166 resultados para daily intake


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A routine activity for a sports dietitian is to estimate energy and nutrient intake from an athlete's self-reported food intake. Decisions made by the dietitian when coding a food record are a source of variability in the data. The aim of the present study was to determine the variability in estimation of the daily energy and key nutrient intakes of elite athletes, when experienced coders analyzed the same food record using the same database and software package. Seven-day food records from a dietary survey of athletes in the 1996 Australian Olympic team were randomly selected to provide 13 sets of records, each set representing the self-reported food intake of an endurance, team, weight restricted, and sprint/power athlete. Each set was coded by 3-5 members of Sports Dietitians Australia, making a total of 52 athletes, 53 dietitians, and 1456 athlete-days of data. We estimated within- and between- athlete and dietitian variances for each dietary nutrient using mixed modeling, and we combined the variances to express variability as a coefficient of variation (typical variation as a percent of the mean). Variability in the mean of 7-day estimates of a nutrient was 2- to 3-fold less than that of a single day. The variability contributed by the coder was less than the true athlete variability for a 1-day record but was of similar magnitude for a 7-day record. The most variable nutrients (e.g., vitamin C, vitamin A, cholesterol) had approximately 3-fold more variability than least variable nutrients (e.g., energy, carbohydrate, magnesium). These athlete and coder variabilities need to be taken into account in dietary assessment of athletes for counseling and research.

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Background The pattern of protein intake following exercise may impact whole-body protein turnover and net protein retention. We determined the effects of different protein feeding strategies on protein metabolism in resistance-trained young men. Methods: Participants were randomly assigned to ingest either 80g of whey protein as 8x10g every 1.5h (PULSE; n=8), 4x20g every 3h (intermediate, INT; n=7), or 2x40g every 6h (BOLUS; n=8) after an acute bout of bilateral knee extension exercise (4x10 repetitions at 80% maximal strength). Whole-body protein turnover (Q), synthesis (S), breakdown (B), and net balance (NB) were measured throughout 12h of recovery by a bolus ingestion of [ 15N]glycine with urinary [15N]ammonia enrichment as the collected end-product. Results PULSE Q rates were greater than BOLUS (?19%, P<0.05) with a trend towards being greater than INT (?9%, P=0.08). Rates of S were 32% and 19% greater and rates of B were 51% and 57% greater for PULSE as compared to INT and BOLUS, respectively (P<0.05), with no difference between INT and BOLUS. There were no statistical differences in NB between groups (P=0.23); however, magnitude-based inferential statistics revealed likely small (mean effect90%CI; 0.590.87) and moderate (0.800.91) increases in NB for PULSE and INT compared to BOLUS and possible small increase (0.421.00) for INT vs. PULSE. Conclusion We conclude that the pattern of ingested protein, and not only the total daily amount, can impact whole-body protein metabolism. Individuals aiming to maximize NB would likely benefit from repeated ingestion of moderate amounts of protein (?20g) at regular intervals (?3h) throughout the day.

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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.

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Quantifying the competing rates of intake and elimination of persistent organic pollutants (POPs) in the human body is necessary to understand the levels and trends of POPs at a population level. In this paper we reconstruct the historical intake and elimination of ten polychlorinated biphenyls (PCBs) and five organochlorine pesticides (OCPs) from Australian biomonitoring data by fitting a population-level pharmacokinetic (PK) model. Our analysis exploits two sets of cross-sectional biomonitoring data for PCBs and OCPs in pooled blood serum samples from the Australian population that were collected in 2003 and 2009. The modeled adult reference intakes in 1975 for PCB congeners ranged from 0.89 to 24.5 ng/kg bw/day, lower than the daily intakes of OCPs ranging from 73 to 970 ng/kg bw/day. Modeled intake rates are declining with half-times from 1.1 to 1.3 years for PCB congeners and 0.83 to 0.97 years for OCPs. The shortest modeled intrinsic human elimination half-life among the compounds studied here is 6.4 years for hexachlorobenzene, and the longest is 30 years for PCB-74. Our results indicate that it is feasible to reconstruct intakes and to estimate intrinsic human elimination half-lives using the population-level PK model and biomonitoring data only. Our modeled intrinsic human elimination half-lives are in good agreement with values from a similar study carried out for the population of the United Kingdom, and are generally longer than reported values from other industrialized countries in the Northern Hemisphere.

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Vitamin D deficiency and insufficiency are now seen as a contemporary health problem in Australia with possible widespread health effects not limited to bone health1. Despite this, the Vitamin D status (measured as serum 25-hydroxyvitamin D (25(OH)D)) of ambulatory adults has been overlooked in this country. Serum 25(OH)D status is especially important among this group as studies have shown a link between Vitamin D and fall risk in older adults2. Limited data also exists on the contributions of sun exposure via ultraviolet radiation and dietary intake to serum 25(OH)D status in this population. The aims of this project were to assess the serum 25(OH)D status of a group of older ambulatory adults in South East Queensland, to assess the association between their serum 25(OH)D status and functional measures as possible indicators of fall risk, obtain data on the sources of Vitamin D in this population and assess whether this intake was related to serum 25(OH)D status and describe sun protection and exposure behaviors in this group and investigate whether a relationship existed between these and serum 25(OH)D status. The collection of this data assists in addressing key gaps identified in the literature with regard to this population group and their Vitamin D status in Australia. A representative convenience sample of participants (N=47) over 55 years of age was recruited for this cross-sectional, exploratory study which was undertaken in December 2007 in south-east Queensland (Brisbane and Sunshine coast). Participants were required to complete a sun exposure questionnaire in addition to a Calcium and Vitamin D food frequency questionnaire. Timed up and go and handgrip dynamometry tests were used to examine functional capacity. Serum 25(OH)D status and blood measures of Calcium, Phosphorus and Albumin were determined through blood tests. The Mean and Median serum 25-Hydroxyvitamin D (25(OH)D) for all participants in this study was 85.8nmol/L (Standard Deviation 29.7nmol/L) and 81.0nmol/L (Range 22-158nmol/L), respectively. Analysis at the bivariate level revealed a statistically significant relationship between serum 25(OH)D status and location, with participants living on the Sunshine Coast having a mean serum 25(OH)D status 21.3nmol/L higher than participants living in Brisbane (p=0.014). While at the descriptive level there was an apparent trend towards higher outdoor exposure and increasing levels of serum 25(OH)D, no statistically significant associations between the sun measures of outdoor exposure, sun protection behaviors and phenotypic characteristics and serum 25(OH)D status were observed. Intake of both Calcium and Vitamin D was low in this sample with sixty-eight (68%) of participants not meeting the Estimated Average Requirements (EAR) for Calcium (Median=771.0mg; Range=218.0-2616.0mg), while eighty-seven (87%) did not meet the Adequate Intake for Vitamin D (Median=4.46ug; Range=0.13-30.0ug). This raises the question of how realistic meeting the new Adequate Intakes for Vitamin D is, when there is such a low level of Vitamin D fortification in this country. However, participants meeting the Adequate Intake (AI) for Vitamin D were observed to have a significantly higher serum 25(OH)D status compared to those not meeting the AI for Vitamin D (p=0.036), showing that meeting the AI for Vitamin D may play a significant role in determining Vitamin D status in this population. By stratifying our data by categories of outdoor exposure time, a trend was observed between increased importance of Vitamin D dietary intake as a possible determinant of serum 25(OH)D status in participants with lower outdoor exposures. While a trend towards higher Timed Up and Go scores in participants with higher 25(OH) D status was seen, this was only significant for females (p=0.014). Handgrip strength showed statistically significant association with serum 25(OH)D status. The high serum 25(OH)D status in our sample almost certainly explains the limited relationship between functional measures and serum 25(OH)D. However, the observation of an association between slower Time Up and Go speeds, and lower serum 25(OH)D levels, even with a small sample size, is significant as slower Timed Up and Go speeds have been associated with increased fall risk in older adults3. Multivariable regression analysis revealed Location as the only significant determinant of serum 25(OH)D status at p=0.014, with trends (p=>0.1) for higher serum 25(OH)D being shown for participants that met the AI for Vitamin D and rated themselves as having a higher health status. The results of this exploratory study show that 93.6% of participants had adequate 25(OH)D status-possibly due to measurement being taken in the summer season and the convenience nature of the sample. However, many participants do not meet their dietary Calcium and Vitamin D requirements, which may indicate inadequate intake of these nutrients in older Australians and a higher risk of osteoporosis. The relationship between serum 25(OH)D and functional measures in this population also requires further study, especially in older adults displaying Vitamin D insufficiency or deficiency.

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

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Polybrominated diphenyl ethers (PBDEs) are lipophilic, persistent pollutants found worldwide in environmental and human samples. Exposure pathways for PBDEs remain unclear but may include food, air and dust. The aim of this study was to conduct an integrated assessment of PBDE exposure and human body burden using 10 matched samples of human milk, indoor air and dust collected in 2007–2008 in Brisbane, Australia. In addition, temporal analysis was investigated comparing the results of the current study with PBDE concentrations in human milk collected in 2002–2003 from the same region. PBDEs were detected in all matrices and the median concentrations of BDEs -47 and -209 in human milk, air and dust were: 4.2 and 0.3 ng/g lipid; 25 and 7.8 pg/m3; and 56 and 291 ng/g dust, respectively. Significant correlations were observed between the concentrations of BDE-99 in air and human milk (r = 0.661, p = 0.038) and BDE-153 in dust and BDE-183 in human milk (r = 0.697, p = 0.025). These correlations do not suggest causal relationships — there is no hypothesis that can be offered to explain why BDE-153 in dust and BDE-183 in milk are correlated. The fact that so few correlations were found in the data could be a function of the small sample size, or because additional factors, such as sources of exposure not considered or measured in the study, might be important in explaining exposure to PBDEs. There was a slight decrease in PBDE concentrations from 2002–2003 to 2007–2008 but this may be due to sampling and analytical differences. Overall, average PBDE concentrations from these individual samples were similar to results from pooled human milk collected in Brisbane in 2002–2003 indicating that pooling may be an efficient, cost-effective strategy of assessing PBDE concentrations on a population basis. The results of this study were used to estimate an infant's daily PBDE intake via inhalation, dust ingestion and human milk consumption. Differences in PBDE intake of individual congeners from the different matrices were observed. Specifically, as the level of bromination increased, the contribution of PBDE intake decreased via human milk and increased via dust. As the impacts of the ban of the lower brominated (penta- and octa-BDE) products become evident, an increased use of the higher brominated deca-BDE product may result in dust making a greater contribution to infant exposure than it does currently. To better understand human body burden, further research is required into the sources and exposure pathways of PBDEs and metabolic differences influencing an individual's response to exposure. In addition, temporal trend analysis is necessary with continued monitoring of PBDEs in the human population as well as in the suggested exposure matrices of food, dust and air.

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Aims: Dietary glycemic index (GI) and glycemic load (GL) have been associated with risk of chronic diseases, yet limited research exists on patterns of consumption in Australia. Our aims were to investigate glycemic carbohydrate in a population of older women, identify major contributing food sources, and determine low, moderate and high ranges. Methods: Subjects were 459 Brisbane women aged 42-81 years participating in the Longitudinal Assessment of Ageing in Women. Diet history interviews were used to assess usual diet and results were analysed into energy and macronutrients using the FoodWorks dietary analysis program combined with a customised GI database. Results: Mean±SD dietary GI was 55.6±4.4% and mean dietary GL was 115±25. A low GI in this population was ≤52.0, corresponding to the lowest quintile of dietary GI, and a low GL was ≤95. GI showed a quadratic relationship with age (P=0.01), with a slight decrease observed in women aged in their 60’s relative to younger or older women. GL decreased linearly with age (P<0.001). Bread was the main contributor to carbohydrate and dietary GL (17.1% and 20.8%, respectively), followed by fruit (15.5% and 14.2%), and dairy for carbohydrate (9.0%) or breakfast cereals for GL (8.9%). Conclusions: In this population, dietary GL decreased with increasing age, however this was likely to be a result of higher energy intakes in younger women. Focus on careful selection of lower GI items within bread and breakfast cereal food groups would be an effective strategy for decreasing dietary GL in this population of older women.

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BACKGROUND:Previous epidemiological investigations of associations between dietary glycemic intake and insulin resistance have used average daily measures of glycemic index (GI) and glycemic load (GL). We explored multiple and novel measures of dietary glycemic intake to determine which was most predictive of an association with insulin resistance.METHODS:Usual dietary intakes were assessed by diet history interview in women aged 42-81 years participating in the Longitudinal Assessment of Ageing in Women. Daily measures of dietary glycemic intake (n = 329) were carbohydrate, GI, GL, and GL per megacalorie (GL/Mcal), while meal based measures (n = 200) were breakfast, lunch and dinner GL; and a new measure, GL peak score, to represent meal peaks. Insulin resistant status was defined as a homeostasis model assessment (HOMA) value of >3.99; HOMA as a continuous variable was also investigated.RESULTS:GL, GL/Mcal, carbohydrate (all P < 0.01), GL peak score (P = 0.04) and lunch GL (P = 0.04) were positively and independently associated with insulin resistant status. Daily measures were more predictive than meal-based measures, with minimal difference between GL/Mcal, GL and carbohydrate. No significant associations were observed with HOMA as a continuous variable.CONCLUSION:A dietary pattern with high peaks of GL above the individual's average intake was a significant independent predictor of insulin resistance in this population, however the contribution was less than daily GL and carbohydrate variables. Accounting for energy intake slightly increased the predictive ability of GL, which is potentially important when examining disease risk in more diverse populations with wider variations in energy requirements.

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My perspective on the problems associated with building in bushfire prone landscapes comes from 12 years of study of the biophysical and cultural landscapes in the Great Southern Region of WA which resulted in the design and construction of the ‘Hhouse’ at Bremer Bay. The house was developed using a ‘ground up’ approach whereby I conducted a topographical survey and worked with a local botanist and a bushfire risk consultant to ascertain the level of threat that fire presented to this particular site. My intention from the outset however, was not to design a bushfire resistant house per se, but to develop a design which would place the owners in close proximity to the highly biodiverse heath vegetation of the site. I was also seeking a means—through architectural design—of linking the patterns of usage of the house with other site specific conditions related to the prevailing winds, solar orientation and seasonal change.

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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.