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Brummer J, Glasbrenner C, Hechenbichler Figueroa S, Koehler K, Höchsmann C. Continuous glucose monitoring for automatic real-time assessment of eating events and nutrition: a scoping review. Front Nutr 2024; 10:1308348. [PMID: 38264192 PMCID: PMC10804456 DOI: 10.3389/fnut.2023.1308348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 12/13/2023] [Indexed: 01/25/2024] Open
Abstract
Background Accurate dietary assessment remains a challenge, particularly in free-living settings. Continuous glucose monitoring (CGM) shows promise in optimizing the assessment and monitoring of ingestive activity (IA, i.e., consumption of calorie-containing foods/beverages), and it might enable administering dietary Just-In-Time Adaptive Interventions (JITAIs). Objective In a scoping review, we aimed to answer the following questions: (1) Which CGM approaches to automatically detect IA in (near-)real-time have been investigated? (2) How accurate are these approaches? (3) Can they be used in the context of JITAIs? Methods We systematically searched four databases until October 2023 and included publications in English or German that used CGM-based approaches for human (all ages) IA detection. Eligible publications included a ground-truth method as a comparator. We synthesized the evidence qualitatively and critically appraised publication quality. Results Of 1,561 potentially relevant publications identified, 19 publications (17 studies, total N = 311; for 2 studies, 2 publications each were relevant) were included. Most publications included individuals with diabetes, often using meal announcements and/or insulin boluses accompanying meals. Inpatient and free-living settings were used. CGM-only approaches and CGM combined with additional inputs were deployed. A broad range of algorithms was tested. Performance varied among the reviewed methods, ranging from unsatisfactory to excellent (e.g., 21% vs. 100% sensitivity). Detection times ranged from 9.0 to 45.0 min. Conclusion Several CGM-based approaches are promising for automatically detecting IA. However, response times need to be faster to enable JITAIs aimed at impacting acute IA. Methodological issues and overall heterogeneity among articles prevent recommending one single approach; specific cases will dictate the most suitable approach.
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Hiraguchi H, Perone P, Toet A, Camps G, Brouwer AM. Technology to Automatically Record Eating Behavior in Real Life: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:7757. [PMID: 37765812 PMCID: PMC10534458 DOI: 10.3390/s23187757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 09/04/2023] [Accepted: 09/05/2023] [Indexed: 09/29/2023]
Abstract
To monitor adherence to diets and to design and evaluate nutritional interventions, it is essential to obtain objective knowledge about eating behavior. In most research, measures of eating behavior are based on self-reporting, such as 24-h recalls, food records (food diaries) and food frequency questionnaires. Self-reporting is prone to inaccuracies due to inaccurate and subjective recall and other biases. Recording behavior using nonobtrusive technology in daily life would overcome this. Here, we provide an up-to-date systematic overview encompassing all (close-to) publicly or commercially available technologies to automatically record eating behavior in real-life settings. A total of 1328 studies were screened and, after applying defined inclusion and exclusion criteria, 122 studies were included for in-depth evaluation. Technologies in these studies were categorized by what type of eating behavior they measure and which type of sensor technology they use. In general, we found that relatively simple sensors are often used. Depending on the purpose, these are mainly motion sensors, microphones, weight sensors and photo cameras. While several of these technologies are commercially available, there is still a lack of publicly available algorithms that are needed to process and interpret the resulting data. We argue that future work should focus on developing robust algorithms and validating these technologies in real-life settings. Combining technologies (e.g., prompting individuals for self-reports at sensed, opportune moments) is a promising route toward ecologically valid studies of eating behavior.
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Affiliation(s)
- Haruka Hiraguchi
- TNO Human Factors, Netherlands Organization for Applied Scientific Research, Kampweg 55, 3769 DE Soesterberg, The Netherlands (A.-M.B.)
- Kikkoman Europe R&D Laboratory B.V., Nieuwe Kanaal 7G, 6709 PA Wageningen, The Netherlands
| | - Paola Perone
- TNO Human Factors, Netherlands Organization for Applied Scientific Research, Kampweg 55, 3769 DE Soesterberg, The Netherlands (A.-M.B.)
| | - Alexander Toet
- TNO Human Factors, Netherlands Organization for Applied Scientific Research, Kampweg 55, 3769 DE Soesterberg, The Netherlands (A.-M.B.)
| | - Guido Camps
- Division of Human Nutrition and Health, Wageningen University & Research, Stippeneng 4, 6708 WE Wageningen, The Netherlands
- OnePlanet Research Center, Plus Ultra II, Bronland 10, 6708 WE Wageningen, The Netherlands
| | - Anne-Marie Brouwer
- TNO Human Factors, Netherlands Organization for Applied Scientific Research, Kampweg 55, 3769 DE Soesterberg, The Netherlands (A.-M.B.)
- Department of Artificial Intelligence, Radboud University, Thomas van Aquinostraat 4, 6525 GD Nijmegen, The Netherlands
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Allman-Farinelli M. Digital dietetics and the era of artificial intelligence. Nutr Diet 2023; 80:334-337. [PMID: 37670607 DOI: 10.1111/1747-0080.12841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/04/2023] [Indexed: 09/07/2023]
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Allman-Farinelli M, Boljevac B, Vuong T, Hekler E. Nutrition-Related N-of-1 Studies Warrant Further Research to Provide Evidence for Dietitians to Practice Personalized (Precision) Medical Nutrition Therapy: A Systematic Review. Nutrients 2023; 15:nu15071756. [PMID: 37049595 PMCID: PMC10097352 DOI: 10.3390/nu15071756] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 03/28/2023] [Accepted: 03/31/2023] [Indexed: 04/14/2023] Open
Abstract
N-of-1 trials provide a higher level of evidence than randomized controlled trials for determining which treatment works best for an individual, and the design readily accommodates testing of personalized nutrition. The aim of this systematic review was to synthesize nutrition-related studies using an N-of-1 design. The inclusion criterion was adult participants; the intervention/exposure was any nutrient, food, beverage, or dietary pattern; the comparators were baseline values, a control condition untreated or placebo, or an alternate treatment, alongside any outcomes such as changes in diet, body weight, biochemical outcomes, symptoms, quality of life, or a disease outcome resulting from differences in nutritional conditions. The information sources used were Medline, Embase, Scopus, Cochrane Central, and PsychInfo. The quality of study reporting was assessed using the Consort Extension for N-of-1 trials (CENT) statement or the STrengthening Reporting of OBservational Studies in Epidemiology (STROBE) guidelines, as appropriate. From 211 articles screened, a total of 7 studies were included and were conducted in 5 countries with a total of 83 participants. The conditions studied included prediabetes, diabetes, irritable bowel syndrome, weight management, and investigation of the effect of diet in healthy people. The quality of reporting was mostly adequate, and dietary assessment quality varied from poor to good. The evidence base is small, but served to illustrate the main characteristics of N-of-1 study designs and considerations for moving research forward in the era of personalized medical nutrition therapy.
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Affiliation(s)
- Margaret Allman-Farinelli
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
- The Charles Perkins Centre, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Brianna Boljevac
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Tiffany Vuong
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Eric Hekler
- The Design Lab, University of California San Diego, San Diego, CA 92093, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA 92093, USA
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Wang L, Chan V, Allman-Farinelli M, Davies A, Wellard-Cole L, Rangan A. Wearable Cameras Reveal Large Intra-Individual Variability in Timing of Eating among Young Adults. Nutrients 2022; 14:nu14204349. [PMID: 36297030 PMCID: PMC9611808 DOI: 10.3390/nu14204349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 10/13/2022] [Accepted: 10/16/2022] [Indexed: 11/16/2022] Open
Abstract
Studies have shown that young adults follow less structured eating patterns compared with older cohorts. This may have implications for dietary assessment methods which rely on memory and structured meal patterns. Our aim was to describe the intra-individual variation of eating times in young adults aged 18−30 years. Participants (n = 41) wore an Autographer camera that captured first-person perspective images every 30 s for three consecutive days. All images were timestamped and those showing food consumption were used to extract data such as the timing of the first and last eating occasions (EOs), number of EOs per day, and length of eating window. Intra-individual variability was calculated from these data using composite phase deviation (CPD) and coefficient of variation (CV). The number of individuals with high or very high variability was 28 and 18 for timing of first and last EOs, respectively (CPD > 1.70), and 27 and 17 for number of EOs and eating window, respectively (CV > 20%). In this sample of young adults, the lack of regularity in eating patterns should be considered when selecting a dietary assessment method.
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Affiliation(s)
- Leanne Wang
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
| | - Virginia Chan
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
| | - Margaret Allman-Farinelli
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
| | - Alyse Davies
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
| | - Lyndal Wellard-Cole
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia
- Cancer Prevention and Advocacy Division, Cancer Council NSW, Sydney, NSW 2011, Australia
| | - Anna Rangan
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
- Correspondence:
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