Beneficial effects of exercise : shifting the focus from body weight to other markers of health

Background: Exercise is widely promoted as a method of weight management, while the other health benefits are often ignored. The purpose of this study was to examine whether exercise-induced improvements in health are influenced by changes in body weight. Methods: Fifty-eight sedentary overweight/obese men and women (BMI 31.8 (SD 4.5) kg/m2) participated in a 12-week supervised aerobic exercise intervention (70% heart rate max, five times a week, 500 kcal per session). Body composition, anthropometric parameters, aerobic capacity, blood pressure and acute psychological response to exercise were measured at weeks 0 and 12. Results: The mean reduction in body weight was −3.3 (3.63) kg (p<0.01). However, 26 of the 58 participants failed to attain the predicted weight loss estimated from individuals’ exercise-induced energy expenditure. Their mean weight loss was only −0.9 (1.8) kg (p<0.01). Despite attaining a lower-than-predicted weight reduction, these individuals experienced significant increases in aerobic capacity (6.3 (6.0) ml/kg/min; p<0.01), and a decreased systolic (−6.00 (11.5) mm Hg; p<0.05) and diastolic blood pressure (−3.9 (5.8) mm Hg; p<0.01), waist circumference (−3.7 (2.7) cm; p<0.01) and resting heart rate (−4.8 (8.9) bpm, p<0.001). In addition, these individuals experienced an acute exercise-induced increase in positive mood. Conclusions: These data demonstrate that significant and meaningful health benefits can be achieved even in the presence of lower-than-expected exercise-induced weight loss. A less successful reduction in body weight does not undermine the beneficial effects of aerobic exercise. From a public health perspective, exercise should be encouraged and the emphasis on weight loss reduced.

Exercise alone is not enough : weight loss also needs a healthy (Mediterranean) diet?

Objective: In the majority of exercise intervention studies, the aggregate reported weight loss is often small. The efficacy of exercise as a weight loss tool remains in question. The aim of the present study was to investigate the variability in appetite and body weight when participants engaged in a supervised and monitored exercise programme. ---------- Design: Fifty-eight obese men and women (BMI = 31·8 ± 4·5 kg/m2) were prescribed exercise to expend approximately 2092 kJ (500 kcal) per session, five times a week at an intensity of 70 % maximum heart rate for 12 weeks under supervised conditions in the research unit. Body weight and composition, total daily energy intake and various health markers were measured at weeks 0, 4, 8 and 12. ---------- Results: Mean reduction in body weight (3·2 ± 1·98 kg) was significant (P < 0·001); however, there was large individual variability (−14·7 to +2·7 kg). This large variability could be largely attributed to the differences in energy intake over the 12-week intervention. Those participants who failed to lose meaningful weight increased their food intake and reduced intake of fruits and vegetables. ---------- Conclusion: These data have demonstrated that even when exercise energy expenditure is high, a healthy diet is still required for weight loss to occur in many people.

Acute compensatory eating following exercise is associated with implicit hedonic wanting for food

The efficacy of exercise to promote weight loss could potentially be undermined by its influence on explicit or implicit processes of liking and wanting for food which in turn alter food preference. The present study was designed to examine hedonic and homeostatic mechanisms involved in the acute effects of exercise on food intake. 24 healthy female subjects were recruited to take part in two counterbalanced activity sessions; 50 min of high intensity (70% max heart rate) exercise (Ex) or no exercise (NEx). Subjective appetite sensations, explicit and implicit hedonic processes, food preference and energy intake (EI) were measured immediately before and after each activity session and an ad libitum test meal. Two groups of subjects were identified in which exercise exerted different effects on compensatory EI and food preference. After exercise, compensators (C) increased their EI, rated the food to be more palatable, and demonstrated increased implicit wanting. Compensators also showed a preference for high-fat sweet food compared with non-compensators (NC), independent of the exercise intervention. Exercise-induced changes in the hedonic response to food could be an important consideration in the efficacy of using exercise as a means to lose weight. An enhanced implicit wanting for food after exercise may help to explain why some people overcompensate during acute eating episodes. Some individuals could be resistant to the beneficial effects of exercise due to a predisposition to compensate for exercise-induced energy expenditure as a result of implicit changes in food preferences.

Tesofensine : a novel potent weight loss medicine

Background: The incidence of obesity is increasing; this is of major concern, as obesity is associated with cardiovascular disease, stroke, type 2 diabetes, respiratory tract disease, and cancer. Objectives/methods: This evaluation is of a Phase II clinical trial with tesofensine in obese subjects. Results: After 26 weeks, tesofensine caused a significant weight loss, and may have a higher maximal ability to reduce weight than the presently available anti-obesity agents. However, tesofensine also increased blood pressure and heart rate, and may increase psychiatric disorders. Conclusions: It is encouraging that tesofensine 0.5 mg may cause almost double the weight loss observed with sibutramine or rimonabant. As tesofensine and sibutramine have similar pharmacological profiles, it would be of interest to compare the weight loss with tesofensine in a head-to-head clinical trial with sibutramine, to properly assess their comparative potency. Also, as teso fensine 0.5 mg increases heart rate, as well as increasing the incidence of adverse effects such as nausea, drug mouth, flatulence, insomnia, and depressed mode, its tolerability needs to be further evaluated in large Phase III clinical trials.

Within- and between-day repeatability and variability in children's physiological responses during submaximal treadmill exercise

The purpose of this study was to verify within- and between-day repeatability and variability in children's oxygen uptake (VO^sub 2^), gross economy (GE; VO^sub 2^ divided by speed) and heart rate (HR) during treadmill walking based on self-selected speed (SS). Fourteen children (10.1 ± 1.4 years) undertook three testing sessions over 2 days in which four walking speeds, including SS were tested. Within- and between-day repeatability were assessed using the Bland and Altman method, and coefficients of variability (CV) were determined for each child across exercise bouts and averaged to obtain a mean group CV value for VO^sub 2^, GE, and HR per speed. Repeated measures analysis of variance showed no statistically significant differences in within- or between-day CV for VO^sub 2^, GE, or HR at any speed. Repeatability within- and between-day for VO^sub 2^, GE, and HR for all speeds was verified. These results suggest that submaximal VO^sub 2^ during treadmill walking is stable and reproducible at a range of speeds based on children's SS.

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.

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.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

A compact mock circulation loop for the in vitro testing of cardiovascular devices

In vitro cardiovascular device performance evaluation in a mock circulation loop (MCL) is a necessary step prior to in vivo testing.A MCL that accurately represents the physiology of the cardiovascular system accelerates the assessment of the device’s ability to treat pathological conditions. To serve this purpose, a compact MCL measuring 600 ¥ 600 ¥ 600 mm (L ¥ W¥ H) was constructed in conjunction with a computer mathematical simulation.This approach allowed the effective selection of physical loop characteristics, such as pneumatic drive parameters, to create pressure and flow, and pipe dimensions to replicate the resistance, compliance, and fluid inertia of the native cardiovascular system. The resulting five-element MCL reproduced the physiological hemodynamics of a healthy and failing heart by altering ventricle contractility, vascular resistance/compliance, heart rate, and vascular volume. The effects of interpatient anatomical variability, such as septal defects and valvular disease, were also assessed. Cardiovascular hemodynamic pressures (arterial, venous, atrial, ventricular), flows (systemic, bronchial, pulmonary), and volumes (ventricular, stroke) were analyzed in real time. The objective of this study is to describe the developmental stages of the compact MCL and demonstrate its value as a research tool for the accelerated development of cardiovascular devices.

The low-affinity site of the β1-adrenoceptor and its relevance to cardiovascular pharmacology

β-Adrenoceptor blocking agents (β-blockers) that at low concentrations antagonize cardiostimulant effects of catecholamines, but at high concentrations also cause cardiostimulation, have been appearing since the late 1960s. These cardiostimulant β-blockers, coined non-conventional partial agonists, antagonize the effects of catecholamines through a high-affinity site (β1HAR), but cause cardiostimulation mainly through a low-affinity site (β1LAR) of the myocardial β1-adrenoceptor. The experimental non-conventional partial agonist (−)-CGP12177 increases cardiac L-type Ca2+ current density and Ca2+ transients, shortens action potential duration but augments action potential plateau, increases heart rate and force, as well as causes arrhythmic Ca2+ transients and arrhythmic cardiocyte contractions. Other β-blockers, which do not cause cardiostimulation, consistently have lower affinity for β1LAR than β1HAR. These sites were verified and the cardiac pharmacology of non-conventional partial agonists confirmed on recombinant β1-adrenoceptors and on β1-adrenoceptors overexpressed into the heart. A targeted mutation of Asp138 to Glu138 virtually abolished the pharmacology of β1HAR but left intact the pharmacology of β1LAR. Non-conventional partial agonists may be beneficial for the treatment of peripheral autonomic neuropathy but probably due to their arrhythmic propensities, may be harmful for the treatment of chronic heart failure.

Application of higher order statistics/spectra in biomedical signals : a review

For many decades correlation and power spectrum have been primary tools for digital signal processing applications in the biomedical area. The information contained in the power spectrum is essentially that of the autocorrelation sequence; which is sufficient for complete statistical descriptions of Gaussian signals of known means. However, there are practical situations where one needs to look beyond autocorrelation of a signal to extract information regarding deviation from Gaussianity and the presence of phase relations. Higher order spectra, also known as polyspectra, are spectral representations of higher order statistics, i.e. moments and cumulants of third order and beyond. HOS (higher order statistics or higher order spectra) can detect deviations from linearity, stationarity or Gaussianity in the signal. Most of the biomedical signals are non-linear, non-stationary and non-Gaussian in nature and therefore it can be more advantageous to analyze them with HOS compared to the use of second order correlations and power spectra. In this paper we have discussed the application of HOS for different bio-signals. HOS methods of analysis are explained using a typical heart rate variability (HRV) signal and applications to other signals are reviewed.

The ecological dynamics of 1v1 sub-phases in association football

This paper analyzes effects of different practice task constraints on heart rate (HR) variability during 4v4 smallsided football games. Participants were sixteen football players divided into two age groups (U13, Mean age: 12.4±0.5 yrs; U15: 14.6±0.5). The task consisted of a 4v4 sub-phase without goalkeepers, on a 25x15 m field, of 15 minutes duration with an active recovery period of 6 minutes between each condition. We recorded players’ heart rates using heart rate monitors (Polar Team System, Polar Electro, Kempele, Finland) as scoring mode was manipulated (line goal: scoring by dribbling past an extended line; double goal: scoring in either of two lateral goals; and central goal: scoring only in one goal). Subsequently, %HR reserve was calculated with the Karvonen formula. We performed a time-series analysis of HR for each individual in each condition. Mean data for intra-participant variability showed that autocorrelation function was associated with more short-range dependence processes in the “line goal” condition, compared to other conditions, demonstrating that the “line goal” constraint induced more randomness in HR response. Relative to inter-individual variability, line goal constraints demonstrated lower %CV and %RMSD (U13: 9% and 19%; U15: 10% and 19%) compared with double goal (U13: 12% and 21%; U15: 12% and 21%) and central goal (U13: 14% and 24%; U15: 13% and 24%) task constraints, respectively. Results suggested that line goal constraints imposed more randomness on cardiovascular stimulation of each individual and lower inter-individual variability than double goal and central goal constraints.

Real-time evaluation of driver’s alertness on highways

Suburbanisation has been internationally a major phenomenon in the last decades. Suburb-to-suburb routes are nowadays the most widespread road journeys; and this resulted in an increment of distances travelled, particularly on faster suburban highways. The design of highways tends to over-simplify the driving task and this can result in decreased alertness. Driving behaviour is consequently impaired and drivers are then more likely to be involved in road crashes. This is particularly dangerous on highways where the speed limit is high. While effective countermeasures to this decrement in alertness do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behaviour in real-time. The aim of this study is to evaluate in real-time the level of alertness of the driver through surrogate measures that can be collected from in-vehicle sensors. Slow EEG activity is used as a reference to evaluate driver's alertness. Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). Four different types of highways (driving scenario of 40 minutes each) are implemented through the variation of the road design (amount of curves and hills) and the roadside environment (amount of buildings and traffic). We show with Neural Networks that reduced alertness can be detected in real-time with an accuracy of 92% using lane positioning, steering wheel movement, head rotation, blink frequency, heart rate variability and skin conductance level. Such results show that it is possible to assess driver's alertness with surrogate measures. Such methodology could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring in real-time drivers' behaviour on highways, and therefore it could result in improved road safety.