Food Intake during School Lunch Is Better Explained by Objectively Measured Eating Behaviors than by Subjectively Rated Food Taste and Fullness: A Cross-Sectional Study

Food intake and eating behaviour during a real-life Snack Scenario in childhood obesity-An experiment using a hidden camera

OBJECTIVE

To compare food intake and eating behaviour in children and adolescents with obesity (OBE) undergoing weight loss intervention and normal weight (NW) in a real-life Snack Scenario.

METHODS

Sixty OBE were examined before (T0) and after weight loss (T1) and compared to a single measurement comparison group of 27 NW. Participants watched a 20-min film and were encouraged to snack from a variety of foods ad libitum. Food intake was measured and eating behaviour assessed via a hidden camera and a validated questionnaire.

RESULTS

The food and energy intake did not differ between NW (155 ± 83 g, 1067 ± 732 kJ) and OBE at T0 (144 ± 106 g, 1088 ± 883 kJ) but increased in OBE at T1 (187 ± 91 g, 1544 ± 845 kJ). Latency of food intake was significantly shorter in NW (0 m:07 s ± 0 m:08 s) compared to OBE (T0: 1 m:11 s ± 2 m:57 s). After weight loss, latency decreased in OBE (0 m:26 s ± 1 m:00 s). NW touched food more often (49 ± 24) than OBE (T0: 29 ± 23), but takes from plate were similar. The questionnaire revealed differences between OBE and NW, not correlating with Snack Scenario observations.

CONCLUSION

Eating behaviours differed in NW versus OBE at T0 but food intake was similar. Therefore, behaviour while eating may be an underestimated factor in the considerations for childhood obesity.

CLINICAL TRIAL REGISTRATION

German Clinical Trials Register (DRKS) with the trial number DRKS00005122.

Fast Eating Is Associated with Increased BMI among High-School Students

Fast self-reported eating rate (SRER) has been associated with increased adiposity in children and adults. No studies have been conducted among high-school students, and SRER has not been validated vs. objective eating rate (OBER) in such populations. The objectives were to investigate (among high-school student populations) the association between OBER and BMI z-scores (BMIz), the validity of SRER vs. OBER, and potential differences in BMIz between SRER categories. Three studies were conducted. Study 1 included 116 Swedish students (mean ± SD age: 16.5 ± 0.8, 59% females) who were eating school lunch. Food intake and meal duration were objectively recorded, and OBER was calculated. Additionally, students provided SRER. Study 2 included students (n = 50, mean ± SD age: 16.7 ± 0.6, 58% females) from Study 1 who ate another objectively recorded school lunch. Study 3 included 1832 high-school students (mean ± SD age: 15.8 ± 0.9, 51% females) from Sweden (n = 748) and Greece (n = 1084) who provided SRER. In Study 1, students with BMIz ≥ 0 had faster OBER vs. students with BMIz < 0 (mean difference: +7.7 g/min or +27%, p = 0.012), while students with fast SRER had higher OBER vs. students with slow SRER (mean difference: +13.7 g/min or +56%, p = 0.001). However, there was “minimal” agreement between SRER and OBER categories (κ = 0.31, p < 0.001). In Study 2, OBER during lunch 1 had a “large” correlation with OBER during lunch 2 (r = 0.75, p < 0.001). In Study 3, fast SRER students had higher BMIz vs. slow SRER students (mean difference: 0.37, p < 0.001). Similar observations were found among both Swedish and Greek students. For the first time in high-school students, we confirm the association between fast eating and increased adiposity. Our validation analysis suggests that SRER could be used as a proxy for OBER in studies with large sample sizes on a group level. With smaller samples, OBER should be used instead. To assess eating rate on an individual level, OBER can be used while SRER should be avoided.

A smartphone application for semi-controlled collection of objective eating behavior data from multiple subjects

BACKGROUND & OBJECTIVE

The study of eating behavior has made significant progress towards understanding the association of specific eating behavioral patterns with medical problems, such as obesity and eating disorders. Smartphones have shown promise in monitoring and modifying unhealthy eating behavior patterns, often with the help of sensors for behavior data recording. However, when it comes to semi-controlled deployment settings, smartphone apps that facilitate eating behavior data collection are missing. To fill this gap, the present work introduces ASApp, one of the first smartphone apps to support researchers in the collection of heterogeneous objective (sensor-acquired) and subjective (self-reported) eating behavior data in an integrated manner from large-scale, naturalistic human subject research (HSR) studies.

METHODS

This work presents the overarching and deployment-specific requirements that have driven the design of ASApp, followed by the heterogeneous eating behavior dataset that is collected and the employed data collection protocol. The collected dataset combines objective and subjective behavior information, namely (a) dietary self-assessment information, (b) the food weight timeseries throughout an entire meal (using a portable weight scale connected wirelessly), (c) a photograph of the meal, and (d) a series of quantitative eating behavior indicators, mainly calculated from the food weight timeseries. The designed data collection protocol is quick, straightforward, robust and capable of satisfying the requirement of semi-controlled HSR deployment.

RESULTS

The implemented functionalities of ASApp for research assistants and study participants are presented in detail along with the corresponding user interfaces. ASApp has been successfully deployed for data collection in an in-house testing study and the SPLENDID study, i.e., a real-life semi-controlled HSR study conducted in the cafeteria of a Swedish high-school in the context of an EC-funded research project. The two deployment studies are described and the promising results from the evaluation of the app with respect to attractiveness, usability, and technical soundness are discussed. Access details for ASApp are also provided.

CONCLUSIONS

This work presents the requirement elucidation, design, implementation and evaluation of a novel smartphone application that supports researchers in the integrated collection of a concise yet rich set of heterogeneous eating behavior data for semi-controlled HSR.

Lower Energy Intake among Advanced vs. Early Parkinson's Disease Patients and Healthy Controls in a Clinical Lunch Setting: A Cross-Sectional Study

Unintentional weight loss has been observed among Parkinson's disease (PD) patients. Changes in energy intake (EI) and eating behavior, potentially caused by fine motor dysfunction and eating-related symptoms, might contribute to this. The primary aim of this study was to investigate differences in objectively measured EI between groups of healthy controls (HC), early (ESPD) and advanced stage PD patients (ASPD) during a standardized lunch in a clinical setting. The secondary aim was to identify clinical features and eating behavior abnormalities that explain EI differences. All participants (n = 23 HC, n = 20 ESPD, and n = 21 ASPD) went through clinical evaluations and were eating a standardized meal (200 g sausages, 400 g potato salad, 200 g apple purée and 500 mL water) in front of two video cameras. Participants ate freely, and the food was weighed pre- and post-meal to calculate EI (kcal). Multiple linear regression was used to explain group differences in EI. ASPD had a significantly lower EI vs. HC (-162 kcal, p < 0.05) and vs. ESPD (-203 kcal, p < 0.01) when controlling for sex. The number of spoonfuls, eating problems, dysphagia and upper extremity tremor could explain most (86%) of the lower EI vs. HC, while the first three could explain ~50% vs. ESPD. Food component intake analysis revealed significantly lower potato salad and sausage intakes among ASPD vs. both HC and ESPD, while water intake was lower vs. HC. EI is an important clinical target for PD patients with an increased risk of weight loss. Our results suggest that interventions targeting upper extremity tremor, spoonfuls, dysphagia and eating problems might be clinically useful in the prevention of unintentional weight loss in PD. Since EI was lower in ASPD, EI might be a useful marker of disease progression in PD.

Validation of a Deep Learning System for the Full Automation of Bite and Meal Duration Analysis of Experimental Meal Videos

Eating behavior can have an important effect on, and be correlated with, obesity and eating disorders. Eating behavior is usually estimated through self-reporting measures, despite their limitations in reliability, based on ease of collection and analysis. A better and widely used alternative is the objective analysis of eating during meals based on human annotations of in-meal behavioral events (e.g., bites). However, this methodology is time-consuming and often affected by human error, limiting its scalability and cost-effectiveness for large-scale research. To remedy the latter, a novel "Rapid Automatic Bite Detection" (RABiD) algorithm that extracts and processes skeletal features from videos was trained in a video meal dataset (59 individuals; 85 meals; three different foods) to automatically measure meal duration and bites. In these settings, RABiD achieved near perfect agreement between algorithmic and human annotations (Cohen's kappa κ = 0.894; F1-score: 0.948). Moreover, RABiD was used to analyze an independent eating behavior experiment (18 female participants; 45 meals; three different foods) and results showed excellent correlation between algorithmic and human annotations. The analyses revealed that, despite the changes in food (hash vs. meatballs), the total meal duration remained the same, while the number of bites were significantly reduced. Finally, a descriptive meal-progress analysis revealed that different types of food affect bite frequency, although overall bite patterns remain similar (the outcomes were the same for RABiD and manual). Subjects took bites more frequently at the beginning and the end of meals but were slower in-between. On a methodological level, RABiD offers a valid, fully automatic alternative to human meal-video annotations for the experimental analysis of human eating behavior, at a fraction of the cost and the required time, without any loss of information and data fidelity.

Consumer Choices and Service Quality in the University Canteens in Warsaw, Poland

The purpose of this study was to identify and analyze consumer choices and service quality in university canteens in Warsaw. Our study consists of two parts. The first part of our research was conducted using a sample of 1250 adult respondents in 25 university canteens located at five higher education institutions. The reasons and frequency for using canteens, types of selected dishes and opinions on a given catering facility management system were analyzed. The second part of the study was conducted as an inspection to assess internal control and reliability of information. The respondents’ opinions are not in line with inspection assessments. This may be due to the fact that students do not pay attention to the quality of services in university canteens or have little knowledge about service, quality of services or hygiene aspects. For a detailed analysis of consumer choices and service quality assessment, we used Analysis of Variance (ANOVA) test and multi-dimensional cluster analysis. We identified four clusters regarding the type of meals and consumed frequency of consumption in university canteens, and five profiles in relation to evaluation of canteen interior, service and menu. In the correspondence analysis performed using the multidimensional Multiple Correspondence Analysis (MCA) method, we identified five clusters of consumers based on nine features, i.e., canteen location, frequency of using the canteen, gender of respondents, dwelling place, financial status of respondents. Our research on the functioning of university canteens is one of the first not only in Poland, but also in the countries of Central and Eastern Europe. The evaluation of the quality of nutrition in canteens should be continued in order to prevent diet-related diseases. Based on the results of our research, we postulate to introduce an evaluation guide for university canteens taking into account various aspects of services.

Skipping Breakfast and a Meal at School: Its Correlates in Adiposity Context. Report from the ABC of Healthy Eating Study of Polish Teenagers

Little is known on skipping breakfast and a meal at school, especially considered together. The study identified nutrition knowledge-related, lifestyle (including diet quality, physical activity, and screen time) and socioeconomic correlates of skipping breakfast and a meal at school, considered together or alone and assessed the association of skipping these meals with adiposity markers in Polish teenagers. The sample consisted of 1566 fourth and fifth grade elementary school students (11–13 years). The study was designed as a cross-sectional study. Data related to the consumption of selected food items and meals, physical activity, screen time, sociodemographic factors, and nutrition knowledge (all self-reported) were collected (in 2015–2016) with a short form of a food frequency questionnaire. Respondents reported the usual consumption of breakfast (number of days/week) and a meal or any food eaten at school (number of school days/week) labelled as ‘a meal at school’. The measurements of body weight, height, and waist circumference were taken. BMI-for-age ≥25 kg/m² was considered as a marker of overweight/obesity (general adiposity), while waist-to-height ratio ≥0.5 as a marker of central obesity (central adiposity). A multivariate logistic regression was applied to verify the association between variables. A total of 17.4% of teenagers frequently skipped breakfast (4–7 days/week), 12.9% frequently skipped a meal at school (3–5 school days/week), while 43.6% skipped both of these meals a few times a week. Predictors of skipping breakfast and/or a meal at school were female gender, age over 12 years, urban residence, lower family affluence, lower nutrition knowledge, higher screen time, and lower physical activity. In comparison to “never-skippers,” “frequent breakfast skippers” were more likely to be overweight/obese (odds ratio, OR 1.89; 95% confidence interval, 95%CI 1.38, 2.58) and centrally obese (OR 1.63; 95%CI 1.09, 2.44), while skippers a few times a week of both of these meals were more likely to be overweight/obese (OR 1.37; 95%CI 1.06, 1.78). Concluding, we estimated that a large percentage of Polish teenagers (approx. 44%) usually skipped both breakfast and a meal at school a few times a week. Similar predictors of skipping breakfast and predictors of skipping a meal at school were identified. Special attention should be paid to promoting shortening screen time and increasing physical activity and teenagers’ nutrition knowledge which are relatively easily modifiable correlates. The study shows that skipping both of these meals a few times a week was associated with general adiposity and also strengthens previous evidence showing the association of frequent skipping breakfast with general and central adiposity.