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1
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Li C, Hu Y. In vitro and animal models to predict the glycemic index value of carbohydrate-containing foods. Trends Food Sci Technol 2022. [DOI: 10.1016/j.tifs.2021.12.031] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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2
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Aguiar LM, Cazarin CBB. In vitro and in vivo methods to predict carbohydrate bioaccessibility. Curr Opin Food Sci 2021. [DOI: 10.1016/j.cofs.2021.05.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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Riccardi G, Giosuè A, Calabrese I, Vaccar O. Authors Reply to: Limitations of the Glycemic Index and the Need for Nuance When Determining Carbohydrate Quality, by Mitch Kanter, Siddhartha Angadi, Julie Miller Jones, Katherine A. Beals. Cardiovasc Res 2021; 118:e40-e41. [PMID: 34613364 DOI: 10.1093/cvr/cvab313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Gabriele Riccardi
- University of Naples Federico II, Universita degli Studi di Napoli Federico II, Napoli, Italy
| | - Annalisa Giosuè
- University of Naples Federico II, Universita degli Studi di Napoli Federico II, Napoli, Italy
| | - Ilaria Calabrese
- University of Naples Federico II, Universita degli Studi di Napoli Federico II, Napoli, Italy
| | - Olga Vaccar
- University of Naples Federico II, Universita degli Studi di Napoli Federico II, Napoli, Italy
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Barclay AW, Augustin LSA, Brighenti F, Delport E, Henry CJ, Sievenpiper JL, Usic K, Yuexin Y, Zurbau A, Wolever TM, Astrup A, Bulló M, Buyken A, Ceriello A, Ellis PR, Vanginkel MA, Kendall CW, La Vecchia C, Livesey G, Poli A, Riccardi G, Salas-Salvadó J, Trichopoulou A, Bhaskaran K, Jenkins DJ, Willett WC, Brand-Miller JC. Dietary Glycaemic Index Labelling: A Global Perspective. Nutrients 2021; 13:3244. [PMID: 34579120 PMCID: PMC8466312 DOI: 10.3390/nu13093244] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 09/07/2021] [Accepted: 09/14/2021] [Indexed: 11/28/2022] Open
Abstract
The glycaemic index (GI) is a food metric that ranks the acute impact of available (digestible) carbohydrates on blood glucose. At present, few countries regulate the inclusion of GI on food labels even though the information may assist consumers to manage blood glucose levels. Australia and New Zealand regulate GI claims as nutrition content claims and also recognize the GI Foundation's certified Low GI trademark as an endorsement. The GI Foundation of South Africa endorses foods with low, medium and high GI symbols. In Asia, Singapore's Healthier Choice Symbol has specific provisions for low GI claims. Low GI claims are also permitted on food labels in India. In China, there are no national regulations specific to GI; however, voluntary claims are permitted. In the USA, GI claims are not specifically regulated but are permitted, as they are deemed to fall under general food-labelling provisions. In Canada and the European Union, GI claims are not legal under current food law. Inconsistences in food regulation around the world undermine consumer and health professional confidence and call for harmonization. Global provisions for GI claims/endorsements in food standard codes would be in the best interests of people with diabetes and those at risk.
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Affiliation(s)
| | | | - Furio Brighenti
- Human Nutrition Unit, Food & Drug Department, Università Degli Studi di Parma, 43121 Parma, Italy;
| | - Elizabeth Delport
- Glycemic Index Foundation of South Africa or Glycemic Index Foundation SA, Nelspruit 1201, South Africa;
| | - C. Jeyakumar Henry
- Singapore Institute of Food and Biotechnology Innovation, Singapore 117599, Singapore;
| | - John L. Sievenpiper
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada; (J.L.S.); (A.Z.); (C.W.C.K.); (D.J.A.J.)
- Clinical Nutrition and Risk Factor Modification Centre, St. Michael’s Hospital, Toronto, ON M5B 1W8, Canada
- Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, St. Michael’s Hospital, Toronto, ON M5B 1W8, Canada
- Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON M5B 1W8, Canada
| | - Kathy Usic
- Glycemic Index Foundation, Glebe 2037, Australia;
| | - Yang Yuexin
- National Institute of Nutrition for Health, Beijing 100051, China;
| | - Andreea Zurbau
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada; (J.L.S.); (A.Z.); (C.W.C.K.); (D.J.A.J.)
- INQUIS Clinical Research Ltd., Toronto, ON M5C 2N8, Canada;
| | | | - Arne Astrup
- Healthy Weight Center, Novo Nordisk Foundation, Tuborg Havnevej 19, DK 2900 Hellerup, Denmark;
| | - Mònica Bulló
- Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, 43003 Reus, Spain; (M.B.); (J.S.-S.)
- Institut d’Investigació Pere Virgili (IISPV), Hospital Universitari de Sant Joan de Reus, 43204 Reus, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain
| | - Anette Buyken
- Institute of Nutrition, Consumption and Health, Paderborn University, 33098 Paderborn, Germany;
| | | | - Peter R. Ellis
- Biopolymers Group, Departments of Biochemistry and Nutritional Sciences, Faculty of Life Sciences & Medicine, King’s College London, London SE1 9NH, UK;
| | - Marie-Ann Vanginkel
- School of Sport and Health Sciences, University of Brighton, Brighton BN2 4AT, UK;
| | - Cyril W.C. Kendall
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada; (J.L.S.); (A.Z.); (C.W.C.K.); (D.J.A.J.)
| | - Carlo La Vecchia
- Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, 20122 Milano, Italy;
| | | | - Andrea Poli
- NFI—Nutrition Foundation of Italy, 20124 Milan, Italy;
| | - Gabriele Riccardi
- Department of Clinical Medicine and Surgery, Federico II University, 80147 Naples, Italy;
| | - Jordi Salas-Salvadó
- Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, 43003 Reus, Spain; (M.B.); (J.S.-S.)
- Institut d’Investigació Pere Virgili (IISPV), Hospital Universitari de Sant Joan de Reus, 43204 Reus, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain
| | | | - Kalpana Bhaskaran
- Glycemic Index Research Unit, Centre for Applied Nutrition Services, Temasek Polytechnic, Singapore 52975, Singapore;
| | - David J.A. Jenkins
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada; (J.L.S.); (A.Z.); (C.W.C.K.); (D.J.A.J.)
- Clinical Nutrition and Risk Factor Modification Centre, St. Michael’s Hospital, Toronto, ON M5B 1W8, Canada
- Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, St. Michael’s Hospital, Toronto, ON M5B 1W8, Canada
- Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON M5B 1W8, Canada
| | - Walter C. Willett
- Departments of Nutrition and Epidemiology, Harvard T. H. Chan School of Public Health and Harvard Medical School, Harvard University, Boston, MA 02115, USA;
| | - Jennie C. Brand-Miller
- School of Life and Environmental Sciences and Charles Perkins Centre, University of Sydney, Camperdown, Sydney 2006, Australia;
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Balanced carbohydrate ratios are associated with improved diet quality in Australia: A nationally representative cross-sectional study. PLoS One 2021; 16:e0253582. [PMID: 34242252 PMCID: PMC8270120 DOI: 10.1371/journal.pone.0253582] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 06/09/2021] [Indexed: 12/30/2022] Open
Abstract
Background Carbohydrate quality influences major health outcomes; however, the best criteria to assess carbohydrate quality remain unknown. Objective The objectives were to: i) evaluate whether a diet that meets a carbohydrate ratio (simple, modified or dual ratio) is associated with higher nutrient intakes and diet quality, and ii) model the impact of substituting carbohydrate foods that meet the proposed ratios in place of foods that do not, on nutrient intakes. Design A secondary analysis of cross-sectional data from the 2011–12 Australian National Nutrition and Physical Activity Survey. Participants/Setting National data from participants aged 2 years and older (n = 12,153). Main outcome measures Ratios were defined as (i) simple ratio, 10:1 (10g carbohydrate:≥1g dietary fiber); (ii) modified ratio, 10:1:2 (10g carbohydrate:≥1g dietary fiber:≤2g free sugars); and (iii) dual ratio, 10:1 & 1:2 (10g carbohydrate:≥1g dietary fiber & ≤2g free sugars per 1g dietary fiber). Ratios were compared to nutrient intakes obtained via automated multiple-pass 24-hour dietary recall and diet quality calculated using the Australian Healthy Eating Index. Statistical analyses performed Substitution dietary modelling was performed. Data were analyzed using paired and independent sample t-tests. Results Ratio adherence was highest for simple (50.2% adults; 28.6% children), followed by dual (40.6% adults; 21.7% children), then modified (32.7% adults; 18.6% children) ratios. Participants who met any ratio reported higher nutrient intake and diet quality compared to those who failed to meet the respective ratio (P < .001 for all), with the greatest nutrient intakes found for those who met modified or dual ratios. Dietary modelling improved nutrient intakes for all ratios, with the greatest improvement found for the dual ratio. Conclusions All carbohydrate ratios were associated with higher diet quality, with a free sugars constraint in the dual ratio providing the greatest improvements.
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Flavel M, Jois M, Kitchen B. Potential contributions of the methodology to the variability of glycaemic index of foods. World J Diabetes 2021; 12:108-123. [PMID: 33594331 PMCID: PMC7839170 DOI: 10.4239/wjd.v12.i2.108] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 12/03/2020] [Accepted: 12/23/2020] [Indexed: 02/06/2023] Open
Abstract
Glycaemic index (GI) testing provides a useful point of comparison between carbohydrate sources. For this comparison to be meaningful, the methods used to determine GI values need to be rigorous and consistent between testing events. This requirement has led to increasing standardization of the GI methodology, with an international standard developed in joint consultation with FAO/WHO (ISO 26642:2010) currently the most up to date document. The purpose of this review is to compare the international standard to methods of published studies claiming to have performed a GI test. This analysis revealed that the international standard permits a wide range of choices for researchers when designing a GI testing plan, rather than a single standardized protocol. It has also been revealed that the literature contains significant variation, both between studies and from the international standard for critical aspects of GI testing methodology. The primary areas of variation include; what glucose specification is used, which reference food is used, how much reference food is given, what drink is given during testing, the blood sampling site chosen and what assay and equipment is used to measure blood glucose concentration. For each of these aspects we have explored some of the methodological and physiological implications of these variations. These insights suggest that whilst the international standard has assisted with framing the general parameters of GI testing, further stan-dardization to testing procedures is still required to ensure the continued relevance of the GI to clinical nutrition.
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Affiliation(s)
- Matthew Flavel
- Bioactive Division, The Product Makers, Keysborough 3173, Victoria, Australia
- School of Life Sciences, La Trobe University, Bundoora 3086, Australia
| | - Markandeya Jois
- School of Life Sciences, La Trobe University, Bundoora 3086, Australia
| | - Barry Kitchen
- Bioactive Division, The Product Makers, Keysborough 3173, Victoria, Australia
- School of Life Sciences, La Trobe University, Bundoora 3086, Australia
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Wong THT, Wan JMF, Louie JCY. Flash Glucose Monitoring Can Accurately Reflect Postprandial Glucose Changes in Healthy Adults in Nutrition Studies. J Am Coll Nutr 2020; 40:26-32. [PMID: 32213009 DOI: 10.1080/07315724.2020.1734990] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
OBJECTIVE This study investigated the accuracy of a flash glucose monitoring system (FGMS) in a postprandial setting. METHODS Ten fasted adults without diabetes wore the FGMS sensors then consumed a standard breakfast. Their glucose levels were subsequently recorded for 2 hours, both by the FGMS and by measuring capillary glucose levels using the glucose oxidase method. The accuracy of the FGMS data was assessed using the accuracy limits stated in ISO 15197:2013. RESULTS FGMS measurements were mostly lower than glucose oxidase measurements (mean absolute relative difference ± SD: 25.4 ± 17.0%, p < 0.001). However, the maximum difference from baseline captured by the two methods was not significantly different (mean ± SD, glucose oxidase: 58.5 ± 18.9 mg/dl; FGMS, 54.4 ± 28.9 mg/dl, p = 0.366). CONCLUSIONS FGMS could track the incremental glycaemic excursions after meals in adults without diabetes, yet further studies with greater sample sizes are needed to confirm this finding.
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Affiliation(s)
- Tommy H T Wong
- School of Biological Sciences, University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region
| | - Jennifer M F Wan
- School of Biological Sciences, University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region
| | - Jimmy Chun Yu Louie
- School of Biological Sciences, University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region
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Dall'Asta M, Del Rio D, Tappy L, Potì F, Agostoni C, Brighenti F. Critical and emerging topics in dietary carbohydrates and health. Int J Food Sci Nutr 2019; 71:286-295. [PMID: 32279625 DOI: 10.1080/09637486.2019.1661979] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Multiple factors may affect the metabolic fate of carbohydrates. Today, well-standardised and accepted methods may allow for the definitions of the changes in the glucose and insulin curves following the ingestion of either carbohydrate-based and other foods. More debate is still raised on the clinical meaning of these classifications when used at a population level, while emphasis is raised on the approach to carbohydrate metabolism on an individual basis. Within these ranges of applications, other compounds, such as plant polyphenols, may favourably add synergic effects through the modulation of carbohydrate digestion and glucose metabolic steps, resulting in lowering postprandial glucose and insulin levels. Finally, a growing knowledge suggests that the balance of dietary fructose and individual physical activity represent the key point to address the compound towards either positive, energy sparing effects, or a degenerative metabolic burden. The carbohydrate quality within a whole dietary and lifestyle pattern may therefore challenge the individual balance towards health or disease.
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Affiliation(s)
| | - Daniele Del Rio
- Laboratory of Phytochemicals in Physiology, Department of Veterinary Science, University of Parma, Parma, Italy
| | - Luc Tappy
- Department of Physiology, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Francesco Potì
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Carlo Agostoni
- Pediatric Intermediate Care Unit, Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Milan, Italy.,Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Furio Brighenti
- Department of Food and Drug, University of Parma, Parma, Italy
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9
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Livesey G, Taylor R, Livesey HF, Buyken AE, Jenkins DJA, Augustin LSA, Sievenpiper JL, Barclay AW, Liu S, Wolever TMS, Willett WC, Brighenti F, Salas-Salvadó J, Björck I, Rizkalla SW, Riccardi G, Vecchia CL, Ceriello A, Trichopoulou A, Poli A, Astrup A, Kendall CWC, Ha MA, Baer-Sinnott S, Brand-Miller JC. Dietary Glycemic Index and Load and the Risk of Type 2 Diabetes: A Systematic Review and Updated Meta-Analyses of Prospective Cohort Studies. Nutrients 2019; 11:1280. [PMID: 31195724 PMCID: PMC6627334 DOI: 10.3390/nu11061280] [Citation(s) in RCA: 128] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 05/28/2019] [Accepted: 05/30/2019] [Indexed: 02/06/2023] Open
Abstract
Published meta-analyses indicate significant but inconsistent incident type-2 diabetes(T2D)-dietary glycemic index (GI) and glycemic load (GL) risk ratios or risk relations (RR). It is nowover a decade ago that a published meta-analysis used a predefined standard to identify validstudies. Considering valid studies only, and using random effects dose-response meta-analysis(DRM) while withdrawing spurious results (p < 0.05), we ascertained whether these relationswould support nutrition guidance, specifically for an RR > 1.20 with a lower 95% confidence limit>1.10 across typical intakes (approximately 10th to 90th percentiles of population intakes). Thecombined T2D-GI RR was 1.27 (1.15-1.40) (p < 0.001, n = 10 studies) per 10 units GI, while that forthe T2D-GL RR was 1.26 (1.15-1.37) (p < 0.001, n = 15) per 80 g/d GL in a 2000 kcal (8400 kJ) diet.The corresponding global DRM using restricted cubic splines were 1.87 (1.56-2.25) (p < 0.001, n =10) and 1.89 (1.66-2.16) (p < 0.001, n = 15) from 47.6 to 76.1 units GI and 73 to 257 g/d GL in a 2000kcal diet, respectively. In conclusion, among adults initially in good health, diets higher in GI or GLwere robustly associated with incident T2D. Together with mechanistic and other data, thissupports that consideration should be given to these dietary risk factors in nutrition advice.Concerning the public health relevance at the global level, our evidence indicates that GI and GLare substantial food markers predicting the development of T2D worldwide, for persons ofEuropean ancestry and of East Asian ancestry.
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Affiliation(s)
- Geoffrey Livesey
- Independent Nutrition Logic Ltd, 21 Bellrope Lane, Wymondham NR180QX, UK.
| | - Richard Taylor
- Independent Nutrition Logic Ltd, 21 Bellrope Lane, Wymondham NR180QX, UK.
| | - Helen F Livesey
- Independent Nutrition Logic Ltd, 21 Bellrope Lane, Wymondham NR180QX, UK.
| | - Anette E Buyken
- Institute of Nutrition, Consumption and Health, Faculty of Natural Sciences, Paderborn University,33098 Paderborn, Germany.
| | - David J A Jenkins
- Department of Nutritional Science and Medicine, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.
- Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Toronto, ON M5C 2T2, Canada.
- Division of Endocrinology & Metabolism, Department of Medicine, St. Michael's Hospital, Toronto, ON M5C 2T2, Canada.
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON M5C 2T2, Canada.
| | - Livia S A Augustin
- Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Toronto, ON M5C 2T2, Canada.
- Epidemiology, Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale", 80131 Napoli, Italy.
| | - John L Sievenpiper
- Department of Nutritional Science and Medicine, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.
- Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Toronto, ON M5C 2T2, Canada.
- Division of Endocrinology & Metabolism, Department of Medicine, St. Michael's Hospital, Toronto, ON M5C 2T2, Canada.
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON M5C 2T2, Canada.
| | - Alan W Barclay
- Glycemic Index Foundation, 26 Arundel St, Glebe, NSW 2037 Sydney, Australia.
| | - Simin Liu
- Department of Epidemiology and Medicine, Brown University, Providence, RI 02912, USA.
| | - Thomas M S Wolever
- Department of Nutritional Science and Medicine, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.
- Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Toronto, ON M5C 2T2, Canada.
| | - Walter C Willett
- Departments of Nutrition and Epidemiology, Harvard T. H. Chan School of Public Health and Harvard Medical School, Boston, MA 02115, USA.
| | - Furio Brighenti
- Department of Food and Drug, University of Parma, 43120 Parma, Italy.
| | - Jordi Salas-Salvadó
- Human Nutrition Unit, Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili (IISPV), Rovira i Virgili University, 43201 Reus, Spain.
- Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 27400 Madrid, Spain.
| | - Inger Björck
- Retired from Food for Health Science Centre, Antidiabetic Food Centre, Lund University, S-221 00 Lund, Sweden.
| | - Salwa W Rizkalla
- Institute of Cardiometabolism and Nutrition, ICAN, Pitié Salpêtrière Hospital, F75013 Paris, France.
| | - Gabriele Riccardi
- Department of Clinical Medicine and Surgery, Federico II University, 80147 Naples, Italy.
| | - Carlo La Vecchia
- Department of Clinical Sciences and Community Health, Università degli Studi di Milano, 201330 Milan, Italy.
| | - Antonio Ceriello
- IRCCS MultiMedica, Diabetes Department, 20099 Sesto San Giovanni, Milan, Italy.
| | | | - Andrea Poli
- Nutrition Foundation of Italy, Viale Tunisia 38, I-20124 Milan, Italy.
| | - Arne Astrup
- Department of Nutrition, Exercise and Sports (NEXS) Faculty of Science, University of Copenhagen, 2200 Copenhagen, Denmark.
| | - Cyril W C Kendall
- Department of Nutritional Science and Medicine, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.
- Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Toronto, ON M5C 2T2, Canada.
- College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK S7N 5B5, Canada.
| | - Marie-Ann Ha
- Spinney Nutrition, Shirwell, Barnstaple, Devon EX31 4JR, UK.
| | | | - Jennie C Brand-Miller
- Charles Perkins Centre and School of Life and Environmental Sciences, University of Sydney, Sydney NSW 2006, Australia.
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Popp CJ, St-Jules DE, Hu L, Ganguzza L, Illiano P, Curran M, Li H, Schoenthaler A, Bergman M, Schmidt AM, Segal E, Godneva A, Sevick MA. The rationale and design of the personal diet study, a randomized clinical trial evaluating a personalized approach to weight loss in individuals with pre-diabetes and early-stage type 2 diabetes. Contemp Clin Trials 2019; 79:80-88. [PMID: 30844471 DOI: 10.1016/j.cct.2019.03.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Revised: 02/20/2019] [Accepted: 03/01/2019] [Indexed: 12/31/2022]
Abstract
Weight loss reduces the risk of type 2 diabetes mellitus (T2D) in overweight and obese individuals. Although the physiological response to food varies among individuals, standard dietary interventions use a "one-size-fits-all" approach. The Personal Diet Study aims to evaluate two dietary interventions targeting weight loss in people with prediabetes and T2D: (1) a low-fat diet, and (2) a personalized diet using a machine-learning algorithm that predicts glycemic response to meals. Changes in body weight, body composition, and resting energy expenditure will be compared over a 6-month intervention period and a subsequent 6-month observation period intended to assess maintenance effects. The behavioral intervention is delivered via mobile health technology using the Social Cognitive Theory. Here, we describe the design, interventions, and methods used.
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Affiliation(s)
- Collin J Popp
- Department of Population Health, Center for Healthful Behavior Change, New York University School of Medicine, New York, NY, USA
| | - David E St-Jules
- Department of Population Health, Center for Healthful Behavior Change, New York University School of Medicine, New York, NY, USA
| | - Lu Hu
- Department of Population Health, Center for Healthful Behavior Change, New York University School of Medicine, New York, NY, USA
| | - Lisa Ganguzza
- Department of Population Health, Center for Healthful Behavior Change, New York University School of Medicine, New York, NY, USA
| | - Paige Illiano
- Department of Population Health, Center for Healthful Behavior Change, New York University School of Medicine, New York, NY, USA
| | - Margaret Curran
- Department of Population Health, Center for Healthful Behavior Change, New York University School of Medicine, New York, NY, USA
| | - Huilin Li
- Department of Population Health, Division of Biostatistics, New York University School of Medicine, New York, NY, USA
| | - Antoinette Schoenthaler
- Department of Population Health, Center for Healthful Behavior Change, New York University School of Medicine, New York, NY, USA
| | - Michael Bergman
- Department of Population Health, Center for Healthful Behavior Change, New York University School of Medicine, New York, NY, USA; Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, New York University School of Medicine, New York, NY, USA
| | - Ann Marie Schmidt
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, New York University School of Medicine, New York, NY, USA
| | - Eran Segal
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
| | - Anastasia Godneva
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
| | - Mary Ann Sevick
- Department of Population Health, Center for Healthful Behavior Change, New York University School of Medicine, New York, NY, USA; Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, New York University School of Medicine, New York, NY, USA.
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11
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Affiliation(s)
- Huicui Meng
- From the Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA
| | - Nirupa R Matthan
- From the Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA
| | - Alice H Lichtenstein
- From the Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA
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12
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Affiliation(s)
- Huicui Meng
- From the Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA (HM; NRM; and AHL, e-mail: )
| | - Nirupa R Matthan
- From the Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA (HM; NRM; and AHL, e-mail: )
| | - Alice H Lichtenstein
- From the Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA (HM; NRM; and AHL, e-mail: )
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Cheng G, Xue H, Luo J, Jia H, Zhang L, Dai J, Buyken AE. Relevance of the dietary glycemic index, glycemic load and genetic predisposition for the glucose homeostasis of Chinese adults without diabetes. Sci Rep 2017; 7:400. [PMID: 28341844 PMCID: PMC5428428 DOI: 10.1038/s41598-017-00453-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Accepted: 02/27/2017] [Indexed: 01/19/2023] Open
Abstract
Type 2 diabetes (T2DM) and pre-diabetes have become a major public health problem in China. We examined whether a higher dietary glycemic index (GI) or glycemic load (GL) was associated with a less favorable glucose homeostasis among Chinese adults and whether these associations were modified by their genetic predisposition or whether combined effects exist with their cereal fiber intake. Multivariable regression analyses were performed in 3918 adults aged 23-69 years for whom three 24-hour dietary recalls and information on glucose homeostasis, genetic background and potential confounders was available. Adults in the highest GI (GL) tertile had an approximately 9% (5%) higher fasting plasma glucose, 11% (3%) higher glycated haemoglobin, 12% (7%) higher insulin level, and 28% (22%) higher hepatic insulin resistance compared to those in the lowest tertile (adjusted pfor-trend ≤ 0.04). Moreover, a higher dietary GI or GL was associated with higher odds of pre-diabetes (pfor-trend = 0.03). These associations were more pronounced among persons with a high T2DM genetic risk score (pfor-interaction ≤ 0.06) or a low cereal fiber intake (pfor-interaction ≤ 0.05). In conclusion, our study indicates that the dietary GI or GL is of relevance for glucose homeostasis among Chinese adults, particularly among individuals genetically predisposed to T2DM.
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Affiliation(s)
- Guo Cheng
- West China School of Public Health and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, Chengdu, P.R. China.
| | - Hongmei Xue
- West China School of Public Health, Sichuan University, Chengdu, P.R. China
| | - Jiao Luo
- West China School of Public Health, Sichuan University, Chengdu, P.R. China
| | - Hong Jia
- Department of Epidemiology and Biostatistics, School of Public Health, Southwest Medical University, Luzhou, China
| | - Lishi Zhang
- West China School of Public Health, Sichuan University, Chengdu, P.R. China
| | - Junbiao Dai
- MOE Key Laboratory of Bioinformatics and Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China
| | - Anette E Buyken
- IEL-Nutritional Epidemiology, University of Bonn, DONALD Study, Dortmund, Germany
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