Zur Ermittlung des Energieverbrauches bei Mensch und Tier stehen verschiedene Methoden zur Verfügung. Im Jahre 1780 nutzte Lavoisier die Schmelzwassermenge, um den Energieverlust eines Meerschweinchens zu berechnen. Das Tier saß in einem von Eis umgebenen Kalorimeter, die von ihm abgegebene Wärme brachte das Eis zum Schmelzen. Derzeit sind die indirekte Kalorimetrie, die den Energieumsatz über den im Respirationsversuch gemessenen Gaswechsel von O2 und CO2 sowie die im Harn ausgeschiedene Stickstoffmenge bestimmt, und die Isotopendilutionsmethode, die mit der unterschiedlichen Ausscheidungsrate von markierten Wasserstoff- (2H) und Sauerstoff- (18O) Atomen im Urin arbeitet, der „Goldstandard“ für die Bestimmung des Energieverbrauchs. Seit einigen Jahren bis heute steht die Herzfrequenzmethode in der Diskussion. Sie nutzt die Beziehung zwischen Herzfrequenz und Sauerstoffverbrauch zur Ermittlung des Energieumsatzes. Alle genannten Methoden haben Vor- und Nachteile, insbesondere für den einfachen und schnellen täglichen Einsatz sowie bei Langzeitstudien. Deshalb werden Alternativen gesucht. Diese Dissertation untersucht die Beziehung zwischen der akzelerometrisch erfassten dreidimensionalen Körperbeschleunigung und der Herzfrequenz beim Pferd in verschiedenen Gangarten. Dabei wird die Herzfrequenz als Vergleichs- und Bezugsgröße verwendet. Sie stellt das direkte Bindeglied zum Sauerstoffverbrauch und damit Energieaufwand dar. Es wurden drei Versuchsvarianten durchgeführt. Die Pferde gingen an der Hand, „geführt“, liefen frei in einem umzäunten Oval, „freilaufend“, oder wurden „geritten“. Bei den beiden Varianten „geführt“ und „freilaufend“ kamen jeweils dieselben vier Pferde zum Einsatz, die Variante „geritten“ absolvierten fünf andere Tiere. Die Versuche folgten verschiedenen Schemata mit den Gangarten Schritt, Trab und, zum Teil, Galopp. Bei allen Versuchen wurden parallel die dreidimensionale Körperbeschleunigung mit einer Frequenz von 32 Hz sowie die Herzfrequenz gemessen. Die Pulsuhr speicherte im kleinstmöglichen Intervall von fünf Sekunden. Nach Aufbereitung der Beschleunigungsrohdaten wurde letztendlich der dynamische Anteil der dreidimensionalen Beschleunigung in Form von „fünf-Sekunden-Mittelwerten“ berechnet. Anschließend wurden diese Beschleunigungswerte über die Regressionsanalyse mit den Originalwerten der Herzfrequenz in Beziehung gesetzt. Dabei wurden die Übergangsphasen zwischen den Gangarten ausgenommen, da die beiden Parameter hier ein sehr unterschiedliches und zeitversetztes Verhalten zeigen. Bei der Analyse der Gangarten Schritt und Trab konnte gut mit dem Modell der einfachen linearen Regression (y = a + bx) gearbeitet werden, mit Hinzukommen der dritten Gangart, Galopp, erwies sich das Modell der polynomialen Regression (y = a + bx + cx²) von Vorteil. Die Stärke des Zusammenhanges der beiden Größen wurde durch den Korrelationskoeffizienten r angezeigt. Bei differenzierter Betrachtung der Versuchsvarianten und der einzelnen Pferde erreichte r Werte von 0,86 bis 0,94, bei zusammenfassender Betrachtung aller Pferde einer Versuchsvariante Werte zwischen 0,82 und 0,87, stets bei signifikanter Korrelation (p < 0,05). Somit kann für die Parameter Herzfrequenz und Beschleunigung ein signifikanter und starker Zusammenhang beschrieben werden. Sie verhalten sich dabei nicht proportional zueinander. Schlussfolgernd lässt sich sagen, dass die Akzelerometrie für bestimmte Zielstellungen und unter bestimmten Voraussetzungen eine geeignete Methode ist, um den Energieaufwand von Pferden zu bestimmen. Sie ist schnell und meist störungsfrei durchzuführen und im Gegensatz zur Herzfrequenz nahezu unabhängig von emotionalen Einflüssen. Des Weiteren bietet die Akzelerometrie die Möglichkeit, die Ermittlung des Energieumsatzes mit einer Verhaltensanalyse zu kombinieren. Bedingungen für ihren Einsatz sind eine situationsspezifische und möglichst individuelle Kalibrierung, denn die Beschleunigungsmessung weist insofern Nachteile auf, als dass sie die Auswirkungen von zum Beispiel Bodenbeschaffenheit, Umwelteinflüssen oder das Tragen einer Last auf den Energieumsatz nicht berücksichtigt. Die parallele Erfassung von Herzfrequenz und Beschleunigung kann zum Beispiel zur Analyse und Kontrolle von Trainingserfolgen genutzt werden. Somit bringt die Kombination von Herzfrequenz- und Beschleunigungsmessung klare Vorteile. / There are different opportunities to determine the consumption of energy in humans and animals. In 1780 Lavoisier used the quantity of melt water to calculate the energy loss of a guinea pig. The guinea pig was located inside a calorimeter which was surrounded by ice. The emitted heat induced the melting of the ice. At present both, indirect calorimetry that estimates energy expenditure from respiratory measurements of oxygen consumption and carbon dioxide production plus the excretion of nitrogen with the urine and the DLW-method that uses the different urinary elimination rates of the isotopes 2H and 18O are the so called “golden standard” for the calculation of energy consumption. For several years until now there has been a discussion about the heart rate-method. This method uses the correlation between heart rate and oxygen consumption for the calculation of energy expenditure. All above mentioned methods have pros and cons, especially for simple and quick every day application and for long-term studies. Therefore alternatives are searched. This dissertation examines the relation between the accelerometricly measured three-dimensional body acceleration and the heart rate in horses at different gaits. The heart rate has been used for comparison and as a reference item. It directly relates the acceleration with the oxygen consumption and thus with the energy expenditure. There have been three variants of trials. Horses were led by the hand (HD), moved freely (MF) in an enclosed oval or were ridden (R). In the HD- and MF-trials the same four horses were used, for the R-trials five other horses came into action. The trials followed different schemes with the gaits of walk, trot and gallop. At every trial three-dimensional body-acceleration with a logging frequency of 32 Hz and heart rate were measured simultaneously. The heart rate meter stored the heart rate in the smallest possible intervals of five seconds. After processing the crude data the dynamic part of the three-dimensional acceleration was calculated in form of “five-second-means”. After that the regression analysis was used to relate these acceleration data to the original heart rate data. In this process the transitional phases between the gaits were excluded because there both parameters have a highly varying and time-shifted relation. The model of simple linear regression (y = a + bx) suited well for analysing walking and trotting. With adding the third gait gallop the model of polynomial regression (y = a + bx + cx²) became more favourable. The correlation coefficient r showed the strength of the correlation between both parameters. By the separate inspection of the variants of trials and the individual horses r reached values from 0,86 to 0,94; pooling all horses of each variant of trials yields r-values from 0,82 to 0,87, always with a significant correlation (p < 0,05). Hence a significant and strong correlation can be attributed to the parameters heart rate and acceleration. They are not proportional to each other. In conclusion one can say: for specific aims and under certain conditions the accelerometry is an appropriate method to assess energy expenditure in horses. You can implement it quickly and mostly disturbance-free and in contrast to the heart rate it is nearly independent of emotional influence. Furthermore accelerometry gives the opportunity to combine the determination of the energy expenditure with the analysis of behaviour. A possibly individual and situation-specific calibration are the preconditions for its application. A setback of the accelerometry is that the effects of such factors like the condition of the ground, environmental influences or carrying weights are not taken into consideration. Simultaneous measurement of heart rate and body-acceleration can for example be used for analysing and controlling the success of training. Consequently there are clear advantages of combining the measurement of heart rate and acceleration.

Being able to effectively match energy intake to energy expenditure (EE) is an important aspect in preventing weight re-gain in the post-obese. Although it is generally agreed upon that resting EE decreases concomitantly with weight loss, there is no set standard comparing the deviations with differing weight loss protocols and additionally, controversy remains as to whether this decrease is greater than can predicted. In order to address these issues 2977 subjects were analyzed using a systematic review and the differences of both the protocol and length of various interventions in addition to sex were compared. Next, data was selected from this systematic review and 815 subjects were analyzed for weight loss-induced changes in resting EE, FM and FFM. Another subgroup of studies (n = 1450) was analyzed and compared against the Harris-Benedict prediction equation to determine whether the changes in resting EE were greater than what was expected. Finally, in order to determine which factors may be involved in regulating changes in resting EE during weight loss, a secondary analysis was performed on 28 post-menopausal women (age= 50.4 ± 2.0 yrs; BMI= 32.4 ± 5.2 kg/m²) who were submitted to a 6-month caloric restriction. Body composition (DXA), resting EE (indirect calorimetry), physical activity EE (PAEE) and total EE (TEE) (doubly-labelled water) were measured before and after the 6 month weight loss. Blood samples were collected before and after to measure leptin and peptide YY. The results indicate that there was indeed a depression in resting EE during weight loss regardless of the type of intervention utilized. Furthermore, these findings suggest that the changes could not fully be explained by changes of FM and FFM alone and that leptin may be an important contributor to the changes of resting EE during weight loss.

The stride interval of typical human gait is correlated over thousands of strides. This statistical persistence diminishes with age, disease, and pace-constrained walking. Considering the widespread use of treadmills in rehabilitation and research, it is important to understand the effect of this speed-constrained locomotor modality on stride interval dynamics. To this end, and given that the dynamics of children have been largely unexplored, this study investigated the impact of treadmill walking, both with and without handrail use, on paediatric stride interval dynamics. An initial stationarity analysis of stride interval time series identified both non-stationary and stationary signals during all walking conditions. Subsequent scaling analysis revealed diminished stride interval persistence during unsupported treadmill walking compared to overground walking. Finally, while the correlation between stride interval dynamics and gross energy expenditure was investigated in an effort to elucidate the clinical meaning of persistence, no simple linear correlation was found.

Technological advances in physical activity measurement have increased the development and utilization of accelerometers and pedometers for assessing physical activity in controlled and free-living conditions. Individual differences in leg length, stride length and stride frequency may affect the reliability and validity of accelerometers in estimating energy expenditure. To address this theory, this thesis investigated the influence of leg length, stride length and stride frequency on accelerometer counts and energy expenditure using four accelerometers (AMP, Actical, MTI, and RT3) and one pedometer (Yamax). Eighty-six participants, age 8 to 40 (17.6 ± 8.0) years performed three ten-minute bouts of treadmill activity at self-selected speeds (4 to 12 km/h). Energy expenditure (kcal/min) was measured through expired gas analysis and used as the criterion standard to compare physical activity data from activity monitors. A 3 (models) x 2 (duplicates of each model) x 3 (speeds) x 7 (minutes) repeated measures ANOVA was used to assess intra-device, inter-device, and inter-model reliability. Coefficients of variation were calculated to compare within-device variation and between-device variation in accelerometer counts. Differences between measured and predicted energy expenditure were assessed across five height categories to determine the influence of leg length on the validity of accelerometer/pedometer data. Regression equations for each model were developed using mean activity counts/steps generated for each speed, adjusting for various predictor variables (i.e., age, weight, leg length). These were compared to model-specific equations to determine whether the addition of certain variables might explain more variance in energy expenditure. Leg length and stride frequency directly influenced variability in accelerometer data and thus predicted energy expenditure. At high speeds and stride frequencies counts began to level off in the Actical, however this did not occur in the other devices. Intra-device and inter-device variation in accelerometer counts was less than 10% and was lowest at very high speeds for the Actical, MTI, and RT3 (p<0.05). When compared to measured values, energy expenditure was consistently underestimated by the AMP, Actical, and Yamax models and consistently overestimated by the RT3 across speed. The MTI underestimated and overestimated energy expenditure depending on speed. Energy expenditure was both underestimated and overestimated to the greatest extent during the treadmill run for the tallest participants (p<0.05). Accelerometer counts or pedometer steps, when entered into regression equations with age, weight and leg length, explained from 85 to 94 % of the variance in measured energy expenditure, supporting the inclusion of these variables within manufacturer-based equations. These results suggest that individual differences in leg length and stride frequency affect the reliability and validity of accelerometer data and therefore must be controlled for when using accelerometry to predict energy expenditure.

The stride interval of typical human gait is correlated over thousands of strides. This statistical persistence diminishes with age, disease, and pace-constrained walking. Considering the widespread use of treadmills in rehabilitation and research, it is important to understand the effect of this speed-constrained locomotor modality on stride interval dynamics. To this end, and given that the dynamics of children have been largely unexplored, this study investigated the impact of treadmill walking, both with and without handrail use, on paediatric stride interval dynamics. An initial stationarity analysis of stride interval time series identified both non-stationary and stationary signals during all walking conditions. Subsequent scaling analysis revealed diminished stride interval persistence during unsupported treadmill walking compared to overground walking. Finally, while the correlation between stride interval dynamics and gross energy expenditure was investigated in an effort to elucidate the clinical meaning of persistence, no simple linear correlation was found.

Being able to effectively match energy intake to energy expenditure (EE) is an important aspect in preventing weight re-gain in the post-obese. Although it is generally agreed upon that resting EE decreases concomitantly with weight loss, there is no set standard comparing the deviations with differing weight loss protocols and additionally, controversy remains as to whether this decrease is greater than can predicted. In order to address these issues 2977 subjects were analyzed using a systematic review and the differences of both the protocol and length of various interventions in addition to sex were compared. Next, data was selected from this systematic review and 815 subjects were analyzed for weight loss-induced changes in resting EE, FM and FFM. Another subgroup of studies (n = 1450) was analyzed and compared against the Harris-Benedict prediction equation to determine whether the changes in resting EE were greater than what was expected. Finally, in order to determine which factors may be involved in regulating changes in resting EE during weight loss, a secondary analysis was performed on 28 post-menopausal women (age= 50.4 ± 2.0 yrs; BMI= 32.4 ± 5.2 kg/m²) who were submitted to a 6-month caloric restriction. Body composition (DXA), resting EE (indirect calorimetry), physical activity EE (PAEE) and total EE (TEE) (doubly-labelled water) were measured before and after the 6 month weight loss. Blood samples were collected before and after to measure leptin and peptide YY. The results indicate that there was indeed a depression in resting EE during weight loss regardless of the type of intervention utilized. Furthermore, these findings suggest that the changes could not fully be explained by changes of FM and FFM alone and that leptin may be an important contributor to the changes of resting EE during weight loss.

Technological advances in physical activity measurement have increased the development and utilization of accelerometers and pedometers for assessing physical activity in controlled and free-living conditions. Individual differences in leg length, stride length and stride frequency may affect the reliability and validity of accelerometers in estimating energy expenditure. To address this theory, this thesis investigated the influence of leg length, stride length and stride frequency on accelerometer counts and energy expenditure using four accelerometers (AMP, Actical, MTI, and RT3) and one pedometer (Yamax). Eighty-six participants, age 8 to 40 (17.6 ± 8.0) years performed three ten-minute bouts of treadmill activity at self-selected speeds (4 to 12 km/h). Energy expenditure (kcal/min) was measured through expired gas analysis and used as the criterion standard to compare physical activity data from activity monitors. A 3 (models) x 2 (duplicates of each model) x 3 (speeds) x 7 (minutes) repeated measures ANOVA was used to assess intra-device, inter-device, and inter-model reliability. Coefficients of variation were calculated to compare within-device variation and between-device variation in accelerometer counts. Differences between measured and predicted energy expenditure were assessed across five height categories to determine the influence of leg length on the validity of accelerometer/pedometer data. Regression equations for each model were developed using mean activity counts/steps generated for each speed, adjusting for various predictor variables (i.e., age, weight, leg length). These were compared to model-specific equations to determine whether the addition of certain variables might explain more variance in energy expenditure. Leg length and stride frequency directly influenced variability in accelerometer data and thus predicted energy expenditure. At high speeds and stride frequencies counts began to level off in the Actical, however this did not occur in the other devices. Intra-device and inter-device variation in accelerometer counts was less than 10% and was lowest at very high speeds for the Actical, MTI, and RT3 (p<0.05). When compared to measured values, energy expenditure was consistently underestimated by the AMP, Actical, and Yamax models and consistently overestimated by the RT3 across speed. The MTI underestimated and overestimated energy expenditure depending on speed. Energy expenditure was both underestimated and overestimated to the greatest extent during the treadmill run for the tallest participants (p<0.05). Accelerometer counts or pedometer steps, when entered into regression equations with age, weight and leg length, explained from 85 to 94 % of the variance in measured energy expenditure, supporting the inclusion of these variables within manufacturer-based equations. These results suggest that individual differences in leg length and stride frequency affect the reliability and validity of accelerometer data and therefore must be controlled for when using accelerometry to predict energy expenditure.

This investigation examined acute energy compensation and macronutrient intake in habitually active and sedentary, college-aged males, following an exercise session as compared to a resting (control) session, to see if habitually active males compensate intake better to an energy deficit incurred by exercise, than sedentary males. Participants were males, aged 18-30 years, of a normal percent body fat and body mass index, and exercised < 60 min per week (sedentary) or > 150 min per week (habitually active). Participants came in for two sessions: 1) 45 minutes of resting (control) and then eating an ad libitum meal; and 2) riding a cycle ergometer for 45 minutes (exercise) and then eating an ad libitum meal. Sessions were counterbalanced across participants. Energy and macronutrient intake were calculated for the meal and over the remaining part of the day. Sedentary individuals ate significantly less during the meal in the exercise session (which expended a mean of 453.5 kcals across both groups) as compared to the control session (934.8 + 222.0 kcals vs. 1073.9 + 470.3 kcals, p < 0.03), which demonstrated negative energy compensation (-30.6%). The habitually active group showed no significant difference in energy intake between sessions at the meal (1016.8 + 396.7 kcal [control] vs. 1105.6 + 389.2 kcal [exercise]). While the habitually active group showed no significant difference in intake at the meal, the slight increase in intake at the meal in the exercise session demonstrated some energy compensation (19.6%), which was significantly better (p < 0.03) than that in the sedentary group. No differences in macronutrient intake at the meal were found between the sessions. Over the day following the sessions, both groups reported a significant increase in energy intake after the exercise session as compared to the control session (1457.5 + 646.2 kcals vs. 1356.1 + 657.2 kcals, p < 0.04), with no difference in macronutrient intake between the sessions. These results indicate that, although complete acute compensation did not occur, the habitually active group acutely compensated intake significantly more so than the sedentary group, demonstrating better energy regulation ability.

No description available.

Various research studies have indicated that the prevalence of overweight and obesity among children and adolescents has increased worldwide and has, therefore, become a serious health problem. Besides the various health implications of childhood obesity, it can also have psychological consequences for these children and they have a greater risk than a normal weight child to suffer from poor self perception. The effect of a physical activity, diet and behaviour modification intervention on the total energy expenditure, physical activity levels and self perception of 9 to 12 year old overweight and obese children is, however, not clear. The aim of the study was firstly to determine the effect of a physical activity, diet and behaviour modification intervention on the total energy expenditure and physical activity levels of 9 to 12 year old overweight and obese children. Secondly, to determine the effect of such an intervention on the self perception, and more specifically athletic and physical self perception of these children. An availability sample of 20 overweight and obese subjects (13 girls and 7 boys) between the ages of 9 and 12 years with a mean age of 11 years, participated in a 13 week (3 times/week) multidisciplinary intervention programme. Actical® monitors were used to monitor energy expenditure as well as physical activity levels during 2 weekdays and 1 weekend day before and after the intervention programme. From the results, analyzed by means of t-testing and linear regression, it is apparent that the total energy expenditure of the group, when adjusted for the effect of the intervention, showed a significant increase (p < 0.05) and body fat percentage as well as waist and upper arm circumferences decreased significantly. Although not significant, a decrease of 2,9 kg in body mass and 2,00 kg.rh" in body mass index were also indicated. However, the moderate and high intensity physical activity levels of the groups decreased significantly after the intervention programme. A possible reason for this decrease can be ascribed to the fact that the post-test took place during the school holidays. Further analysis of the data also indicated that the group slept longer hours, which increased their hours spent in the sedentary activity zone. The group also spent more time during the day watching television which also contributed to a decrease in the percentage of time spent in the moderate intensity zone. It is, however, concluded that increased total energy expenditure alone could not bring about effective weight loss and must, therefore, be accompanied by activity in the moderate and high intensity zones. For the purpose of the second aim, twenty children (13 girls and 7 boys) between the ages of 9 and 12 years, with a mean age of 11 years, participated in a 13 week multidisciplinary intervention programme (3 times per week). Eighteen children (11 girls and 7 boys) between the ages of 9 and 12 years, with a mean age of 11 years, served as a control group. Self perception, which consisted of 6 subcomponents, was determined by using the Harter Scale for Self Perception (Harter, 1985). It is clear from the results of the t-test (p < 0.05) that all subcomponents of self perception of the experimental group, especially physical, athletic and global self perception, increased significantly in relation to the control group which remained the same in all the subcomponents (p > 0.05), while a decrease in their social self perception was noted (p < 0.05). The experimental and control group did not differ significantly before the intervention programme, therefore the significant differences with regard to the subcomponents during the post-test, confirm the effect of the programme. On the basis of the abovementioned results the assumption can be made that a multidisciplinary intervention programme holds various benefits for overweight and obese children and is, therefore, another strategy in the prevention of overweight and obesity in children in South Africa. A multidisciplinary intervention programme, as used in this programme, is not only advantageous for weight loss in overweight and obese children, but also significantly improves their self perception. / Thesis (M.Sc. (Human Movement Science))--North-West University, Potchefstroom Campus, 2009.