Objective: We identify individuals who set daily intake budgets and examine if an intervention making people estimate their calorie intake up to a certain point in the day helps those setting daily budgets to regulate their calorie intake for the remainder of the day, after high prior consumption.
Design: We conducted an online experiment in five countries: Australia, China, Germany, India, and the UK (n = 3,032) using a 2 (setting calorie budget: yes vs. no, measured) x 2 (intervention: intake reminder vs. control, manipulated) between-subjects design, with the amount of prior consumption measured. Participants were contacted in the afternoon. Those in the intervention condition were asked to estimate their prior calorie intake on that day.
Main Outcome Measures: We measured the individual characteristics of those who set daily calorie budgets and the intended calorie intake for the remainder of the day.
Results: Among people who set daily calorie budgets, the intervention reduced intended calorie intake for the remainder of the day by 176 calories if they had already consumed a high amount of calories that day.
Conclusion: A timely intervention to estimate one's calorie intake can lower additional intended calorie intake among those who set daily calorie budget.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1080/08870446.2021.1972111 | DOI Listing |
World J Clin Cases
January 2025
Naval Medical Center of PLA, Naval Medical University, Shanghai 200052, China.
In this editorial, we have commented on the article that has been published in the recent issue of . The authors have described a case of unilateral thyroid cyst and have opined that the acute onset of infection may be linked to diabetes mellitus (DM). We have focused on the role of nutrition in the association between DM and infection.
View Article and Find Full Text PDFHeliyon
January 2025
Institute of Statistical Research and Training, University of Dhaka, Bangladesh.
This paper examines the current state of food insecurity in Bangladesh and its socio-economic drivers using data from the latest Household Income and Expenditure Survey (HIES 2022). Unlike previous studies that relied on less precise measures of food insecurity, such as food expenditure, diversity, and calorie intake, this study employs the internationally recognized Food Insecurity Experience Scale (FIES) and Rasch model-based thresholds to classify households as food secure or insecure. Multilevel logistic regression is used to identify significant predictors of moderate and severe food insecurity, considering the hierarchical structure of the data, with households nested within geographical clusters.
View Article and Find Full Text PDFNutrients
January 2025
Department of Nutrition, Food Sciences and Physiology, Center for Nutrition and Research, University of Navarra, 31008 Pamplona, Spain.
Background And Aim: Telomere length (TL) is a key biomarker of cellular aging, with shorter telomeres associated with age-related diseases. Lifestyle interventions mitigating telomere shortening are essential for preventing such conditions. This study aimed to examine the effects of two weight loss dietary strategies, based on a moderately high-protein (MHP) diet and a low-fat (LF) diet on TL in individuals with overweight or obesity.
View Article and Find Full Text PDFNutrients
January 2025
Department of Pediatric Intensive Care, Faculty of Medicine, Mugla Sitki Kocman University, Mugla 48000, Türkiye.
Background: The inability to ensure adequate nutrition for patients, and failure to provide adequate calorie and protein intake, result in malnutrition, leading to increased morbidity and mortality. The present study assesses the two approaches to enteral nutrition-intermittent and continuous enteral feeding-in critically ill pediatric patients in Türkiye to determine the superiority of one method over the other.
Methods: Included in this multicenter prospective study were patients receiving enteral nutrition via a tube who were followed up over a 3-month period.
Nutrients
January 2025
Division of Nutrition, Food & Dietetics, School of Biosciences, University of Nottingham, Leics LE12 5RD, UK.
With the rise of artificial intelligence (AI) in nutrition and healthcare, AI-driven chatbots are increasingly recognised as potential tools for generating personalised diet plans. This study aimed to evaluate the capabilities of three popular chatbots-Gemini, Microsoft Copilot, and ChatGPT 4.0-in designing weight-loss diet plans across varying caloric levels and genders.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!