Variability in estimation of self-reported dietary intake data from elite athletes resulting from coding by different sports dietitians

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.

Computer-based assessments of expected satiety predict behavioural measures of portion-size selection and food intake

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.

Medical nutrition therapy and simple interventions can improve intake in patients who eat poorly in hospital

The Australasian Nutrition Care Day Survey (ANCDS) reported two-in-five patients in Australian and New Zealand hospitals consume ≤50% of the offered food. The ANCDS found a significant association between poor food intake and increased in-hospital mortality after controlling for confounders (nutritional status, age, disease type and severity)1. Evidence for the effectiveness of medical nutrition therapy (MNT) in hospital patients eating poorly is lacking. An exploratory study was conducted in respiratory, neurology and orthopaedic wards of an Australian hospital. At baseline, 24-hour food intake (0%, 25%, 50%, 75%, 100% of offered meals) was evaluated for patients hospitalised for ≥2 days and not under dietetic review. Patients consuming ≤50% of offered meals due to nutrition-impact symptoms were referred to ward dietitians for MNT with food intake re-evaluated on day-7. 184 patients were observed over four weeks. Sixty-two patients (34%) consumed ≤50% of the offered meals. Simple interventions (feeding/menu assistance, diet texture modifications) improved intake to ≥75% in 30 patients who did not require further MNT. Of the 32 patients referred for MNT, baseline and day-7 data were available for 20 patients (68±17years, 65% females, BMI: 22±5kg/m2, median energy, protein intake: 2250kJ, 25g respectively). On day-7, 17 participants (85%) demonstrated significantly higher consumption (4300kJ, 53g; p<0.01). Three participants demonstrated no improvement due to ongoing nutrition-impact symptoms. “Percentage food intake” was a quick tool to identify patients in whom simple interventions could enhance intake. MNT was associated with improved dietary intake in hospital patients. Further research is needed to establish a causal relationship.

An exploratory study to evaluate whether medical nutrition therapy can improve dietary intake in hospital patients who eat poorly

Background and aims The Australasian Nutrition Care Day Survey (ANCDS) reported two-in-five patients consume ≤50% of the offered food in Australian and New Zealand hospitals. After controlling for confounders (nutritional status, age, disease type and severity), the ANCDS also established an independent association between poor food intake and increased in-hospital mortality. This study aimed to evaluate if medical nutrition therapy (MNT) could improve dietary intake in hospital patients eating poorly. Methods An exploratory pilot study was conducted in the respiratory, neurology and orthopaedic wards of an Australian hospital. At baseline, percentage food intake (0%, 25%, 50%, 75%, and 100%) was evaluated for each main meal and snack for a 24-hour period in patients hospitalised for ≥2 days and not under dietetic review. Patients consuming ≤50% of offered meals due to nutrition-impact symptoms were referred to ward dietitians for MNT. Food intake was re-evaluated on the seventh day following recruitment (post-MNT). Results 184 patients were observed over four weeks; 32 patients were referred for MNT. Although baseline and post-MNT data for 20 participants (68±17years, 65% females) indicated a significant increase in median energy and protein intake post-MNT (3600kJ/day, 40g/day) versus baseline (2250kJ/day, 25g/day) (p<0.05), the increased intake met only 50% of dietary requirements. Persistent nutrition impact symptoms affected intake. Conclusion In this pilot study whilst dietary intake improved, it remained inadequate to meet participants’ estimated requirements due to ongoing nutrition-impact symptoms. Appropriate medical management and early enteral feeding could be a possible solution for such patients.

Daytime pattern of post-exercise protein intake affects whole-body protein turnover in resistance-trained males

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.

Validity of dietary questionnaires in Sri Lankan adults and the association of dietary intake with obesity

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.

Satiety responsiveness in toddlerhood predicts energy intake and weight status at four years of age

The aim of this study was to examine whether maternal-report of child eating behaviour at two years predicted self-regulation of energy intake and weight status at four years. Using an ‘eating in the absence of hunger’ paradigm, children’s energy intake (kJ) from a semi-standardized lunch meal and a standardized selection of snacks were measured. Participants were 37 mother-child dyads (16 boys, Median child age = 4.4 years, Inter-quartile range = 3.7-4.5 years) recruited from an existing longitudinal study (NOURISH randomised controlled trial). All participants were tested in their own home. Details of maternal characteristics, child eating behaviours (at age two years) reported by mothers on a validated questionnaire, and measured child height and weight (at age 3.5-4 years) were sourced from existing NOURISH trial data. Correlation and partial correlation analyses were used to examine longitudinal relationships. Satiety responsiveness and Slowness in eating were inversely associated with energy intake of the lunch meal (partial r = -.40, p =.023, and partial r = -.40, p = .023) and the former was also negatively associated with BMI-for-age Z score (partial r = -.42, p = .015). Food responsiveness and Enjoyment of food were not related to energy intake or BMI Z score. None of the eating behaviours were significantly associated with energy intake of the snacks (i.e., eating in the absence of hunger). The small and predominantly ‘healthy weight’ sample of children may have limited the ability to detect some hypothesized effects. Nevertheless, the study provides evidence for the predictive validity of two eating behaviours and future research with a larger and more diverse sample should be able to better evaluate the predictive validity of other children’s early eating behaviour styles.

Gastric emptying, appetite, energy intake and exercise in males

The main aim was to expand existing knowledge on the influence of physical activity on gastric emptying and appetite control. Through a series of three complementary research studies interactions between exercise, gastric emptying, appetite and energy intake were investigated in males. Relationships with body composition and energy expenditure were also addressed.

Associations of body mass index and waist circumference with: energy intake and percentage energy from macronutrients, in a cohort of Australian children

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.

The obesity epidemic : both energy intake and physical activity contribute

Recent data from Australia, the United States and Europe show increased self-reported energy intake associated with obesity, in contrast to earlier suggestions that the obesity epidemic has occurred despite minimal or no increase in per capita energy intake from food. The effect of increased energy intake is compounded by sedentary lifestyles. Both physical activity and nutrition must be addressed to reduce the prevalence of obesity and improve the health of Australians.

Measuring dietary intake in remote Australian Aboriginal communities

This paper reports a comparison of the practicality, acceptability and face validity of five dietary intake methods in two remote Australian Aboriginal communities: weighed dietary intake, 24‐hour recall, ‘store‐turnover’, diet history and food frequency methods. The methods used to measure individual dietary intake were poorly accepted by the communities. Quantitative data were obtained only from the first three methods. The 24‐hour recall method tended to produce higher nutrient intakes than the weighed intake method and certain foods appeared to be selectively recalled according to perceived nutritional desirability. The ‘store‐turnover’ method was most acceptable to the communities and had less potential for bias than the other methods. It was also relatively objective, non‐intrusive, rapid, easy and inexpensive. However, food distribution patterns within the communities could not be assessed by this method. Nevertheless, other similarly isolated communities may benefit by use of the ‘store‐turnover’ method.

Apparent dietary intake in remote Aboriginal communities

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.

Aboriginal dietary intake and a successful nutrition intervention project in a Northern Territory community

This paper summarises the development and testing of the 'store-turnover' method, a non-invasive dietary survey methodology for quantitative measurement of food and nutrient intake in remote, centralised Aboriginal communities. It then describes the use of the method in planning, implementation and evaluation of a community-based nutrition intervention project in a small Aboriginal community in the Northern Territory. During this project marked improvements in both the dietary intake of the community and biological indicators of nutritional health (including vitamin status and the degree and prevalence of several risk factors for non-communicable disease) were measured in the community over a 12-month period following the development of intervention strategies with the community. Although these specific strategies are presented, emphasis is directed towards the process involved, particularly the evaluation procedures used to monitor all stages of the project with the community.

The adaptive metabolic response to exercise-induced weight loss influences both energy expenditure and energy intake

BACKGROUND/OBJECTIVEs A decline in resting energy expenditure (REE) beyond that predicted from changes in body composition has been noted following dietary-induced weight loss. However, it is unknown whether a compensatory downregulation in REE also accompanies exercise (EX)-induced weight loss, or whether this adaptive metabolic response influences energy intake (EI). SUBJECTS/METHODS Thirty overweight and obese women (body mass index (BMI)=30.6±3.6 kg/m2) completed 12 weeks of supervised aerobic EX. Body composition, metabolism, EI and metabolic-related hormones were measured at baseline, week 6 and post intervention. The metabolic adaptation (MA), that is, difference between predicted and measured REE was also calculated post intervention (MApost), with REE predicted using a regression equation generated in an independent sample of 66 overweight and obese women (BMI=31.0±3.9 kg/m2). RESULTS Although mean predicted and measured REE did not differ post intervention, 43% of participants experienced a greater-than-expected decline in REE (−102.9±77.5 kcal per day). MApost was associated with the change in leptin (r=0.47; P=0.04), and the change in resting fat (r=0.52; P=0.01) and carbohydrate oxidation (r=−0.44; P=0.02). Furthermore, MApost was also associated with the change in EI following EX (r=−0.44; P=0.01). CONCLUSIONS Marked variability existed in the adaptive metabolic response to EX. Importantly, those who experienced a downregulation in REE also experienced an upregulation in EI, indicating that the adaptive metabolic response to EX influences both physiological and behavioural components of energy balance.