Differences in post-prandial responses to fat and carbohydrate loads in habitual high and low fat consumers (phenotypes).

The present study investigated metabolic responses to fat and carbohydrate ingestion in lean male individuals consuming an habitual diet high or low in fat. Twelve high-fat phenotypes (HF) and twelve low-fat phenotypes (LF) participated in the study. Energy intake and macronutrient intake variables were assessed using a food frequency questionnaire. Resting (RMR) and postprandial metabolic rate and substrate oxidation (respiratory quotient; RQ) were measured by indirect calorimetry. HF had a significantly higher RMR and higher resting heart rate than LF. These variables remained higher in HF following the macronutrient challenge. In all subjects the carbohydrate load increased metabolic rate and heart rate significantly more than the fat load. Fat oxidation (indicated by a low RQ) was significantly higher in HF than in LF following the fat load; the ability to oxidise a high carbohydrate load did not differ between the groups. Lean male subjects consuming a diet high in fat were associated with increased energy expenditure at rest and a relatively higher fat oxidation in response to a high fat load; these observations may be partly responsible for maintaining energy balance on a high-fat (high-energy) diet. In contrast, a low consumer of fat is associated with relatively lower energy expenditure at rest and lower fat oxidation, which has implications for weight gain if high-fat foods or meals are periodically introduced to the diet.

Description and evaluation of a Newton-based electronic appetite rating system for temporal tracking of appetite in human subjects

This study assessed the reliability and validity of a palm-top-based electronic appetite rating system (EARS) in relation to the traditional paper and pen method. Twenty healthy subjects [10 male (M) and 10 female (F)] — mean age M=31 years (S.D.=8), F=27 years (S.D.=5); mean BMI M=24 (S.D.=2), F=21 (S.D.=5) — participated in a 4-day protocol. Measurements were made on days 1 and 4. Subjects were given paper and an EARS to log hourly subjective motivation to eat during waking hours. Food intake and meal times were fixed. Subjects were given a maintenance diet (comprising 40% fat, 47% carbohydrate and 13% protein by energy) calculated at 1.6×Resting Metabolic Rate (RMR), as three isoenergetic meals. Bland and Altman's test for bias between two measurement techniques found significant differences between EARS and paper and pen for two of eight responses (hunger and fullness). Regression analysis confirmed that there were no day, sex or order effects between ratings obtained using either technique. For 15 subjects, there was no significant difference between results, with a linear relationship between the two methods that explained most of the variance (r2 ranged from 62.6 to 98.6). The slope for all subjects was less than 1, which was partly explained by a tendency for bias at the extreme end of results on the EARS technique. These data suggest that the EARS is a useful and reliable technique for real-time data collection in appetite research but that it should not be used interchangeably with paper and pen techniques.

A novel technique to demonstrate disturbed appetite profiles in haemodialysis patients

Background Malnutrition is common among dialysis patients and is associated with an adverse outcome. One cause of this is a persistent reduction in nutrient intake, suggesting an abnormality of appetite regulation. Methods We used a novel technique to describe the appetite profile in 46 haemodialysis (HD) patients and 40 healthy controls. The Electronic Appetite Rating System (EARS) employs a palmtop computer to collect hourly ratings of motivation to eat and mood. We collected data on hunger, desire to eat, fullness, and tiredness. HD subjects were monitored on the dialysis day and the interdialytic day. Controls were monitored for 1 or 2 days. Results Temporal profiles of motivation to eat for the controls were similar on both days. Temporal profiles of motivation to eat for the HD group were lower on the dialysis day. Mean HD scores were not significantly different from controls. Dietary records indicated that dialysis patients consumed less food than controls. Conclusions Our data indicate that the EARS can be used to monitor subjective appetite states continuously in a group of HD patients. A HD session reduces hunger and desire to eat. Patients feel more tired after dialysis. This does not correlate with their hunger score, but does correlate with their fullness rating. Nutrient intake is reduced, suggesting a resetting of appetite control for the HD group. The EARS may be useful for intervention studies.

The use of visual analogue scales to assess motivation to eat in human subjects: a review of their reliability and validity with an evaluation of new hand-held computerized stsytems for temporal tracking of appetite ratings.

This present paper reviews the reliability and validity of visual analogue scales (VAS) in terms of (1) their ability to predict feeding behaviour, (2) their sensitivity to experimental manipulations, and (3) their reproducibility. VAS correlate with, but do not reliably predict, energy intake to the extent that they could be used as a proxy of energy intake. They do predict meal initiation in subjects eating their normal diets in their normal environment. Under laboratory conditions, subjectively rated motivation to eat using VAS is sensitive to experimental manipulations and has been found to be reproducible in relation to those experimental regimens. Other work has found them not to be reproducible in relation to repeated protocols. On balance, it would appear, in as much as it is possible to quantify, that VAS exhibit a good degree of within-subject reliability and validity in that they predict with reasonable certainty, meal initiation and amount eaten, and are sensitive to experimental manipulations. This reliability and validity appears more pronounced under the controlled (but more arti®cial) conditions of the laboratory where the signal : noise ratio in experiments appears to be elevated relative to real life. It appears that VAS are best used in within-subject, repeated-measures designs where the effect of different treatments can be compared under similar circumstances. They are best used in conjunction with other measures (e.g. feeding behaviour, changes in plasma metabolites) rather than as proxies for these variables. New hand-held electronic appetite rating systems (EARS) have been developed to increase reliability of data capture and decrease investigator workload. Recent studies have compared these with traditional pen and paper (P&P) VAS. The EARS have been found to be sensitive to experimental manipulations and reproducible relative to P&P. However, subjects appear to exhibit a signi®cantly more constrained use of the scale when using the EARS relative to the P&P. For this reason it is recommended that the two techniques are not used interchangeably

Ghrelin and obestatin concentrations during puberty: Relationships with adiposity, nutrition and physical activity

Ghrelin and obestatin are two peptides associated with appetite control and the regulation of energy balance in adults. It is intuitive that they have an important role in growth and development during puberty. Therefore, it is acknowledged that these peptides, in addition to others, form part of the substrate underlying energy homeostasis which in turn will contribute to body weight regulation and could explain changes in energy balance during puberty. Both peptides originate from the stomach; hence, it is intuitive that they are involved in generating signals from tissue stores which influence food intake. This could be manifested via alterations in the drive to eat (i.e. hunger), eating behaviors and appetite regulation. Furthermore, there is some evidence that these peptides might also be associated with physical activity behaviors and metabolism. Anecdotally, children and adolescents experience behavioral and metabolic changes during growth and development which will be associated with physiological changes.

Characterising the homeostatic and hedonic markers of the susceptible phenotype

Over the years, approaches to obesity prevention and treatment have gone from focusing on genetic and other biological factors to exploring a diversity of diets and individual behavior modification interventions anchored primarily in the power of the mind, to the recent shift focusing on societal interventions to design ";temptation-proof"; physical, social, and economic environments. In spite of repeated calls to action, including those of the World Health Organization (WHO), the pandemic continues to progress. WHO recently projected that if the current lifestyle trend in young and adult populations around the world persist, by 2012 in countries like the USA, health care costs may amount to as much as 17.7% of the GDP. Most importantly, in large part due to the problems of obesity, those children may be the first generation ever to have a shorter life expectancy than that of their parents. This work presents the most current research and proposals for addressing the pandemic. Past studies have focused primarly on either genetic or behavioral causes for obesity, however today's research indicates that a strongly integrated program is the best prospect for success in overcoming obesity. Furthermore, focus on the role of society in establishing an affordable, accessible and sustainable program for implementing these lifestyle changes is vital, particularly for those in economically challenged situations, who are ultimately at the highest risk for obesity. Using studies from both neuroscience and behavioral science to present a comprehensive overview of the challenges and possible solutions, The brain-to-society approach to obesity prevention focuses on what is needed in order to sustain a healthy, pleasurable and affordable lifestyle.

Physical inactivity, appetite regulation and obesity

In a consumerist society obsessed with body image and thinness, obesity levels have reached an all-time high. This multi-faceted book written by a range of experts, explores the social, cultural, clinical and psychological factors that lie behind the Obesity Epidemic . It is required reading for the many healthcare professionals dealing with the effects of obesity and for anyone who wants to know more about the causes of weight gain and the best ways of dealing with it. Fat Matters covers a range of issues from sociology through medicine to technology. This is not a book for the highly specialised expert. Rather it is a book that shows the diversity of approaches to the phenomenon of obesity, tailored to the reader who wants to be up-to-date and well-informed on a subject that is possibly as frequently discussed and as misunderstood as the weather.

Physical activity and regulation of food intake: current evidence

Objective: The evidence was reviewed on how physical activity could influence the regulation of food intake by either adjusting the sensitivity of appetite control mechanisms or by generating an energy deficit that could adjust the drive to eat. Design: Interventionist and correlational studies that had a significant influence on the relationship between physical activity and food intake were reviewed. Interventionist studies involve a deliberate imposition of physical activity with subsequent monitoring of the eating response. Correlational studies make use of naturally occurring differences in the levels of physical activity (between and within subjects) with simultaneous assessment of energy expenditure and intake. Subjects: Studies using lean, overweight, and obese men and women were included. Results: Only 19% of interventionist studies report an increase in energy intake after exercise; 65% show no change and 16% show a decrease in appetite. Of the correlational studies, approximately half show no relationship between energy expenditure and intake. These data indicate a rather loose coupling between energy expenditure and intake. A common sense view is that exercise is futile as a form of weight control because the energy deficit drives a compensatory increase in food intake. However, evidence shows that this is not generally true. One positive aspect of this is that raising energy expenditure through physical activity (or maintaining an active life style) can cause weight loss or prevent weight gain. A negative feature is that when people become sedentary after a period of high activity, food intake is not “down-regulated” to balance a reduced energy expenditure. Conclusion: Evidence suggests that a high level of physical activity can aid weight control either by improving the matching of food intake to energy expenditure (regulation) or by raising expenditure so that it is difficult for people to eat themselves into a positive energy balance.

The regulation of food intake in humans

Knowledge of the regulation of food intake is crucial to an understanding of body weight and obesity. Strictly speaking, we should refer to the control of food intake whose expression is modulated in the interests of the regulation of body weight. Food intake is controlled, body weight is regulated. However, this semantic distinction only serves to emphasize the importance of food intake. Traditionally food intake has been researched within the homeostatic approach to physiological systems pioneered by Claude Bernard, Walter Cannon and others; and because feeding is a form of behaviour, it forms part of what Curt Richter referred to as the behavioural regulation of body weight (or behavioural homeostasis). This approach views food intake as the vehicle for energy supply whose expression is modulated by a metabolic drive generated in response to a requirement for energy. The idea was that eating behaviour is stimulated and inhibited by internal signalling systems (for the drive and suppression of eating respectively) in order to regulate the internal environment (energy stores, tissue needs).

Physical activity and obesity.

The authors explore our understanding of the part played by physical activity in preventing obesity through suitable activity or fostering obesity through reduced levels of activity. The international group of authors review physical activity as an important part of obesity on the one hand and appropriate weight on the other. The role of physical activity and exercise in those age-groups, and the natural history of weight and overweight during growth and development, are among essential public health topics under review here

Obesity

It is now widely accepted that there are important links between inactivity and lifestyle-related chronic diseases, and that exercise can bring tangible therapeutic benefits to people with long-term chronic conditions. Exercise and Chronic Disease: An Evidence-Based Approach offers the most up-to-date survey currently available of the scientific and clinical evidence underlying the effects of exercise in relation to functional outcomes, disease-specific health-related outcomes and quality of life in patients with chronic disease conditions. Drawing on data from randomized controlled trials and observational evidence, and written by a team of leading international researchers and medical and health practitioners, the book explores the evidence across a wide range of chronic diseases, including:

Effect of physical activity and other stressors on appetite: Overcoming underconsumption of military operational rations revisited.

Recognizing the importance of good nutrition for physical and mental status, the Department of Defense asked the Institute of Medicine to guide the design of the nutritional composition of a ration for soldiers on short-term, high-stress missions. Nutrient Composition of Rations for Short-Term, High-Intensity Combat Operations considers military performance, health concerns, food intake, energy expenditure, physical exercise, and food technology issues. The success of military operations depends to a large extent on the physical and mental status of the individuals involved.

Exercise-induced energy expenditure : implications for exercise prescription and obesity

Objective: Walking is commonly recommended to help with weight management. We measured total energy expenditure (TEE) and its components to quantify the impact of increasing exercise-induced energy expenditure (ExEE) on other components of TEE. Methods: Thirteen obese women underwent an 8-week walking group intervention. TEE was quantified using doubly labeled water, ExEE was quantified using heart rate monitors, daily movement was assessed by accelerometry and resting metabolic rate was measured using indirect calorimetry. Results: Four of the 13 participants achieved the target of 1500 kcal wk−1 of ExEE and all achieved 1000 kcal wk−1. The average ExEE achieved by the group across the 8 weeks was 1434 ± 237 kcal wk−1. Vigorous physical activity, as assessed by accelerometry, increased during the intervention by an average of 30 min per day. Non-exercise activity thermogenesis (NEAT) decreased, on average, by 175 kcal d−1 (−22%) from baseline to the intervention and baseline fitness was correlated with change in NEAT. Conclusions: Potential alterations in non-exercise activity should be considered when exercise is prescribed. The provision of appropriate education on how to self-monitor daily activity levels may improve intervention outcomes in groups who are new to exercise. Practice implications: Strategies to sustain incidental and light physical activity should be offered to help empower individuals as they develop and maintain healthy and long-lasting lifestyle habits.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.