Estimated Energy Intake Research Articles

Quantifying the Foodscape for Stream‐Dwelling Cutthroat Trout Reveals Spatial and Temporal Ranges of Resource Exploitation and Energy Intake

AbstractFood availability is a primary factor limiting the abundance of wild populations, but quantifying it requires an understanding of when and where prey are vulnerable to predators. Salmonid fishes in streams are commonly thought to forage on drifting aquatic invertebrates during daylight hours. However, past studies also report benthic and nocturnal foraging despite the predominant view of salmonids as diurnal drift‐feeding predators. We used instream videography to assess foraging mode and energy intake for stream‐dwelling Yellowstone Cutthroat Trout Oncorhynchus clarkii bouvieri. We recorded the foraging behavior of wild fish with a waterproof video camera and estimated energy intake based on fish size, foraging rate, retention rate, and caloric values of prey. Fish captured prey primarily from the water column and surface, targeting drifting invertebrates during daytime hours; however, they also foraged from the stream benthos and during nighttime. Yellowstone Cutthroat Trout foraging rate was most strongly related to foraging location in the stream, diel period, and month. Energy intake was highest from daytime drift‐foraging behavior and exceeded a modeled metabolic limit of food intake during October and November. Nocturnal and benthic foraging contributed the smallest proportion of total foraging attempts but was observed over all months of our study and sometimes comprised up to 30% of estimated energy intake. Our results indicate that Yellowstone Cutthroat Trout in streams acquire most of the food intake as daytime drift‐feeding predators.

Risk and Reward in Foraging Migrations of North Pacific Albacore Determined From Estimates of Energy Intake and Movement Costs

North Pacific albacore (Thunnus alalunga) is a commercially important tuna species known to undertake extensive migratory movements between nearshore waters of the California Current and offshore environments in the central Pacific. However, these migration behaviors are highly variable, with some individuals traveling thousands of kilometers within a season, and others largely resident in the southern California Current throughout the year. In this study, we use data from 33 archival-tagged albacore (released between 2003 and 2011) to examine the movements, physiology and ecology of tuna following different migratory pathways. We used direct measurements of body temperature and ambient water temperature from internal archival tags to estimate energy intake via the Heat Increment of Feeding (HIF), the increased internal heat production associated with digestion of a meal. Our results indicate that HIF was variable in space and time, but it was highest for individuals foraging in the offshore North Pacific Transition Zone and southern California Current during spring and summer, and lowest in the Transition Zone in fall. None of the migratory strategies examined appeared to confer consistently higher energetic benefits than the others. Fish remaining resident in the southern California Current year-round incurred lower migration costs, and could access favorable foraging conditions off Baja California in spring and summer. In contrast, fish which undertook longer migrations had much higher energetic costs during periods of faster transit times, but were able to reach highly productive foraging areas in the central and western Pacific. HIF was generally higher in larger fish, and when ambient temperatures were cooler, but was not strongly correlated with other environmental covariates. Our analyses offer new avenues for studying the physiology of wild tuna populations, and can complement diet and isotopic studies to further understanding of fish ecology.

Commercial Devices Provide Estimates of Energy Balance with Varying Degrees of Validity in Free-Living Adults

BackgroundThe challenges of accurate estimation of energy intake (EI) are well-documented, with self-reported values 12%–20% below expected values. New approaches rely on gold-standard assessments of the other components of energy balance, energy expenditure (EE) and energy storage (ES), to estimate EI. ObjectivesThe purpose of this study was to evaluate the validity, repeatability, and measurement error of consumer devices when estimating energy balance in a free-living population. MethodsTwenty-four healthy adults (14 women, 10 men; mean ± SD age: 30.7 ± 8.2 y) completed two 14-d assessment periods, including assessments of EE and ES using gold-standard [doubly labeled water (DLW) and DXA] and commercial devices [Fitbit Alta HR activity monitor (Alta) and Fitbit Aria wireless body composition scale (Aria)], and of EI by dietician-administered recalls. Accuracy and validity were assessed using Spearman correlation, interclass correlation, mean absolute percentage error, and equivalency testing. We also applied linear measurement error modeling including error in gold-standard devices and within-subject repeated-measures design to calibrate consumer devices and quantify error. ResultsThere was moderate to strong agreement for EE between the Fitbit Alta and DLW at each time point (rs = 0.82 and 0.66 for Times 1 and 2, respectively). There was weak agreement for ES between the Fitbit Aria and DXA (rs = 0.15 and 0.49 for Times 1 and 2, respectively). Correlations between methods to assess EI ranged from weak to strong, with agreement between the DXA/DLW-calculated EI and dietary recalls being the highest (rs = 0.63 for Time 1 and 0.73 for Time 2). Only EE from the Fitbit Alta at Time 1 was equivalent to the DLW value using equivalency testing. ConclusionsCommercial devices provide estimates of energy balance in free-living adults with varying degrees of validity compared to gold-standard techniques. EE estimates were the most robust overall, whereas ES estimates were generally poor.

A control-based observer approach for estimating energy intake during pregnancy.

Gestational weight gain outside of Institute of Medicine guidelines poses a risk to both the mother and her unborn child. Behavioral interventions such as Healthy Mom Zone (HMZ) that aim to regulate gestational weight gain require self-monitoring of energy intake, which is often significantly under-reported by participants. This paper describes the use of a control systems approach for energy intake estimation during pregnancy. It relies on an energy balance model that predicts gestational weight based on physical activity and energy intake, the latter treated as an unmeasured disturbance. Two control-based observer formulations relying on Internal Model Control and Model Predictive Control, respectively, are presented in this paper, first for a hypothetical participant, then on data collected from four HMZ participants. Results demonstrate the effectiveness of the method, with generally best results obtained when estimating energy intake over a weekly time period.

Estimated energy and nutrient intake for infants following baby-led and traditional weaning approaches.

BackgroundBaby‐led weaning (BLW), where infants self‐feed without the use of spoon‐feeding by a caregiver, continues to be a popular approach for starting solids. However, concerns remain amongst health professionals that infants using this method may not consume sufficient energy or nutrients from solid foods. Little research has examined how different weaning approaches shape dietary intake. The present study aimed to use a 3‐day weighed diet diary to measure estimated energy and nutrient intake in infants aged 6–12 months.MethodsDiet diaries were completed by 71 parents and analysed to compare estimated infant intake from milk and solid foods for those either following a BLW or traditional spoon‐feeding approach (TW). Intake was analysed for each weaning group in two age groups: 26–39 and 40–52 weeks, to account for different eating patterns at the start and end of the weaning process.ResultsFor the younger infants, significant differences in estimated energy intake were found, with TW infants consuming 285 kcal from solid foods compared with 120 kcal for BLW infants. Conversely, BLW infants consumed more calories and nutrients from breast or formula milk, consistent with a slower transition to solid foods. No differences were found in estimated intake amongst older infants, suggesting that BLW infants had ‘caught up’ with their spoon‐fed peers.ConclusionsOverall, few infants regardless of weaning group met recommended intake guidelines for energy (either over or under consuming) with many deficient in iron and zinc intake. The findings are important for those supporting parents through the transition to solid foods.

Genetic polymorphisms are not associated with energy intake 1 year after Roux-en-Y gastric bypass in women.

The present study aimed to investigate the influence of food intake on body weight loss (WL) and the association of gene polymorphisms, 1 year after Roux-en-Y gastric bypass (RYGB) surgery. In total, 95 obese women (age ranged 20-50 years) in a Brazilian cohort underwent RYGB surgery and completed the study. Anthropometric measurements and food intake were assessed before and 1 year after surgery. Twelve gene polymorphisms (GHRL rs26802; GHSR rs572169; LEP rs7799039; LEPR rs1137101; 5-HT2C rs3813929; UCP2 rs659366; UCP2 rs660339; UCP3 rs1800849; SH2B1 rs7498665; TAS1R2 rs35874116; TAS1R2 rs9701796; and FTO rs9939609) were determined using a real-time polymerase chain reaction and a TaqMan assay. The subjects were divided into quartiles regarding percentage of excess weight loss (%EWL). The effect of genetic variants on energy and macronutrient intake was evaluated by simple logistic regression, followed by multiple logistic regression. Subjects in the first and second quartiles showed a higher initial body mass index. Energy and macronutrient intake before and 1 year after RYGB surgery did not differ between the %EWL quartiles. None of gene polymorphisms investigated showed an association with the estimated energy intake 1 year after surgery. In conclusion, the estimate energy and food intake did not predict a greater body WL 1 year after RYGB surgery. In addition, the 12 gene polymorphism investigated did not affect the energy intake among female patients.

Effect of inclusion levels of low-fat dried distillers grains in finishing diets on protein and energy intake and retention and estimation of protein and energy requirements of young Nellore bulls fed with high concentrate diets.

The objective was to evaluate the effect of including low-fat dried distillers grains (DDG) in finishing diets on protein and energy intake and retention and to estimate the protein and energy requirement of young Nellore bulls. Thirty-five animals were used: baseline (n = 4), maintenance (n = 4), and ad libitum intake (n = 27). Ad libitum animals were divided into four groups: diets with the inclusion of DDG at the levels of 0, 150, 300, and 450 g/kg (dry matter basis). At the end of the experiment, all animals were slaughtered. There was a linear reduction with increasing DDG levels in the total digestible nutrients intake (p = 0.008), metabolizable energy (ME) intake (p < 0.010), in total retained energy (p = 0.065), and in heat production (p < 0.001). Metabolizable protein (MP) intake increased linearly (p < 0.010) but retained protein did not differ (p = 0.499). Daily net energy and ME requirement for maintenance were 75.9 and 122 kcal/kg0.75 EBW, respectively. Daily MP for maintenance was 3.6g/kg0.75 shrunk body weight. DDG inclusion in finishing diets reduces energy intake and deposition, and we recommend the equations of this study to estimate the requirements of young Nellore bulls.

Comparison of total energy intakes estimated by 24-hour diet recall with total energy expenditure measured by the doubly labeled water method in adults.

BACKGROUND/OBJECTIVESThe doubly labeled water (DLW) method is the gold standard for estimating total energy expenditure (TEE) and is also useful for verifying the validities of dietary evaluation tools. In this study, we compared the accuracy of total energy intakes (TEI) estimated by the 24-h diet recall method with TEE obtained using the doubly labeled water method.SUBJECTS/METHODSThis study involved 71 subjects aged 20–49 yrs. Over a 14-day period, three 24-h diet recalls per subject (2 weekdays and 1 weekend day) were used to estimate energy intakes, while TEE was measured using the DLW method. The paired t-test was used to determine the significance of differences between TEI and TEE results, and the accuracy of the 24-h recall method was determined by accuracy predictions percentage, root mean square error, and bias.RESULTSAverage study subject age was 33.4 ± 8.6 yrs. The association between TEI and TEE was positive and significant (r = 0.463, P < 0.001), and the difference between TEI (2,084.3 ± 684.2 kcal/day) and TEE (2,401.7 ± 480.3 kcal/day) was also significant (P < 0.001). In all study subjects, mean TEI was 12.0% (307.5 ± 629.3 kcal/day) less than mean TEE, and 12.2% (349.4 ± 632.5 kcal/day) less in men and 11.8% (266.7 ± 632.5 kcal/day) less in women. Rates of TEI underprediction for all study subjects, men, and women, were 60.5%, 51.4%, and 66.7%, respectively.CONCLUSIONSThis study shows that 24-h diet recall underreports energy intakes. More research is needed to corroborate our findings and evaluate the accuracy of 24-h recall with respect to additional demographics.

Accuracy and Cost-effectiveness of Technology-Assisted Dietary Assessment Comparing the Automated Self-administered Dietary Assessment Tool, Intake24, and an Image-Assisted Mobile Food Record 24-Hour Recall Relative to Observed Intake: Protocol for a Randomized Crossover Feeding Study.

BackgroundThe assessment of dietary intake underpins population nutrition surveillance and nutritional epidemiology and is essential to inform effective public health policies and programs. Technological advances in dietary assessment that use images and automated methods have the potential to improve accuracy, respondent burden, and cost; however, they need to be evaluated to inform large-scale use.ObjectiveThe aim of this study is to compare the accuracy, acceptability, and cost-effectiveness of 3 technology-assisted 24-hour dietary recall (24HR) methods relative to observed intake across 3 meals.MethodsUsing a controlled feeding study design, 24HR data collected using 3 methods will be obtained for comparison with observed intake. A total of 150 healthy adults, aged 18 to 70 years, will be recruited and will complete web-based demographic and psychosocial questionnaires and cognitive tests. Participants will attend a university study center on 3 separate days to consume breakfast, lunch, and dinner, with unobtrusive documentation of the foods and beverages consumed and their amounts. Following each feeding day, participants will complete a 24HR process using 1 of 3 methods: the Automated Self-Administered Dietary Assessment Tool, Intake24, or the Image-Assisted mobile Food Record 24-Hour Recall. The sequence of the 3 methods will be randomized, with each participant exposed to each method approximately 1 week apart. Acceptability and the preferred 24HR method will be assessed using a questionnaire. Estimates of energy, nutrient, and food group intake and portion sizes from each 24HR method will be compared with the observed intake for each day. Linear mixed models will be used, with 24HR method and method order as fixed effects, to assess differences in the 24HR methods. Reporting bias will be assessed by examining the ratios of reported 24HR intake to observed intake. Food and beverage omission and intrusion rates will be calculated, and differences by 24HR method will be assessed using chi-square tests. Psychosocial, demographic, and cognitive factors associated with energy misestimation will be evaluated using chi-square tests and multivariable logistic regression. The financial costs, time costs, and cost-effectiveness of each 24HR method will be assessed and compared using repeated measures analysis of variance tests.ResultsParticipant recruitment commenced in March 2021 and is planned to be completed by the end of 2021.ConclusionsThis protocol outlines the methodology of a study that will evaluate the accuracy, acceptability, and cost-effectiveness of 3 technology-enabled dietary assessment methods. This will inform the selection of dietary assessment methods in future studies on nutrition surveillance and epidemiology.Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12621000209897; https://tinyurl.com/2p9fpf2sInternational Registered Report Identifier (IRRID)DERR1-10.2196/32891

Late Evening Eating Patterns among US Adults Vary in Their Associations With, and Impact on, Energy Intake and Diet Quality: Evidence from What We Eat in America, National Health and Nutrition Examination Survey 2013-2016

BackgroundEvening eating has been associated with higher energy intake and lower nutrient density. However, these qualities may not characterize all late evening (LE) eating patterns. ObjectiveWe sought to characterize US adults’ LE eating patterns on a given day and identify differences, if any, in pattern-specific associations with, and impact on, daily energy intake and total diet quality. DesignLE eating patterns, energy intakes, and Healthy Eating Index (HEI) scores were identified using Day-1 dietary recall data from the cross-sectional National Health and Nutrition Examination Survey 2013-2016. Participants/settingThe sample included adults aged ≥ 20 years (n = 9,861). LE reporters were respondents who consumed foods/beverages between 20:00 and 23:59 on the intake day. Main outcome measuresEnergy intake and HEI-2015 scores by LE status/pattern and the impact of LE consumption on these measures. Statistical analysesCluster analysis assigned individuals to LE eating patterns based on the LE energy contribution of food/beverage groups. Regression models estimated energy intake and HEI-2015 scores; estimates were compared between LE reporters and nonreporters. Similarly, LE’s contribution to total energy and the difference in total HEI inclusive vs exclusive of LE consumption were estimated and compared among patterns. ResultsAmong US adults, 64.4% were LE reporters. Eleven LE patterns were identified; the six most prevalent patterns (representing 89% of LE reporters) were further analyzed. Daily energy intake in all prevalent patterns except the fruit pattern exceeded that of nonreporters by ≥ 268 kcal (unadjusted; P < 0.001), varying by pattern. Conversely, total HEI score did not differ from that of nonreporters (51.0) in any pattern except the fruit pattern, where it was higher (57.4, unadjusted; P < 0.001). Generally, LE consumption’s impact on energy was high and its impact on HEI scores was low. ConclusionsLate evening food/beverage consumption is common among US adults, and LE patterns are not monolithic in their associations with, and impact on, total energy intake and dietary quality.

Comparison of the Diet Photograph Record to Weighed Dietary Record and 24 h Dietary Recall for Estimating Energy and Nutrient Intakes Among Chinese Preschoolers.

This study aimed to assess the relative validity of the diet photograph record (DP) for measuring the energy and nutrient intakes against the weighed dietary record (WD) and the 24 h dietary recall (HR) in the Chinese preschoolers. In this study, 40 preschool children aged 4–6 years and their parents were recruited from a kindergarten in southwest China. Dietary intake of the preschoolers on a same day, as estimated by the DP and the HR were compared with the WD. These three methods were administered by the three group of investigators independently. The mean differences, correlation coefficients, cross-classifications, and weighted κ, as well as the Bland–Altman plots were performed to assess the differences and agreements among the estimates from the DP, the HR, and the WD. For the DP and the HR, the estimates of energy and nutrient intakes were moderate to high correlated with the WD, with the higher coefficients ranging from 0.73 to 0.94 for the DP. Both the methods tended to underestimate the dietary intake, but the differences from the known weights using the DP were significantly smaller than those using the HR. The weighed κ values ranking the preschoolers ranged from 0.48 to 0.80 for the DP and ranged from 0.28 to 0.64 for the HR. Furthermore, the Bland–Altman plots indicated a better agreement between the DP and the WD for estimating energy and nutrient intakes. This DP is a valid tool for measuring energy and nutrient intakes among the preschoolers.

Energy Intake Evaluation by a Learning Approach Using the Number of Food Portions and Body Weight.

An accurate quantification of energy intake is critical; however, under-reporting is frequent. The aim of this study was to develop an indirect statistical method of the total energy intake estimation based on gender, weight, and the number of portions. The energy intake prediction was developed and evaluated for validity using energy expenditure. Subjects with various BMIs were recruited and assigned either in the training or the test group. The mean energy provided by a portion was evaluated by linear regression models from the training group. The absolute values of the error between the energy intake estimation and the energy expenditure measurement were calculated for each subject, by subgroup and for the whole group. The performance of the models was determined using the test dataset. As the number of portions is the only variable used in the model, the error was 26.5%. After adding body weight in the model, the error decreased to 8.8% and 10.8% for the normal-weight women and men, respectively, and 11.7% and 12.8% for the overweight women and men, respectively. The results prove that a statistical approach and knowledge of the usual number of portions and body weight is effective and sufficient to obtain a precise evaluation of energy intake after a simple and brief enquiry.

Maternal feeding benefits of allomaternal care in black-and-white colobus (Colobus guereza).

Caring for infants involves lactation, protection, provisioning, and carrying-all energetically taxing states for primate mothers. Holding and carrying clinging infants often constrains mothers from moving and traveling, potentially reducing their food and energy intake; however, when separated from its mother an infant is at risk of predation. This separation therefore requires that mothers be vigilant, further deterring them from feeding. Allomaternal care (AMC) is hypothesized to allow mothers to safely detach from their infants to feed, permitting them to increase energy intake, which is particularly needed for lactation. We examined the nutritional benefits of AMC in black-and-white colobus monkeys (Colobus guereza) by estimating energy intake by lactating mothers during AMC versus non-AMC. We studied seven mother-infant dyads in three groups of C. guereza during six months in Kibale National Park, Uganda. Immature group members handled infants more often than adults, and females handled infants more often than males. An infant's distance to its mother and its nearest neighbor's age and sex best predicted the occurrence of AMC. Lactating mothers fed more often, fed and rested for longer durations, and consumed more metabolizable energy during AMC compared to when they were caring for their infants. These results demonstrate that AMC in C. guereza provides mothers with feeding opportunities that increase their energy intake.

Doubly labelled water-calibration approach attenuates the underestimation of energy intake calculated from self-reported dietary assessment data in Japanese older adults.

Self-reported energy intake (EI) estimation may incur systematic errors that could be attenuated through biomarker calibration. We aimed to confirm whether calibrated EI was comparable to total energy expenditure (TEE) measured using the doubly labelled water (DLW) technique. Cross-sectional study. General older population from the Kyoto-Kameoka Study, Japan. This study included sub- and main cohorts of 72 and 8058 participants aged≥ 65 years, respectively. EI was evaluated using a validated FFQ, and calibrated EI was obtained using a previously developed equation based on the DLW method. TEE was considered representative of true EI and also measured using the DLW method. We used a Wilcoxon signed-rank test and correlation analysis to compare the uncalibrated and calibrated EI with TEE. In the sub-cohort, the median TEE, uncalibrated EI and calibrated EI were 8559 kJ, 7088 kJ and 9269 kJ, respectively. The uncalibrated EI was significantly lower than the TEE (median difference = -1847 kJ; interquartile range (IQR): -2785 to -1096), although the calibrated EI was not (median difference = 463 kJ; IQR: -330 to 1541). The uncalibrated (r = 0·275) and calibrated EI (r = 0·517) significantly correlated with TEE. The reproducibility was higher for calibrated EI (interclass correlation coefficient (ICC) = 0·982) than for uncalibrated EI (ICC = 0·637). Similar findings were observed when stratifying the sample by sex. For medians, uncalibrated EI was lower (about 17 %) than calibrated EI in the main cohort. Biomarker calibration may improve the accuracy of self-reported dietary intake estimation.

Feasibility and Acceptability of Photographic Food Record, Food Diary and Weighed Food Record in People with Serious Mental Illness.

People with serious mental illness (SMI) experience challenges that may make typical dietary assessment methods less feasible and accurate. This study aims to determine the feasibility, acceptability and preliminary validity of a 3-day photographic food record (PR), a 1-day food diary (FD) and a 1-day weighed food protocol (WR) in people with SMI. Participants completed measures at two timepoints, with a 4-week interval. Feasibility and acceptability for each method were measured through four outcomes: percent of completers, quality assessment, number of participants requiring technical devices and satisfaction questionnaire. Relative validity was measured by agreement in estimated energy intake between methods, using Bland–Altman analysis and WR as the benchmark, and prevalence of misreporting, using the Goldberg cut-off method, updated by Black. In total, 63 participants were recruited, with a dropout rate of 19.0% prior to timepoint 1 and additional 6.4% prior to timepoint 2. Quality deficits were identified for all methods. The FD was most acceptable to participants, followed by the PR. The difference in estimated energy intake between assessment methods was not statistically significant, though there was considerable individual variability. Underreporting was considerable across all methods but appeared highest in the PR. A FD and PR present as feasible and acceptable methods for assessing dietary intake in people with SMI. Further validity testing is required. In addition, clear guidance for completion and removal of potential barriers is required for participants.

A Standard Scale to Measure Equine Keeper Status and the Effect of Metabolic Tendency on Gut Microbiome Structure.

Simple SummaryHorses with different metabolic tendencies are anecdotally referred to as “easy” or “hard” keepers. Easy keepers tend to gain weight easily while hard keepers require extra feed to maintain condition. Both easy and hard keeper horses carry a managerial and financial burden which can be a dissuading factor for horse shoppers. This research uses energy intake/need and body condition to develop a standard Equine Keeper Status Scale (EKSS) for assigning keeper status. The microbiome compositions based on EKSS assignments are then compared to explore microbiome differences based on metabolic tendencies of each group. The EKSS can be used by owners to accurately assess their horses’ metabolic tendencies and make improved feeding decisions to meet their horses’ needs. Understanding microbiome differences between easy, medium and hard keeper horses points to potential microbial roles in these metabolic tendencies.Thriftiness in horses has been associated with more efficient nutrient harvesting in digestion, absorption and/or utilization, but the relative contribution of the gut microbiome to host metabolic tendency is not well understood. Recognizing the unreliability of owner reported assignment of keeper status, this research describes a novel tool for calculating whether a horse is an easy (EK) or hard (HK) keeper and then characterizes microbiome differences in these groups. The Equine Keeper Status Scale (EKSS) was developed and validated based on data gathered from 240 horses. Estimates of dietary energy intakes and requirements to achieve the optimal BCS score of 5 were used in EKSS assignments. Sixty percent of owners’ characterizations disagreed with EKSS identified keeper assignments. Equine fecal 16S rRNA profiles (n = 73) revealed differences in α and β diversities and taxa abundances based on EKSS assignments. EK communities had more Planctomycetes and fewer Euryarcheaota, Spirochaetes and Proteobacteria than HK indicating functional differences in nutrient harvesting between groups. Differences in the gut microbiomes of horses based on keeper assignment point to host/microbial interactions that may underlie some differences in metabolic tendency. The EKSS enables robust, repeatable determination of keeper status which can be used by researchers and horse owners.

Statistical Evaluation of Total Energy Intake Based on the Number of Food Portions and Body Weight

The evaluation of food intake based on various assessment methods is critical and underreporting is frequent. The aim of the study was to develop an indirect statistical method of the total energy intake estimation based on gender, weight and the number of portions. Energy intake prediction was developed and evaluated for validity using energy expenditure measurements given by the WellBeNet app. A total of 190 volunteers with various BMIs were recruited and assigned either in the train or the test sample. The mean energy provided by a portion was evaluated by linear regression models from the train sample. The absolute values of the error between the energy intake estimation and the energy expenditure measurement were calculated for each volunteer, by subgroup and for the whole group. The performance of the models was determined using the validation dataset. As the number of portions is the only variable used in the model, the error was 30.7% and 26.5% in the train and test sample. After adding body weight in the model, the error in absolute value decreased to 8.8% and 10.8% for the normal-weight women and men, and 11.7% and 12.8% for the overweight female and male volunteers, respectively. The findings of this study indicate that a statistical approach and knowledge of the usual number of portions and body weight is effective and sufficient to obtain a precise evaluation of energy intake (about 10% of error) after a simple and brief enquiry.

The effect of different methods to identify, and scenarios used to address energy intake misestimation on dietary patterns derived by cluster analysis

BackgroundAll self-reported dietary intake data are characterized by measurement error, and validation studies indicate that the estimation of energy intake (EI) is particularly affected.MethodsUsing self-reported food frequency and physical activity data from Alberta’s Tomorrow Project participants (n = 9847 men 16,241 women), we compared the revised-Goldberg and the predicted total energy expenditure methods in their ability to identify misreporters of EI. We also compared dietary patterns derived by k-means clustering under different scenarios where misreporters are included in the cluster analysis (Inclusion); excluded prior to completing the cluster analysis (ExBefore); excluded after completing the cluster analysis (ExAfter); and finally, excluded before the cluster analysis but added to the ExBefore cluster solution using the nearest neighbor method (InclusionNN).ResultsThe predicted total energy expenditure method identified a significantly higher proportion of participants as EI misreporters compared to the revised-Goldberg method (50% vs. 47%, p < 0.0001). k-means cluster analysis identified 3 dietary patterns: Healthy, Meats/Pizza and Sweets/Dairy. Among both men and women, participants assigned to dietary patterns changed substantially between ExBefore and ExAfter and also between the Inclusion and InclusionNN scenarios (Hubert and Arabie’s adjusted Rand Index, Kappa and Cramer’s V statistics < 0.8).ConclusionsDifferent scenarios used to account for EI misreporters influenced cluster analysis and hence the composition of the dietary patterns. Continued efforts are needed to explore and validate methods and their ability to identify and mitigate the impact of EI misestimation in nutritional epidemiology.

A comparison of food portion size estimation methods among 11\u201312\u2009year olds: 3D food models vs an online tool using food portion photos (Intake24)

BackgroundTechnology has advanced bringing new cost-effective methods to measure food intake. The aim of the study was to compare food and drink portion estimates from a traditional portion estimation method using 3D food models with portion estimates using an online dietary recall tool, Intake24.Methods11-12 year old children were recruited from secondary schools in Newcastle upon Tyne. Each pupil completed a two-day food diary followed by an interview during which pupils estimated food portion sizes using a range of 3D food models. They also completed Intake24 for the same 2 days. Bland Altman analyses were used to compare mean intake for each method.ResultsSeventy pupils completed both portion estimation methods. There was good agreement in food weight estimations between the two methods (geometric mean ratio 1.00), with limits of agreement ranging from minus 35% to plus 53%. Intake24 provided estimates of energy intake that were 1% lower on average than estimates of energy intake using the food models. Mean intakes of all macro and micronutrients using Intake24 were within 6% of the food model estimates.ConclusionsThe findings suggest that there was little difference in portion estimations from the two methods, allowing comparisons to be made between Intake24 data and food diary data collected from same age pupils using 3D food models in previous years.

An Hospital Application Involving Deep Learning Methodology for Detecting Nutrients Intake

This paper presents a prospective view of how much calories is consumed by a person before and after a meal. From the calorie intake project, the management gets to know whether the person consumed the necessary amount of calorie. Although the hospital diet can provide adequate energy and nutrients, many patients may not consume sufficient food to meet their needs. The estimated energy intake of about one-third of patients was very low, and vitamin C, calcium and zinc intakes were also of concern. At least one-third of patients arriving at the hospital are malnourished. This can mean a patient’s diet does not provide the right amount or appropriate ratio of calories, macronutrients, or micronutrients to promote adequate healing. If this continuous then it may be a risk to the patient’s health and may not be a good sign. In this project, we proposed a deep learning system to monitor the nutrient intake for hospitalized patients. A Camera will scan the amount of food given to the patient, when the patient finishes the meal again the camera will again scan the amount of food the patient has taken. It will also note down the number of calories the patient has intake and the amount of calories the patient has left. This will help hospitalized patient to be healthy and will also help hospital staffs to monitor with ease.