic phenomena linked to hedonism and reward seem to profoundly impair EH. In this review, the apparent failed homeostatic responses to energy challenges such as exercise, cafeteria diet, overfeeding and diet-induced weight loss, as well as their putative determinants, are analyzed to highlight the mechanisms of EH. Then, the hormonal, neuronal, and metabolic factors of energy intake or energy expenditure are briefly presented. Last, this review focuses on the contributions of two of the most pivotal and often overlooked determinants of EH: the availability of endogenous energy and the pattern of energy intake. A glucoadipostatic loop model is finally proposed to link energy stored in adipose tissue to EH through changes in eating behavior via leptin and sympathetic nervous system activity.

[Gut microbiota and obesity: Pathogenetic relationships and ways to normalize the intestinal microflora]

The review demonstrates mechanisms in the relationship of obesity to gut microbiota, as well as possible therapeutic measures to normalize the intestinal microflora. There is evidence that the latter makes a great contribution to the pathogenesis of obesity and related diseases. Investigations have shown the role of the nature of consumed foods (fatty foods) in reducing the amount of bifidobacteria and lactobacilli, as well as the effects of bacterial lipopolysaccharides and metabolites from the intestinal microflora (trimethylamine-N-oxide, bile acids, etc.). The use of prebiotics, probiotics and ursodeoxycholic acid preparations and fecal transplantation are promising in correcting the microflora and in providing their positive effect on metabolic disturbances. Certain probiotic strains are effective in treating dyslipidemia, diabetes mellitus, obesity, and metabolic syndrome. Gut microbiota is impaired in obesity and contributes to the development of cardiovascular diseases. The control of the gut microbiota and the use of drugs altering the composition of the microflora may become a novel approach to reducing the risk of cardiovascular diseases.

Impact of dietary fat on gut microbiota and low-grade systemic inflammation: mechanisms and clinical implications on obesity

Dietary fat strongly affects human health by modulating gut microbiota composition and low-grade systemic inflammation. High-fat diets have been implicated in reduced gut microbiota richness, increased Firmicutes to Bacteroidetes ratio, and several changes at family, genus and species levels. Saturated (SFA), monounsaturated (MUFA), polyunsaturated (PUFA) and conjugated linolenic fatty acids share important pathways of immune system activation/inhibition with gut microbes, modulating obesogenic and proinflammatory profiles. Mechanisms that link dietary fat, gut microbiota and obesity are mediated by increased intestinal permeability, systemic endotoxemia, and the activity of the endocannabinoid system. Although the probiotic therapy could be a complementary strategy to improve gut microbiota composition, it did not show permanent effects to treat fat-induced dysbiosis. Based upon evidence to date, we believe that high-fat diets and SFA consumption should be avoided, and MUFA and omega-3 PUFA intake should be encouraged in order to regulate gut microbiota and inflammation, promoting body weight/fat control.

Indirect Calorimetry: A Practical Guide for Clinicians

This review provides clinicians with a comprehensive overview of indirect calorimetry including the principles, methodology, technologic advancements, benefits, and challenges. Clinical applications for indirect calorimetry and the potential limitations are specifically addressed for both the inpatient and outpatient setting. Measurement of energy expenditure is the most accurate method to assess energy needs. Indirect calorimetry remains a gold standard in measuring energy expenditure in the clinical settings. The benefits of providing optimal nutrition for recovery from illness and chronic health management are well documented. Indirect calorimetry offers a scientifically-based approach to customize a patient's energy needs and nutrient delivery to maximize the benefits of nutrition therapy. With recent advances in technology, indirect calorimeters are easier to operate, more portable, and affordable. Increased utilization of indirect calorimetry would facilitate individualized patient care and should lead to improved treatment outcomes.

Translational research into gut microbiota: new horizons on obesity treatment: updated 2014

Obesity is currently a pandemic of worldwide proportions affecting millions of people. Recent studies have proposed the hypothesis that mechanisms not directly related to the human genome could be involved in the genesis of obesity, due to the fact that, when a population undergoes the same nutritional stress, not all individuals present weight gain related to the diet or become hyperglycemic. The human intestine is colonized by millions of bacteria which form the intestinal flora, known as gut flora. Studies show that lean and overweight human may present a difference in the composition of their intestinal flora; these studies suggest that the intestinal flora could be involved in the development of obesity. Several mechanisms explain the correlation between intestinal flora and obesity. The intestinal flora would increase the energetic extraction of non-digestible polysaccharides. In addition, the lipopolysaccharide from intestinal flora bacteria could trigger a chronic sub-clinical inflammatory process, leading to obesity and diabetes. Another mechanism through which the intestinal flora could lead to obesity would be through the regulation of genes of the host involved in energy storage and expenditure. In the past five years data coming from different sources established causal effects between intestinal microbiota and obesity/insulin resistance, and it is clear that this area will open new avenues of therapeutic to obesity, insulin resistance and DM2.

Gut microbiota, immune development and function

The microbiota of Westerners is significantly reduced in comparison to rural individuals living a similar lifestyle to our Paleolithic forefathers but also to that of other free-living primates such as the chimpanzee. The great majority of ingredients in the industrially produced foods consumed in the West are absorbed in the upper part of small intestine and thus of limited benefit to the microbiota. Lack of proper nutrition for microbiota is a major factor under-pinning dysfunctional microbiota, dysbiosis, chronically elevated inflammation, and the production and leakage of endotoxins through the various tissue barriers. Furthermore, the over-comsumption of insulinogenic foods and proteotoxins, such as advanced glycation and lipoxidation molecules, gluten and zein, and a reduced intake of fruit and vegetables, are key factors behind the commonly observed elevated inflammation and the endemic of obesity and chronic diseases, factors which are also likely to be detrimental to microbiota. As a consequence of this lifestyle and the associated eating habits, most barriers, including the gut, the airways, the skin, the oral cavity, the vagina, the placenta, the blood-brain barrier, etc., are increasingly permeable. Attempts to recondition these barriers through the use of so called 'probiotics', normally applied to the gut, are rarely successful, and sometimes fail, as they are usually applied as adjunctive treatments, e.g. in parallel with heavy pharmaceutical treatment, not rarely consisting in antibiotics and chemotherapy. It is increasingly observed that the majority of pharmaceutical drugs, even those believed to have minimal adverse effects, such as proton pump inhibitors and anti-hypertensives, in fact adversely affect immune development and functions and are most likely also deleterious to microbiota. Equally, it appears that probiotic treatment is not compatible with pharmacological treatments. Eco-biological treatments, with plant-derived substances, or phytochemicals, e.g. curcumin and resveratrol, and pre-, pro- and syn-biotics offers similar effects as use of biologicals, although milder but also free from adverse effects. Such treatments should be tried as alternative therapies; mainly, to begin with, for disease prevention but also in early cases of chronic diseases. Pharmaceutical treatment has, thus far, failed to inhibit the tsunami of endemic diseases spreading around the world, and no new tools are in sight. Dramatic alterations, in direction of a paleolithic-like lifestyle and food habits, seem to be the only alternatives with the potential to control the present escalating crisis. The present review focuses on human studies, especially those of clinical relevance.

The intestinal microbiota and obesity

Obesity has been and continues to be an epidemic in the United States. Obesity has been addressed in multiple health initiatives, including Healthy People 2010, with no state meeting the proposed goal of a prevalence of obesity < 15% of the adult population. In contrast, obesity rates have continued to increase, with the self-reported prevalence of obesity among adults increasing by 1.1% from 2007 to the present. Indeed, since 2009, 33 states reported obesity prevalences of 25% or more with only 1 state reporting prevalence < 20%. There have been multiple approaches for the treatment of obesity, including fad diets, incentive-based exercise programs, and gastric bypass surgery; none of which have been optimal. In a murine model, it was shown that the majority of the intestinal microbiome consists of two bacterial phyla, the Bacteroidetes and the Firmicutes, and that the relative abundance of these two phyla differs among lean and obese mice; the obese mouse had a higher proportion of Firmicutes to Bacteroidetes (50% greater) than the lean mouse. The same results were appreciated in obese humans compared to lean subjects. The postulated explanation for this finding is that Firmicutes produce more complete metabolism of a given energy source than do Bacteroidetes, thus promoting more efficient absorption of calories and subsequent weight gain. Researchers were able to demonstrate that colonizing germ-free mice with the intestinal microbiome from obese mice led to an increased total body fat in the recipient mice despite a lack of change in diet. The converse, that, colonizing germ-free obese mice with the intestinal microbiome of thin mice causing a decreased total body fat in the recipient mice, has not yet been done. Other possible mechanisms by which the intestinal microbiome affects host obesity include induction of low-grade inflammation with lipopolysaccharide, regulation of host genes responsible for energy expenditure and storage, and hormonal communication between the intestinal microbiome and the host. The following review discusses the microbiome-obesity relationship and proposed mechanisms by which the intestinal microbiota is hypothesized to influence weight gain.

Poor prediction of resting energy expenditure in obese women by established equations

The objective of the study was to evaluate the accuracy of established prediction equations that calculate resting energy expenditure (REE) in obese women. This was a cross-sectional study. In 273 mildly to severely obese women (age, 41.7 +/- 13.2 years; body mass index, 42.8 +/- 7.0 kg/m(2)), REE was measured by indirect calorimetry (mREE), along with fat mass (FM) and fat-free mass (FFM) by bioelectrical impedance analysis. Eleven established equations were used to predict REE (pREE), with 9 equations basing on the anthropometric parameters body weight and height and 2 equations including body composition parameters (FM, FFM). All equations provided pREE values that significantly correlated with mREE (r > 0.66, P < .001), although 8 equations systematically underestimated mREE (P < .05). Of note, even the best equation was not able to accurately predict mREE with a deviation of less than +/-10% in more than 70% of the tested women. Furthermore, equations using body composition data were not superior in predicting REE as compared with equations exclusively including anthropometric variables. Multiple linear regression analyses revealed 2 new equations--one including body weight and age and another including FM, FFM, and age--that explained 56.9% and 57.2%, respectively, of variance in mREE. However, when these 2 new equations were applied to an independent sample of 33 obese women, they also provided an accurate prediction (+/-10%) of mREE in only 56.7% and 60.6%, respectively, of the women. Data show that an accurate prediction of REE is not feasible using established equations in obese women. Equations that include body composition parameters as assessed by bioelectrical impedance analysis do not increase the accuracy of prediction. Based on our results, we conclude that calculating REE by standard prediction equations does not represent a reliable alternative to indirect calorimetry for the assessment of REE in obese women.

[Gut microflora is a key player in host energy homeostasis]

Gut microflora is now considered as a key organ involved in host energy homeostasis. Recent data suggest that the alterations of the gut bacteria ecosystem could contribute to the development of metabolic disorders such as type 2 diabetes and obesity. First, gut microflora may increase energy efficiency of non digested food via the fermentation, thus providing more energy to the host. Secondly, fatty acids flux and storage in the adipose tissue is under the control of the fasting-induced adipocyte factor FIAF, which expression depends on gut microflora. Third, high-fat diet feeding changes gut bacteria profile, leading to a drop in bifidobacteria content, which correlates with a higher LPS plasma levels, thereby participating to the onset of inflammation, insulin resistance and type 2 diabetes associated with obesity. Changing gut microflora composition could be a useful tool to prevent or to treat high-fat/low fibres diet-induced metabolic syndrome. double dagger.

Gut microflora as a target for energy and metabolic homeostasis

PURPOSE OF REVIEW

Gut microbiota plays an important role in health and disease, but this ecosystem remains incompletely characterized and shows a wide diversity. This review discusses new findings that may explain how gut microbiota can be involved in the control of energy and metabolic homeostasis.

RECENT FINDINGS

Over the past 5 years studies have highlighted some key aspects of the mammalian host-gut microbial relationship. Gut microbiota could now be considered a 'microbial organ' placed within a host organ. Recent data suggest that the modulation of gut microbiota affects host metabolism and has an impact on energy storage. Several mechanisms are proposed that link events occurring in the colon and the regulation of energy metabolism.

SUMMARY

Gut microflora may play an even more important role in maintaining human health than previously thought. The literature provides new evidence that the increased prevalence of obesity and type 2 diabetes cannot be attributed solely to changes in the human genome, nutritional habits, or reduction of physical activity in our daily lives. One must also consider this important new environmental factor, namely gut microbiota. Scientists may take into consideration a key question: could we manipulate the microbiotic environment to treat or prevent obesity and type 2 diabetes? This opens up a new area in nutrition research.

Changes in gene expression in skeletal muscle in response to fat overfeeding in lean men

OBJECTIVE

The adaptive mechanisms in response to excess energy supply are still poorly known in humans. Our aims were to define metabolic responses and changes in gene expression in skeletal muscle of healthy volunteers during fat overfeeding.

RESEARCH METHODS AND PROCEDURES

Eight lean young healthy men were given a diet rich in saturated fat with an excess of approximately 550 kcal/d for 4 weeks. Using oligonucleotide microarrays, gene expression changes in skeletal muscle were analyzed at Day 0, Day 14, and Day 28.

RESULTS

Fat overfeeding led to an increase in body weight (1.0 +/- 0.3 kg) and waist circumference (2.2 +/- 0.5 cm, p = 0.005) and a significant decrease in fasting non-esterified fatty acid plasma levels (-29 +/- 5%, p = 0.028). Respiratory quotient was significantly increased (0.84 +/- 0.01 to 0.88 +/- 0.02, p = 0.034) and lipid oxidation rate tended to decrease. The expression of 55 genes was modified in skeletal muscle. The main pathways indicated a coordinated stimulation of triacylglycerol synthesis, inhibition of lipolysis, reduction of fatty acid oxidation, and development of adipocytes. Promoter analysis of the regulated genes suggests that sterol regulatory element binding proteins might be important players of the short-term adaptation to fat overfeeding in human skeletal muscle.

DISCUSSION

This combined metabolic and genomic investigation shows that fat overfeeding for 28 days promotes the storage of the excess energy in lean men and demonstrates the usefulness of a transcriptomic approach to a better understanding of the metabolic adaptation to changes in nutritional behavior in human.

Resting energy expenditure during mechanical ventilation and its relationship with the type of lesion

BACKGROUND

Resting energy expenditure (REE) of critically ill patients is usually calculated according to basal energy expenditure obtained from Harris-Benedict equations traditionally corrected by different stress factors, resulting in a variable accuracy for the individual patient. The objective of this study was to investigate whether or not the type of lesion affects the metabolism level of critically ill patients treated with mechanical ventilation. We performed a retrospective study measuring the REE of critically ill patients with 3 different types of lesions (trauma, medical, surgical) who were treated with mechanical ventilation and sedation. Each lesion group of patients was matched with another group, differing in the type of lesion, according to gender, age, and weight.

METHODS

Eighty-seven from a database of 175 critically ill patients undergoing indirect calorimetry were necessary for matching. Twenty matched pairs of patients for each of the following different type of lesion were obtained: medical vs surgical, medical vs trauma, and surgical vs trauma.

RESULTS

The mean REE difference was 52 kcal/d (95% confidence interval [CI] of -136 -241 kcal/d) for the medical vs surgical group, 5 kcal/d (95% CI -236 -247 kcal/d) for the medical vs trauma group and 43 kcal/d (95% CI of -132-219 kcal/d) for the surgical vs trauma group. No statistically significant differences between groups were found in the measured REE. We did not find statistically significant differences in the measured REE of patients with and without infection.

CONCLUSIONS

Critically ill patients with different types of lesion treated with mechanical ventilation have similar measured REE.

Influence of ß2-adrenoceptor gene polymorphisms on diet-induced thermogenesis

The sympathetic nervous system is involved in the control of energy metabolism and expenditure. Diet-induced thermogenesis is mediated partly by the ß-adrenergic component of this system. The aim of the present study was to investigate the role of genetic variation in the ß2-adrenoceptor in diet-induced thermogenesis. Data from twenty-four subjects (fourteen men and ten women; BMI 26·7(sem 0·8) kg/m2; age 45·2(sem1·4) years) with different polymorphisms of the ß2-adrenoceptor at codon 16 (Gly16Gly, Gly16Arg or Arg16Arg) were recruited for this study. Subjects were given a high-carbohydrate liquid meal, and the energy expenditure, respiratory exchange ratio, and plasma concentrations of NEFA, glycerol, glucose, insulin and catecholamines were measured before and over 4 h after the meal. The AUC of energy expenditure (diet-induced thermogenesis) was not significantly different between polymorphism groups, nor was the response of any of the other measured variables to the meal. In a multiple regression model, the only variable that explained a significant proportion (32 %) of the variation in diet-induced thermogenesis was the increase in plasma adrenaline in response to the meal (P<0·05). The ß2-adrenoceptor codon16 polymorphisms did not contribute significantly. In conclusion, an independent contribution of the codon 16 polymorphism of the ß2-adrenoceptor gene to the variation in thermogenic response to a high-carbohydrate meal could not be demonstrated. The interindividual variation in thermogenic response to the meal was correlated with variations in the plasma adrenaline response to the meal.

How much may I eat? Calorie estimates based upon energy expenditure prediction equations

How much may I eat? Most healthcare workers, when asked this question, have insufficient knowledge to educate their patients on a healthy energy intake level. In this review we examine the available methods for estimating adult energy requirements with a focus on the newly developed National Academy of Sciences/Institute of Medicine (NAS/IOM) doubly-labelled water total energy expenditure (TEE) prediction equations. An overview is first provided of the traditional factorial method of estimating energy requirements. We then extend this overview by exploring the development of the NAS/IOM TEE prediction models and their role in estimating energy requirements as a function of sex, age, weight, height and physical activity level. The NAS/IOM prediction models were developed for evaluating group energy requirements, although the formulas can be applied in individual 'example' patients for educational purposes. Potential limitations and interpretation issues of both the factorial and NAS/IOM methods are examined. This information should provide healthcare professionals with the tools and understanding to appropriately answer the question, 'How much may I eat?'