Literature DB >> 19444225

Toward objective monitoring of ingestive behavior in free-living population.

Edward S Sazonov1, Stephanie A C Schuckers, Paulo Lopez-Meyer, Oleksandr Makeyev, Edward L Melanson, Michael R Neuman, James O Hill.   

Abstract

Understanding of eating behaviors associated with obesity requires objective and accurate monitoring of food intake patterns. Accurate methods are available for measuring total energy expenditure and its components in free-living populations, but methods for measuring food intake in free-living people are far less accurate and involve self-reporting or subjective monitoring. We suggest that chews and swallows can be used for objective monitoring of ingestive behavior. This hypothesis was verified in a human study involving 20 subjects. Chews and swallows were captured during periods of quiet resting, talking, and meals of varying size. The counts of chews and swallows along with other derived metrics were used to build prediction models for detection of food intake, differentiation between liquids and solids, and for estimation of the mass of ingested food. The proposed prediction models were able to detect periods of food intake with >95% accuracy and a fine time resolution of 30 s, differentiate solid foods from liquids with >91% accuracy, and predict mass of ingested food with >91% accuracy for solids and >83% accuracy for liquids. In earlier publications, we have shown that chews and swallows can be captured by noninvasive sensors that could be developed into a wearable device. Thus, the proposed methodology could lead to the development of an innovative new way of assessing human eating behavior in free-living conditions.

Entities:  

Mesh:

Year:  2009        PMID: 19444225      PMCID: PMC2865137          DOI: 10.1038/oby.2009.153

Source DB:  PubMed          Journal:  Obesity (Silver Spring)        ISSN: 1930-7381            Impact factor:   5.002


  20 in total

Review 1.  Markers of the validity of reported energy intake.

Authors:  M Barbara E Livingstone; Alison E Black
Journal:  J Nutr       Date:  2003-03       Impact factor: 4.798

2.  Predicting energy expenditure of physical activity using hip- and wrist-worn accelerometers.

Authors:  Kong Y Chen; Sari A Acra; Karen Majchrzak; Candice L Donahue; Lemont Baker; Linda Clemens; Ming Sun; Maciej S Buchowski
Journal:  Diabetes Technol Ther       Date:  2003       Impact factor: 6.118

Review 3.  How do we get fat? An epidemiologic and metabolic approach.

Authors:  George A Bray
Journal:  Clin Dermatol       Date:  2004 Jul-Aug       Impact factor: 3.541

4.  Obesity and 33-year follow-up for coronary heart disease and cancer mortality.

Authors:  D Carmelli; H Zhang; G E Swan
Journal:  Epidemiology       Date:  1997-07       Impact factor: 4.822

5.  Energy expenditure of nonexercise activity.

Authors:  J A Levine; S J Schleusner; M D Jensen
Journal:  Am J Clin Nutr       Date:  2000-12       Impact factor: 7.045

Review 6.  Environmental contributions to the obesity epidemic.

Authors:  J O Hill; J C Peters
Journal:  Science       Date:  1998-05-29       Impact factor: 47.728

Review 7.  Estimating human energy expenditure: a review of techniques with particular reference to doubly labelled water.

Authors:  Philip Ainslie; Thomas Reilly; Klass Westerterp
Journal:  Sports Med       Date:  2003       Impact factor: 11.136

8.  Chews and swallows and the microstructure of eating.

Authors:  E Stellar; E E Shrager
Journal:  Am J Clin Nutr       Date:  1985-11       Impact factor: 7.045

9.  Genome-wide association scans identified CTNNBL1 as a novel gene for obesity.

Authors:  Yong-Jun Liu; Xiao-Gang Liu; Liang Wang; Christian Dina; Han Yan; Jian-Feng Liu; Shawn Levy; Christopher J Papasian; Betty M Drees; James J Hamilton; David Meyre; Jerome Delplanque; Yu-Fang Pei; Lei Zhang; Robert R Recker; Philippe Froguel; Hong-Wen Deng
Journal:  Hum Mol Genet       Date:  2008-03-05       Impact factor: 6.150

10.  Increased portion size leads to increased energy intake in a restaurant meal.

Authors:  Nicole Diliberti; Peter L Bordi; Martha T Conklin; Liane S Roe; Barbara J Rolls
Journal:  Obes Res       Date:  2004-03
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  24 in total

1.  A Sensor System for Automatic Detection of Food Intake Through Non-Invasive Monitoring of Chewing.

Authors:  Edward S Sazonov; Juan M Fontana
Journal:  IEEE Sens J       Date:  2012       Impact factor: 3.301

2.  Automatic ingestion monitor: a novel wearable device for monitoring of ingestive behavior.

Authors:  Juan M Fontana; Muhammad Farooq; Edward Sazonov
Journal:  IEEE Trans Biomed Eng       Date:  2014-06       Impact factor: 4.538

3.  A novel approach for food intake detection using electroglottography.

Authors:  Muhammad Farooq; Juan M Fontana; Edward Sazonov
Journal:  Physiol Meas       Date:  2014-03-26       Impact factor: 2.833

4.  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

5.  Detection of food intake from swallowing sequences by supervised and unsupervised methods.

Authors:  Paulo Lopez-Meyer; Oleksandr Makeyev; Stephanie Schuckers; Edward L Melanson; Michael R Neuman; Edward Sazonov
Journal:  Ann Biomed Eng       Date:  2010-03-30       Impact factor: 3.934

6.  Energy intake estimation from counts of chews and swallows.

Authors:  Juan M Fontana; Janine A Higgins; Stephanie C Schuckers; France Bellisle; Zhaoxing Pan; Edward L Melanson; Michael R Neuman; Edward Sazonov
Journal:  Appetite       Date:  2014-11-07       Impact factor: 3.868

7.  Short and long-term energy intake patterns and their implications for human body weight regulation.

Authors:  Carson C Chow; Kevin D Hall
Journal:  Physiol Behav       Date:  2014-02-28

8.  Evaluation of Chewing and Swallowing Sensors for Monitoring Ingestive Behavior.

Authors:  Juan M Fontana; Edward S Sazonov
Journal:  Sens Lett       Date:  2013-03

9.  Automatic detection of swallowing events by acoustical means for applications of monitoring of ingestive behavior.

Authors:  Edward S Sazonov; Oleksandr Makeyev; Stephanie Schuckers; Paulo Lopez-Meyer; Edward L Melanson; Michael R Neuman
Journal:  IEEE Trans Biomed Eng       Date:  2009-09-29       Impact factor: 4.538

10.  Individual differences in the forced swimming test and neurochemical kinetics in the rat brain.

Authors:  Andrey Sequeira-Cordero; Andrea Mora-Gallegos; Patricia Cuenca-Berger; Jaime Fornaguera-Trías
Journal:  Physiol Behav       Date:  2014-02-08
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