950 resultados para Energy intake


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To determine whether changes in dietary intakes predict weight loss, we studied 80 overweight adults who attended a nutritional counseling program during 6 months of follow-up at a primary health care center in Brazil. Habitual diet was assessed using a validated food frequency questionnaire at baseline and after 6 months. The mean age (+/-SD) of the participants was 46.5 +/- 9.5 years, and their mean body mass index was 29 +/- 3 kg/m(2) at baseline. After 6 months, the differences in body weight and fruit/vegetable intake were -1.4 +/- 3 kg and 109 +/- 320 g daily, respectively. Using multiple linear regression models adjusted for age, sex, changes in walking time, and total energy intake, the increased intake of dietary fiber from fruits/vegetables was associated with a greater weight loss (beta 1 [95% confidence interval (CI)] = -0.180 [-0.269, -0.0911) after 6 months of follow-up. Similar results were observed for increased intake of vegetables (beta 1 [95% CI] = -0.00497 [-0.008, -0.0021) and fruits (beta 1 [95% CI] = -0.00290 [-0.005, -0.001]) as predictors of weight loss. The increase of 100 g/d of vegetables and fruits represented a body weight loss of 500 and 300 g after 6 months, respectively (P <.05). Our findings support the relevance of increased intakes of fruits and vegetables that may help avoid weight gain in overweight adults. (C) 2008 Elsevier Inc. All rights reserved.

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Residents from high level (nursing homes) and low-level care facilities (hostel) being served the three common diet texture modifications (full diet, soft-minced diet and pureed diet) were assessed. Individual plate waste was estimated at three meals on one day. Fifty-six males and 156 females, mean age 82.9+/-9.5 (SD) years, of which 139 lived in nursing homes (NH) and 76 in hostels (H) were included. Mean total energy served from meals was 5.3 MJ/day, 5.1 to 5.6 MJ/day, 95% confidence intervals (CI), in NH which was less than in H, 5.9 MJ/day (CI 5.6 to 6.2 MJ/day) (P=0.007). Protein and calcium intakes were lower in NH, 44.5g (CI 41.5 to 47.5g), 359.0mg (CI 333.2 to 384.8mg), versus 50.5g (CI 46.6 to 54.3g), 480.5mg (CI 444.3 to 516.7mg) in H (P=0.017, P<0.001 respectively). There was no difference in nutrient/energy ratios, except for protein/energy, which was higher in NH 11.7 (CI 11.3 to 12.2) than in H 9.8 (CI 9.4 to 10.3) (P<0.001). Ability to self-feed had no significant effect on nutrient intakes in NH. The self fed group (N=63) had the following nutrient intakes: energy 4.0 MJ (CI 3.6 to 4.3 MJ), protein 44.6g (CI 40.3 to 48.9g), calcium 356.9mg (CI 316.3 to 397.4mg), fibre 14.9g (CI 13.2 to 16.5g). The assisted group (N=64) had the following nutrient intakes: energy 3.9MJ (CI 3.6 to 4.2MJ), protein 46.0g (CI 40.7 to 49.6), calcium 361.9mg (CI 327.8 to 396.1mg), fibre 14.9g (CI 13.2 to 16.1g). Of NH classified as eating impaired, 36% received no assistance with feeding and had lower intakes of protein 37.8g (CI 33.0 to 42.1g) compared to those receiving some assistance 46.1g (CI 41.3 to 50.9g) (P=0.026). Reduced energy intake accounted for the differences in nutrient intakes between nursing homes and hostels, except for protein. Strategies to effectively monitor nutrient intakes and to identify those with eating impairment are required in order to ensure adequate nutrition of residents in nursing homes and hostels.

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The present study examined whether replacing fat with inulin or lupin-kernel fibre influenced palatability, perceptions of satiety, and food intake in thirty-three healthy men (mean age 52 years, BMI 27·4 kg/m2), using a within-subject design. On separate occasions, after fasting overnight, the participants consumed a breakfast consisting primarily of either a full-fat sausage patty (FFP) or a reduced-fat patty containing inulin (INP) or lupin-kernel fibre (LKP). Breakfast variants were alike in mass, protein and carbohydrate content; however the INP and LKP breakfasts were 36 and 37 % lower in fat and 15 and 17 % lower in energy density respectively compared with the FFP breakfast. The participants rated their satiety before breakfast then evaluated patty acceptability. Satiety was rated immediately after consuming the breakfast, then over the subsequent 4·5 h whilst fasting. Food consumed until the end of the following day was recorded. All patties were rated above ‘neither acceptable or unacceptable’, however the INP rated lower for general acceptability (P=0·039) and the LKP lower for flavour (P=0·023) than the FFP. The LKP breakfast rated more satiating than the INP (P=0·010) and FFP (P=0·016) breakfasts. Total fat intake was 18 g lower on the day of the INP (P=0·035) and 26 g lower on the day of the LKP breakfast (P=0·013) than the FFP breakfast day. Energy intake was lower (1521 kJ) only on the day of the INP breakfast (P=0·039). Both inulin and lupin-kernel fibre appear to have potential as fat replacers in meat products and for reducing fat and energy intake in men.

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BACKGROUND: Estimating changes in weight from changes in energy balance is important for predicting the effect of obesity prevention interventions. OBJECTIVE: The objective was to develop and validate an equation for predicting the mean weight of a population of children in response to a change in total energy intake (TEI) or total energy expenditure (TEE). DESIGN: In 963 children with a mean (+/-SD) age of 8.1 +/- 2.8 y (range: 4-18 y) and weight of 31.5 +/- 17.6 kg, TEE was measured by using doubly labeled water. Log weight (dependent variable) and log TEE (independent variable) were analyzed in a linear regression model with height, age, and sex as covariates. It was assumed that points of dynamic balance, called "settling points," occur for populations wherein energy is in balance (TEE = TEI), weight is stable (ignoring growth), and energy flux (EnFlux) equals TEE. RESULTS: TEE (or EnFlux) explained 74% of the variance in weight. The unstandardized regression coefficient was 0.45 (95% CI: 0.38, 0.51; R(2) = 0.86) after including covariates. Conversion into proportional changes (time(1) to time(2)) gave the equation (weight(2)/weight(1)) = (EnFlux(2)/EnFlux(1))(0.45). In 3 longitudinal studies (n = 212; mean follow-up of 3.4 y), the equation predicted the mean follow-up measured weight to within 0.5%. CONCLUSIONS: The relation of EnFlux with weight was positive, which implied that a high TEI (rather than low physical activity and low TEE) was the main determinant of high body weight. Two populations of children with a 10% difference in mean EnFlux would have a 4.5% difference in mean weight.

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Objective: The aims of this study were to estimate average yearly weight gain in midage women and to identify the determinants of weight gain and gaining weight at double the average rate.
Research Methods and Procedures: The study sample comprised 8071 participants (45 to 55 years old) in the Australian Longitudinal Study on Women's Health who completed mailed surveys in 1996, 1998, and 2001.
Results: On average, the women gained almost 0.5 kg per year [average 2.42 kg (95% confidence interval, 2.29 to 2.54) over 5 years]. In multivariate analyses, variables associated with energy balance (physical activity, sitting time, and energy intake), as well as quitting smoking, menopause/hysterectomy, and baseline BMI category were significantly associated with weight gain, but other behavioral and demographic characteristics were not. After adjustment for all of the other biological and behavioral variables, the odds of gaining weight at about twice the average rate (>5 kg over 5 years) were highest for women who quit smoking (odds ratio = 2.94; 95% confidence interval, 2.17, 3.96). There were also independent relationships between the odds of gaining >5 kg and lower levels of habitual physical activity, more time spent sitting, energy intake (but only in women with BMI > 25 at baseline), menopause transition, and hysterectomy.
Discussion: The average weight gain equates with an energy imbalance of only about 10 kcal or 40 kJ per day, which suggests that small sustained changes in the modifiable behavioral variables could prevent further weight gain.


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Objective: To determine the plate waste, energy and selected-nutrient intake, from elderly residents living in a high-level care (HLC) and low-level care (LLC) facility.

Design: Three, single, whole day assessments of plate waste, energy, and selected nutrients, using a visual rating plate waste scale.

Setting: Long-term residential care establishment.

Subjects: One hundred and sixty-nine (93 HLC and 76 LLC) individual daily intakes.

Main findings: The mean energy wasted throughout the whole day was 17%. The energy wasted from main meals (16%) was significantly less than the energy wasted at mid-meals (22%, P=0.049). The lowest mean energy wastage occurred at breakfast (8%) compared to lunch (22%) and dinner (25%, P<0.001). The mean (s.d.) daily energy served and consumed was 8.1 (2.0) and 6.6 (2.2) MJ, respectively. There was no difference in energy served or consumed between HLC and LLC residents. On the observation day, 60% of residents consumed less than their estimated energy requirement. The mean calcium intake was 796 (346) mg, and the median (inter-quartile range) vitamin D intake was 1.78 (2.05) μg.

Conclusion: On 1 day, more than half the residents surveyed were at risk of consuming an inadequate energy intake, which over-time, may result in body weight loss. Although wastage was not excessive and energy served was adequate, the amount of food eaten was insufficient to meet energy and calcium requirements for a significant number of residents and it is not possible to consume sufficient vitamin D through food sources.


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Background: The daily energy imbalance gap associated with the current population weight gain in the obesity epidemic is relatively small. However, the substantially higher body weights of populations that have accumulated over several years are associated with a substantially higher total energy expenditure (TEE) and total energy intake (TEI), or energy flux (EnFlux = TEE = TEI).
Objective: The objective was to develop an equation relating EnFlux to body weight in adults for estimating the rise in EnFlux associated with the obesity epidemic.
Design: Multicenter, cross-sectional data for TEE from doubly labeled water studies in 1399 adults aged 5.9 ± 18.8 y (mean ± SD) were analyzed in linear regression models with natural log (ln) weight as the dependent variable and ln EnFlux as the independent variable, adjusted for height, age, and sex. These equations were compared with those for children and applied to population trends in weight gain.
Results: ln EnFlux was positively related to ln weight (β = 0.71; 95% CI: 0.66, 0.76; R2 = 0.52), adjusted for height, age, and sex. This slope was significantly steeper than that previously described for children (β = 0.45; 95% CI: 0.38, 0.51).
Conclusions: This relation suggests that substantial increases in TEI have driven the increases in body weight over the past 3 decades. Adults have a higher proportional weight gain than children for the same proportional increase in energy intake, mostly because of a higher fat content of the weight being gained. The obesity epidemic will not be reversed without large reductions in energy intake, increases in physical activity, or both.

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Background – Excessive consumption of sugar sweetened beverages (SSB) is a contributing factor in the occurrence of overweight and obesity. The high energy intake, low satiation, high glycemic index, and intense marketing are all thought to contribute to their over consumption. In addition, the role of the mildly-addictive chemical caffeine in SSB has been questioned (Griffiths and Vernotica, 2000, Keast and Riddell, 2007). We have previously shown that low concentrations of caffeine may decrease sweetness of sugars and thereby result in excess energy in SSB formulations (Ebbeling et al., 2006).
Objective – Without noticeably affecting flavour, to determine potential energy reduction when decreasing sucrose concentration from caffeinated and de-caffeinated SSB.
Design – Human psychophysical taste evaluations in water, sucrose and model SSB. Triangle forced-choice ascending method of limits was used to determine caffeine taste threshold in water and sucrose (n= 62). Directional paired comparison tests to determine 1/ the influence of caffeine on sweetness of sucrose (n= 23), and 2/ the nonperceivable difference when decreasing the sucrose and caffeine concentrations in a model SSB (n= 30).
Outcomes – Caffeine, at sub-threshold concentrations in common SSB (0.67mM) can be perceived in sucrose solutions because it significantly inhibits sweetness (p<0.001), the ‘caffeine sweetness effect’. Presumably coremoval of caffeine and sucrose could be achieved without affecting the sweetness of the SSB. Removing caffeine from the model SSB allowed an energy reduction of 137.4 KJ per 500 ml serving (12.6% sucrose reduction) without noticeably affecting flavour for 80% of the population. The energy reduction possible without co-removal of caffeine was a more modest 32 KJ per 500 ml serving (3.5% sucrose reduction).
Conclusion – Sub-threshold concentrations of caffeine suppress sweetness resulting in higher concentrations of sugars in SSB. Excessive consumption of SSB is linked to the obesity epidemic, and we suggest the removal of caffeine and subsequent removal of 137.4 KJ energy will have long term public health benefits.

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Background: The major drivers of the obesity epidemic are much debated and have considerable policy importance for the population-wide prevention of obesity.

Objective: The objective was to determine the relative contributions of increased energy intake and reduced physical activity to the US obesity epidemic.

Design:
We predicted the changes in weight from the changes in estimated energy intakes in US children and adults between the 1970s and 2000s. The increased US food energy supply (adjusted for wastage and assumed to be proportional to energy intake) was apportioned to children and adults and inserted into equations that relate energy intake to body weight derived from doubly labeled water studies. The weight increases predicted from the equations were compared with weight increases measured in representative US surveys over the same period.

Results: For children, the measured weight gain was 4.0 kg, and the predicted weight gain for the increased energy intake was identical at 4.0 kg. For adults, the measured weight gain was 8.6 kg, whereas the predicted weight gain was somewhat higher (10.8 kg).

Conclusions:
Increased energy intake appears to be more than sufficient to explain weight gain in the US population. A reversal of the increase in energy intake of 2000 kJ/d (500 kcal/d) for adults and of 1500 kJ/d (350 kcal/d) for children would be needed for a reversal to the mean body weights of the 1970s. Alternatively, large compensatory increases in physical activity (eg, 110–150 min of walking/d), or a combination of both, would achieve the same outcome. Population approaches to reducing obesity should emphasize a reduction in the drivers of increased energy intake.

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Female athletes may demonstrate a poor ability to quantify portion sizes and educational sessions using food models do not always improve accuracy. Female cyclists with the highest body fat do not report the highest energy intakes during 70 days of training and racing. Training loads can influence reported daily energy intake.

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The objectives of the present study were to assess the intake of different food groups in French children aged 3–17 years (n 1455), and to analyse trends since a dietary survey undertaken 8 years ago. Dietary intake was evaluated using data from the 2006–7 cross-sectional INCA2 national dietary survey (étude Individuelle Nationale sur les Consommations Alimentaires), based on a 7 d food record. Dietary intake (percentage of subjects consuming the food group and amount eaten) was assessed for thirty-nine food categories. We observed variations in food consumption by age, sex, North–South regional gradient, seasonal period and educational level of the responding parent. Trends in dietary intake between 1999 and 2007 were determined by comparing the INCA1 (n 1126) and the INCA2 surveys. Both surveys had been carried out using the same methodology. The findings showed a decrease in energy intake in children aged 3–14 years, due to a reduction in the consumption of foods of animal origin and sweetened products. In adolescents aged 15–17 years, energy intake remained rather stable; during this 8-year period, the consumption of meat decreased, whereas the consumption of savoury snacks such as sandwiches and hamburgers significantly increased. These trends occurred during a time of growing concern about overweight and the associated co-morbidities in France. A number of public health measures were implemented over this period to improve dietary habits and physical activity patterns in children and adults. The periodic monitoring of dietary patterns through the INCA surveys is an essential part of the surveillance network in France.

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During periods of high energy demand an animal may be constrained by a physiological maximum to its energy intake rate. Predictions by allometric equations describing this maximum for endotherms were significantly surpassed during a few recent laboratory experiments on birds and mammals, being given access to food 24 h day-1. How relevant this is in the field remains to be assessed. We predicted that Bewick’s swans Cygnus columbianus bewickii might surpass this maximum during stopover on their migration. We determined intake rate by measuring initial and final biomass density, and dividing the biomass difference by the feeding time required to reach this difference. This feeding time was given by the functional response. After conversion to daily energy intake rates, these exceeded the previously assumed maximum on two of the three stopover sites studied. The exception was a stopover site where daily foraging time was limited by the tidal cycle. Our study confirms that intake rates may exceed the formerly generally supposed maximum under natural conditions when foraging is possible day and night.

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An abdominal profile index (API) was developed for pink-footed geese Anser brachyrhynchus as a measure of body condition. On basis of carcass analysis of 56 adult geese with known API prior to collection, we found significant linear relationships between API against body mass, abdominal fat and total energy content. Hence, changes in API reflect net energy intake rates. As an example of the applicability of the calibration, we compared APIs of individually marked geese before and after long migration episodes and estimated the cost of flight at 8.9 kJ/km. In addition we estimated gain rates at three major staging sites along the spring flyway indicating an increase in fueling rates with latitude. Calibration of APIs and energy contents offers new opportunities for field studies of waterfowl energetics.

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The daily metabolizable energy intake of an animal is potentially limited by either the available feeding time or by its capacity to process energy. Animals are generally considered not to be time-limited but rather to be energy-processing-limited. This is concluded from the common observation that an animal's feeding time per day increases with a decrease in food density. We argue that such changes in feeding time are in theory also expected when no constraints are operating. Thus, a study of the constraints on energy intakes of free-living animals should be performed during demanding phases of the year. As an example, we collected data on time and energy budgets of Bewick's swan (Cygnus columbianus bewickii) refuelling during migration on fennel pondweed (Potamogeton pectinatus) tubers in two years differing two-fold in tuber biomass density. As predicted by time limitation, the feeding time (defined as the time with the head submerged) did not change in response to a change in food biomass density, both within and between years (averaging 12.2 h d−1). Contrary to energy-processing limitation, and again in line with time limitation, the daily metabolizable energy intake varied, being greater in the year with high than in the year with low food densities. We conclude that more studies are needed of animals operating under demanding conditions before it can be assessed whether free-living animals are generally energy-processing- or time-limited.

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Objective: Previous research has demonstrated a relationship between adiposity and bipolar disorder, although data are derived predominantly from patient samples and use indirect methods of assessing adiposity. This study investigated the association between bipolar disorder and several indices of adiposity, including body fat mass as measured by dual energy X-ray absorptiometry (DXA), in a community-based sample.

Methods: In this study, 21 women with bipolar disorder and 523 healthy controls were drawn from an age-stratified, random, community-based sample of women (20–93 years) participating in the Geelong Osteoporosis Study. Bipolar disorder was diagnosed utilising a semi-structured clinical interview. Anthropometric measurements (weight, height, waist and hip circumference) were taken and fat mass was determined from whole body DXA scans (Lunar DPX-L).

Results: Those with bipolar disorder tended to have greater adiposity. Age-adjusted mean (95% CI) values for bipolar versus controls according to adiposity indices were weight 75.6 (68.9–82.3) versus 72.6 (71.3–74.0) kg, waist circumference 89.8 (84.1–95.6) versus 87.3 (86.1–88.5) cm, waist:hip ratio 0.85 (0.82–0.87) versus 0.84 (0.83–0.84), body mass index 27.6 (25.1–30.1) versus 27.5 (27.0–28.0) kg/m2, fat mass 31.4 (26.5–36.3) versus 28.6 (27.5–29.5) kg and %body fat 40.4 (36.9–43.9) versus 38.0 (37.3–38.7)%; all p > 0.05. Further adjustment for height, smoking, alcohol, psychotropic medication, energy intake or physical activity did not influence these patterns.

Conclusion: Although a pattern suggestive of greater adiposity among those with bipolar disorder was observed, no significant differences were detected. We cannot exclude the possibility of a type II error. Further research with a larger sample may produce more conclusive results.