Journal Article

Applying Ecological Momentary Assessment (EMA) to Understand Overweight and Obesity: A Systematic Review

Tossani, Eliana, Grandi, Silvana, Pietrabissa, Giada, Spatola, Chiara A. M., Martino, Gabriella, Castelnuovo, Gianluca, Cattivelli, Roberto, Rapelli, Giada, Landi, Giulia

2025

Overview

Background: Obesity is a complex health issue influenced by various factors, including behavioral patterns that can be assessed more deeply in real time using Ecological Momentary Assessment (EMA), which can capture the moment in which a person experiences a situation or an emotion that could trigger an eating behavior. Methods: This systematic review synthesizes findings from 89 studies employing EMA to investigate obesity and overweight-related behaviors. The studies were identified through comprehensive searches across multiple databases and included peer-reviewed articles. The primary aim was to analyze how EMA contributes to understanding the temporal dynamics of eating behaviors, physical activity, and psychological factors associated with overweight and obesity. Results: Key findings indicate that EMA provides a nuanced understanding of real-time contexts influencing behaviors contributing to overweight and obesity. Studies consistently report that EMA captures fluctuations in eating habits, exercise routines, stress levels, and emotional states, elucidating the interplay between these factors and weight status. Methodological variations across studies included differences in EMA implementation (e.g., smartphone apps, electronic diaries), assessment frequency, and duration. These variances highlight the flexibility and adaptability of EMA in capturing diverse behavioral aspects relevant to obesity and overweight research. Moreover, the review discusses methodological challenges such as participant compliance, data integration, and real-time data interpretation in longitudinal analyses. Conclusions: In conclusion, EMA emerges as a powerful tool for exploring the complex, dynamic nature of overweight and obesity-related behaviors. Future research should focus on refining EMA methodologies, enhancing data analysis techniques, and integrating findings into personalized interventions aimed at reducing obesity effectively.

• Publisher: MDPI AG,Multidisciplinary Digital Publishing Institute (MDPI)
• Subject: Analysis / Binge eating / Body mass index / Body weight / Bulimia / Clinical medicine / Clinical psychology / Eating behavior / Eating disorders / Emotional regulation / Ethnicity / Food habits / Health aspects / Information management / Obesity / Overweight / Physical activity / Physiology / Psychotherapy / Research methodology / Smith, A / Stress (Psychology) / Systematic Review / Type 2 diabetes / Weight control