Between- and Within-Subjects Predictors of the Kilocalorie Content of Bites of Food
This study builds on previous research that seeks to estimate kilocalorie intake through microstructural analysis of eating behaviors. As opposed to previous methods, which used a static, individual-based measure of kilocalories per bite, the new method incorporates time- and food-varying predictors...
Saved in:
Published in | Journal of the Academy of Nutrition and Dietetics Vol. 119; no. 7; pp. 1109 - 1117 |
---|---|
Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
01.07.2019
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | This study builds on previous research that seeks to estimate kilocalorie intake through microstructural analysis of eating behaviors. As opposed to previous methods, which used a static, individual-based measure of kilocalories per bite, the new method incorporates time- and food-varying predictors. A measure of kilocalories per bite (KPB) was estimated using between- and within-subjects variables.
The purpose of this study was to examine the relationship between within-subjects and between-subjects predictors and KPB, and to develop a model of KPB that improves over previous models of KPB. Within-subjects predictors included time since last bite, food item enjoyment, premeal satiety, and time in meal. Between-subjects predictors included body mass index, mouth volume, and sex.
Seventy-two participants (39 female) consumed two random meals out of five possible meal options with known weights and energy densities. There were 4,051 usable bites measured.
The outcome measure of the first analysis was KPB. The outcome measure of the second analysis was meal-level kilocalorie intake, with true intake compared to three estimation methods.
Multilevel modeling was used to analyze the influence of the seven predictors of KPB. The accuracy of the model was compared to previous methods of estimating KPB using a repeated-measured analysis of variance.
All hypothesized relationships were significant, with slopes in the expected direction, except for body mass index and time in meal. In addition, the new model (with nonsignificant predictors removed) improved over earlier models of KPB.
This model offers a new direction for methods of inexpensive, accurate, and objective estimates of kilocalorie intake from bite-based measures. |
---|---|
AbstractList | This study builds on previous research that seeks to estimate kilocalorie intake through microstructural analysis of eating behaviors. As opposed to previous methods, which used a static, individual-based measure of kilocalories per bite, the new method incorporates time- and food-varying predictors. A measure of kilocalories per bite (KPB) was estimated using between- and within-subjects variables. The purpose of this study was to examine the relationship between within-subjects and between-subjects predictors and KPB, and to develop a model of KPB that improves over previous models of KPB. Within-subjects predictors included time since last bite, food item enjoyment, premeal satiety, and time in meal. Between-subjects predictors included body mass index, mouth volume, and sex. Seventy-two participants (39 female) consumed two random meals out of five possible meal options with known weights and energy densities. There were 4,051 usable bites measured. The outcome measure of the first analysis was KPB. The outcome measure of the second analysis was meal-level kilocalorie intake, with true intake compared to three estimation methods. Multilevel modeling was used to analyze the influence of the seven predictors of KPB. The accuracy of the model was compared to previous methods of estimating KPB using a repeated-measured analysis of variance. All hypothesized relationships were significant, with slopes in the expected direction, except for body mass index and time in meal. In addition, the new model (with nonsignificant predictors removed) improved over earlier models of KPB. This model offers a new direction for methods of inexpensive, accurate, and objective estimates of kilocalorie intake from bite-based measures. This study builds on previous research that seeks to estimate kilocalorie intake through microstructural analysis of eating behaviors. As opposed to previous methods, which used a static, individual-based measure of kilocalories per bite, the new method incorporates time- and food-varying predictors. A measure of kilocalories per bite (KPB) was estimated using between- and within-subjects variables. The purpose of this study was to examine the relationship between within-subjects and between-subjects predictors and KPB, and to develop a model of KPB that improves over previous models of KPB. Within-subjects predictors included time since last bite, food item enjoyment, premeal satiety, and time in meal. Between-subjects predictors included body mass index, mouth volume, and sex. Seventy-two participants (39 female) consumed two random meals out of five possible meal options with known weights and energy densities. There were 4,051 usable bites measured. The outcome measure of the first analysis was KPB. The outcome measure of the second analysis was meal-level kilocalorie intake, with true intake compared to three estimation methods. Multilevel modeling was used to analyze the influence of the seven predictors of KPB. The accuracy of the model was compared to previous methods of estimating KPB using a repeated-measured analysis of variance. All hypothesized relationships were significant, with slopes in the expected direction, except for body mass index and time in meal. In addition, the new model (with nonsignificant predictors removed) improved over earlier models of KPB. This model offers a new direction for methods of inexpensive, accurate, and objective estimates of kilocalorie intake from bite-based measures. This study builds on previous research that seeks to estimate kilocalorie intake through microstructural analysis of eating behaviors. As opposed to previous methods, which used a static, individual-based measure of kilocalories per bite, the new method incorporates time- and food-varying predictors. A measure of kilocalories per bite (KPB) was estimated using between- and within-subjects variables.BACKGROUNDThis study builds on previous research that seeks to estimate kilocalorie intake through microstructural analysis of eating behaviors. As opposed to previous methods, which used a static, individual-based measure of kilocalories per bite, the new method incorporates time- and food-varying predictors. A measure of kilocalories per bite (KPB) was estimated using between- and within-subjects variables.The purpose of this study was to examine the relationship between within-subjects and between-subjects predictors and KPB, and to develop a model of KPB that improves over previous models of KPB. Within-subjects predictors included time since last bite, food item enjoyment, premeal satiety, and time in meal. Between-subjects predictors included body mass index, mouth volume, and sex.OBJECTIVEThe purpose of this study was to examine the relationship between within-subjects and between-subjects predictors and KPB, and to develop a model of KPB that improves over previous models of KPB. Within-subjects predictors included time since last bite, food item enjoyment, premeal satiety, and time in meal. Between-subjects predictors included body mass index, mouth volume, and sex.Seventy-two participants (39 female) consumed two random meals out of five possible meal options with known weights and energy densities. There were 4,051 usable bites measured.PARTICIPANTS/SETTINGSeventy-two participants (39 female) consumed two random meals out of five possible meal options with known weights and energy densities. There were 4,051 usable bites measured.The outcome measure of the first analysis was KPB. The outcome measure of the second analysis was meal-level kilocalorie intake, with true intake compared to three estimation methods.MAIN OUTCOME MEASURESThe outcome measure of the first analysis was KPB. The outcome measure of the second analysis was meal-level kilocalorie intake, with true intake compared to three estimation methods.Multilevel modeling was used to analyze the influence of the seven predictors of KPB. The accuracy of the model was compared to previous methods of estimating KPB using a repeated-measured analysis of variance.STATISTICAL ANALYSES PERFORMEDMultilevel modeling was used to analyze the influence of the seven predictors of KPB. The accuracy of the model was compared to previous methods of estimating KPB using a repeated-measured analysis of variance.All hypothesized relationships were significant, with slopes in the expected direction, except for body mass index and time in meal. In addition, the new model (with nonsignificant predictors removed) improved over earlier models of KPB.RESULTSAll hypothesized relationships were significant, with slopes in the expected direction, except for body mass index and time in meal. In addition, the new model (with nonsignificant predictors removed) improved over earlier models of KPB.This model offers a new direction for methods of inexpensive, accurate, and objective estimates of kilocalorie intake from bite-based measures.CONCLUSIONSThis model offers a new direction for methods of inexpensive, accurate, and objective estimates of kilocalorie intake from bite-based measures. |
Author | Muth, Eric R. Hoover, Adam W. Salley, James N. |
Author_xml | – sequence: 1 givenname: James N. surname: Salley fullname: Salley, James N. – sequence: 2 givenname: Adam W. surname: Hoover fullname: Hoover, Adam W. – sequence: 3 givenname: Eric R. surname: Muth fullname: Muth, Eric R. email: muth@clemson.edu |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30777655$$D View this record in MEDLINE/PubMed |
BookMark | eNqFkk1vFSEYhYlpYz_sH3BhZulmRj46wBhjYm-sNW2iSTUuCQPveBnnQgVuTf99md56o120bCB5zzk58HCAdnzwgNBLghuCCX8zNqP2tqGYyIbQBuPuGdqnlNCacol3tmdB99BRSiMui2PGJH6O9hgWQvC23UeXJ5D_APi6KmnVD5eXzteX634Ek1P1NYJ1JoeYqjBUeQnVuZuC0VOIDqpF8Bl8nkcnLsOd5jQE-wLtDnpKcHS_H6Lvpx-_Lc7qiy-fPi8-XNSmZV2uDWacGeCGC831IPqeSEyE7KltCWMMWugYJ8edBZBWGqt7QgDjwfDBDkSyQ_R-k3u17ldgTekS9aSuolvpeKOCdur_iXdL9TNcK952VLS8BLy-D4jh9xpSViuXDEyT9hDWSVFKsSyvycTT0tKHt5Qc4yJ99W-tbZ-_j14EdCMwMaQUYdhKCFYzXDWqGa6a4SpCVYFbTPKBybisswvz1dz0uPXdxgoFxrWDqJJx4E1hGwtmZYN73P72gd1MzrvyC37BzVPmWzY50u0 |
CitedBy_id | crossref_primary_10_1016_j_appet_2023_107176 crossref_primary_10_1177_2055207620988212 |
Cites_doi | 10.1001/jama.2016.6458 10.1016/S0149-7634(99)00079-2 10.1016/S0195-6663(84)80026-4 10.1016/j.appet.2006.11.010 10.1016/j.physbeh.2017.09.002 10.1016/j.appet.2004.05.007 10.1109/TBME.2014.2306773 10.1038/ijo.2014.199 10.1016/j.appet.2014.11.003 10.1109/JBHI.2016.2632621 10.1111/j.1745-459X.2001.tb00293.x 10.1016/S0149-7634(99)00077-9 10.1016/j.jand.2013.09.017 10.1016/j.jand.2016.03.007 10.1038/ijo.2015.96 10.1016/j.physbeh.2008.08.016 10.1016/j.compbiomed.2015.07.013 10.1007/s00455-002-0105-0 10.3945/ajcn.2009.27694 10.1016/0195-6663(93)90005-5 10.3945/ajcn.113.062125 10.1016/j.jada.2011.05.005 |
ContentType | Journal Article |
Copyright | 2019 Academy of Nutrition and Dietetics Copyright © 2019 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved. |
Copyright_xml | – notice: 2019 Academy of Nutrition and Dietetics – notice: Copyright © 2019 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved. |
DBID | AAYXX CITATION NPM 7X8 7S9 L.6 5PM |
DOI | 10.1016/j.jand.2018.12.009 |
DatabaseName | CrossRef PubMed MEDLINE - Academic AGRICOLA AGRICOLA - Academic PubMed Central (Full Participant titles) |
DatabaseTitle | CrossRef PubMed MEDLINE - Academic AGRICOLA AGRICOLA - Academic |
DatabaseTitleList | AGRICOLA PubMed MEDLINE - Academic |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Diet & Clinical Nutrition |
EISSN | 2212-2680 |
EndPage | 1117 |
ExternalDocumentID | PMC6592756 30777655 10_1016_j_jand_2018_12_009 S2212267218306841 |
Genre | Journal Article Research Support, N.I.H., Extramural |
GrantInformation_xml | – fundername: NHLBI NIH HHS grantid: R01 HL118181 – fundername: NIDDK NIH HHS grantid: R41 DK091141 – fundername: NIDDK NIH HHS grantid: R42 DK091141 |
GroupedDBID | --- --K --M -RU ..I .1- .FO .~1 0R~ 186 1P~ 1~. 1~5 4.4 457 4G. 53G 5VS 7-5 7RV 8G5 8P~ AABNK AABSN AAEDT AAEDW AAHBH AAIKC AAIKJ AAKOC AALRI AAMNW AAOAW AAQFI AAQQT AATTM AAXKI AAXUO AAYWO ABBQC ABGRD ABJNI ABMAC ABMZM ABWVN ABXDB ACDAQ ACGFS ACGOD ACIEU ACJTP ACPRK ACRLP ACRPL ACVFH ADBBV ADCNI ADEZE ADHUB ADMUD ADNMO ADQTV ADUKH AEBSH AEIPS AEKER AENEX AEQOU AEUPX AEUYN AEVXI AFJKZ AFKRA AFPUW AFRAH AFRHN AFTJW AFXBA AFXIZ AGCQF AGHFR AGNAY AGUBO AGYEJ AHMBA AIEXJ AIGII AIIUN AIKHN AITUG AJRQY AJUYK AKBMS AKRWK AKYEP ALMA_UNASSIGNED_HOLDINGS AMRAJ ANKPU ANZVX APXCP AXJTR AZQEC BKOJK BLXMC BNPGV CCPQU COPKO EBS EFJIC EFKBS EJD EX3 FAFAN FDB FIRID FNPLU FYGXN GBLVA HF~ HMCUK HZ~ K-O KOM M41 MO0 NAPCQ O-L O9- OAUVE P-8 P-9 P-O PADUT PC. PHGZM PHGZT PJZUB PPXIY PQQKQ PRG PROAC PSQYO PUEGO Q2X Q38 ROL S0X SDF SEL SNC SND SNG SPCBC SSH SSZ T5K UBH UBW UKHRP WH7 WOW Z5R ~G- AABVA AACTN AAIAV AATLK ABLVK ABYKQ AFKWA AISVY AJBFU AJOXV AMFUW CBWCG EFLBG LCYCR NAHTW RIG SSA ZAH AAYXX AGRNS CITATION NPM UCJ 7X8 7S9 L.6 5PM |
ID | FETCH-LOGICAL-c539t-c0363ce6c67a6af7bb180178b2d51333e5e936149dee8d8cdab11e00fc6fdf183 |
IEDL.DBID | .~1 |
ISSN | 2212-2672 |
IngestDate | Thu Aug 21 18:35:12 EDT 2025 Tue Aug 05 11:27:21 EDT 2025 Sun Aug 24 03:48:49 EDT 2025 Thu Apr 03 07:02:07 EDT 2025 Tue Jul 01 03:53:34 EDT 2025 Thu Apr 24 23:08:29 EDT 2025 Fri Feb 23 02:44:08 EST 2024 Tue Aug 26 18:32:01 EDT 2025 |
IsDoiOpenAccess | false |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 7 |
Keywords | Energy intake Self-monitoring Free-living Microstructural analysis Bite count |
Language | English |
License | Copyright © 2019 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c539t-c0363ce6c67a6af7bb180178b2d51333e5e936149dee8d8cdab11e00fc6fdf183 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 JNS collected the data and wrote the first draft of the manuscript. AWH provided the tools and algorithms for detecting bite counts and bite weights. ERM assisted with study design manuscript drafting. All authors reviewed and commented on subsequent drafts. |
OpenAccessLink | http://www.jandonline.org/article/S2212267218306841/pdf |
PMID | 30777655 |
PQID | 2183652140 |
PQPubID | 23479 |
PageCount | 9 |
ParticipantIDs | pubmedcentral_primary_oai_pubmedcentral_nih_gov_6592756 proquest_miscellaneous_2220868037 proquest_miscellaneous_2183652140 pubmed_primary_30777655 crossref_primary_10_1016_j_jand_2018_12_009 crossref_citationtrail_10_1016_j_jand_2018_12_009 elsevier_sciencedirect_doi_10_1016_j_jand_2018_12_009 elsevier_clinicalkey_doi_10_1016_j_jand_2018_12_009 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2019-07-01 |
PublicationDateYYYYMMDD | 2019-07-01 |
PublicationDate_xml | – month: 07 year: 2019 text: 2019-07-01 day: 01 |
PublicationDecade | 2010 |
PublicationPlace | United States |
PublicationPlace_xml | – name: United States |
PublicationTitle | Journal of the Academy of Nutrition and Dietetics |
PublicationTitleAlternate | J Acad Nutr Diet |
PublicationYear | 2019 |
Publisher | Elsevier Inc |
Publisher_xml | – name: Elsevier Inc |
References | Lawless, Bender, Oman, Pelletier (bib12) 2003; 18 Accessed February 11, 2019. Zijlstra, De Wijk, Mars, Stafleu, De Graaf (bib24) 2009; 90 Yao, Roberts (bib10) 2001; 59 Scisco, Muth, Dong, Hoover (bib15) 2011; 111 Spiegel, Kaplan, Tomassini, Stellar (bib23) 1993; 21 Cardello, Schutz, Lesher, Merrill (bib18) 2005; 44 NHLBI Obesity Education Initiative. Westerterp-Plantenga (bib8) 2000; 24 Kalantarian, Sarrafzadeh (bib6) 2015; 65 Tabachnick, Fidell (bib20) 2014 Guss, Kissileff (bib7) 2000; 24 Bethesda, MD: National Heart, Lung, and Blood Institute; 1998. Dhurandhar, Schoeller, Brown (bib2) 2015; 39 Laessle, Lehrke, Dückers (bib27) 2007; 49 Salley, Hoover, Wilson, Muth (bib4) 2016; 116 Schutz, Cardello (bib19) 2001; 16 Hofmann, Gavin (bib22) 1998; 24 Ohkuma, Hirakawa, Nakamura, Kiyohara, Kitazono, Ninomiya (bib9) 2015; 39 Fontana, Higgins, Schuckers (bib5) 2015; 85 Flegal, Kruszon-Moran, Carroll, Fryar, Ogden (bib1) 2016; 315 Hill, McCutcheon (bib11) 1984; 5 Mattfeld, Muth, Hoover (bib17) 2017; 21 Scisco, Muth, Hoover (bib13) 2014; 114 (bib21) 2013 Fontana, Farooq, Sazonov (bib14) 2014; 61 Mattfeld, Muth, Hoover (bib25) 2017; 181 Dovey, Clark-Carter, Boyland, Halford (bib26) 2009; 96 Schoeller, Thomas, Archer (bib3) 2013; 97 Salley (10.1016/j.jand.2018.12.009_bib4) 2016; 116 Hofmann (10.1016/j.jand.2018.12.009_bib22) 1998; 24 Dhurandhar (10.1016/j.jand.2018.12.009_bib2) 2015; 39 Yao (10.1016/j.jand.2018.12.009_bib10) 2001; 59 Schoeller (10.1016/j.jand.2018.12.009_bib3) 2013; 97 Flegal (10.1016/j.jand.2018.12.009_bib1) 2016; 315 Zijlstra (10.1016/j.jand.2018.12.009_bib24) 2009; 90 Tabachnick (10.1016/j.jand.2018.12.009_bib20) 2014 (10.1016/j.jand.2018.12.009_bib21) 2013 Scisco (10.1016/j.jand.2018.12.009_bib13) 2014; 114 Hill (10.1016/j.jand.2018.12.009_bib11) 1984; 5 10.1016/j.jand.2018.12.009_bib16 Cardello (10.1016/j.jand.2018.12.009_bib18) 2005; 44 Fontana (10.1016/j.jand.2018.12.009_bib5) 2015; 85 Westerterp-Plantenga (10.1016/j.jand.2018.12.009_bib8) 2000; 24 Lawless (10.1016/j.jand.2018.12.009_bib12) 2003; 18 Kalantarian (10.1016/j.jand.2018.12.009_bib6) 2015; 65 Dovey (10.1016/j.jand.2018.12.009_bib26) 2009; 96 Laessle (10.1016/j.jand.2018.12.009_bib27) 2007; 49 Spiegel (10.1016/j.jand.2018.12.009_bib23) 1993; 21 Mattfeld (10.1016/j.jand.2018.12.009_bib25) 2017; 181 Mattfeld (10.1016/j.jand.2018.12.009_bib17) 2017; 21 Schutz (10.1016/j.jand.2018.12.009_bib19) 2001; 16 Fontana (10.1016/j.jand.2018.12.009_bib14) 2014; 61 Guss (10.1016/j.jand.2018.12.009_bib7) 2000; 24 Ohkuma (10.1016/j.jand.2018.12.009_bib9) 2015; 39 Scisco (10.1016/j.jand.2018.12.009_bib15) 2011; 111 |
References_xml | – volume: 85 start-page: 14 year: 2015 end-page: 21 ident: bib5 article-title: Energy intake estimation from counts of chews and swallows publication-title: Appetite – volume: 24 start-page: 623 year: 1998 end-page: 641 ident: bib22 article-title: Centering decisions in hierarchical linear models: Implications for research in organizations publication-title: J Manage – volume: 116 start-page: 1568 year: 2016 end-page: 1577 ident: bib4 article-title: Comparison between human and bite-based methods of estimating caloric intake publication-title: J Acad Nutr Diet – year: 2013 ident: bib21 publication-title: IBM SPSS Statistics for Windows [computer program]. Version 22.0 – volume: 49 start-page: 399 year: 2007 end-page: 404 ident: bib27 article-title: Laboratory eating behavior in obesity publication-title: Appetite – volume: 111 start-page: 1231 year: 2011 end-page: 1235 ident: bib15 article-title: Slowing bite-rate reduces energy intake: an application of the bite counter device publication-title: J Am Diet Assoc – volume: 24 start-page: 239 year: 2000 end-page: 248 ident: bib8 article-title: Eating behavior in humans, characterized by cumulative food intake curves—a review publication-title: Neurosci Biobehav Rev – volume: 315 start-page: 2284 year: 2016 ident: bib1 article-title: Trends in obesity among adults in the United States, 2005 to 2014 publication-title: JAMA – volume: 96 start-page: 78 year: 2009 end-page: 84 ident: bib26 article-title: A guide to analysing Universal Eating Monitor data: Assessing the impact of different analysis techniques publication-title: Physiol Behav – volume: 18 start-page: 196 year: 2003 end-page: 202 ident: bib12 article-title: Gender, age, vessel size, cup vs. straw sipping, and sequence effects on sip volume publication-title: Dysphagia – volume: 97 start-page: 1413 year: 2013 end-page: 1415 ident: bib3 article-title: Self-report-based estimates of energy intake offer an inadequate basis for scientific conclusions publication-title: Am J Clin Nutr – reference: NHLBI Obesity Education Initiative. – volume: 59 start-page: 247 year: 2001 end-page: 258 ident: bib10 article-title: Dietary energy density and weight regulation publication-title: Nutr Rev – volume: 5 start-page: 73 year: 1984 end-page: 83 ident: bib11 article-title: Contributions of obesity, gender, hunger, food preference, and body size to bite size, bite speed, and rate of eating publication-title: Appetite – volume: 44 start-page: 1 year: 2005 end-page: 13 ident: bib18 article-title: Development and testing of a labeled magnitude scale of perceived satiety publication-title: Appetite – reference: . Accessed February 11, 2019. – volume: 24 start-page: 261 year: 2000 end-page: 268 ident: bib7 article-title: Microstructural analyses of human ingestive patterns: From description to mechanistic hypotheses publication-title: Neurosci Biobehav Rev – volume: 114 start-page: 464 year: 2014 end-page: 469 ident: bib13 article-title: Examining the utility of a bite-count-based measure of eating activity in free-living human beings publication-title: J Acad Nutr Diet – volume: 181 start-page: 38 year: 2017 end-page: 42 ident: bib25 article-title: A comparison of bite size and BMI in a cafeteria setting publication-title: Physiol Behav – volume: 39 start-page: 1109 year: 2015 end-page: 1113 ident: bib2 article-title: Energy balance measurement: When something is not better than nothing publication-title: Int J Obes – volume: 16 start-page: 117 year: 2001 end-page: 159 ident: bib19 article-title: A labeled affective magnitude (LAM) scale for assessing food liking/disliking publication-title: J Sens Stud – volume: 21 start-page: 1711 year: 2017 end-page: 1718 ident: bib17 article-title: Measuring the consumption of individual solid and liquid bites using a table-embedded scale during unrestricted eating publication-title: IEEE J Biomed Heal Informatics – volume: 61 start-page: 1772 year: 2014 end-page: 1779 ident: bib14 article-title: Automatic Ingestion Monitor: A Novel Wearable Device for Monitoring of Ingestive Behavior publication-title: IEEE Trans Biomed Eng – volume: 21 start-page: 131 year: 1993 end-page: 145 ident: bib23 article-title: Bite size, ingestion rate, and meal size in lean and obese women publication-title: Appetite – volume: 39 start-page: 1589 year: 2015 end-page: 1596 ident: bib9 article-title: Association between eating rate and obesity: A systematic review and meta-analysis publication-title: Int J Obes – reference: . Bethesda, MD: National Heart, Lung, and Blood Institute; 1998. – volume: 90 start-page: 269 year: 2009 end-page: 275 ident: bib24 article-title: Effect of bite size and oral processing time of a semisolid food on satiation publication-title: Am J Clin Nutr – volume: 65 start-page: 1 year: 2015 end-page: 9 ident: bib6 article-title: Audio-based detection and evaluation of eating behavior using the smartwatch platform publication-title: Comput Biol Med – year: 2014 ident: bib20 article-title: Using Multivariate Statistics – volume: 315 start-page: 2284 issue: 21 year: 2016 ident: 10.1016/j.jand.2018.12.009_bib1 article-title: Trends in obesity among adults in the United States, 2005 to 2014 publication-title: JAMA doi: 10.1001/jama.2016.6458 – volume: 24 start-page: 261 issue: 2 year: 2000 ident: 10.1016/j.jand.2018.12.009_bib7 article-title: Microstructural analyses of human ingestive patterns: From description to mechanistic hypotheses publication-title: Neurosci Biobehav Rev doi: 10.1016/S0149-7634(99)00079-2 – volume: 5 start-page: 73 issue: 2 year: 1984 ident: 10.1016/j.jand.2018.12.009_bib11 article-title: Contributions of obesity, gender, hunger, food preference, and body size to bite size, bite speed, and rate of eating publication-title: Appetite doi: 10.1016/S0195-6663(84)80026-4 – volume: 49 start-page: 399 issue: 2 year: 2007 ident: 10.1016/j.jand.2018.12.009_bib27 article-title: Laboratory eating behavior in obesity publication-title: Appetite doi: 10.1016/j.appet.2006.11.010 – volume: 181 start-page: 38 year: 2017 ident: 10.1016/j.jand.2018.12.009_bib25 article-title: A comparison of bite size and BMI in a cafeteria setting publication-title: Physiol Behav doi: 10.1016/j.physbeh.2017.09.002 – volume: 44 start-page: 1 issue: 1 year: 2005 ident: 10.1016/j.jand.2018.12.009_bib18 article-title: Development and testing of a labeled magnitude scale of perceived satiety publication-title: Appetite doi: 10.1016/j.appet.2004.05.007 – volume: 61 start-page: 1772 issue: 6 year: 2014 ident: 10.1016/j.jand.2018.12.009_bib14 article-title: Automatic Ingestion Monitor: A Novel Wearable Device for Monitoring of Ingestive Behavior publication-title: IEEE Trans Biomed Eng doi: 10.1109/TBME.2014.2306773 – volume: 39 start-page: 1109 issue: 7 year: 2015 ident: 10.1016/j.jand.2018.12.009_bib2 article-title: Energy balance measurement: When something is not better than nothing publication-title: Int J Obes doi: 10.1038/ijo.2014.199 – volume: 85 start-page: 14 year: 2015 ident: 10.1016/j.jand.2018.12.009_bib5 article-title: Energy intake estimation from counts of chews and swallows publication-title: Appetite doi: 10.1016/j.appet.2014.11.003 – year: 2013 ident: 10.1016/j.jand.2018.12.009_bib21 – volume: 21 start-page: 1711 issue: 6 year: 2017 ident: 10.1016/j.jand.2018.12.009_bib17 article-title: Measuring the consumption of individual solid and liquid bites using a table-embedded scale during unrestricted eating publication-title: IEEE J Biomed Heal Informatics doi: 10.1109/JBHI.2016.2632621 – ident: 10.1016/j.jand.2018.12.009_bib16 – volume: 16 start-page: 117 issue: 2 year: 2001 ident: 10.1016/j.jand.2018.12.009_bib19 article-title: A labeled affective magnitude (LAM) scale for assessing food liking/disliking publication-title: J Sens Stud doi: 10.1111/j.1745-459X.2001.tb00293.x – volume: 24 start-page: 239 issue: 2 year: 2000 ident: 10.1016/j.jand.2018.12.009_bib8 article-title: Eating behavior in humans, characterized by cumulative food intake curves—a review publication-title: Neurosci Biobehav Rev doi: 10.1016/S0149-7634(99)00077-9 – volume: 114 start-page: 464 issue: 3 year: 2014 ident: 10.1016/j.jand.2018.12.009_bib13 article-title: Examining the utility of a bite-count-based measure of eating activity in free-living human beings publication-title: J Acad Nutr Diet doi: 10.1016/j.jand.2013.09.017 – volume: 116 start-page: 1568 issue: 10 year: 2016 ident: 10.1016/j.jand.2018.12.009_bib4 article-title: Comparison between human and bite-based methods of estimating caloric intake publication-title: J Acad Nutr Diet doi: 10.1016/j.jand.2016.03.007 – volume: 59 start-page: 247 issue: 8 Pt 1 year: 2001 ident: 10.1016/j.jand.2018.12.009_bib10 article-title: Dietary energy density and weight regulation publication-title: Nutr Rev – year: 2014 ident: 10.1016/j.jand.2018.12.009_bib20 – volume: 39 start-page: 1589 issue: 11 year: 2015 ident: 10.1016/j.jand.2018.12.009_bib9 article-title: Association between eating rate and obesity: A systematic review and meta-analysis publication-title: Int J Obes doi: 10.1038/ijo.2015.96 – volume: 24 start-page: 623 issue: 5 year: 1998 ident: 10.1016/j.jand.2018.12.009_bib22 article-title: Centering decisions in hierarchical linear models: Implications for research in organizations publication-title: J Manage – volume: 96 start-page: 78 issue: 1 year: 2009 ident: 10.1016/j.jand.2018.12.009_bib26 article-title: A guide to analysing Universal Eating Monitor data: Assessing the impact of different analysis techniques publication-title: Physiol Behav doi: 10.1016/j.physbeh.2008.08.016 – volume: 65 start-page: 1 year: 2015 ident: 10.1016/j.jand.2018.12.009_bib6 article-title: Audio-based detection and evaluation of eating behavior using the smartwatch platform publication-title: Comput Biol Med doi: 10.1016/j.compbiomed.2015.07.013 – volume: 18 start-page: 196 issue: 3 year: 2003 ident: 10.1016/j.jand.2018.12.009_bib12 article-title: Gender, age, vessel size, cup vs. straw sipping, and sequence effects on sip volume publication-title: Dysphagia doi: 10.1007/s00455-002-0105-0 – volume: 90 start-page: 269 issue: 2 year: 2009 ident: 10.1016/j.jand.2018.12.009_bib24 article-title: Effect of bite size and oral processing time of a semisolid food on satiation publication-title: Am J Clin Nutr doi: 10.3945/ajcn.2009.27694 – volume: 21 start-page: 131 issue: 2 year: 1993 ident: 10.1016/j.jand.2018.12.009_bib23 article-title: Bite size, ingestion rate, and meal size in lean and obese women publication-title: Appetite doi: 10.1016/0195-6663(93)90005-5 – volume: 97 start-page: 1413 issue: 6 year: 2013 ident: 10.1016/j.jand.2018.12.009_bib3 article-title: Self-report-based estimates of energy intake offer an inadequate basis for scientific conclusions publication-title: Am J Clin Nutr doi: 10.3945/ajcn.113.062125 – volume: 111 start-page: 1231 issue: 8 year: 2011 ident: 10.1016/j.jand.2018.12.009_bib15 article-title: Slowing bite-rate reduces energy intake: an application of the bite counter device publication-title: J Am Diet Assoc doi: 10.1016/j.jada.2011.05.005 |
SSID | ssj0000603380 |
Score | 2.3045669 |
Snippet | This study builds on previous research that seeks to estimate kilocalorie intake through microstructural analysis of eating behaviors. As opposed to previous... |
SourceID | pubmedcentral proquest pubmed crossref elsevier |
SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
StartPage | 1109 |
SubjectTerms | Bite count body mass index eating habits Energy intake females Free-living Microstructural analysis mouth satiety Self-monitoring |
Title | Between- and Within-Subjects Predictors of the Kilocalorie Content of Bites of Food |
URI | https://www.clinicalkey.com/#!/content/1-s2.0-S2212267218306841 https://dx.doi.org/10.1016/j.jand.2018.12.009 https://www.ncbi.nlm.nih.gov/pubmed/30777655 https://www.proquest.com/docview/2183652140 https://www.proquest.com/docview/2220868037 https://pubmed.ncbi.nlm.nih.gov/PMC6592756 |
Volume | 119 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnR3LatwwUITkkktp-nSbBhVKL0Vd2ZIl-5hHl01Cl0IampuwZJk4BDskzjXfnhn5QbYtW-jFYGsGLM1oHtI8CPmkC-vi3EpWwnZiUnrPMuszpqSVgrssEaHO9velWpzLk4v0YoMcjrkwGFY5yP5epgdpPXyZDas5u6nr2VkCUjdRGnU8V1lIXpdSI5d_fYincxauOHhheNSC8AwRhtyZPszrChx2jPDKwqkgxiX-XT_9aX_-Hkb5RC_Nn5Nng0FJ9_t_3iEbvnlBoqPad_QzHap-XtPlWHT_JTk76EOzGIV_or_q7rJuGMgPPJC5oz9u8eYGW_DQtqJgHdLTOui7FnxqGmpZNR0OHYCtGmDmbVu-Iufzbz8PF2xorcBcKvKOOby_dV45pQtVVNraGFSVzmxSYsMX4VOfC9Dceel9hg2OChvHnvPKqaqsYMVfk82mbfxbQsECElWqcngIWRTgv7nEWhGsMRDDPCLxuKDGDXXHsf3FtRkDzK4MEsEgEUycGCBCRL5MODd91Y210GKkkxnzSUECGlAKa7HSCWuF4_6J93FkBQNbEe9Xisa393cGOVGBOST5GpgkAScy40JH5E3PPtMMQdxqrdI0InqFsSYALAW-OtLUl6EkOF6O61S9-885vSfb8Jb3Yci7ZLO7vfcfwNjq7F7YTXtka__4dLF8BHGwJ-s |
linkProvider | Elsevier |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1La9wwEBZhc2gvpe86falQeiliZcuS7GOSdtl0k6WQhOYmLFkmDsEOifP_O2PLptuWLfTig6UBPUbz0ugbQj7qwro4tykr4TixNPWeZdZnTKU2Fdxliehxtk_WanmefruQFzvkcHwLg2mVQfYPMr2X1uHPPKzm_Kau56cJSN1EadTxXGX4eH0X0ankjOzuH62W6ynUwhUHRwyjLUjCkCY8nxkyva7AZ8ckr6wPDGJq4t9V1J8m6O-ZlL-opsVj8ijYlHR_GPYTsuObpyT6UvuOfqIB-POarkfc_Wfk9GDIzmIUxkR_1N1l3TAQIRiTuaPfb_HyBqvw0LaiYCDSVd2rvBbcatrDWTUdNh2Audr3WbRt-ZycL76eHS5ZqK7AnBR5xxxe4TqvnNKFKiptbQzaSmc2KbHmi_DS5wKUd156n2GNo8LGsee8cqoqK1j0F2TWtI1_RSgYQaKSKoePSIsCXDiXWCt6gwwkMY9IPC6ocQF6HCtgXJsxx-zK4CYY3AQTJwY2ISKfJ5qbAXhja28x7pMZn5SCEDSgF7ZSyYlqg-n-SfdhZAUDpxGvWIrGt_d3BplRgUWU8i19kgT8yIwLHZGXA_tMMwSJq7WSMiJ6g7GmDogGvtnS1Jc9Kjjej2up9v5zTu_Jg-XZybE5PlqvXpOH0JIPWclvyKy7vfdvwfbq7Ltwtn4Cf6kqnA |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Between-+and+Within-Subjects+Predictors+of+the+Kilocalorie+Content+of+Bites+of+Food&rft.jtitle=Journal+of+the+Academy+of+Nutrition+and+Dietetics&rft.au=Salley%2C+James+N.&rft.au=Hoover%2C+Adam+W.&rft.au=Muth%2C+Eric+R.&rft.date=2019-07-01&rft.pub=Elsevier+Inc&rft.issn=2212-2672&rft.eissn=2212-2680&rft.volume=119&rft.issue=7&rft.spage=1109&rft.epage=1117&rft_id=info:doi/10.1016%2Fj.jand.2018.12.009&rft.externalDocID=S2212267218306841 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2212-2672&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2212-2672&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2212-2672&client=summon |