Remote Food Photography Method Research Articles

Energetics of a World-Tour Female Road Cyclist During a Multistage Race (Tour de France Femmes).

Despite the increased popularity of female elite road cycling, research to inform the fueling requirements of these endurance athletes is lacking. In this case study, we report for the first time the energetics of a female world-tour cyclist competing in the 2023 Tour de France Femmes, an 8-day race of the Union Cycliste Internationale. The 29-year-old athlete presented with oligomenorrhea and low T3 before the race. Total daily energy expenditure assessed with the doubly labeled water technique was 7,572kcal/day (∼4.3 physical activity levels), among the highest reported in the literature to date for a female. Crank-based mean maximal power was consistent with female world-tour cyclists (5min, mean 342W, 4.8W/kg; 20min 289W, 4.1W/kg). The average daily energy intake measured with the remote food photography method (Stage Days 1-7) was 5,246kcal and carbohydrate intake was 13.7g/kg (range 9.7-15.9g/kg), and 84g/hr during stages, and an average fat intake of 15% of daily energy intake. An estimated 2,326kcal/day energy deficit was evidenced in a 2.2kg decrease in body mass. Notwithstanding the high carbohydrate intake, the athlete was unable to match the energy requirements of the competition. Despite signs of energy deficiency preexisting (oligomenorrhea and low T3), and other further developing during the race (weight loss), performance was in line with that of other world-tour cyclists and a best personal performance was recorded for the last stage. This case study emphasizes the need for further research to inform energy requirements for female athletes' optimal performance and health.

The Association Between Diet Quality and Glycemic Outcomes Among People with Type 1 Diabetes

BackgroundThe amount and type of food consumed impacts the glycemic response and insulin needs of people with type 1 diabetes mellitus (T1DM). Daily variability in consumption, reflected in diet quality, may acutely impact glycemic levels and insulin needs. ObjectiveType 1 Diabetes Exercise Initiative (T1DEXI) data were examined to evaluate the impact of daily diet quality on near-term glycemic control and interaction with exercise. MethodsUsing the Remote Food Photography Method, ≤8 d of dietary intake data were analyzed per participant. Diet quality was quantified with the Healthy Eating Index-2015 (HEI), where a score of 100 indicates the highest-quality diet. Each participant day was classified as low HEI (≤57) or high HEI (>57) based on the mean of nationally reported HEI data. Within participants, the relationship between diet quality and subsequent glycemia measured by continuous glucose monitoring (CGM) and total insulin dose usage was evaluated using a paired t-test and robust regression models. ResultsTwo hundred twenty-three adults (76% female) with mean ± SD age, HbA1c, and body mass index (BMI) of 37 ± 14 y, 6.6% ± 0.7%, and 25.1 ± 3.6 kg/m2, respectively, were included in these analyses. The mean HEI score was 56 across all participant days. On high HEI days (mean, 66 ± 4) compared with low HEI days (mean, 47 ± 5), total time in range (70–180 mg/dL) was greater (77.2% ± 14% compared with 75.7% ± 14%, respectively, P = 0.01), whereas time above 180 mg/dL (19% ± 14% compared with 21% ± 15%, respectively, P = 0.004), mean glucose (143 ± 22 compared with 145 ± 22 mg/dL, respectively, P = 0.02), and total daily insulin dose (0.52 ± 0.18 compared with 0.54 ± 0.18 U/kg/d, respectively, P = 0.009) were lower. The interaction between diet quality and exercise on glycemia was not significant. ConclusionsHigher HEI scores correlated with improved glycemia and lower insulin needs, although the impact of diet quality was modest and smaller than the previously reported impact of exercise.

An explanation for the accuracy of sensor-based measures of energy intake: Amount of food consumed matters more than dietary composition

Understanding and intervening on eating behavior often necessitates measurement of energy intake (EI); however, commonly utilized and widely accepted methods vary in accuracy and place significant burden on users (e.g., food diaries), or are costly to implement (e.g., doubly labeled water). Thus, researchers have sought to leverage inexpensive and low-burden technologies such as wearable sensors for EI estimation. Paradoxically, one such methodology that estimates EI via smartwatch-based bite counting has demonstrated high accuracy in laboratory and free-living studies, despite only measuring the amount, not the composition, of food consumed. This secondary analysis sought to further explore this phenomenon by evaluating the degree to which EI can be explained by a sensor-based estimate of the amount consumed versus the energy density (ED) of the food consumed. Data were collected from 82 adults in free-living conditions (51.2% female, 31.7% racial and/or ethnic minority; Mage = 33.5, SD = 14.7) who wore a bite counter device on their wrist and used smartphone app to implement the Remote Food Photography Method (RFPM) to assess EI and ED for two weeks. Bite-based estimates of EI were generated via a previously validated algorithm. At a per-meal level, linear mixed effect models indicated that bite-based EI estimates accounted for 23.4% of the variance in RFPM-measured EI, while ED and presence of a beverage accounted for only 0.2% and 0.1% of the variance, respectively. For full days of intake, bite-based EI estimates and ED accounted for 41.5% and 0.2% of the variance, respectively. These results help to explain the viability of sensor-based EI estimation even in the absence of information about dietary composition.

Under-Fuelling for the Work Required? Assessment of Dietary Practices and Physical Loading of Adolescent Female Soccer Players during an Intensive International Training and Game Schedule.

Previous studies demonstrate that "under-fuelling" (i.e., reduced carbohydrate (CHO) and energy intake (EI) in relation to recommended guidelines) is prevalent within adult female soccer players, the consequence of which may have acute performance and chronic health implications. However, the dietary practices of adolescent female soccer players, a population who may be particularly at risk for the negative aspects of low energy availability (LEA), are not well documented. Accordingly, we aimed to quantify EI and CHO intake, physical loading and estimated energy availability (EA) in elite national team adolescent female soccer players (n = twenty-three; age, 17.9 ± 0.5 years) during a 10-day training and game schedule comprising two match days on day six (MDa) and nine (MDb). The players self-reported their EI via the remote food photography method, whilst the physical loading and associated exercise energy expenditure were assessed via GPS technology. The relative CHO intake was significantly greater (all p < 0.05) on the day before the first match (MD-1a) (4.1 ± 0.8 g·kg-1), on the day before the second match (MD-1b) (4.3 ± 1.1 g·kg-1), MDa (4.8 ± 1.2 g·kg-1) and MDb (4.8 ± 1.4 g·kg-1) in comparison to most other days (<4 g·kg-1). The mean daily measured EA over the 10-day period was 34 ± 12 kcal·kg FFM-1·day-1 (with six players, i.e., 34%, presenting LEA), though, when adjusting the energy intake for potential under-reporting, these values changed substantially (44 ± 14 kcal·kg FFM-1·day-1, only one player was classed as presenting LEA). Such data suggest that the prevalence of LEA amongst female team sport athletes may be over-estimated. Nonetheless, players are still likely under-fuelling for the work required in relation to the daily CHO recommendations (i.e., >6 g·kg-1) for intensive training and game schedules. These data provide further evidence for the requirement to create and deliver targeted player and stakeholder education and behaviour change interventions (especially for younger athletes) that aim to promote increased daily CHO intake in female soccer players.

330-OR: Healthy Eating Index Correlates with Better Glycemic Control among People with Type 1 Diabetes

The amount and type of food consumed impacts glycemic response and insulin needs of people with type 1 diabetes (T1D). Day to day variation in types of foods consumed or diet quality may acutely impact glycemic levels and insulin needs within an individual with T1D. As part of the Type 1 Diabetes Exercise Initiative (T1Dexi), we examined the impact of overall daily diet quality on glycemic control. Diet quality was assessed by the Healthy Eating Index-2015 (HEI) where a score of 100 indicates highest quality diet characterized by intake of more vegetables, fruits, and whole grains and less intake of saturated fat and added sugar. Dietary intake was captured on up to 12 different days per participant during the one-month study via food photography with the T1Dexi app. Food photos were analyzed for nutrient intake by the Remote Food Photography Method. Mean HEI score for all participants was 57, similar to the general US population. Each day of dietary intake was classified as low (HEI≤57) or high (HEI&amp;gt;57) within a participant and only participants with at least two low and two high HEI days were included in the analysis. CGM and insulin metrics were compared using a linear mixed effect model with a random subject effect. Participants (n=223) were 19-68 years (37±14 years), 76% identified as female, had a mean HbA1C of 6.6±0.7 and a mean body mass index of 25.1±3.6. On high HEI days (mean score: 66±4), total time in range (70-180 mg/dl) was greater (77.2±14% vs 75.7±14% p=0.01), while time above 180 mg/dl (19±14% vs 21±15%, p=0.01) and mean glucose (143±22 vs 145±22 mg/dl, p=0.02) were lower compared to low HEI days (mean score: 47±5). Total daily insulin dose was lower on high HEI days (0.52±0.18 vs 0.54±0.18 U/kg/day p=0.01). Higher diet quality correlates with improved glycemia and lowered insulin needs during that 24-hour period of time within an individual T1D participant but the impact of diet quality was smaller than the impact of exercise and represents an incremental improvement among well-controlled subjects. Disclosure M.B.Gillingham: None. T1dexi study group: n/a. C.Marak: None. P.Calhoun: None. K.E.Neubig: None. S.R.Patton: None. J.R.Castle: Advisory Panel; Novo Nordisk, Zealand Pharma A/S, Research Support; Dexcom, Inc., Stock/Shareholder; Pacific Diabetes Technologies. P.G.Jacobs: Board Member; Pacific Diabetes Technologies, Other Relationship; Pacific Diabetes Technologies, Research Support; Dexcom, Inc. R.L.Gal: None. C.K.Martin: Board Member; EHE Health, Wondr Health, Other Relationship; ABGIL, Research Support; Pack Health, Evidation Health, Lilly, WW International, Inc. Funding The Leona M. and Harry B. Helmsley Charitable Trust; Verily Life Sciences; Dexcom, Inc.

Ecological Validation and Practical Challenges of Conducting Dietary Analysis in Athletic Individuals Using a Novel Remote Food Photography Method Mobile Phone Application

PurposeDietary analysis is an important part of the sports nutrition practitioners’ role, however the ability to accurately collect and analyze dietary intake data is questionable. The remote food photography method (RFPM) has been proposed as a low-burden and potentially valid approach to collecting and interpreting dietary intake data. Preliminary research suggests that this is valid in some athletic populations, however the ecological validation in real-life settings warrants further investigation.MethodsTwenty athletic individuals completed simultaneous three-day RFPM diaries and weighed food diaries for the analysis of energy, protein, carbohydrate, and fat. Participants were required to provide details alongside provided photographs that did not include food weights to allow for the estimation of nutrient intake from minimally invasive photographs and descriptions.ResultsRFPM demonstrated non-significant random and systematic error against the weighed food diary for energy, protein, carbohydrate, and fat at − 20.0 ± 455.5 kcal, − 2.9 ± 34.6 g, − 12.4 ± 49.3 g and 2.3 ± 26.8 g, respectively. Coefficient of variation suggest acceptable agreement between RFPM and weighed food diary for energy and poor agreement for protein, carbohydrate, and fat. Considerable variability is observed in the individual calculated values, with the least and greatest difference being 0% and − 83.0%, respectively.ConclusionThe results indicate that the RFPM may be an ecologically valid tool for the collection and analysis of dietary intake data on a group level; on an individual basis, data and subsequent recommendations based on this method must be applied with caution.

Significant Changes in Resting Metabolic Rate Over a Competitive Match Week Are Accompanied by an Absence of Nutritional Periodization in Male Professional Soccer Players.

Resting metabolic rate (RMR) is an important component of total daily energy expenditure; however, it is currently not understood how it varies across a typical competitive match week in professional soccer players. For the first time, we aimed to assess RMR throughout an in-season competitive week in professional soccer players. Additionally, we aimed to assess energy and carbohydrate intake across the same week. Twenty-four professional soccer players from an English Premier League club (age: 18 ± 1.6years) completed the study. RMR was assessed each morning of a typical competitive match week (match day [MD] -3, -2, -1, +1, +2, and + 3), and dietary intake (including MD) was assessed daily via the remote food photography method and 24-hr recall. Daily training load was quantified using Global Positioning System, daily muscle soreness ratings were recorded, and body composition was assessed via dual-energy X-ray absorptiometry. There was a significant (p = .0004) increase in mean RMR of ∼261kcal/day on MD + 1, compared with MD - 1. Additionally, volume of oxygen consumed significantly increased at MD + 1 (p = .0002) versus MD - 1. There were no significant differences in daily energy or carbohydrate intake across the competitive week (p > .05), with inadequate carbohydrate intakes on MD - 1 (∼3.9g/kg body mass), MD (∼4.2g/kg body mass), and MD + 1 (∼3.6g/kg body mass) in relation to current recommendations. We report, for the first time, that RMR is significantly increased following a competitive match in professional soccer players. In addition, we confirm previous findings to reinforce that players exhibit inadequate nutrition periodization practices, which may impair physical performance and recovery.

The Influence of Full-Time Holistic Support Delivered by a Sports Nutritionist on Within-Day Macronutrient Distribution in New Zealand Provincial Academy Rugby Union Players

Dietary intake is an important consideration for rugby union ('rugby') players to ensure substrate provision for optimal performance and facilitate recovery. Within-day meal distribution is especially important for athletes, particularly those with congested schedules and multiple daily training sessions. In the present study, 10 provincial academy rugby players engaged in a holistic support protocol informed by behaviour-change techniques led by a full-time sports nutritionist. Dietary intake was estimated during a 4-week monitoring and 4-week intervention period using the remote food photography method on one high-volume training day (two training sessions) and two low-volume training days (≤1 training session) per week. Lean body mass did not change significantly in response to the intervention. Significant increases were observed for protein on both low-volume (breakfast, AM snack, evening snack) and high-volume (post-gym, AM snack, evening snack) training days. Carbohydrate intake post-intervention was significantly greater at the pre-gym eating occasion but lower at PM snack and dinner eating occasions on high-volume days. These data suggest that incorporating a holistic support protocol led by a sports nutritionist can influence within-day nutrient intake in rugby players; however, no change to lean body mass was observed, and the influence of these changes in nutrient intake on performance and recovery warrants further investigation.

Acute fuelling and recovery practices of academy soccer players: implications for growth, maturation, and physical performance

ABSTRACT Academy soccer players frequently train in the evening (i.e. 1700-2000 h), hence limited time to nutritionally prepare and recover due to schooling, travel and sleep schedules. Accordingly, we assessed timing and quantity of energy intake in the pre-training and post-training period. Over a 3-day in-season training period, male players (n=48; n=8 from under (U) 12, 13, 14, 15/16, 18 and 23 players) from an English Premier League academy self-reported dietary intake and physical activity levels (via the remote food photography method and activity diary, respectively) in the four hours pre- and post-training. Timing of pre-training energy intake ranged from 40 ± 28 mins (U15/U16 players) to 114 ± 71 mins (U18) before training and mean carbohydrate (CHO) intake ranged from 0.8±0.4 g.kg-1 (U23) to 1.5±0.9 g.kg-1 (U12). Timing of post-training energy intake ranged from 39 ± 27 mins (U14) to 70 ± 84 mins (U23) and mean CHO intake ranged from 1.6±0.8 g.kg-1 (U12) to 0.9±0.5 g.kg-1 (U14). In contrast to CHO, all age groups consumed sufficient protein intake in the post-training period (i.e. > 0.3 g.kg-1). We conclude academy soccer players habitually practice sub-optimal fuelling and recovery strategies, the consequence of which could impair growth, maturation and physical performance.

Patterns of energy availability of free-living athletes display day-to-day variability that is not reflected in laboratory-based protocols: Insights from elite male road cyclists

ABSTRACT The physiological effects of low energy availability (EA) have been studied using a homogenous daily EA pattern in laboratory settings. However, whether this daily EA pattern represents those of free-living athletes and is therefore ecologically valid is unknown. To investigate this, we assessed daily exercise energy expenditure, energy intake and EA in 10 free-living elite male road cyclists (20 min Mean Maximal Power: 5.27 ± 0.25 W · kg−1) during 7 consecutive days of late pre-season training. Energy intake was measured using the remote-food photography method and exercise energy expenditure estimated from cycling crank-based power-metres. Seven-day mean ± SD energy intake and exercise energy expenditure was 57.9 ± 10.4 and 38.4 ± 8.6 kcal · kg FFM−1 · day−1, respectively. EA was 19.5 ± 9.1 kcal · kg FFM−1 · day−1. Within-participants correlation between daily energy intake and exercise energy expenditure was .62 (95% CI: .43 – .75; P < .001), and .60 (95% CI: .41 – .74; P < .001) between carbohydrate intake and exercise energy expenditure. However, energy intake only partially compensated for exercise energy expenditure, increasing 210 kcal · day−1 per 1000 kcal · day−1 increase in expenditure. EA patterns displayed marked day-to-day fluctuation (range: −22 to 76 kcal · kg FFM−1 · day−1). The validity of research using homogenous low EA patterns therefore requires further investigation.

P019 Validation of a Smartphone-Based App for Assessing Energy Intake: A Pilot Study

<h3>Background</h3> Smartphone-based methods are innovative and promising tools to accurately quantify energy intake (EI). The PortionSize^TM app measures dietary intake using embedded templates and provides real-time feedback. PortionSize also sends food images to a server where they can be analyzed using the Remote Food Photography Method (RFPM). The RFPM accurately measures EI; however, it requires human raters to analyze food images; therefore, the RFPM does not provide dietary feedback in real-time. <h3>Objective</h3> To compare the validity of EI estimates from PortionSize and RFPM to weighed meals (WM). <h3>Study Design, Setting, Participants</h3> Fifteen adults used the PortionSize app during covertly-weighed simulated meals in a laboratory setting. Trained personnel also quantified EI from the images captured from the PortionSize using the RFPM. <h3>Measurable Outcome/ Analysis</h3> Demographics and body mass index (BMI). Dependent t-tests were performed to investigate whether EI measured with templates in PortionSize or using the RFPM differed to EI from WM. <h3>Results</h3> Mean (± SD) age and BMI of participants were 28 (± 12) years and 24.1 ± 6.6 kg/m2, respectively, and 73.3% were female. PortionSize estimated EI was 743 ± 328 kcal, EI RFPM-estimated intake was 660 ± 196 kcal, and weighed intake was 659 ± 191 kcal. The mean differences of EI estimation between PortionSize and WM (84 ± 288 kcal) and between RFPM and WM (1 ± 32 kcal) were not significant (<i>P</i> > .05). The mean difference in EI estimation (83 ±284 kcal) between PortionSize and RFPM was not significant (<i>P</i> > .05). <h3>Conclusions</h3> RFPM produced very close estimates of EI to WM but requires a human rater and is not easily scalable. These findings are important as PortionSize provides real-time feedback on dietary intake, which may assist with timely behavior change. Improvements to make PortionSize more scalable are ongoing. This work warrants future well-powered trials. <h3>Funding</h3> NIH; Pennington Biomedical (PBRC)/Louisiana Nutrition Obesity Research Center; Louisiana Clinical and Translational Science Center

Study Protocol for the Feasibility and Acceptability of Remote Food Photography Method (RFPM) to Document Dietary Intake Among Individuals With Spinal Cord Injury (SCI)

Abstract Objectives There is a high prevalence of neurogenic obesity among individuals with spinal cord injury (SCI) with percentages reaching 97% when using body fat percentage cutoff of 22% for men and 35% for women. Accurately measuring energy intake in individuals with SCI is crucial to assess if they are exceeding caloric needs, which can further contribute to obesity. Currently, the pen/paper food record is commonly used to track dietary intake in both the able-bodied (AB) and persons with SCI; however this method is known to be burdensome and to under-report true dietary intake by up to 37% in AB persons. The remote food photography method (RFPM) is a reliable and validated method to accurately measure dietary intake by taking pictures of food and beverages before and after consumption. This method of tracking dietary intake has been validated in individuals without SCI, but not in persons with SCI. Persons with SCI may benefit from a convenient method to track dietary intake due to SCI-specific challenges, such as difficulty writing. The objective of this study protocol is to assess feasibility and acceptability of RFPM in individuals with chronic SCI. Methods 20 participants with SCI (10 with paraplegia and 10 with tetraplegia) will be recruited. Participants must be at least 18 years of age and have chronic SCI (at least 1-year post-injury). Participants will track their dietary intake for a total of two weeks (2 weekdays and 1 weekend for each week) by using RFPM for one week and the traditional pen/paper method for another week. Participants will be randomly assigned to track their intake using either method (RFPM or pen/paper food record) the first week and then cross-over to using the remaining method the second week. Photos of dietary intake will be sent electronically (i.e., smartphone, tablet, etc.). A registered dietitian will review dietary entries for completeness per week with each participant. Feasibility of the RFPM of tracking dietary intake in individuals with SCI will be measured by the number of entries that are documented using RFPM compared to dietary intake as reported by the participant at the end of the week. Acceptability of the RFPM will be assessed by a short survey at the end of the study examining the acceptance of the RFPM for capturing and tracking dietary intake. Results N/A - Protocol Abstract Conclusions N/A - Protocol Abstract Funding Sources N/A.

A Qualitative Analysis of the Remote Food Photography Method and the Automated Self-Administered 24-hour Dietary Assessment Tool for Assessing Children’s Food Intake Reported by Parent Proxy

BackgroundAccuracy and participant burden are two key considerations in the selection of a dietary assessment tool for assessing children’s full-day dietary intake. ObjectiveThe aim of this study was to identify barriers experienced by parents and burden when using two technology-based measures of dietary intake to report their child’s intake: the Remote Food Photography Method (RFPM) and the Automated Self-Administered 24-hour Dietary Assessment Tool (ASA24). DesignQualitative, semistructured, focus groups were conducted with parents who served as proxy reporters of their child’s dietary intake using the two different dietary assessment methods (ie, RFPM and ASA24) 1 week apart. Participants/settingThis study was conducted in 2019 and included 32 parents of children aged 7 to 8 years in Colorado and Louisiana. Main outcome measuresBarriers adhering to the protocol and burden with the RFPM and ASA24. Qualitative analysesQualitative content analysis and Atlas.ti software were used to analyze and interpret focus group data. ResultsFor the RFPM, parents described missing photos due to unobserved intake, forgetting to capture images, disruption of mealtimes, and child embarrassment when meals were photographed at school. For the ASA24, parents described the time commitment as the main source of burden and the need to expand the food database to include additional ethnic foods and restaurant items. The main strengths were ease of use for the RFPM and the consolidated workload for the ASA24. ConclusionsThe barriers experienced by parents and burden differed by method, highlighting the importance of considering the unique characteristics of each assessment tool when designing a pediatric dietary assessment study and interpreting findings.

Preference, Expected Burden, and Willingness to Use Digital and Traditional Methods to Assess Food and Alcohol Intake.

We conducted an online survey to examine the preference, expected burden, and willingness of people to use four different methods of assessing food and alcohol intake such as food/drink record, 24-h recall, Remote Food Photography Method© (RFPM, via SmartIntake® app), and a novel app (PortionSize®) that allows the in-app portion size estimation of foods/drinks by the user. For food (N = 1959) and alcohol (N = 466) intake assessment, 67.3% and 63.3%, respectively, preferred the RFPM/SmartIntake®, 51.9% and 53.4% preferred PortionSize®, 48.0% and 49.3% the food records, and 32.9% and 33.9% the 24-h recalls (difference in preference across all methods was p < 0.001 for food and alcohol intake). Ratings of burden and preference of methods were virtually superimposable, and we found strong correlations between high preference and low expected burden for all methods (all ρ ≥ 0.82; all p < 0.001). Willingness (mean (SD)) to use the RFPM/SmartIntake® (food: 6.6 (2.0); alcohol: 6.4 (2.4)) was greater than PortionSize® (food: 6.0 (2.2); alcohol: 6.0 (2.4); all p < 0.001) and 24-h recalls (food: 6.1 (2.2); alcohol: 5.7 (2.7); p < 0.001), but not different from food records (food: 6.6 (2.0); alcohol: 6.5 (2.3); all p ≥ 0.33). Our results can be used in conjunction with existing data on the reliability and validity of these methods in order to inform the selection of methods for the assessment of food and alcohol intake.

A comparison of the remote food photography method and the automated self-administered 24-h dietary assessment tool for measuring full-day dietary intake among school-age children.

The limitations of self-report measures of dietary intake are well-known. Novel, technology-based measures of dietary intake may provide a more accurate, less burdensome alternative to existing tools. The first objective of this study was to compare participant burden for two technology-based measures of dietary intake among school-age children: the Automated-Self-Administered 24-hour Dietary Assessment Tool-2018 (ASA24-2018) and the Remote Food Photography Method (RFPM). The second objective was to compare reported energy intake for each method to the Estimated Energy Requirement for each child, as a benchmark for actual intake. Forty parent-child dyads participated in two, 3-d dietary assessments: a parent proxy-reported version of the ASA24 and the RFPM. A parent survey was subsequently administered to compare satisfaction, ease of use and burden with each method. A linear mixed model examined differences in total daily energy intake between assessments, and between each assessment method and the Estimated Energy Requirement (EER). Reported energy intake was 379 kcal higher with the ASA24 than the RFPM (P = 0·0002). Reported energy intake with the ASA24 was 231 kcal higher than the EER (P = 0·008). Reported energy intake with the RFPM did not differ significantly from the EER (difference in predicted means = -148 kcal, P = 0·09). Median satisfaction and ease of use scores were five out of six for both methods. A higher proportion of parents reported that the ASA24 was more time-consuming than the RFPM (74·4 % v. 25·6 %, P = 0·002). Utilisation of both methods is warranted given their high satisfaction among parents.

An Assessment of the Validity of the Remote Food Photography Method (Termed Snap-N-Send) in Experienced and Inexperienced Sport Nutritionists

The remote food photography method, often referred to as "Snap-N-Send" by sport nutritionists, has been reported as a valid method to assess energy intake in athletic populations. However, preliminary studies were not conducted in true free-living conditions, and dietary assessment was performed by one researcher only. The authors, therefore, assessed the validity of Snap-N-Send to assess the energy and macronutrient composition in experienced (EXP, n = 23) and inexperienced (INEXP, n = 25) sport nutritionists. The participants analyzed 2 days of dietary photographs, comprising eight meals. Day 1 consisted of "simple" meals based around easily distinguishable foods (i.e.,chicken breast and rice), and Day 2 consisted of "complex" meals, containing "hidden" ingredients (i.e.,chicken curry). The estimates of dietary intake were analyzed for validity using one-sample t tests and typical error of estimates (TEE). The INEXP and EXP nutritionists underestimated energy intake for the simple day (mean difference [MD] = -1.5MJ, TEE = 10.1%; -1.2MJ, TEE = 9.3%, respectively) and the complex day (MD = -1.2MJ, TEE = 17.8%; MD = -0.6MJ, 14.3%, respectively). Carbohydrate intake was underestimated by INEXP (MD = -65.5g/day, TEE = 10.8% and MD = -28.7g/day, TEE = 24.4%) and EXP (MD = -53.4g/day, TEE = 10.1% and -19.9g/day, TEE = 17.5%) for both the simple and complex days, respectively. Interpractitioner reliability was generally "poor" for energy and macronutrients. The data demonstrate that the remote food photography method/Snap-N-Send underestimates energy intake in simple and complex meals, and these errors are evident in the EXP and INEXP sport nutritionists.

No association between consumption of eggs with energy or macronutrient intake: Objective evidence from the remote food photography method

Background and aimsGreater egg consumption is associated with poor glycemic control. However, greater egg intake could simply be a marker for other dietary indiscretions such as greater intake of energy or saturated fat, which may influence glycemic control. We examined the association between egg consumption and total energy intake and saturated fat intake, measured using the remote food photography method. MethodsAn observational study was conducted with 48 healthy adults consuming ≥1 eggs/week. Photographs of all meals consumed for seven days were captured via a smartphone application called SmartIntake® and analyzed for nutrient intake. Fasting blood samples were collected. Linear correlations between egg consumption and nutrient intake or measures of glycemic control were determined. ResultsDaily egg intake was significantly associated with cholesterol intake, but not with the daily energy and saturated fat intake or measures of glycemic control. ConclusionsHigher consumption of eggs in free-living conditions was not associated with undesirable profiles of macronutrient intake, total EI, or an impaired glycemic profile in this study population. Thus, the assertion that eggs are linked with impaired glycemic control because of the accompanying intake of greater energy and saturated fat, does not appear valid. Trial registrationNCT 03404700.

Assessing Mealtime Macronutrient Content: Patient Perceptions Versus Expert Analyses via a Novel Phone App.

Background: People with type 1 diabetes estimate meal carbohydrate content to accurately dose insulin, yet, protein and fat content of meals also influences postprandial glycemia. We examined accuracy of macronutrient content estimation via a novel phone app. Participant estimates were compared with expert nutrition analyses performed via the Remote Food Photography Method© (RFPM©). Methods: Data were collected through a novel phone app. Participants were asked to take photos of meals/snacks on the day of and day after scheduled exercise, enter carbohydrate estimates, and categorize meals as low, typical, or high protein and fat. Glycemia was measured via continuous glucose monitoring. Results: Participants (n = 48) were 15-68 years (34 ± 14 years); 40% were female. The phone app plus RFPM© analysis captured 88% ± 29% of participants' estimated total energy expenditure. The majority (70%) of both low-protein and low-fat meals were accurately classified. Only 22% of high-protein meals and 17% of high-fat meals were accurately classified. Forty-nine percent of meals with <30 g of carbohydrates were overestimated by an average of 25.7 ± 17.2 g. The majority (64%) of large carbohydrate meals (≥60 g) were underestimated by an average of 53.6 ± 33.8 g. Glycemic response to large carbohydrate meals was similar between participants who underestimated or overestimated carbohydrate content, suggesting that factors beyond carbohydrate counting may impact postprandial glycemic response. Conclusions: Accurate estimation of total macronutrients in meals could be leveraged to improve insulin decision support tools and closed loop insulin delivery systems; development of tools to improve macronutrient estimation skills should be considered.

Resistant Starch Has No Effect on Appetite and Food Intake in Individuals with Prediabetes

BackgroundType 2 resistant starch (RS2) has been shown to improve metabolic health outcomes and may increase satiety and suppress appetite and food intake in humans. ObjectiveThis study assessed whether 12 weeks of daily RS2 supplementation could influence appetite perception, food intake, and appetite-related gut hormones in adults with prediabetes, relative to the control (CTL) group. DesignThe study was a randomized controlled trial and analysis of secondary study end points. Participants/settingSixty-eight adults (body mass index ≥27) aged 35 to 75 years with prediabetes were enrolled in the study at Pennington Biomedical Research Center (2012 to 2016). Fifty-nine subjects were included in the analysis. InterventionParticipants were randomized to consume 45 g/day of high-amylose maize (RS2) or an isocaloric amount of the rapidly digestible starch amylopectin (CTL) for 12 weeks. Main outcome measuresSubjective appetite measures were assessed via visual analogue scale and the Eating Inventory; appetite-related gut hormones (glucagon-like peptide 1, peptide YY, and ghrelin) were measured during a standard mixed-meal test; and energy and macronutrient intake were assessed by a laboratory food intake (buffet) test, the Remote Food Photography Method, and SmartIntake app. Statistical analyses performedData were analyzed using linear mixed models, adjusting for treatment group and time as fixed effects, with a significance level of α=.05. ResultsRS2 had no effect on subjective measures of appetite, as assessed by visual analogue scale (P>0.05) and the Eating Inventory (P≥0.24), relative to the CTL group. There were no effects of RS2 supplementation on appetite-related gut hormones, including glucagon-like peptide 1 (P=0.61), peptide YY (P=0.34), and both total (P=0.26) and active (P=0.47) ghrelin compared with the CTL. RS2 had no effect on total energy (P=0.30), carbohydrate (P=0.11), protein (P=0.64), or fat (P=0.37) consumption in response to a buffet meal test, relative to the CTL. In addition, total energy (P=0.40), carbohydrate (P=0.15), protein (P=0.46), and fat (P=0.53) intake, as quantified by the Remote Food Photography Method, were also unaffected by RS2, relative to the CTL. ConclusionsRS2 supplementation did not increase satiety or reduce appetite and food intake in adults with prediabetes.

The current state of parent feeding behavior, child eating behavior, and nutrition intake in young children with type 1 diabetes.

One integral component of type 1 diabetes (T1D) management is attention to nutrition, which can be particularly challenging in young children. The current study reports on parent and child eating/feeding behavior and nutrition intake as compared with current recommendations for pediatric T1D. Participants were 46 children ages 2 to 5 diagnosed with T1D and one parent. The Behavioral Pediatrics Feeding Assessment Scale (BPFAS) was used to assess parent feeding and child eating behaviors. The Remote Food Photography Method (RFPM) was used to analyze nutrition intake at breakfast. Demographic and medical information were collected via self-report and medical chart review. In the current sample, 37% of BPFAS scores were above the cutoff for problem child eating behavior. Only 28% of participants met the recommended goals for glycemic control (hemoglobin A1c, HbA1c < 7.5). Children who did not meet glycemic control targets reported higher carbohydrate intake than those meeting targets. Protein recommendations were met by 46%; 22.7% met the recommendation for carbohydrate intake, and 45.5% met fat intake recommendations. The majority of the sample did not meet body mass index percentile (BMI%) recommendations with 51% having a BMI% above the 85th percentile. Many parents of young children with T1D report problem child eating behaviors. Further, a significant number of young children are not meeting glycemic, nutritional, or BMI guidelines for T1D. Routine screening for dietary difficulties in young children is warranted. Future research should aim to examine interventions targeting families with young children not meeting nutrition, glycemic, or BMI guidelines.