403 resultados para Energy Intake


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Background To determine whether changes in appetite and energy intake (EI) can be detected and play a role in the effectiveness of interventions, it is necessary to identify their variability under normal conditions. We assessed the reproducibility of subjective appetite ratings and ad libitum test meal EI after a standardised pre-load in overweight and obese males. Methods Fifteen overweight and obese males (BMI 30.3 ± 4.9 kg/m2, aged 34.9 ± 10.6 years) completed two identical test days, 7 days apart. Participants were provided with a standardised fixed breakfast (1676 kJ) and 5 h later an ad libitum pasta lunch. An electronic appetite rating system was used to assess subjective ratings before and after the fixed breakfast, and periodically during the postprandial period. EI was assessed at the ad libitum lunch meal. Sample size estimates for paired design studies were calculated. Results Appetite ratings demonstrated a consistent oscillating pattern between test days, and were more reproducible for mean postprandial than fasting ratings. The correlation between ad libitum EI on the two test days was r = 0.78 (P < 0.01). Using a paired design and a power of 0.8, a minimum of 12 participants would be needed to detect a 10 mm change in 5 h postprandial mean ratings and 17 to detect a 500 kJ difference in ad libitum EI. Conclusion Intra-individual variability of appetite and ad libitum test meal EI in overweight and obese males is comparable to previous reports in normal weight adults. Sample size requirements for studies vary depending on the parameter of interest and sensitivity needed.

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Abstract PURPOSE: Compensatory responses may attenuate the effectiveness of exercise training in weight management. The aim of this study was to compare the effect of moderate- and high-intensity interval training on eating behavior compensation. METHODS: Using a crossover design, 10 overweight and obese men participated in 4-week moderate (MIIT) and high (HIIT) intensity interval training. MIIT consisted of 5-min cycling stages at ± 20% of mechanical work at 45%VO(2)peak, and HIIT consisted of alternate 30-s work at 90%VO(2)peak and 30-s rests, for 30 to 45 min. Assessments included a constant-load exercise test at 45%VO(2)peak for 45 min followed by 60-min recovery. Appetite sensations were measured during the exercise test using a Visual Analog Scale. Food preferences (liking and wanting) were assessed using a computer-based paradigm, and this paradigm uses 20 photographic food stimuli varying along two dimensions, fat (high or low) and taste (sweet or nonsweet). An ad libitum test meal was provided after the constant-load exercise test. RESULTS: Exercise-induced hunger and desire to eat decreased after HIIT, and the difference between MIIT and HIIT in desire to eat approached significance (p = .07). Exercise-induced liking for high-fat nonsweet food tended to increase after MIIT and decreased after HIIT (p = .09). Fat intake decreased by 16% after HIIT, and increased by 38% after MIIT, with the difference between MIIT and HIIT approaching significance (p = .07). CONCLUSIONS: This study provides evidence that energy intake compensation differs between MIIT and HIIT.

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Exercise is known to cause physiological changes that could affect the impact of nutrients on appetite control. This study was designed to assess the effect of drinks containing either sucrose or high-intensity sweeteners on food intake following exercise. Using a repeated-measures design, three drink conditions were employed: plain water (W), a low-energy drink sweetened with artificial sweeteners aspartame and acesulfame-K (L), and a high-energy, sucrose-sweetened drink (H). Following a period of challenging exercise (70% VO2 max for 50 min), subjects consumed freely from a particular drink before being offered a test meal at which energy and nutrient intakes were measured. The degree of pleasantness (palatability) of the drinks was also measured before and after exercise. At the test meal, energy intake following the artificially sweetened (L) drink was significantly greater than after water and the sucrose (H) drinks (p < 0.05). Compared with the artificially sweetened (L) drink, the high-energy (H) drink suppressed intake by approximately the energy contained in the drink itself. However, there was no difference between the water (W) and the sucrose (H) drink on test meal energy intake. When the net effects were compared (i.e., drink + test meal energy intake), total energy intake was significantly lower after the water (W) drink compared with the two sweet (L and H) drinks. The exercise period brought about changes in the perceived pleasantness of the water, but had no effect on either of the sweet drinks. The remarkably precise energy compensation demonstrated after the higher energy sucrose drink suggests that exercise may prime the system to respond sensitively to nutritional manipulations. The results may also have implications for the effect on short-term appetite control of different types of drinks used to quench thirst during and after exercise.

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Given the present worldwide epidemic of obesity, it is pertinent to ask how effective exercise could be in helping people to lose weight or to prevent weight gain. There is a widely held belief that exercise is futile for weight reduction because any energy expended in exercise is automatically compensated for by a corresponding increase in energy intake (EI). In other words, exercise elevates the intensity of hunger and drives food consumption. This “commonsense” view appears to originate in an energy-balance model of appetite control, which stipulates that energy expended will drive EI as a consequence of the regulation of energy balance. However, it is very clear that EI (food consumption or eating) is not just a biological matter. Eating does not occur solely to rectify some internal need state. Indeed, an examination of the relation between exercise and appetite control has shown a very weak coupling; most studies have demonstrated that food intake does not immediately rise after exercise, even after very high energy expenditure (EE).[1] The processes of exercise-induced EE and food consumption do not appear to be tightly linked. After exercise, there is only slow and partial compensation for the energy expended. Therefore, exercise can be very useful in helping to bring about weight loss and is even more important in preventing weight gain or weight regain. This editorial explores this issue.

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The objective of this investigation was to compare the acute effects of exercise and diet manipulations on energy intake, between dietary restrained and unrestrained females. Comparisons of two studies using an identical 2 x 2 repeated-measures design (level of activity (rest or exercise) and lunch type (high-fat or low-fat)) including thirteen dietary unrestrained and twelve restrained females were performed. Energy expenditure during the rest session was estimated and the energy cost of exercise was measured by indirect calorimetry. Relative energy intake was calculated by subtracting the energy expenditure of the exercise session from the energy intake of the test meal. Post-meal hedonic ratings were completed after lunch. Energy intake and relative energy intake increased during high-fat conditions compared with the low-fat, independently of exercise (P < 0.001). There was a positive relationship between dietary restraint scores and energy intake or relative energy intake in the rest conditions only (r 0.54, P < 0.01). The decrease of relative energy intake between the rest and exercise conditions was higher in restrained than in unrestrained eaters (P < 0.01). These results confirm that a high-fat diet reversed the energy deficit due to exercise. There was no energy compensation in response to an acute bout of exercise during the following meal. In restrained eaters, exercise was more effective in creating an energy deficit than in unrestrained eaters. Exercise may help restrained eaters to maintain control over appetite.

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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.

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Nutrition interventions in the form of both self-management education and individualised diet therapy are considered essential for the long-term management of type 2 diabetes mellitus (T2DM). The measurement of diet is essential to inform, support and evaluate nutrition interventions in the management of T2DM. Barriers inherent within health care settings and systems limit ongoing access to personnel and resources, while traditional prospective methods of assessing diet are burdensome for the individual and often result in changes in typical intake to facilitate recording. This thesis investigated the inclusion of information and communication technologies (ICT) to overcome limitations to current approaches in the nutritional management of T2DM, in particular the development, trial and evaluation of the Nutricam dietary assessment method (NuDAM) consisting of a mobile phone photo/voice application to assess nutrient intake in a free-living environment with older adults with T2DM. Study 1: Effectiveness of an automated telephone system in promoting change in dietary intake among adults with T2DM The effectiveness of an automated telephone system, Telephone-Linked Care (TLC) Diabetes, designed to deliver self-management education was evaluated in terms of promoting dietary change in adults with T2DM and sub-optimal glycaemic control. In this secondary data analysis independent of the larger randomised controlled trial, complete data was available for 95 adults (59 male; mean age(±SD)=56.8±8.1 years; mean(±SD)BMI=34.2±7.0kg/m2). The treatment effect showed a reduction in total fat of 1.4% and saturated fat of 0.9% energy intake, body weight of 0.7 kg and waist circumference of 2.0 cm. In addition, a significant increase in the nutrition self-efficacy score of 1.3 (p<0.05) was observed in the TLC group compared to the control group. The modest trends observed in this study indicate that the TLC Diabetes system does support the adoption of positive nutrition behaviours as a result of diabetes self-management education, however caution must be applied in the interpretation of results due to the inherent limitations of the dietary assessment method used. The decision to use a close-list FFQ with known bias may have influenced the accuracy of reporting dietary intake in this instance. This study provided an example of the methodological challenges experienced with measuring changes in absolute diet using a FFQ, and reaffirmed the need for novel prospective assessment methods capable of capturing natural variance in usual intakes. Study 2: The development and trial of NuDAM recording protocol The feasibility of the Nutricam mobile phone photo/voice dietary record was evaluated in 10 adults with T2DM (6 Male; age=64.7±3.8 years; BMI=33.9±7.0 kg/m2). Intake was recorded over a 3-day period using both Nutricam and a written estimated food record (EFR). Compared to the EFR, the Nutricam device was found to be acceptable among subjects, however, energy intake was under-recorded using Nutricam (-0.6±0.8 MJ/day; p<0.05). Beverages and snacks were the items most frequently not recorded using Nutricam; however forgotten meals contributed to the greatest difference in energy intake between records. In addition, the quality of dietary data recorded using Nutricam was unacceptable for just under one-third of entries. It was concluded that an additional mechanism was necessary to complement dietary information collected via Nutricam. Modifications to the method were made to allow for clarification of Nutricam entries and probing forgotten foods during a brief phone call to the subject the following morning. The revised recording protocol was evaluated in Study 4. Study 3: The development and trial of the NuDAM analysis protocol Part A explored the effect of the type of portion size estimation aid (PSEA) on the error associated with quantifying four portions of 15 single foods items contained in photographs. Seventeen dietetic students (1 male; age=24.7±9.1 years; BMI=21.1±1.9 kg/m2) estimated all food portions on two occasions: without aids and with aids (food models or reference food photographs). Overall, the use of a PSEA significantly reduced mean (±SD) group error between estimates compared to no aid (-2.5±11.5% vs. 19.0±28.8%; p<0.05). The type of PSEA (i.e. food models vs. reference food photograph) did not have a notable effect on the group estimation error (-6.7±14.9% vs. 1.4±5.9%, respectively; p=0.321). This exploratory study provided evidence that the use of aids in general, rather than the type, was more effective in reducing estimation error. Findings guided the development of the Dietary Estimation and Assessment Tool (DEAT) for use in the analysis of the Nutricam dietary record. Part B evaluated the effect of the DEAT on the error associated with the quantification of two 3-day Nutricam dietary records in a sample of 29 dietetic students (2 males; age=23.3±5.1 years; BMI=20.6±1.9 kg/m2). Subjects were randomised into two groups: Group A and Group B. For Record 1, the use of the DEAT (Group A) resulted in a smaller error compared to estimations made without the tool (Group B) (17.7±15.8%/day vs. 34.0±22.6%/day, p=0.331; respectively). In comparison, all subjects used the DEAT to estimate Record 2, with resultant error similar between Group A and B (21.2±19.2%/day vs. 25.8±13.6%/day; p=0.377 respectively). In general, the moderate estimation error associated with quantifying food items did not translate into clinically significant differences in the nutrient profile of the Nutricam dietary records, only amorphous foods were notably over-estimated in energy content without the use of the DEAT (57kJ/day vs. 274kJ/day; p<0.001). A large proportion (89.6%) of the group found the DEAT helpful when quantifying food items contained in the Nutricam dietary records. The use of the DEAT reduced quantification error, minimising any potential effect on the estimation of energy and macronutrient intake. Study 4: Evaluation of the NuDAM The accuracy and inter-rater reliability of the NuDAM to assess energy and macronutrient intake was evaluated in a sample of 10 adults (6 males; age=61.2±6.9 years; BMI=31.0±4.5 kg/m2). Intake recorded using both the NuDAM and a weighed food record (WFR) was coded by three dietitians and compared with an objective measure of total energy expenditure (TEE) obtained using the doubly labelled water technique. At the group level, energy intake (EI) was under-reported to a similar extent using both methods, with the ratio of EI:TEE was 0.76±0.20 for the NuDAM and 0.76±0.17 for the WFR. At the individual level, four subjects reported implausible levels of energy intake using the WFR method, compared to three using the NuDAM. Overall, moderate to high correlation coefficients (r=0.57-0.85) were found across energy and macronutrients except fat (r=0.24) between the two dietary measures. High agreement was observed between dietitians for estimates of energy and macronutrient derived for both the NuDAM (ICC=0.77-0.99; p<0.001) and WFR (ICC=0.82-0.99; p<0.001). All subjects preferred using the NuDAM over the WFR to record intake and were willing to use the novel method again over longer recording periods. This research program explored two novel approaches which utilised distinct technologies to aid in the nutritional management of adults with T2DM. In particular, this thesis makes a significant contribution to the evidence base surrounding the use of PhRs through the development, trial and evaluation of a novel mobile phone photo/voice dietary record. The NuDAM is an extremely promising advancement in the nutritional management of individuals with diabetes and other chronic conditions. Future applications lie in integrating the NuDAM with other technologies to facilitate practice across the remaining stages of the nutrition care process.

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BACKGROUND: Malnutrition, and poor intake during hospitalisation, are common in older medical patients. Better understanding of patient-specific factors associated with poor intake may inform nutritional interventions. AIMS: To measure the proportion of older medical patients with inadequate nutritional intake, and identify patient-related factors associated with this outcome. METHODS: Prospective cohort study enrolling consecutive consenting medical inpatients aged 65 years or older. Primary outcome was energy intake less than resting energy expenditure estimated using weight-based equations. Energy intake was calculated for a single day using direct observation of plate waste. Explanatory variables included age, gender, number of co-morbidities, number of medications, diagnosis, usual residence, nutritional status, functional and cognitive impairment, depressive symptoms, poor appetite, poor dentition, and dysphagia. RESULTS: Of 134 participants (mean age 80 years, 51% female), only 41% met estimated resting energy requirements. Mean energy intake was 1220 kcal/day (SD 440), or 18.1 kcal/kg/day. Factors associated with inadequate energy intake in multivariate analysis were poor appetite, higher BMI, diagnosis of infection or cancer, delirium and need for assistance with feeding. CONCLUSIONS: Inadequate nutritional intake is common, and patient factors contributing to poor intake need to be considered in nutritional interventions.

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Background & Aims: Inadequate feeding assistance and mealtime interruptions during hospitalisation may contribute to malnutrition and poor nutritional intake in older people. This study aimed to implement and compare three interventions designed to specifically address mealtime barriers and improve energy intakes of medical inpatients aged ≥65 years. Methods: Pre-post study compared three mealtime assistance interventions: PM: Protected Mealtimes with multidisciplinary education; AIN: additional assistant-in-nursing (AIN) with dedicated meal role; PM+AIN: combined intervention. Dietary intake of 254 patients (pre: n=115, post: n=141; mean age 80±8) was visually estimated on a single day in the first week of hospitalisation and compared with estimated energy requirements. Assistance activities were observed and recorded. Results: Mealtime assistance levels significantly increased in all interventions (p<0.01). Post-intervention participants were more likely to achieve adequate energy intake (OR=3.4, p=0.01), with no difference noted between interventions (p=0.29). Patients with cognitive impairment or feeding dependency appeared to gain substantial benefit from mealtime assistance interventions. Conclusions: Protected Mealtimes and additional AIN assistance (implemented alone or in combination) may produce modest improvements in nutritional intake. Targeted feeding assistance for certain patient groups holds promise; however, alternative strategies are required to address the complex problem of malnutrition in this population.

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A long-running issue in appetite research concerns the influence of energy expenditure on energy intake. More than 50 years ago, Otto G. Edholm proposed that "the differences between the intakes of food [of individuals] must originate in differences in the expenditure of energy". However, a relationship between energy expenditure and energy intake within any one day could not be found, although there was a correlation over 2 weeks. This issue was never resolved before interest in integrative biology was replaced by molecular biochemistry. Using a psychobiological approach, we have studied appetite control in an energy balance framework using a multi-level experimental system on a single cohort of overweight and obese human subjects. This has disclosed relationships between variables in the domains of body composition [fat-free mass (FFM), fat mass (FM)], metabolism, gastrointestinal hormones, hunger and energy intake. In this Commentary, we review our own and other data, and discuss a new formulation whereby appetite control and energy intake are regulated by energy expenditure. Specifically, we propose that FFM (the largest contributor to resting metabolic rate), but not body mass index or FM, is closely associated with self-determined meal size and daily energy intake. This formulation has implications for understanding weight regulation and the management of obesity.

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Previously, expected satiety (ES) has been measured using software and two-dimensional pictures presented on a computer screen. In this context, ES is an excellent predictor of self-selected portions, when quantified using similar images and similar software. In the present study we sought to establish the veracity of ES as a predictor of behaviours associated with real foods. Participants (N = 30) used computer software to assess their ES and ideal portion of three familiar foods. A real bowl of one food (pasta and sauce) was then presented and participants self-selected an ideal portion size. They then consumed the portion ad libitum. Additional measures of appetite, expected and actual liking, novelty, and reward, were also taken. Importantly, our screen-based measures of expected satiety and ideal portion size were both significantly related to intake (p < .05). By contrast, measures of liking were relatively poor predictors (p > .05). In addition, consistent with previous studies, the majority (90%) of participants engaged in plate cleaning. Of these, 29.6% consumed more when prompted by the experimenter. Together, these findings further validate the use of screen-based measures to explore determinants of portion-size selection and energy intake in humans.

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Diet Induced Thermogenesis (DIT) is the energy expended consequent to meal consumption, and reflects the energy required for the processing and digestion of food consumed throughout each day. Although DIT is the total energy expended across a day in digestive processes to a number of meals, most studies measure thermogenesis in response to a single meal (Meal Induced Thermogenesis: MIT) as a representation of an individual’s thermogenic response to acute food ingestion. As a component of energy expenditure, DIT may have a contributing role in weight gain and weight loss. While the evidence is inconsistent, research has tended to reveal a suppressed MIT response in obese compared to lean individuals, which identifies individuals with an efficient storage of food energy, hence a greater tendency for weight gain. Appetite is another factor regulating body weight through its influence on energy intake. Preliminary research has shown a potential link between MIT and postprandial appetite as both are responses to food ingestion and have a similar response dependent upon the macronutrient content of food. There is a growing interest in understanding how both MIT and appetite are modified with changes in diet, activity levels and body size. However, the findings from MIT research have been highly inconsistent, potentially due to the vastly divergent protocols used for its measurement. Therefore, the main theme of this thesis was firstly, to address some of the methodological issues associated with measuring MIT. Additionally this thesis aimed to measure postprandial appetite simultaneously to MIT to test for any relationships between these meal-induced variables and to assess changes that occur in MIT and postprandial appetite during periods of energy restriction (ER) and following weight loss. Two separate studies were conducted to achieve these aims. Based on the increasing prevalence of obesity, it is important to develop accurate methodologies for measuring the components potentially contributing to its development and to understand the variability within these variables. Therefore, the aim of Study One was to establish a protocol for measuring the thermogenic response to a single test meal (MIT), as a representation of DIT across a day. This was done by determining the reproducibility of MIT with a continuous measurement protocol and determining the effect of measurement duration. The benefit of a fixed resting metabolic rate (RMR), which is a single measure of RMR used to calculate each subsequent measure of MIT, compared to separate baseline RMRs, which are separate measures of RMR measured immediately prior to each MIT test meal to calculate each measure of MIT, was also assessed to determine the method with greater reproducibility. Subsidiary aims were to measure postprandial appetite simultaneously to MIT, to determine its reproducibility between days and to assess potential relationships between these two variables. Ten healthy individuals (5 males, 5 females, age = 30.2 ± 7.6 years, BMI = 22.3 ± 1.9 kg/m2, %Fat Mass = 27.6 ± 5.9%) undertook three testing sessions within a 1-4 week time period. During the first visit, participants had their body composition measured using DXA for descriptive purposes, then had an initial 30-minute measure of RMR to familiarise them with the testing and to be used as a fixed baseline for calculating MIT. During the second and third testing sessions, MIT was measured. Measures of RMR and MIT were undertaken using a metabolic cart with a ventilated hood to measure energy expenditure via indirect calorimetry with participants in a semi-reclined position. The procedure on each MIT test day was: 1) a baseline RMR measured for 30 minutes, 2) a 15-minute break in the measure to consume a standard 576 kcal breakfast (54.3% CHO, 14.3% PRO, 31.4% FAT), comprising muesli, milk toast, butter, jam and juice, and 3) six hours of measuring MIT with two, ten-minute breaks at 3 and 4.5 hours for participants to visit the bathroom. On the MIT test days, pre and post breakfast then at 45-minute intervals, participants rated their subjective appetite, alertness and comfort on visual analogue scales (VAS). Prior to each test, participants were required to be fasted for 12 hours, and have undertaken no high intensity physical activity for the previous 48 hours. Despite no significant group changes in the MIT response between days, individual variability was high with an average between-day CV of 33%, which was not significantly improved by the use of a fixed RMR to 31%. The 95% limits of agreements which ranged from 9.9% of energy intake (%EI) to -10.7%EI with the baseline RMRs and between 9.6%EI to -12.4%EI with the fixed RMR, indicated very large changes relative to the size of the average MIT response (MIT 1: 8.4%EI, 13.3%EI; MIT 2: 8.8%EI, 14.7%EI; baseline and fixed RMRs respectively). After just three hours, the between-day CV with the baseline RMR was 26%, which may indicate an enhanced MIT reproducibility with shorter measurement durations. On average, 76, 89, and 96% of the six-hour MIT response was completed within three, four and five hours, respectively. Strong correlations were found between MIT at each of these time points and the total six-hour MIT (range for correlations r = 0.990 to 0.998; P < 0.01). The reproducibility of the proportion of the six-hour MIT completed at 3, 4 and 5 hours was reproducible (between-day CVs ≤ 8.5%). This indicated the suitability to use shorter durations on repeated occasions and a similar percent of the total response to be completed. There was a lack of strong evidence of any relationship between the magnitude of the MIT response and subjective postprandial appetite. Given a six-hour protocol places a considerable burden on participants, these results suggests that a post-meal measurement period of only three hours is sufficient to produce valid information on the metabolic response to a meal. However while there was no mean change in MIT between test days, individual variability was large. Further research is required to better understand which factors best explain the between-day variability in this physiological measure. With such a high prevalence of obesity, dieting has become a necessity to reduce body weight. However, during periods of ER, metabolic and appetite adaptations can occur which may impede weight loss. Understanding how metabolic and appetite factors change during ER and weight loss is important for designing optimal weight loss protocols. The purpose of Study Two was to measure the changes in the MIT response and subjective postprandial appetite during either continuous (CONT) or intermittent (INT) ER and following post diet energy balance (post-diet EB). Thirty-six obese male participants were randomly assigned to either the CONT (Age = 38.6 ± 7.0 years, weight = 109.8 ± 9.2 kg, % fat mass = 38.2 ± 5.2%) or INT diet groups (Age = 39.1 ± 9.1 years, weight = 107.1 ± 12.5 kg, % fat mass = 39.6 ± 6.8%). The study was divided into three phases: a four-week baseline (BL) phase where participants were provided with a diet to maintain body weight, an ER phase lasting either 16 (CONT) or 30 (INT) weeks, where participants were provided with a diet which supplied 67% of their energy balance requirements to induce weight loss and an eight-week post-diet EB phase, providing a diet to maintain body weight post weight loss. The INT ER phase was delivered as eight, two-week blocks of ER interspersed with two-week blocks designed to achieve weight maintenance. Energy requirements for each phase were predicted based on measured RMR, and adjusted throughout the study to account for changes in RMR. All participants completed MIT and appetite tests during BL and the ER phase. Nine CONT and 15 INT participants completed the post-diet EB MIT and 14 INT and 15 CONT participants completed the post-diet EB appetite tests. The MIT test day protocol was as follows: 1) a baseline RMR measured for 30 minutes, 2) a 15-minute break in the measure to consume a standard breakfast meal (874 kcal, 53.3% CHO, 14.5% PRO, 32.2% FAT), and 3) three hours of measuring MIT. MIT was calculated as the energy expenditure above the pre-meal RMR. Appetite test days were undertaken on a separate day using the same 576 kcal breakfast used in Study One. VAS were used to assess appetite pre and post breakfast, at one hour post breakfast then a further three times at 45-minute intervals. Appetite ratings were calculated for hunger and fullness as both the intra-meal change in appetite and the AUC. The three-hour MIT response at BL, ER and post-diet EB respectively were 5.4 ± 1.4%EI, 5.1 ± 1.3%EI and 5.0 ± 0.8%EI for the CONT group and 4.4 ± 1.0%EI, 4.7 ± 1.0%EI and 4.8 ± 0.8%EI for the INT group. Compared to BL, neither group had significant changes in their MIT response during ER or post-diet EB. There were no significant time by group interactions (p = 0.17) indicating a similar response to ER and post-diet EB in both groups. Contrary to what was hypothesised, there was a significant increase in postprandial AUC fullness in response to ER in both groups (p < 0.05). However, there were no significant changes in any of the other postprandial hunger or fullness variables. Despite no changes in MIT in both the CONT or INT group in response to ER or post-diet EB and only a minor increase in postprandial AUC fullness, the individual changes in MIT and postprandial appetite in response to ER were large. However those with the greatest MIT changes did not have the greatest changes in postprandial appetite. This study shows that postprandial appetite and MIT are unlikely to be altered during ER and are unlikely to hinder weight loss. Additionally, there were no changes in MIT in response to weight loss, indicating that body weight did not influence the magnitude of the MIT response. There were large individual changes in both variables, however further research is required to determine whether these changes were real compensatory changes to ER or simply between-day variation. Overall, the results of this thesis add to the current literature by showing the large variability of continuous MIT measurements, which make it difficult to compare MIT between groups and in response to diet interventions. This thesis was able to provide evidence to suggest that shorter measures may provide equally valid information about the total MIT response and can therefore be utilised in future research in order to reduce the burden of long measurements durations. This thesis indicates that MIT and postprandial subjective appetite are most likely independent of each other. This thesis also shows that, on average, energy restriction was not associated with compensatory changes in MIT and postprandial appetite that would have impeded weight loss. However, the large inter-individual variability supports the need to examine individual responses in more detail.

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Traditionally, infectious diseases and under-nutrition have been considered major health problems in Sri Lanka with little attention paid to obesity and associated non-communicable diseases (NCDs). However, the recent Sri Lanka Diabetes and Cardiovascular Study (SLDCS) reported the epidemic level of obesity, diabetes and metabolic syndrome. Moreover, obesity-associated NCDs is the leading cause of death in Sri Lanka and there is an exponential increase in hospitalization due to NCDs adversely affecting the development of the country. Despite Sri Lanka having a very high prevalence of NCDs and associated mortality, little is known about the causative factors for this burden. It is widely believed that the global NCD epidemic is associated with recent lifestyle changes, especially dietary factors. In the absence of sufficient data on dietary habits in Sri Lanka, successful interventions to manage these serious health issues would not be possible. In view of the current situation the dietary survey was undertaken to assess the intakes of energy, macro-nutrients and selected other nutrients with respect to socio demographic characteristics and the nutritional status of Sri Lankan adults especially focusing on obesity. Another aim of this study was to develop and validate a culturally specific food frequency questionnaire (FFQ) to assess dietary risk factors of NCDs in Sri Lankan adults. Data were collected from a subset of the national SLDCS using a multi-stage, stratified, random sampling procedure (n=500). However, data collection in the SLDCS was affected by the prevailing civil war which resulted in no data being collected from Northern and Eastern provinces. To obtain a nationally representative sample, additional subjects (n=100) were later recruited from the two provinces using similar selection criteria. Ethical Approval for this study was obtained from the Ethical Review Committee, Faculty of Medicine, University of Colombo, Sri Lanka and informed consent was obtained from the subjects before data were collected. Dietary data were obtained using the 24-h Dietary Recall (24HDR) method. Subjects were asked to recall all foods and beverages, consumed over the previous 24-hour period. Respondents were probed for the types of foods and food preparation methods. For the FFQ validation study, a 7-day weight diet record (7-d WDR) was used as the reference method. All foods recorded in the 24 HDR were converted into grams and then intake of energy and nutrients were analysed using NutriSurvey 2007 (EBISpro, Germany) which was modified for Sri Lankan food recipes. Socio-demographic details and body weight perception were collected from interviewer-administrated questionnaire. BMI was calculated and overweight (BMI ≥23 kg.m-2), obesity (BMI ≥25 kg.m-2) and abdominal obesity (Men: WC ≥ 90 cm; Women: WC ≥ 80 cm) were categorized according to Asia-pacific anthropometric cut-offs. The SPSS v. 16 for Windows and Minitab v10 were used for statistical analysis purposes. From a total of 600 eligible subjects, 491 (81.8%) participated of whom 34.5% (n=169) were males. Subjects were well distributed among different socio-economic parameters. A total of 312 different food items were recorded and nutritionists grouped similar food items which resulted in a total of 178 items. After performing step-wise multiple regression, 93 foods explained 90% of the variance for total energy intake, carbohydrates, protein, total fat and dietary fibre. Finally, 90 food items and 12 photographs were selected. Seventy-seven subjects completed (response rate = 65%) the FFQ and 7-day WDR. Estimated mean energy intake (SD) from FFQ (1794±398 kcal) and 7DWR (1698±333 kcal, P<0.001) was significantly different due to a significant overestimation of carbohydrate (~10 g/d, P<0.001) and to some extent fat (~5 g/d, NS). Significant positive correlations were found between the FFQ and 7DWR for energy (r = 0.39), carbohydrate (r = 0.47), protein (r = 0.26), fat (r =0.17) and dietary fiber (r = 0.32). Bland-Altman graphs indicated fairly good agreement between methods with no relationship between bias and average intake of each nutrient examined. The findings from the nutrition survey showed on average, Sri Lankan adults consumed over 14 portions of starch/d; moreover, males consumed 5 more portions of cereal than females. Sri Lankan adults consumed on average 3.56 portions of added sugars/d. Moreover, mean daily intake of fruit (0.43) and vegetable (1.73) portions was well below minimum dietary recommendations (fruits 2 portions/d; vegetables 3 portions/d). The total fruit and vegetable intake was 2.16 portions/d. Daily consumption of meat or alternatives was 1.75 portions and the sum of meat and pulses was 2.78 portions/d. Starchy foods were consumed by all participants and over 88% met the minimum daily recommendations. Importantly, nearly 70% of adults exceeded the maximum daily recommendation for starch (11portions/d) and a considerable proportion consumed larger numbers of starch servings daily, particularly men. More than 12% of men consumed over 25 starch servings/d. In contrast to their starch consumption, participants reported very low intakes of other food groups. Only 11.6%, 2.1% and 3.5% of adults consumed the minimum daily recommended servings of vegetables, fruits, and fruits and vegetables combined, respectively. Six out of ten adult Sri Lankans sampled did not consume any fruits. Milk and dairy consumption was extremely low; over a third of the population did not consume any dairy products and less than 1% of adults consumed 2 portions of dairy/d. A quarter of Sri Lankans did not report consumption of meat and pulses. Regarding protein consumption, 36.2% attained the minimum Sri Lankan recommendation for protein; and significantly more men than women achieved the recommendation of ≥3 servings of meat or alternatives daily (men 42.6%, women 32.8%; P<0.05). Over 70% of energy was derived from carbohydrates (Male:72.8±6.4%, Female:73.9±6.7%), followed by fat (Male:19.9±6.1%, Female:18.5±5.7%) and proteins (Male:10.6±2.1%, Female:10.9±5.6%). The average intake of dietary fiber was 21.3 g/day and 16.3 g/day for males and females, respectively. There was a significant difference in nutritional intake related to ethnicities, areas of residence, education levels and BMI categories. Similarly, dietary diversity was significantly associated with several socio-economic parameters among Sri Lankan adults. Adults with BMI ≥25 kg.m-2 and abdominally obese Sri Lankan adults had the highest diet diversity values. Age-adjusted prevalence (95% confidence interval) of overweight, obesity, and abdominal obesity among Sri Lankan adults were 17.1% (13.8-20.7), 28.8% (24.8-33.1), and 30.8% (26.8-35.2), respectively. Men, compared with women, were less overweight, 14.2% (9.4-20.5) versus 18.5% (14.4-23.3), P = 0.03, less obese, 21.0% (14.9-27.7) versus 32.7% (27.6-38.2), P < .05; and less abdominally obese, 11.9% (7.4-17.8) versus 40.6% (35.1-46.2), P < .05. Although, prevalence of obesity has reached to epidemic level body weight misperception was common among Sri Lankan adults. Two-thirds of overweight males and 44.7% of females considered themselves as in "about right weight". Over one third of both male and female obese subjects perceived themselves as "about right weight" or "underweight". Nearly 32% of centrally obese men and women perceived that their waist circumference is about right. People who perceived overweight or very overweight (n = 154) only 63.6% tried to lose their body weight (n = 98), and quarter of adults seek advices from professionals (n = 39). A number of important conclusions can be drawn from this research project. Firstly, the newly developed FFQ is an acceptable tool for assessing the nutrient intake of Sri Lankans and will assist proper categorization of individuals by dietary exposure. Secondly, a substantial proportion of the Sri Lankan population does not consume a varied and balanced diet, which is suggestive of a close association between the nutrition-related NCDs in the country and unhealthy eating habits. Moreover, dietary diversity is positively associated with several socio-demographic characteristics and obesity among Sri Lankan adults. Lastly, although obesity is a major health issue among Sri Lankan adults, body weight misperception was common among underweight, healthy weight, overweight, and obese adults in Sri Lanka. Over 2/3 of overweight and 1/3 of obese Sri Lankan adults believe that they are in "right weight" or "under-weight" categories.

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Apparent per capita food and nutrient intake in six remote Australian Aboriginal communities using the ‘store-turnover’ method is described. The method is based on the analysis of community-store food invoices. The face validity of the method supports the notion that, under the unique circumstances of remote Aboriginal communities, the turnover of foodstuffs from the community store is a useful measure of apparent dietary intake for the community as a whole. In all Aboriginal communities studied, the apparent intake of energy, sugars and fat was excessive, while the apparent intake of dietary fibre and several nutrients, including folic acid, was low. White sugar, flour, bread and meat provided in excess of 50 per cent of the apparent total energy intake. Of the apparent high fat intake, fatty meats contributed nearly 40 per cent in northern coastal communities and over 60 per cent in central desert communities. Sixty per cent of the apparent high intake of sugars was derived from sugar per se in both regions. Compared with national Australian apparent consumption data, intakes of sugar, white flour and sweetened carbonated beverages were much higher in Aboriginal communities, and intakes of wholemeal bread, fruit and vegetables were much lower. Results of the store-turnover method have important implications for community-based nutrition intervention programs.

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Objective To describe the quantity and diversity of food and beverage intake in Australian children aged 12–16 months and to determine if the amount and type of milk intake is associated with dietary diversity. Methods Mothers participating in the NOURISH and South Australian Infant Dietary Intake (SAIDI) studies completed a single 24-hour recall of their child's food intake, when children (n=551) were aged 12–16 months. The relationship between dietary diversity and intake of cow's milk, formula or breastmilk was examined using one-way ANOVA. Results Dairy and cereal were the most commonly consumed food groups and the greatest contributors to daily energy intake. Most children ate fruit (87%) and vegetables (77%) on the day of the 24-hour recall while 91% ate discretionary items. Half the sample ate less than 30 g of meat/alternatives. A quarter of the children were breastfeeding while formula was consumed by 32% of the sample, providing 29% of daily energy intake. Lower dietary diversity was associated with increased formula intake. Conclusions The quality of dietary intake in this group of young children is highly variable. Most toddlers were consuming a diverse diet, though almost all ate discretionary items. The amount and type of meat/alternatives consumed was poor. Implications Health professionals should advise parents to offer iron-rich foods, while limiting discretionary choices and use of formula at an age critical in the development of long-term food preferences.