Literature DB >> 25430667

Wearable cameras can reduce dietary under-reporting: doubly labelled water validation of a camera-assisted 24 h recall.

Luke Gemming1, Elaine Rush2, Ralph Maddison1, Aiden Doherty3, Nicholas Gant4, Jennifer Utter5, Cliona Ni Mhurchu1.   

Abstract

Preliminary research has suggested that wearable cameras may reduce under-reporting of energy intake (EI) in self-reported dietary assessment. The aim of the present study was to test the validity of a wearable camera-assisted 24 h dietary recall against the doubly labelled water (DLW) technique. Total energy expenditure (TEE) was assessed over 15 d using the DLW protocol among forty adults (n 20 males, age 35 (sd 17) years, BMI 27 (sd 4) kg/m2 and n 20 females, age 28 (sd 7) years, BMI 22 (sd 2) kg/m2). EI was assessed using three multiple-pass 24 h dietary recalls (MP24) on days 2-4, 8-10 and 13-15. On the days before each nutrition assessment, participants wore an automated wearable camera (SenseCam (SC)) in free-living conditions. The wearable camera images were viewed by the participants following the completion of the dietary recall, and their changes in self-reported intakes were recorded (MP24+SC). TEE and EI assessed by the MP24 and MP24+SC methods were compared. Among men, the MP24 and MP24+SC measures underestimated TEE by 17 and 9%, respectively (P< 0.001 and P= 0.02). Among women, these measures underestimated TEE by 13 and 7%, respectively (P< 0.001 and P= 0.004). The assistance of the wearable camera (MP24+SC) reduced the magnitude of under-reporting by 8% for men and 6% for women compared with the MP24 alone (P< 0.001 and P< 0.001). The increase in EI was predominantly from the addition of 265 unreported foods (often snacks) as revealed by the participants during the image review. Wearable cameras enhance the accuracy of self-report by providing passive and objective information regarding dietary intake. High-definition image sensors and increased imaging frequency may improve the accuracy further.

Entities:  

Keywords:  Dietary studies; Nutrition assessment; SenseCam; Wearable cameras

Mesh:

Year:  2014        PMID: 25430667     DOI: 10.1017/S0007114514003602

Source DB:  PubMed          Journal:  Br J Nutr        ISSN: 0007-1145            Impact factor:   3.718


  39 in total

1.  Dietary under-reporting: what foods and which meals are typically under-reported?

Authors:  L Gemming; C Ni Mhurchu
Journal:  Eur J Clin Nutr       Date:  2015-12-16       Impact factor: 4.016

2.  Advances and Controversies in Diet and Physical Activity Measurement in Youth.

Authors:  Donna Spruijt-Metz; Cheng K Fred Wen; Brooke M Bell; Stephen Intille; Jeannie S Huang; Tom Baranowski
Journal:  Am J Prev Med       Date:  2018-08-19       Impact factor: 5.043

Review 3.  Review of the validity and feasibility of image-assisted methods for dietary assessment.

Authors:  Christoph Höchsmann; Corby K Martin
Journal:  Int J Obes (Lond)       Date:  2020-10-08       Impact factor: 5.095

4.  Automatic food detection in egocentric images using artificial intelligence technology.

Authors:  Wenyan Jia; Yuecheng Li; Ruowei Qu; Thomas Baranowski; Lora E Burke; Hong Zhang; Yicheng Bai; Juliet M Mancino; Guizhi Xu; Zhi-Hong Mao; Mingui Sun
Journal:  Public Health Nutr       Date:  2018-03-26       Impact factor: 4.022

Review 5.  Research Strategies for Nutritional and Physical Activity Epidemiology and Cancer Prevention.

Authors:  Somdat Mahabir; Walter C Willett; Christine M Friedenreich; Gabriel Y Lai; Carol J Boushey; Charles E Matthews; Rashmi Sinha; Graham A Colditz; Joseph A Rothwell; Jill Reedy; Alpa V Patel; Michael F Leitzmann; Gary E Fraser; Sharon Ross; Stephen D Hursting; Christian C Abnet; Lawrence H Kushi; Philip R Taylor; Ross L Prentice
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2017-12-18       Impact factor: 4.254

Review 6.  A systematic review of the validity of dietary assessment methods in children when compared with the method of doubly labelled water.

Authors:  T Burrows; S Goldman; M Rollo
Journal:  Eur J Clin Nutr       Date:  2019-08-07       Impact factor: 4.016

7.  Validation of Wearable Camera Still Images to Assess Posture in Free-Living Conditions.

Authors:  Julian Martinez; Autumn Decker; Chi C Cho; Aiden Doherty; Ann M Swartz; John W Staudenmayer; Scott J Strath
Journal:  J Meas Phys Behav       Date:  2021-02-24

8.  Investigating sex differences in the accuracy of dietary assessment methods to measure energy intake in adults: a systematic review and meta-analysis.

Authors:  Briar L McKenzie; Daisy H Coyle; Joseph Alvin Santos; Tracy Burrows; Emalie Rosewarne; Sanne A E Peters; Cheryl Carcel; Lindsay M Jaacks; Robyn Norton; Clare E Collins; Mark Woodward; Jacqui Webster
Journal:  Am J Clin Nutr       Date:  2021-05-08       Impact factor: 7.045

9.  "Automatic Ingestion Monitor Version 2" - A Novel Wearable Device for Automatic Food Intake Detection and Passive Capture of Food Images.

Authors:  Abul Doulah; Tonmoy Ghosh; Delwar Hossain; Masudul H Imtiaz; Edward Sazonov
Journal:  IEEE J Biomed Health Inform       Date:  2021-02-05       Impact factor: 5.772

10.  Evaluation of PIQNIQ, a Novel Mobile Application for Capturing Dietary Intake.

Authors:  Caroline M Blanchard; Meghan K Chin; Cheryl H Gilhooly; Kathryn Barger; Gregory Matuszek; Akari J Miki; Richard G Côté; Alison L Eldridge; Hilary Green; Fabio Mainardi; Damian Mehers; Frédéric Ronga; Vera Steullet; Sai Krupa Das
Journal:  J Nutr       Date:  2021-05-11       Impact factor: 4.798

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