Ultra-Processed Food vs. Fruit and Vegetable Consumption before and during the COVID-19 Pandemic among Greek and Swedish Students.

Background: The COVID-19 pandemic has impacted children's lifestyles, including dietary behaviors. Of particular concern among these behaviors is the heightened prevalence of ultra-processed food (UPF) consumption, which has been linked to the development of obesity and related non-communicable diseases. The present study examines the changes in (1) UPF and (2) vegetable and/or fruit consumption among school-aged children in Greece and Sweden before and during the COVID-19 pandemic.

Toward Systems Models for Obesity Prevention: A Big Role for Big Data.

The relation among the various causal factors of obesity is not well understood, and there remains a lack of viable data to advance integrated, systems models of its etiology. The collection of big data has begun to allow the exploration of causal associations between behavior, built environment, and obesity-relevant health outcomes. Here, the traditional epidemiologic and emerging big data approaches used in obesity research are compared, describing the research questions, needs, and outcomes of 3 broad research domains: eating behavior, social food environments, and the built environment.

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.

Assessment of real life eating difficulties in Parkinson's disease patients by measuring plate to mouth movement elongation with inertial sensors.

Parkinson's disease (PD) is a neurodegenerative disorder with both motor and non-motor symptoms. Despite the progressive nature of PD, early diagnosis, tracking the disease's natural history and measuring the drug response are factors that play a major role in determining the quality of life of the affected individual. Apart from the common motor symptoms, i.

BigO: A public health decision support system for measuring obesogenic behaviors of children in relation to their local environment.

Obesity is a complex disease and its prevalence depends on multiple factors related to the local socioeconomic, cultural and urban context of individuals. Many obesity prevention strategies and policies, however, are horizontal measures that do not depend on context-specific evidence. In this paper we present an overview of BigO (http://bigoprogram.

Collecting big behavioral data for measuring behavior against obesity.

Obesity is currently affecting very large portions of the global population. Effective prevention and treatment starts at the early age and requires objective knowledge of population-level behavior on the region/neighborhood scale. To this end, we present a system for extracting and collecting behavioral information on the individual-level objectively and automatically.

Using IMU Sensors to Assess Motor Degradation of PD Patients by Modeling In-meal Plate-to-Mouth Movement Elongation.

Parkinson's disease (PD) is the second most common age-related neurodegenerative disorder after Alzheimer's disease, associated, among others, with motor symptoms such as resting tremor, rigidity and bradykinesia. At the same time, early diagnosis of PD is hindered by a high misdiagnosis rate and the subjective nature of the diagnosis process itself. Recent developments in mobile and wearable devices, such as smartphones and smartwatches, have allowed the automated detection and objective measurement of PD symptoms.

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.

Formative Evaluation of a Smartphone App for Monitoring Daily Meal Distribution and Food Selection in Adolescents: Acceptability and Usability Study.

Background: Obesity interventions face the problem of weight regain after treatment as a result of low compliance. Mobile health (mHealth) technologies could potentially increase compliance and aid both health care providers and patients.

Objective: This study aimed to evaluate the acceptability and usability and define system constraints of an mHealth system used to monitor dietary habits of adolescents in real life, as a first step in the development of a self-monitoring and lifestyle management system against adolescent obesity.

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.

Novel e-Health Applications for the Management of Cardiometabolic Risk Factors in Children and Adolescents in Greece.

Obesity in childhood and adolescence represents a major health problem. Novel e-Health technologies have been developed in order to provide a comprehensive and personalized plan of action for the prevention and management of overweight and obesity in childhood and adolescence. We used information and communication technologies to develop a "National Registry for the Prevention and Management of Overweight and Obesity" in order to register online children and adolescents nationwide, and to guide pediatricians and general practitioners regarding the management of overweight or obese subjects.

Assessment of In-Meal Eating Behaviour using Fuzzy SVM.

Certain patterns of eating behaviour during meal have been identified as risk factors for long-term abnormal eating development in healthy individuals and, eventually, can affect the body weight. To detect early signs of problematic eating behaviour, this paper proposes a novel method for building behaviour assessment models. The goal of the models is to predict whether the in-meal eating behaviour resembles patterns associated with obesity, eating disorders, or low-risk behaviours.

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.

Automatic Analysis of Food Intake and Meal Microstructure Based on Continuous Weight Measurements.

The structure of the cumulative food intake (CFI) curve has been associated with obesity and eating disorders. Scales that record the weight loss of a plate from which a subject eats food are used for capturing this curve; however, their measurements are contaminated by additive noise and are distorted by certain types of artifacts. This paper presents an algorithm for automatically processing continuous in-meal weight measurements in order to extract the clean CFI curve and in-meal eating indicators, such as total food intake and food intake rate.

The Effect of Food Unit Sizes and Meal Serving Occasions on Eating Behaviour Characteristics: Within Person Randomised Crossover Studies on Healthy Women.

Manipulating food properties and serving environment during a meal can significantly change food intake at group level. However, the evaluation of the usefulness of such manipulations requires an understanding of individual behavioural changes. Three studies were conducted to explore the effect of unit size and meal occasion on eating behaviour characteristics (food intake, meal duration, number of bites and chews).

Objective quantification of the food proximity effect on grapes, chocolate and cracker consumption in a Swedish high school. A temporal analysis.

Close food proximity leads to increased short-term energy intake, potentially contributing to the long-term development of obesity. However, its precise effects on eating behaviour are still unclear, especially with food available for extended periods of time. This study involved two similar high school student groups (15-17 years old), which had ad libitum access to grapes, chocolates and crackers during an hour-long experimental session.

A parametric Probabilistic Context-Free Grammar for food intake analysis based on continuous meal weight measurements.

Monitoring and modification of eating behaviour through continuous meal weight measurements has been successfully applied in clinical practice to treat obesity and eating disorders. For this purpose, the Mandometer, a plate scale, along with video recordings of subjects during the course of single meals, has been used to assist clinicians in measuring relevant food intake parameters. In this work, we present a novel algorithm for automatically constructing a subject's food intake curve using only the Mandometer weight measurements.

Control of Body Weight by Eating Behavior in Children.

Diet, exercise, and pharmacological interventions have limited effects in counteracting the worldwide increase in pediatric body weight. Moreover, the promise that individualized drug design will work to induce weight loss appears to be exaggerated. We suggest that the reason for this limited success is that the cause of obesity has been misunderstood.

Homeostasis in anorexia nervosa.

Brainstem and hypothalamic "orexigenic/anorexigenic" networks are thought to maintain body weight homeostasis in response to hormonal and metabolic feedback from peripheral sites. This approach has not been successful in managing over- and underweight patients. It is suggested that concept of homeostasis has been misinterpreted; rather than exerting control, the brain permits eating in proportion to the amount of physical activity necessary to obtain food.

Children eat their school lunch too quickly: an exploratory study of the effect on food intake.

Background: Speed of eating, an important aspect of eating behaviour, has recently been related to loss of control of food intake and obesity. Very little time is allocated for lunch at school and thus children may consume food more quickly and food intake may therefore be affected. Study 1 measured the time spent eating lunch in a large group of students eating together for school meals.

Description of chewing and food intake over the course of a meal.

While the average frequency of chewing and food intake have been reported before, a detailed description of the pattern of chewing and the cumulative intake of food over the course of a meal have not. In order to achieve this goal, video recording of the maxillary-mandibular region of women eating food from a plate was synchronized with video recording of the plate and computer recording of the weight-loss of the plate. Video recording of chewing correlated strongly with chewing identified by magnetic tracking of jaw displacement in a test with chewing gum at three different frequencies, thus ensuring the validity of video recording of chewing.