Collections

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    Can we measure food intake in humans? Accurately quantifying food intake is essential to understanding the effect of diet on health and diseases and evaluating the efficacy of dietary interventions. Self-report methods (e.g., food records) remain frequently used despite their evident inaccuracy at assessing energy intake and diet composition. In fact, the many components of food intake: calorie amount, diet composition, eating pattern, meal timing, day-to-day variability, and overall effect on metabolism and energy balance, are excessively difficult to assess in research and in clinical setting. While there are accurate methods to assess sleep and physical activity, there is still a need to develop and validate reliable methods for laboratory and ambulatory measures of many aspects of food intake behavior. The goal of this collection on validated methods to measure food intake in humans, was, in addition to the welcome historical perspectives (Bellisle) (Kissileff), to present current and futuristic methods to measure food intake behavior both in laboratory setting (Bellisle) (Kissileff), (Sazonov) and in ambulatory free-living conditions (Manoogian) (Höchsmann). In a near future, by combining body sensors and remote captors of behavior, validated against state-of-the-art stable isotope methods (Ravelli- Schoeller), with precise quantitative measure of an infinite number of biomarkers (González-Domínguez), we will have a more reliable way to track food intake behavior and its metabolic consequences. However, the technology to support food recognition and portion size estimation is still in its infancy and fully automated precise assessment of food intake in ambulatory setting is not yet a reality. With advance technology and artificial intelligence, we can hope for reduced data analysis-related burden and allow feedback in real-time to users. This will not only help us understand the determinants of this complex behavior but enable targeted dietary interventions to promote health and prevent diseases.

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    See what readers worldwide have been citing and sharing. In this Web Focus we highlight a selection of articles from 2021, which top the list of the journal’s most cited, downloaded and most shared (including press coverage, blogs, Twitter, Facebook and Weibo). They showcase the breadth of scope and coverage that the journal consistently delivers to its readers.

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    The history of IJO's Pediatric Highlights began in 2002 when Associate Editor, Angelo Pietrobelli, remarked that the field of pediatric obesity did not have a journal of its own and inquired whether we thought it was time for such a journal. An analysis of the number and quality of pediatric papers submitted to IJO led to the conclusion that an independent pediatric obesity journal at that time probably would not have sufficient submissions to be successful, however, the seed was planted and a plan was formulated to have a section devoted to papers on pediatric obesity in several IJO issues each year. The Pediatric Highlights section has since flourished with investigators from the pediatric obesity field rewarding IJO by making it a preferred journal for some of their best papers. We now pull these papers into an online collection and look forward to continue serving the field and publishing the very best papers in pediatric obesity each year.

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    Research on the pandemic of Covid-19 has demonstrated that there is a higher risk of contracting the disease, increased severity, and poorer outcomes in individuals who are obese.

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    See what readers world-wide have been citing and sharing. In this Web Focus we highlight a selection of articles from 2020, which top the list of the journal’s most cited, downloaded and most shared (including press coverage, blogs, Twitter, Facebook and Weibo). They showcase the breadth of scope and coverage that the journal consistently delivers to its readers.

    Image: SCIEPRO
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    The ability of modern computers to analyse massive data sets that heretofore were impossible to handle has opened up new vistas in research. Such massive data sets have been named “Big Data”. The International Journal of Obesity strives to identify novel areas for research into obesity and it appears that gleaning information from “Big Data” data sets holds promise to allow identification of questions for more targeted research as well as to directly answer some questions about obesity. There has been a very modest effort to use big data in obesity research to date and most of the questions have regarded identifying genetic loci from genome wide scans that correlate with obesity-related traits. Many types of research will be available using massive data sets, including genetic, biochemical/physiological, clinical, behavioural, economic, and other topics. The Economic and Social Research Council (ERSC) in the United Kingdom funded a Strategic Network for Obesity to address Big Data in obesity research. This collection of articles discuss the potential role of big data in obesity research. Richard L. Atkinson and Ian A. Macdonald, Editors-in-Chief

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    See what scientists world-wide have been citing and sharing. In this Web Focus we highlight a selection of articles from 2019, which top the list of the journal’s most cited and most shared (including press coverage, blogs, Twitter, Facebook and Weibo). They showcase the breadth of scope and coverage that the journal consistently delivers to its readers.

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    Growth in research coming from Asia, specifically China, over recent years has been pronounced. China has now surpassed the US in terms of global publications output and is challenging the US and Europe in terms of R&D investment. Not only has the volume of research increased but the quality of research has also improved with the volume of citations increasing and a greater percentage of top cited authors now coming from this region. This collection showcases a selection of top cited articles published in International Journal of Obesity from authors hailing from this region.

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    See what scientists world-wide have been citing and sharing. In this Web Focus we highlight a selection of articles from 2018 which top the list of the journal’s most cited and most shared (including press coverage, blogs, Twitter, Facebook and Weibo). They showcase the breadth of scope and coverage that the journal consistently delivers to its readers.

    Image: SCIEPRO