New Preventive Healthcare Strategies: The Contribution of Digital Technologies and Models for Weight Gain Prediction

Dear Colleagues,

New information and communication technologies that use accurate and reliable sensors allows not only for the accurate evaluation of behaviors but also large data collection, which is necessary to generate mathematical models for health-related parameter predictions or simulations.

The early detection of being overweight is crucial to prevent weight gain and delay the following onset of chronic non-communicable diseases. Behavioral risk factors associated with obesity are well known: sedentary behavior, lack of physical activity, unbalanced diet, too many calories, consumption of ultra-processed food products, lack of sleep, too much stress, etc.

A holistic approach of behaviors evaluated accurately in free-living conditions is necessary to understand their respective contribution to overall health damage and to come up with new preventive strategies.

This Special Issue aims to disseminate cutting-edge research focused on this trend in research including, but not limited to:

(1) Scientifically validated mobile applications for the estimation of physical activity, sedentary behavior, and energy expenditure;

(2) Scientifically validated mobile applications for the estimation of diet quality and energy intake;

(3) Indirect or alternative approaches to food consumption recording (biomarkers, total energy intake, supermarket/grocery receipts, etc.);

(4) Scientifically validated mobile applications for the estimation of sleep and stress;

(5) Holistic approach to weight gain;

(6) Models of prediction for weight gain from behavioral and individual data;

(7) Models of simulation of weight gain;

(8) Innovative medical devices—wearable devices for the evaluation of behaviors, body weight, and fat mass.

This Special Issue seeks original research, reviews, short reports, and opinion papers. Interdisciplinary contributions are welcome.

Dr. Sylvie M. E. Rousset
Guest Editor

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• weight gain
• physical activity, sedentary behavior and energy expenditure
• evaluation of holistic diet quality, sleep quality, stress level
• evaluation of weight gain and fat mass
• prediction and simulation model
• wearable medical devices
• mobile applications