Advances and Controversies in Diet and Physical Activity Measurement in Youth

Postprandial Glucose Variability Following Typical Meals in Youth Living with Type 1 Diabetes

We explored the association between macronutrient intake and postprandial glucose variability in a large sample of youth living with T1D and consuming free-living meals. In the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) Study, youth took photographs before and after their meals on 3 days during a 10 day observation period. We used the remote food photograph method to obtain the macronutrient content of youth's meals. We also collected physical activity, continuous glucose monitoring, and insulin use data. We measured glycemic variability using standard deviation (SD) and coefficient of variation (CV) of glucose for up to 3 h after meals. Our sample included 208 youth with T1D (mean age: 14 ± 2 years, mean HbA1c: 54 ± 14.2 mmol/mol [7.1 ± 1.3%]; 40% female). We observed greater postprandial glycemic variability (SD and CV) following meals with more carbohydrates. In contrast, we observed less postprandial variability following meals with more fat (SD and CV) and protein (SD only) after adjusting for carbohydrates. Insulin modality, exercise after meals, and exercise intensity did not influence associations between macronutrients and postprandial glycemic variability. To reduce postprandial glycemic variability in youth with T1D, clinicians should encourage diversified macronutrient meal content, with a goal to approximate dietary guidelines for suggested carbohydrate intake.

Population mobility data provides meaningful indicators of fast food intake and diet-related diseases in diverse populations

The characteristics of food environments people are exposed to, such as the density of fast food (FF) outlets, can impact their diet and risk for diet-related chronic disease. Previous studies examining the relationship between food environments and nutritional health have produced mixed findings, potentially due to the predominant focus on static food environments around people's homes. As smartphone ownership increases, large-scale data on human mobility (i.e., smartphone geolocations) represents a promising resource for studying dynamic food environments that people have access to and visit as they move throughout their day. This study investigates whether mobility data provides meaningful indicators of diet, measured as FF intake, and diet-related disease, evaluating its usefulness for food environment research. Using a mobility dataset consisting of 14.5 million visits to geolocated food outlets in Los Angeles County (LAC) across a representative sample of 243,644 anonymous and opted-in adult smartphone users in LAC, we construct measures of visits to FF outlets aggregated over users living in neighborhood. We find that the aggregated measures strongly and significantly correspond to self-reported FF intake, obesity, and diabetes in a diverse, representative sample of 8,036 LAC adults included in a population health survey carried out by the LAC Department of Public Health. Visits to FF outlets were a better predictor of individuals' obesity and diabetes than their self-reported FF intake, controlling for other known risks. These findings suggest mobility data represents a valid tool to study people's use of dynamic food environments and links to diet and health.

Technology to Automatically Record Eating Behavior in Real Life: A Systematic Review

To monitor adherence to diets and to design and evaluate nutritional interventions, it is essential to obtain objective knowledge about eating behavior. In most research, measures of eating behavior are based on self-reporting, such as 24-h recalls, food records (food diaries) and food frequency questionnaires. Self-reporting is prone to inaccuracies due to inaccurate and subjective recall and other biases. Recording behavior using nonobtrusive technology in daily life would overcome this. Here, we provide an up-to-date systematic overview encompassing all (close-to) publicly or commercially available technologies to automatically record eating behavior in real-life settings. A total of 1328 studies were screened and, after applying defined inclusion and exclusion criteria, 122 studies were included for in-depth evaluation. Technologies in these studies were categorized by what type of eating behavior they measure and which type of sensor technology they use. In general, we found that relatively simple sensors are often used. Depending on the purpose, these are mainly motion sensors, microphones, weight sensors and photo cameras. While several of these technologies are commercially available, there is still a lack of publicly available algorithms that are needed to process and interpret the resulting data. We argue that future work should focus on developing robust algorithms and validating these technologies in real-life settings. Combining technologies (e.g., prompting individuals for self-reports at sensed, opportune moments) is a promising route toward ecologically valid studies of eating behavior.

Strengthening Research that Answers Nutrition Questions of Public Health Importance: Leveraging the Experience of the USDA Nutrition Evidence Systematic Review Team

The Nutrition Evidence Systematic Review (NESR) team conducts nutrition- and public health-related systematic reviews and is within the USDA's Center for Nutrition Policy and Promotion. NESR has collaborated with scientific experts to conduct systematic reviews on nutrition and public health topics for more than a decade and is uniquely positioned to share recommendations with the research community to strengthen research quality and impact, especially the evidence base that supports public health nutrition guidance, including future editions of the Dietary Guidelines for Americans. Leveraging the expertise of NESR and its systematic review process resulted in the following recommendations for the research community: a) use the strongest study design feasible with sufficient sample size(s); b) enroll study participants who reflect the diversity of the population of interest and report participant characteristics; c) use valid and reliable dietary assessment methods; d) describe the interventions or exposures of interest and use standard definitions to promote consistency; e) use valid and reliable health outcome measures; f) account for variables that may impact the relationship between nutrition-related interventions or exposures and health outcomes; g) carry out studies for a sufficient duration and include repeated measures, as appropriate; and h) report all relevant information to inform accurate interpretation and evaluation of study results. Implementing these recommendations can strengthen nutrition and public health evidence and increase its utility in future public health nutrition systematic reviews. However, implementation will require additional support from the entire research community, including scientific journals and funding agencies.

Improvement of Methodology for Manual Energy Intake Estimation From Passive Capture Devices

Objective

To describe best practices for manual nutritional analyses of data from passive capture wearable devices in free-living conditions.

Method

18 participants (10 female) with a mean age of 45 ± 10 years and mean BMI of 34.2 ± 4.6 kg/m² consumed usual diet for 3 days in a free-living environment while wearing an automated passive capture device. This wearable device facilitates capture of images without manual input from the user. Data from the first nine participants were used by two trained nutritionists to identify sources contributing to inter-nutritionist variance in nutritional analyses. The nutritionists implemented best practices to mitigate these sources of variance in the next nine participants. The three best practices to reduce variance in analysis of energy intake (EI) estimation were: (1) a priori standardized food selection, (2) standardized nutrient database selection, and (3) increased number of images captured around eating episodes.

Results

Inter-rater repeatability for EI, using intraclass correlation coefficient (ICC), improved by 0.39 from pre-best practices to post-best practices (0.14 vs 0.85, 95% CI, respectively), Bland–Altman analysis indicated strongly improved agreement between nutritionists for limits of agreement (LOA) post-best practices.

Conclusion

Significant improvement of ICC and LOA for estimation of EI following implementation of best practices demonstrates that these practices improve the reproducibility of dietary analysis from passive capture device images in free-living environments.

Validity and Feasibility of the Monitoring and Modeling Family Eating Dynamics System to Automatically Detect In-field Family Eating Behavior: Observational Study

Background

The field of dietary assessment has a long history, marked by both controversies and advances. Emerging technologies may be a potential solution to address the limitations of self-report dietary assessment methods. The Monitoring and Modeling Family Eating Dynamics (M2FED) study uses wrist-worn smartwatches to automatically detect real-time eating activity in the field. The ecological momentary assessment (EMA) methodology was also used to confirm whether eating occurred (ie, ground truth) and to measure other contextual information, including positive and negative affect, hunger, satiety, mindful eating, and social context.

Objective

This study aims to report on participant compliance (feasibility) to the 2 distinct EMA protocols of the M2FED study (hourly time-triggered and eating event–triggered assessments) and on the performance (validity) of the smartwatch algorithm in automatically detecting eating events in a family-based study.

Methods

In all, 20 families (58 participants) participated in the 2-week, observational, M2FED study. All participants wore a smartwatch on their dominant hand and responded to time-triggered and eating event–triggered mobile questionnaires via EMA while at home. Compliance to EMA was calculated overall, for hourly time-triggered mobile questionnaires, and for eating event–triggered mobile questionnaires. The predictors of compliance were determined using a logistic regression model. The number of true and false positive eating events was calculated, as well as the precision of the smartwatch algorithm. The Mann-Whitney U test, Kruskal-Wallis test, and Spearman rank correlation were used to determine whether there were differences in the detection of eating events by participant age, gender, family role, and height.

Results

The overall compliance rate across the 20 deployments was 89.26% (3723/4171) for all EMAs, 89.7% (3328/3710) for time-triggered EMAs, and 85.7% (395/461) for eating event–triggered EMAs. Time of day (afternoon odds ratio [OR] 0.60, 95% CI 0.42-0.85; evening OR 0.53, 95% CI 0.38-0.74) and whether other family members had also answered an EMA (OR 2.07, 95% CI 1.66-2.58) were significant predictors of compliance to time-triggered EMAs. Weekend status (OR 2.40, 95% CI 1.25-4.91) and deployment day (OR 0.92, 95% CI 0.86-0.97) were significant predictors of compliance to eating event–triggered EMAs. Participants confirmed that 76.5% (302/395) of the detected events were true eating events (ie, true positives), and the precision was 0.77. The proportion of correctly detected eating events did not significantly differ by participant age, gender, family role, or height (P>.05).

Conclusions

This study demonstrates that EMA is a feasible tool to collect ground-truth eating activity and thus evaluate the performance of wearable sensors in the field. The combination of a wrist-worn smartwatch to automatically detect eating and a mobile device to capture ground-truth eating activity offers key advantages for the user and makes mobile health technologies more accessible to nonengineering behavioral researchers.

Calibration of the Online Youth Activity Profile Assessment for School-Based Applications

A balance between the feasibility and validity of measures is an important consideration for physical activity research - particularly in school-based research with youth. The present study extends previously tested calibration methods to develop and test new equations for an online version of the Youth Activity Profile (YAP) tool, a self-report tool designed for school applications. Data were collected across different regions and seasons to develop more robust, generalizable equations. The study involved a total of 717 youth from 33 schools (374 elementary (ages 9-11), 224 middle (ages 11-14), and 119 high school (ages 14-18)) in two different states in the U.S. Participants wore a Sensewear monitor for a full week and then completed the online YAP at school to report physical activity (PA) and sedentary behaviors (SB) in school and at home. Accelerometer data were processed using an R-based segmentation program to compute PA and SB levels. Quantile regression models were used with half of the sample to develop item-specific YAP calibration equations and these were cross validated with the remaining half of the sample. Computed values of Mean Absolute Percent Error (MAPE) ranged from 15-25% with slightly lower error observed for the middle school sample. The new equations had improved precision compared to the previous versions when tested on the same sample. The online version of the YAP provides an efficient and effective way to capture school level estimates of PA and SB in youth.

Measurement challenges for childhood obesity research within and between Latin America and the United States

Childhood obesity is a major public health challenge across Latin America and the United States. Addressing childhood obesity depends on valid, reliable, and culturally sensitive measurements. Such progress within and between countries of the Americas could be enhanced through better measurement across different age groups, different countries, and in sending and receiving communities. Additionally, better and more comparable measurements could accelerate cross-border collaboration and learning. Here, we present (1) frameworks that influenced our perspectives on childhood obesity and measurement needs across the Americas; (2) a summary of resources and guidance available concerning measurement and adaptation of measures for childhood obesity research; and (3) three major areas that present challenges and opportunities for measurement advances related to childhood obesity, including parental behavior, acculturation, and the potential to incorporate ethnographic methods to identify critical factors related to economics and globalization. Progress to reduce childhood obesity across the Americas could be accelerated by further transnational collaboration aimed at improving measurement for better surveillance, intervention development and evaluation, implementation research, and evaluation of natural experiments. Additionally, there is a need to improve training related to measurement and for improving access to valid and reliable measures in Spanish and other languages common in the Americas.

Comparison of energy intake assessed by image-assisted food records to doubly labelled water in adolescents with intellectual and developmental disabilities: a feasibility study

BACKGROUND

There are currently no validated methods for energy intake assessment in adolescents with intellectual and developmental disabilities (IDD). The purpose of this study was to determine the feasibility of collecting 3-day image-assisted food records (IARs) and doubly labelled water (TDEE_DLW ) data in adolescents with IDD and to obtain preliminary estimates of validity and reliability for energy intake estimated by IAR.

METHODS

Adolescents with IDD completed a 14-day assessment of mean daily energy expenditure using doubly labelled water. Participants were asked to complete 3-day IARs twice during the 14-day period. To complete the IAR, participants were asked to fill out a hard copy food record over three consecutive days (two weekdays/one weekend day) and to take before and after digital images of all foods and beverages consumed using an iPad tablet provided by the study. Energy intake from the IAR was calculated using Nutrition Data System for Research. Mean differences, intraclass correlations and Bland-Altman limits of agreement were performed.

RESULTS

Nineteen adolescents with IDD, mean age 15.1 years, n = 6 (31.6%) female and n = 6 (31.6%) ethnic/racial minorities, enrolled in the trial. Participants successfully completed their 3-day food records and self-collected doubly labelled water urine samples for 100% of required days. Images were captured for 67.4 ± 30.1% of all meals recorded at assessment 1 and 72.3 ± 29.5% at assessment 2. The energy intake measured by IAR demonstrated acceptable test-retest reliability (intraclass correlation = 0.70). On average, IAR underestimated total energy intake by -299 ± 633 kcal/day (mean per cent error = -9.6 ± 22.2%); however, there was a large amount of individual variability in differences between the IAR and TDEE_DLW (range = -1703 to 430).

CONCLUSIONS

The collection of IAR and TDEE_DLW is feasible in adolescents with IDD. While future validation studies are needed, the preliminary estimates obtained by this study suggest that in adolescents with IDD, the IAR method has acceptable reliability and may underestimate energy intake by ~9%.

Associations of Physical Activity and Sedentary Behaviour Assessed by Accelerometer with Body Composition among Children and Adolescents: A Scoping Review

The possible adverse health effects of reduced physical activity (PA) on children and adolescents have been extensively documented as a result of the global obesity epidemic. However, the research has sometimes led to controversial results, due to the different methods used for the assessment of PA. The main aim of this review was to evaluate the association between PA and body composition parameters based on quantitative PA studies using the same equipment (Actigraph accelerometer) and cutoffs (Evenson’s). A literature review was undertaken using PUBMED and Scopus databases. Subjects aged 6–15 were considered separately by sex. Weighted multiple regression analyses were conducted. From the analysis of fourteen selected articles, it emerged that 35.7% did not evaluate the association of sedentary time (ST) and moderate-to-vigorous physical activity (MVPA) with body composition, while the remaining 64.3% found a negative association of MVPA with BMI and fat mass with different trends according to sex. Furthermore, only 7.1% of these studies identified a positive association between ST and fat percentage. Based on the regression analyses conducted on the literature data, ST and MVPA were found to be significant predictors of body composition parameters, in addition to age and sex. Further studies using standardized methodologies to assess PA and body composition are needed. The inclusion of sex-disaggregated data may also be crucial to understand this phenomenon and to provide stronger evidence of the determinants of body composition in order to prevent the risk of obesity.

Associations Between Parent Self-Reported and Accelerometer-Measured Physical Activity and Sedentary Time in Children: Ecological Momentary Assessment Study

BACKGROUND

Retrospective self-report questionnaires are the most common method for assessing physical activity (PA) and sedentary behavior (SB) in children when the use of objective assessment methods (eg, accelerometry) is cost prohibitive. However, self-report measures have limitations (eg, recall bias). The use of real-time, mobile ecological momentary assessment (EMA) has been proposed to address these shortcomings. The study findings will provide useful information for researchers interested in using EMA surveys for measuring PA and SB in children, particularly when reported by a parent or caregiver.

OBJECTIVE

This study aimed to examine the associations between the parent's EMA report of their child's PA and SB and accelerometer-measured sedentary time (ST), light-intensity PA (LPA), and moderate-to-vigorous-intensity PA (MVPA) and to examine if these associations differed by day of week, sex, and season.

METHODS

A total of 140 parent-child dyads (mean child age 6.4 years, SD 0.8; n=66 girls; n=21 African American; n=24 American Indian; n=25 Hispanic/Latino; n=24 Hmong; n=22 Somali; and n=24 white) participated in this study. During an 8-day period, parents reported child PA and SB via multiple daily signal contingent EMA surveys, and children wore a hip-mounted accelerometer to objectively measure ST, LPA, and MVPA. Accelerometer data was matched to the time period occurring before parent EMA-report of child PA and SB. Generalized estimating equations with interaction-term analyses were performed to determine whether the relationship between parent-EMA report of child PA and SB and accelerometer-measured ST and LPA and MVPA outcomes differed by day of the week, sex and season.

RESULTS

The parent's EMA report of their child's PA and SB was strongly associated with accelerometer-measured ST, LPA, and MVPA. The parent's EMA report of their child's PA was stronger during the weekend than on weekdays for accelerometer-measured ST (P≤.001) and LPA (P<.001). For the parent's EMA report of their child's SB, strong associations were observed with accelerometer-measured ST (P<.001), LPA (P=.005), and MVPA (P=.008). The findings related to sex-interaction terms indicated that the association between the parent-reported child's PA via EMA and the accelerometer-measured MVPA was stronger for boys than girls (P=.02). The association between the parent's EMA report of their child's PA and SB and accelerometer-measured ST and PA was similar across seasons in this sample (all P values >.31).

CONCLUSIONS

When the use of accelerometry-based methods is not feasible and in contexts where the parent is able to spend more proximate time observing the child's PA and SB, the parent's EMA report might be a superior method for measuring PA and SB in young children relative to self-report, given the EMA's strong associations with accelerometer-measured PA and ST.

Automatic, wearable-based, in-field eating detection approaches for public health research: a scoping review

Dietary intake, eating behaviors, and context are important in chronic disease development, yet our ability to accurately assess these in research settings can be limited by biased traditional self-reporting tools. Objective measurement tools, specifically, wearable sensors, present the opportunity to minimize the major limitations of self-reported eating measures by generating supplementary sensor data that can improve the validity of self-report data in naturalistic settings. This scoping review summarizes the current use of wearable devices/sensors that automatically detect eating-related activity in naturalistic research settings. Five databases were searched in December 2019, and 618 records were retrieved from the literature search. This scoping review included N = 40 studies (from 33 articles) that reported on one or more wearable sensors used to automatically detect eating activity in the field. The majority of studies (N = 26, 65%) used multi-sensor systems (incorporating > 1 wearable sensors), and accelerometers were the most commonly utilized sensor (N = 25, 62.5%). All studies (N = 40, 100.0%) used either self-report or objective ground-truth methods to validate the inferred eating activity detected by the sensor(s). The most frequently reported evaluation metrics were Accuracy (N = 12) and F1-score (N = 10). This scoping review highlights the current state of wearable sensors' ability to improve upon traditional eating assessment methods by passively detecting eating activity in naturalistic settings, over long periods of time, and with minimal user interaction. A key challenge in this field, wide variation in eating outcome measures and evaluation metrics, demonstrates the need for the development of a standardized form of comparability among sensors/multi-sensor systems and multidisciplinary collaboration.

The effect of mild sleep deprivation on diet and eating behaviour in children: protocol for the Daily Rest, Eating, and Activity Monitoring (DREAM) randomized cross-over trial

BACKGROUND

Although insufficient sleep has emerged as a strong, independent risk factor for obesity in children, the mechanisms by which insufficient sleep leads to weight gain are uncertain. Observational research suggests that being tired influences what children eat more than how active they are, but only experimental research can determine causality. Few experimental studies have been undertaken to determine how reductions in sleep duration might affect indices of energy balance in children including food choice, appetite regulation, and sedentary time. The primary aim of this study is to objectively determine whether mild sleep deprivation increases energy intake in the absence of hunger.

METHODS

The Daily, Rest, Eating, and Activity Monitoring (DREAM) study is a randomized controlled trial investigating how mild sleep deprivation influences eating behaviour and activity patterns in children using a counterbalanced, cross-over design. One hundred and ten children aged 8-12 years, with normal reported sleep duration of 8-11 h per night will undergo 2 weeks of sleep manipulation; seven nights of sleep restriction by going to bed 1 hr later than usual, and seven nights of sleep extension going to bed 1 hr earlier than usual, separated by a washout week. During each experimental week, 24-h movement behaviours (sleep, physical activity, sedentary behaviour) will be measured via actigraphy; dietary intake and context of eating by multiple 24-h recalls and wearable camera images; and eating behaviours via objective and subjective methods. At the end of each experimental week a feeding experiment will determine energy intake from eating in the absence of hunger. Differences between sleep conditions will be determined to estimate the effects of reducing sleep duration by 1-2 h per night.

DISCUSSION

Determining how insufficient sleep predisposes children to weight gain should provide much-needed information for improving interventions for the effective prevention of obesity, thereby decreasing long-term morbidity and healthcare burden.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12618001671257 . Registered 10 October 2018.

Nutrition Education and Dietary Behavior Change Games: A Scoping Review

Games provide an attractive venue for engaging participants and increasing nutrition-related knowledge and dietary behavior change, but no review has appeared devoted to this literature. A scoping review of nutrition education and dietary behavior change videogames or interactive games was conducted. A systematic search was made of PubMed, Agricola, and Google Scholar. Information was abstracted from 22 publications. To be included, the publication had to include a videogame or interactive experience involving games (a videogame alone, minigames inserted into a larger multimedia experience, or game as part of a human-delivered intervention); game's design objective was to influence dietary behavior, a psychosocial determinant of a dietary behavior, or nutrition knowledge (hereinafter referred to as diet-related); must have been reported in English and must have appeared in a professional publication, including some report of outcomes or results (thereby passing some peer review). This review was restricted to the diet-related information in the selected games. Diversity in targeted dietary knowledge and intake behaviors, targeted populations/audiences, game mechanics, behavioral theories, research designs, and findings was revealed. The diversity and quality of the research in general was poor, precluding a meta-analysis or systematic review. All but one of the studies reported some positive outcome from playing the game(s). One reported that a web-based education program resulted in more change than the game-based intervention. Studies of games may have been missed; a number of dietary/nutrition games are known for which no evaluation is known; and the data presented on the games and research were limited and inconsistent. Conclusions and Implications: A firmer research base is needed to establish the efficacy and effectiveness of nutrition education and dietary behavior change games.

Can Wearable Cameras be Used to Validate School-Aged Children's Lifestyle Behaviours?

Wearable cameras combined with accelerometers have been used to estimate the accuracy of children's self-report of physical activity, health-related behaviours, and the contexts in which they occur. There were two aims to this study; the first was to validate questions regarding self-reported health and lifestyle behaviours in 9⁻11-year-old children using the child's health and activity tool (CHAT), an accelerometer and a wearable camera. Second, the study sought to evaluate ethical challenges associated with taking regular photographs using a wearable camera through interviews with children and their families. Fourteen children wore an autographer and hip-worn triaxial accelerometer for the waking hours of one school and one weekend day. For both of these days, children self-reported their behaviours chronologically and sequentially using the CHAT. Data were examined using limits of agreement and percentage agreement to verify if reference methods aligned with self-reported behaviours. Six parent⁻child dyads participated in interviews. Seven, five, and nine items demonstrated good, acceptable, and poor validity, respectively. This demonstrates that the accuracy of children's recall varies according to the behaviour or item being measured. This is the first study to trial the use of wearable cameras in assessing the concurrent validity of children's physical activity and behaviour recall, as almost all other studies have used parent proxy reports alongside accelerometers. Wearable cameras carry some ethical and technical challenges, which were examined in this study. Parents and children reported that the autographer was burdensome and in a few cases invaded privacy. This study demonstrates the importance of adhering to an ethical framework.