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Calorie Compensation Patterns Observed in App-Based Food Diaries
Self-regulation of food intake is necessary for maintaining a healthy body weight. One of the characteristics of self-regulation is calorie compensation. Calorie compensation refers to adjusting the current meal’s energy content based on the energy content of the previous meal(s). Preload test studi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536014/ https://www.ncbi.nlm.nih.gov/pubmed/37764790 http://dx.doi.org/10.3390/nu15184007 |
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author | Pai, Amruta Sabharwal, Ashutosh |
author_facet | Pai, Amruta Sabharwal, Ashutosh |
author_sort | Pai, Amruta |
collection | PubMed |
description | Self-regulation of food intake is necessary for maintaining a healthy body weight. One of the characteristics of self-regulation is calorie compensation. Calorie compensation refers to adjusting the current meal’s energy content based on the energy content of the previous meal(s). Preload test studies measure a single instance of compensation in a controlled setting. The measurement of calorie compensation in free-living conditions has largely remained unexplored. This paper proposes a methodology that leverages extensive app-based observational food diary data to measure an individual’s calorie compensation profile in free-living conditions. Instead of a single compensation index followed in preload–test studies, we present the compensation profile as a distribution of days a user exhibits under-compensation, overcompensation, non-compensation, and precise compensation. We applied our methodology to the public food diary data of 1622 MyFitnessPal users. We empirically established that four weeks of food diaries were sufficient to characterize a user’s compensation profile accurately. We observed that meal compensation was more likely than day compensation. Dinner compensation had a higher likelihood than lunch compensation. Precise compensation was the least likely. Users were more likely to overcompensate for missing calories than for additional calories. The consequences of poor compensatory behavior were reflected in their adherence to their daily calorie goal. Our methodology could be applied to food diaries to discover behavioral phenotypes of poor compensatory behavior toward forming an early behavioral marker for weight gain. |
format | Online Article Text |
id | pubmed-10536014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105360142023-09-29 Calorie Compensation Patterns Observed in App-Based Food Diaries Pai, Amruta Sabharwal, Ashutosh Nutrients Article Self-regulation of food intake is necessary for maintaining a healthy body weight. One of the characteristics of self-regulation is calorie compensation. Calorie compensation refers to adjusting the current meal’s energy content based on the energy content of the previous meal(s). Preload test studies measure a single instance of compensation in a controlled setting. The measurement of calorie compensation in free-living conditions has largely remained unexplored. This paper proposes a methodology that leverages extensive app-based observational food diary data to measure an individual’s calorie compensation profile in free-living conditions. Instead of a single compensation index followed in preload–test studies, we present the compensation profile as a distribution of days a user exhibits under-compensation, overcompensation, non-compensation, and precise compensation. We applied our methodology to the public food diary data of 1622 MyFitnessPal users. We empirically established that four weeks of food diaries were sufficient to characterize a user’s compensation profile accurately. We observed that meal compensation was more likely than day compensation. Dinner compensation had a higher likelihood than lunch compensation. Precise compensation was the least likely. Users were more likely to overcompensate for missing calories than for additional calories. The consequences of poor compensatory behavior were reflected in their adherence to their daily calorie goal. Our methodology could be applied to food diaries to discover behavioral phenotypes of poor compensatory behavior toward forming an early behavioral marker for weight gain. MDPI 2023-09-16 /pmc/articles/PMC10536014/ /pubmed/37764790 http://dx.doi.org/10.3390/nu15184007 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Pai, Amruta Sabharwal, Ashutosh Calorie Compensation Patterns Observed in App-Based Food Diaries |
title | Calorie Compensation Patterns Observed in App-Based Food Diaries |
title_full | Calorie Compensation Patterns Observed in App-Based Food Diaries |
title_fullStr | Calorie Compensation Patterns Observed in App-Based Food Diaries |
title_full_unstemmed | Calorie Compensation Patterns Observed in App-Based Food Diaries |
title_short | Calorie Compensation Patterns Observed in App-Based Food Diaries |
title_sort | calorie compensation patterns observed in app-based food diaries |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536014/ https://www.ncbi.nlm.nih.gov/pubmed/37764790 http://dx.doi.org/10.3390/nu15184007 |
work_keys_str_mv | AT paiamruta caloriecompensationpatternsobservedinappbasedfooddiaries AT sabharwalashutosh caloriecompensationpatternsobservedinappbasedfooddiaries |