Dietary Intake and Physical Activity Assessment: Current Tools, Techniques, and Technologies for Use in Adult Populations

Abstract

Accurate assessment of dietary intake and physical activity is a vital component for quality research in public health, nutrition, and exercise science. However, accurate and consistent methodology for the assessment of these components remains a major challenge. Classic methods use self-report to capture dietary intake and physical activity in healthy adult populations. However, these tools, such as questionnaires or food and activity records and recalls, have been shown to underestimate energy intake and expenditure as compared with direct measures like doubly labeled water. This paper summarizes recent technological advancements, such as remote sensing devices, digital photography, and multisensor devices, which have the potential to improve the assessment of dietary intake and physical activity in free-living adults. This review will provide researchers with emerging evidence in support of these technologies, as well as a quick reference for selecting the "right-sized" assessment method based on study design, target population, outcome variables of interest, and economic and time considerations. Theme information: This article is part of a theme issue entitled Innovative Tools for Assessing Diet and Physical Activity for Health Promotion, which is sponsored by the North American branch of the International Life Sciences Institute.

Technology Innovations in Dietary Intake and Physical Activity Assessment: Challenges and Recommendations for Future Directions

“…Because of this wide range of perspectives, the forum was specifically structured to share cross-disciplinary efforts on DI and PA assessment tools for EE and health status. The forum resulted in expert review papers on technology innovations in three age cohorts that are published concurrently with this commentary: "Advances and Controversies in Diet and Physical Activity Measurement in Youth" 12 ; "Dietary Intake and Physical Activity Assessment: Current Tools, Techniques, and Technologies for Use in Adult Populations" 13 ; and "Diet and Physical Activity Assessment and Interventions Using Technology in Special Populations: Older Adults." 14…”

Future directions for integrative objective assessment of eating using wearable sensing technology

“…However, food photography currently has considerable researcher and participant burden because of the requirements for training, real-time monitoring, and provision of supplementary information. Crucially, participants still have to actively take photographs of everything they eat, and this may be affected by issues with memory and social desirability 30 .…”

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

“…Emerging technologies present the opportunity to improve these assessment methods by using methods that improve the quality and validity of data that is collected, and by passively measuring eating activity in naturalistic settings over long periods of time with minimal user interaction. Technological advances in dietary assessment tools include: (i) web-based self-administered 24-h recall tool, which aims to reduce respondent burden 23 ; (ii) mobile device-assisted ecological momentary assessment (mEMA), which focuses on reducing recall bias by collecting real-time data in naturalistic settings 24 ; (iii) photo-assisted and image-based dietary assessments, which attempt to reduce respondent burden and recall bias 25 ; and (iv) wearable sensors, which offer a suite of measurement tools that seek to tackle all of these limitations 26,27 . Wearable devices with embedded sensors in particular allow for the passive collection of various data streams that can be used to develop algorithms to infer eating behaviors in naturalistic settings and, with some types of sensors, over long periods of time.…”

“…Wearable devices with embedded sensors in particular allow for the passive collection of various data streams that can be used to develop algorithms to infer eating behaviors in naturalistic settings and, with some types of sensors, over long periods of time. Collecting near-continuous data in the context of daily life, where behavior actually occurs, has proven to be extremely difficult for researchers and burdensome for participants 26,27 . However, wearable sensors can lessen the burden by passively collecting data while users go about their daily lives with minimal user input, compared with existing methods.…”