974 resultados para total energy intake


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Risk variants of the fat-mass and obesity-associated (FTO) gene have been associated with increased obesity. However, the evidence for associations between FTO genotype and macronutrients intake has not been reviewed systematically. Our aim was to evaluate potential associations between FTO genotype and intakes of total energy, fat, carbohydrate and protein. We undertook a systematic literature search in Medline, Scopus, EMBASE and Cochrane of associations between macronutrients intake and FTO genotype in adults. Beta coefficients and confidence intervals were used for per-allele comparisons. Random-effects models assessed the pooled effect sizes. We identified 56 eligible studies reporting on 213 173 adults. For each copy of the FTO risk allele, individuals reported 6.46 kcal/day (95% CI: 10.76, 2.16) lower total energy intake (P=0.003). Total fat (P=0.028) and protein (P=0.006), but not carbohydrate intakes, were higher in those carrying the FTO risk allele. After adjustment for body weight, total energy intakes remained significantly lower in individuals with the FTO risk genotype (P=0.028). The FTO risk allele is associated with a lower reported total energy intake and with altered patterns of macronutrients intake. Although significant, these differences are small and further research is needed to determine whether the associations are independent of dietary misreporting.

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Risk variants of fat mass and obesity-associated (FTO) gene have been associated with increased obesity. However, the evidence for associations between FTO genotype and macronutrient intake has not been reviewed systematically. Our aim was to evaluate the potential associations between FTO genotype and intakes of total energy, fat, carbohydrate and protein. We undertook a systematic literature search in OVID MEDLINE, Scopus, EMBASE and Cochrane of associations between macronutrient intake and FTO genotype in adults. Beta coefficients and confidence intervals (CIs) were used for per allele comparisons. Random-effect models assessed the pooled effect sizes. We identified 56 eligible studies reporting on 213,173 adults. For each copy of the FTO risk allele, individuals reported 6.46 kcal day(-1) (95% CI: 10.76, 2.16) lower total energy intake (P = 0.003). Total fat (P = 0.028) and protein (P = 0.006), but not carbohydrate intakes, were higher in those carrying the FTO risk allele. After adjustment for body weight, total energy intakes remained significantly lower in individuals with the FTO risk genotype (P = 0.028). The FTO risk allele is associated with a lower reported total energy intake and with altered patterns of macronutrient intake. Although significant, these differences are small and further research is needed to determine whether the associations are independent of dietary misreporting.

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PURPOSE: The aim of this study was to further evaluate the validity and clinical meaningfulness of appetite sensations to predict overall energy intake as well as body weight loss. METHODS: Men (n=176) and women (n=139) involved in six weight loss studies were selected to participate in this study. Visual analogue scales were used to measure appetite sensations before and after a fixed test meal. Fasting appetite sensations, 1 h post-prandial area under the curve (AUC) and the satiety quotient (SQ) were used as predictors of energy intake and body weight loss. Two separate measures of energy intake were used: a buffet style ad libitum test lunch and a three-day self-report dietary record. RESULTS: One-hour post-prandial AUC for all appetite sensations represented the strongest predictors of ad libitum test lunch energy intake (p0.001). These associations were more consistent and pronounced for women than men. Only SQ for fullness was associated with ad libitum test lunch energy intake in women. Similar but weaker relationships were found between appetite sensations and the 3-day self-reported energy intake. Weight loss was associated with changes in appetite sensations (p0.01) and the best predictors of body weight loss were fasting desire to eat; hunger; and PFC (p0.01). CONCLUSIONS: These results demonstrate that appetite sensations are relatively useful predictors of spontaneous energy intake, free-living total energy intake and body weight loss. They also confirm that SQ for fullness predicts energy intake, at least in women.

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Background It is evident from previous research that the role of dietary composition in relation to the development of childhood obesity remains inconclusive. Several studies investigating the relationship between body mass index (BMI), waist circumference (WC) and/or skin fold measurements with energy intake have suggested that the macronutrient composition of the diet (protein, carbohydrate, fat) may play an important contributing role to obesity in childhood as it does in adults. This study investigated the possible relationship between BMI and WC with energy intake and percentage energy intake from macronutrients in Australian children and adolescents. Methods Height, weight and WC measurements, along with 24 h food and drink records (FDR) intake data were collected from 2460 boys and girls aged 5-17 years living in the state of Queensland, Australia. Results Statistically significant, yet weak correlations between BMI z-score and WC with total energy intake were observed in grades 1, 5 and 10, with only 55% of subjects having a physiologically plausible 24 hr FDR. Using Pearson correlations to examine the relationship between BMI and WC with energy intake and percentage macronutrient intake, no significant correlations were observed between BMI z-score or WC and percentage energy intake from protein, carbohydrate or fat. One way ANOVAs showed that although those with a higher BMI z-score or WC consumed significantly more energy than their lean counterparts. Conclusion No evidence of an association between percentage macronutrient intake and BMI or WC was found. Evidently, more robust longitudinal studies are needed to elucidate the relationship linking obesity and dietary intake.

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There is debate over the casual factors for the rise in body weight in the UK. The present study investigates whether increases between 1986 and 2000 for men and women were a result of increases in mean total energy intake, decreases in mean physical activity levels or both. Estimates of mean total energy intake in 1986 and 2000 were derived from food availability data adjusted for wastage. Estimates of mean body weight for adults aged 19–64 years were derived from nationally representative dietary surveys conducted in 1986–7 and 2000–1. Predicted body weight in 1986 and 2000 was calculated using an equation relating body weight to total energy intake and sex. Differences in predicted mean body weight and actual mean body weight between the two time points were compared. Monte Carlo simulation methods were used to assess the stability of the estimates. The predicted increase in mean body weight due to changes in total energy intake between 1986 and 2000 was 4·7 (95 % credible interval 4·2, 5·3) kg for men and 6·4 (95 % credible interval 5·9, 7·1) kg for women. Actual mean body weight increased by 7·7 kg for men and 5·4 kg for women between the two time points. We conclude that increases in mean total energy intake are sufficient to explain the increase in mean body weight for women between 1986 and 2000, but for men, the increase in mean body weight is likely to be due to a combination of increased total energy intake and reduced physical activity levels.

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Objective: To assess the effect of graded increases in exercised-induced energy expenditure (EE) on appetite, energy intake (EI), total daily EE and body weight in men living in their normal environment and consuming their usual diets. Design: Within-subject, repeated measures design. Six men (mean (s.d.) age 31.0 (5.0) y; weight 75.1 (15.96) kg; height 1.79 (0.10) m; body mass index (BMI) 23.3(2.4) kg/m2), were each studied three times during a 9 day protocol, corresponding to prescriptions of no exercise, (control) (Nex; 0 MJ/day), medium exercise level (Mex; ~1.6 MJ/day) and high exercise level (Hex; ~3.2 MJ/day). On days 1-2 subjects were given a medium fat (MF) maintenance diet (1.6 ´ resting metabolic rate (RMR)). Measurements: On days 3-9 subjects self-recorded dietary intake using a food diary and self-weighed intake. EE was assessed by continual heart rate monitoring, using the modified FLEX method. Subjects' HR (heart rate) was individually calibrated against submaximal VO2 during incremental exercise tests at the beginning and end of each 9 day study period. Respiratory exchange was measured by indirect calorimetry. Subjects completed hourly hunger ratings during waking hours to record subjective sensations of hunger and appetite. Body weight was measured daily. Results: EE amounted to 11.7, 12.9 and 16.8 MJ/day (F(2,10)=48.26; P<0.001 (s.e.d=0.55)) on the Nex, Mex and Hex treatments, respectively. The corresponding values for EI were 11.6, 11.8 and 11.8 MJ/day (F(2,10)=0.10; P=0.910 (s.e.d.=0.10)), respectively. There were no treatment effects on hunger, appetite or body weight, but there was evidence of weight loss on the Hex treatment. Conclusion: Increasing EE did not lead to compensation of EI over 7 days. However, total daily EE tended to decrease over time on the two exercise treatments. Lean men appear able to tolerate a considerable negative energy balance, induced by exercise, over 7 days without invoking compensatory increases in EI.

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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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Understanding the relationship between diet, physical activity and health in humans requires accurate measurement of body composition and daily energy expenditure. Stable isotopes provide a means of measuring total body water and daily energy expenditure under free-living conditions. While the use of isotope ratio mass spectrometry (IRMS) for the analysis of 2H (Deuterium) and 18O (Oxygen-18) is well established in the field of human energy metabolism research, numerous questions remain regarding the factors which influence analytical and measurement error using this methodology. This thesis was comprised of four studies with the following emphases. The aim of Study 1 was to determine the analytical and measurement error of the IRMS with regard to sample handling under certain conditions. Study 2 involved the comparison of TEE (Total daily energy expenditure) using two commonly employed equations. Further, saliva and urine samples, collected at different times, were used to determine if clinically significant differences would occur. Study 3 was undertaken to determine the appropriate collection times for TBW estimates and derived body composition values. Finally, Study 4, a single case study to investigate if TEE measures are affected when the human condition changes due to altered exercise and water intake. The aim of Study 1 was to validate laboratory approaches to measure isotopic enrichment to ensure accurate (to international standards), precise (reproducibility of three replicate samples) and linear (isotope ratio was constant over the expected concentration range) results. This established the machine variability for the IRMS equipment in use at Queensland University for both TBW and TEE. Using either 0.4mL or 0.5mL sample volumes for both oxygen-18 and deuterium were statistically acceptable (p>0.05) and showed a within analytical variance of 5.8 Delta VSOW units for deuterium, 0.41 Delta VSOW units for oxygen-18. This variance was used as “within analytical noise” to determine sample deviations. It was also found that there was no influence of equilibration time on oxygen-18 or deuterium values when comparing the minimum (oxygen-18: 24hr; deuterium: 3 days) and maximum (oxygen-18: and deuterium: 14 days) equilibration times. With regard to preparation using the vacuum line, any order of preparation is suitable as the TEE values fall within 8% of each other regardless of preparation order. An 8% variation is acceptable for the TEE values due to biological and technical errors (Schoeller, 1988). However, for the automated line, deuterium must be assessed first followed by oxygen-18 as the automated machine line does not evacuate tubes but merely refills them with an injection of gas for a predetermined time. Any fractionation (which may occur for both isotopes), would cause a slight elevation in the values and hence a lower TEE. The purpose of the second and third study was to investigate the use of IRMS to measure the TEE and TBW of and to validate the current IRMS practices in use with regard to sample collection times of urine and saliva, the use of two TEE equations from different research centers and the body composition values derived from these TEE and TBW values. Following the collection of a fasting baseline urine and saliva sample, 10 people (8 women, 2 men) were dosed with a doubly labeled water does comprised of 1.25g 10% oxygen-18 and 0.1 g 100% deuterium/kg body weight. The samples were collected hourly for 12 hrs on the first day and then morning, midday, and evening samples were collected for the next 14 days. The samples were analyzed using an isotope ratio mass spectrometer. For the TBW, time to equilibration was determined using three commonly employed data analysis approaches. Isotopic equilibration was reached in 90% of the sample by hour 6, and in 100% of the sample by hour 7. With regard to the TBW estimations, the optimal time for urine collection was found to be between hours 4 and 10 as to where there was no significant difference between values. In contrast, statistically significant differences in TBW estimations were found between hours 1-3 and from 11-12 when compared with hours 4-10. Most of the individuals in this study were in equilibrium after 7 hours. The TEE equations of Prof Dale Scholler (Chicago, USA, IAEA) and Prof K.Westerterp were compared with that of Prof. Andrew Coward (Dunn Nutrition Centre). When comparing values derived from samples collected in the morning and evening there was no effect of time or equation on resulting TEE values. The fourth study was a pilot study (n=1) to test the variability in TEE as a result of manipulations in fluid consumption and level of physical activity; the magnitude of change which may be expected in a sedentary adult. Physical activity levels were manipulated by increasing the number of steps per day to mimic the increases that may result when a sedentary individual commences an activity program. The study was comprised of three sub-studies completed on the same individual over a period of 8 months. There were no significant changes in TBW across all studies, even though the elimination rates changed with the supplemented water intake and additional physical activity. The extra activity may not have sufficiently strenuous enough and the water intake high enough to cause a significant change in the TBW and hence the CO2 production and TEE values. The TEE values measured show good agreement based on the estimated values calculated on an RMR of 1455 kcal/day, a DIT of 10% of TEE and activity based on measured steps. The covariance values tracked when plotting the residuals were found to be representative of “well-behaved” data and are indicative of the analytical accuracy. The ratio and product plots were found to reflect the water turnover and CO2 production and thus could, with further investigation, be employed to identify the changes in physical activity.

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The idea of body weight regulation implies that a biological mechanism exerts control over energy expenditure and food intake. This is a central tenet of energy homeostasis. However, the source and identity of the controlling mechanism have not been identified, although it is often presumed to be some long-acting signal related to body fat, such as leptin. Using a comprehensive experimental platform, we have investigated the relationship between biological and behavioural variables in two separate studies over a 12-week intervention period in obese adults (total n 92). All variables have been measured objectively and with a similar degree of scientific control and precision, including anthropometric factors, body composition, RMR and accumulative energy consumed at individual meals across the whole day. Results showed that meal size and daily energy intake (EI) were significantly correlated with fat-free mass (FFM, P values ,0·02–0·05) but not with fat mass (FM) or BMI (P values 0·11–0·45) (study 1, n 58). In study 2 (n 34), FFM (but not FM or BMI) predicted meal size and daily EI under two distinct dietary conditions (high-fat and low-fat). These data appear to indicate that, under these circumstances, some signal associated with lean mass (but not FM) exerts a determining effect over self-selected food consumption. This signal may be postulated to interact with a separate class of signals generated by FM. This finding may have implications for investigations of the molecular control of food intake and body weight and for the management of obesity.

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Feed samples received by commercial analytical laboratories are often undefined or mixed varieties of forages, originate from various agronomic or geographical areas of the world, are mixtures (e.g., total mixed rations) and are often described incompletely or not at all. Six unified single equation approaches to predict the metabolizable energy (ME) value of feeds determined in sheep fed at maintenance ME intake were evaluated utilizing 78 individual feeds representing 17 different forages, grains, protein meals and by-product feedstuffs. The predictive approaches evaluated were two each from National Research Council [National Research Council (NRC), Nutrient Requirements of Dairy Cattle, seventh revised ed. National Academy Press, Washington, DC, USA, 2001], University of California at Davis (UC Davis) and ADAS (Stratford, UK). Slopes and intercepts for the two ADAS approaches that utilized in vitro digestibility of organic matter and either measured gross energy (GE), or a prediction of GE from component assays, and one UC Davis approach, based upon in vitro gas production and some component assays, differed from both unity and zero, respectively, while this was not the case for the two NRC and one UC Davis approach. However, within these latter three approaches, the goodness of fit (r(2)) increased from the NRC approach utilizing lignin (0.61) to the NRC approach utilizing 48 h in vitro digestion of neutral detergent fibre (NDF:0.72) and to the UC Davis approach utilizing a 30 h in vitro digestion of NDF (0.84). The reason for the difference between the precision of the NRC procedures was the failure of assayed lignin values to accurately predict 48 h in vitro digestion of NDF. However, differences among the six predictive approaches in the number of supporting assays, and their costs, as well as that the NRC approach is actually three related equations requiring categorical description of feeds (making them unsuitable for mixed feeds) while the ADAS and UC Davis approaches are single equations, suggests that the procedure of choice will vary dependent Upon local conditions, specific objectives and the feedstuffs to be evaluated. In contrast to the evaluation of the procedures among feedstuffs, no procedure was able to consistently discriminate the ME values of individual feeds within feedstuffs determined in vivo, suggesting that the quest for an accurate and precise ME predictive approach among and within feeds, may remain to be identified. (C) 2004 Elsevier B.V. All rights reserved.

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Objective Underreporting of energy intake is prevalent in food surveys, but there is controversy about which dietary assessment method provides greater underreporting rates. Our objective is to compare validity of self-reported energy intake obtained by three dietary assessment methods with total energy expenditure (TEE) obtained by doubly labeled water (DLW) among Brazilian women. Design We used a cross-sectional study. Subjects/setting Sixty-five females aged 18 to 57 years (28 normal-weight, 10 over-weight, and 27 obese) were recruited from two universities to participate. Main outcome measures TEE determined by DLW, energy intake estimated by three 24-hour recalls, 3-day food record, and a food frequency questionnaire (FFQ). Statistical analyses performed Regression and analysis of variance with repeated measures compared TEE and energy intake values, and energy intake-to-TEE ratios and energy intake-TEE values between dietary assessment methods. Bland and Altman plots were provided for each method. chi(2) test compared proportion of underreporters between the methods. Results Mean TEE was 2,622 kcal (standard deviation [SD] =490 kcal), while mean energy intake was 2,078 kcal (SD=430 kcal) for the diet recalls; 2,044 kcal (SD=479 kcal) for the food record and 1,984 kcal (SD=832 kcal) for the FFQ (all energy intake values significantly differed from TEE; P<0.0001). Bland and Altman plots indicated great dispersion, negative mean differences between measurements, and wide limits of agreement. Obese subjects underreported more than normal-weight subjects in the diet recalls and in the food records, but not in the FFQ. Years of education, income and ethnicity were associated with reporting accuracy. Conclusions The FFQ produced greater under- and overestimation of energy intake. Underreporting of energy intake is a serious and prevalent error in dietary self-reports provided by Brazilian women, as has been described in studies conducted in developed countries.

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The aim of the present study was to determine whether under-reporting rates vary between dietary pattern Clusters. Subjects were sixty-five Brazilian women. During 3 weeks, anthropometric data were collected. total energy expenditure (TEE) was determined by the doubly labelled water method and diet Was Measured. Energy intake (El) and the daily frequency of consumption per 1000 kJ of twenty-two food groups were obtained from a FFQ. These frequencies were entered into a Cluster analysis procedure in order to obtain dietary patterns. Under-reporters were defined Lis those who did not lose more than 1 kg of body weight during the study and presented EI:TEE less than 0.82. Three dietary pattern clusters were identified and named according to their most recurrent food groups: sweet foods (SW). starchy foods (ST) and health), (H). Subjects from the healthy cluster had the lowest mean EI:TEE (SW = 0.86, ST = 0.71 and H = 0.58: P = 0.003) and EI - TEE (SW = -0.49 MJ, ST = - 3.20 MJ and H = -5.09 MJ; P = 0.008). The proportion of Under-reporters was 45.2 (95 % CI 35.5, 55.0) % in the SW Cluster: 58.3 (95 % CI 48.6, 68.0) % in the ST Cluster and 70.0 (95 % CI 61.0, 79) % in the H cluster (P=0.34). Thus, in Brazilian women, Under-reporting of El is not uniformly distributed among, dietary pattern clusters and tends to be more severe among subjects from the healthy cluster. This cluster is more consistent with both dietary guidelines and with what lay individuals usually consider `healthy eating`.

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Objectives: The energy density (ED) of the diet is considered an important determinant of total energy intake and thus energy balance and weight change. We aimed to compare relationships between ED and macronutrient content in individual food and beverage items as well as population diet in a typical Western country. Design: Nutrient data for 3673 food items and 247 beverage items came from the Australian Food and Nutrient database (AusNut). Food and beverage intake data came from the 1995 Australian National Nutrition Survey (a 24-h dietary recall survey in 13 858 people over the age of 2). Relationships between ED and macronutrient and water content were analysed by linear regression with 95% prediction bands. Results: For both individual food items and population food intake, there was a positive relationship between ED and percent energy as fat and negative relationships between ED and percent energy as carbohydrate and percent water by weight. In all cases, there was close agreement between the slopes of the regression lines between food items and dietary intake. There were no clear relationships between ED and macronutrient content for beverage items. Carbohydrate (mostly sucrose) contributed 91, 47, and 25% of total energy for sugar-based, fat-based, and alcohol-based beverages respectively. Conclusions: The relationship between ED and fat content of foods holds true across both population diets and individual food items available in the food supply in a typical Western country such as Australia. As high-fat diets are associated with a high BMI, population measures with an overall aim of reducing the ED of diets may be effective in mediating the growing problem of overweight and obesity.

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Background: The utility of fatty acids (FAs) as biomarkers of total fat intake is unknown.

Objective: We compared FA changes in red cells (RCs), plasma phospholipids (PLs), and cholesterol esters (CEs) in response to a low-fat diet (LFD) and a moderate-fat diet (MFD) and assessed whether individual or combination of FAs predict LFD.

Design: Postmenopausal women (n = 66) were randomly assigned to receive an LFD (17% of energy from fat) or an MFD (34% of energy from fat) for 6 wk. All foods were provided. FAs in diets and blood were determined by gas-liquid chromatography. FA changes between baseline and end of study were compared across diets by using t tests. FA predictors of an LFD were selected by logistic regression.

Results: Many FAs in RCs, PLs, and CEs responded differently to the 2 diets. Changes from baseline with an LFD for palmitic acid (16:0) (3–11% increase), behenic (22:0) and lignoceric (24:0) acids (3–20% decrease, in RCs and PLs only), cis-monounsaturated FA (MUFA) (25–35% increase), linoleic acid (18:2n–6) (11–13% decrease), trans octadecanoic acids (trans 18:1) (7–20% decrease), and n–6 highly unsaturated FA (HUFA) (2–8% increase) were significantly different from changes with an MFD. Individually, 18:2n–6 and trans 18:1 were strong predictors of an LFD [receiver operating characteristic (ROC) curves: 0.92–0.80). A logistic regression model with trans 18:1, 18:2n–6, and vaccenic acid (18:1n–7) predicted an LFD with high specificity and sensitivity (ROC curves: 0.99).

Conclusions: Saturated FA, cisMUFA, n–6 HUFA, and exogenous FAs greatly differed in their response to the LFD and MFD. Parallel responses were observed in RCs, PLs, and CEs. A model with a combination of FAs almost perfectly differentiated the consumption of 34% fat from that of 17% fat.