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      Effect of a Personalized Diet to Reduce Postprandial Glycemic Response vs a Low-fat Diet on Weight Loss in Adults With Abnormal Glucose Metabolism and Obesity : A Randomized Clinical Trial

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          Key Points

          Question

          What is the effect of a precision nutrition intervention aimed to reduce the postprandial glycemic response to foods on weight loss in adults with abnormal glucose metabolism and obesity compared with a low-fat diet?

          Findings

          In this randomized clinical trial that included 204 adults who received web-based group behavioral counseling, there was no significant difference in percentage of weight loss at 6 months between participants who followed a personalized diet compared with those who followed a standardized low-fat diet.

          Meaning

          This study found that a precision nutrition intervention targeting a reduction in postprandial glycemic response did not result in greater weight loss compared with a low-fat diet.

          Abstract

          This randomized clinical trial compares personalized vs standardized caloric-restricted weight loss interventions in terms of percentage of weight loss among adults with high postprandial glycemic responses and obesity.

          Abstract

          Importance

          Interindividual variability in postprandial glycemic response (PPGR) to the same foods may explain why low glycemic index or load and low-carbohydrate diet interventions have mixed weight loss outcomes. A precision nutrition approach that estimates personalized PPGR to specific foods may be more efficacious for weight loss.

          Objective

          To compare a standardized low-fat vs a personalized diet regarding percentage of weight loss in adults with abnormal glucose metabolism and obesity.

          Design, Setting, and Participants

          The Personal Diet Study was a single-center, population-based, 6-month randomized clinical trial with measurements at baseline (0 months) and 3 and 6 months conducted from February 12, 2018, to October 28, 2021. A total of 269 adults aged 18 to 80 years with a body mass index (calculated as weight in kilograms divided by height in meters squared) ranging from 27 to 50 and a hemoglobin A 1c level ranging from 5.7% to 8.0% were recruited. Individuals were excluded if receiving medications other than metformin or with evidence of kidney disease, assessed as an estimated glomerular filtration rate of less than 60 mL/min/1.73 m 2 using the Chronic Kidney Disease Epidemiology Collaboration equation, to avoid recruiting patients with advanced type 2 diabetes.

          Interventions

          Participants were randomized to either a low-fat diet (<25% of energy intake; standardized group) or a personalized diet that estimates PPGR to foods using a machine learning algorithm (personalized group). Participants in both groups received a total of 14 behavioral counseling sessions and self-monitored dietary intake. In addition, the participants in the personalized group received color-coded meal scores on estimated PPGR delivered via a mobile app.

          Main Outcomes and Measures

          The primary outcome was the percentage of weight loss from baseline to 6 months. Secondary outcomes included changes in body composition (fat mass, fat-free mass, and percentage of body weight), resting energy expenditure, and adaptive thermogenesis. Data were collected at baseline and 3 and 6 months. Analysis was based on intention to treat using linear mixed modeling.

          Results

          Of a total of 204 adults randomized, 199 (102 in the personalized group vs 97 in the standardized group) contributed data (mean [SD] age, 58 [11] years; 133 women [66.8%]; mean [SD] body mass index, 33.9 [4.8]). Weight change at 6 months was −4.31% (95% CI, −5.37% to −3.24%) for the standardized group and −3.26% (95% CI, −4.25% to −2.26%) for the personalized group, which was not significantly different (difference between groups, 1.05% [95% CI, −0.40% to 2.50%]; P = .16). There were no between-group differences in body composition and adaptive thermogenesis; however, the change in resting energy expenditure was significantly greater in the standardized group from 0 to 6 months (difference between groups, 92.3 [95% CI, 0.9-183.8] kcal/d; P = .05).

          Conclusions and Relevance

          A personalized diet targeting a reduction in PPGR did not result in greater weight loss compared with a low-fat diet at 6 months. Future studies should assess methods of increasing dietary self-monitoring adherence and intervention exposure.

          Trial Registration

          ClinicalTrials.gov Identifier: NCT03336411

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          Most cited references32

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          Greedy function approximation: A gradient boosting machine.

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            • Record: found
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            • Article: not found

            Personalized Nutrition by Prediction of Glycemic Responses.

            Elevated postprandial blood glucose levels constitute a global epidemic and a major risk factor for prediabetes and type II diabetes, but existing dietary methods for controlling them have limited efficacy. Here, we continuously monitored week-long glucose levels in an 800-person cohort, measured responses to 46,898 meals, and found high variability in the response to identical meals, suggesting that universal dietary recommendations may have limited utility. We devised a machine-learning algorithm that integrates blood parameters, dietary habits, anthropometrics, physical activity, and gut microbiota measured in this cohort and showed that it accurately predicts personalized postprandial glycemic response to real-life meals. We validated these predictions in an independent 100-person cohort. Finally, a blinded randomized controlled dietary intervention based on this algorithm resulted in significantly lower postprandial responses and consistent alterations to gut microbiota configuration. Together, our results suggest that personalized diets may successfully modify elevated postprandial blood glucose and its metabolic consequences. VIDEO ABSTRACT.
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              The Automated Self-Administered 24-hour dietary recall (ASA24): a resource for researchers, clinicians, and educators from the National Cancer Institute.

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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                28 September 2022
                September 2022
                28 September 2022
                : 5
                : 9
                : e2233760
                Affiliations
                [1 ]Institute for Excellence in Health Equity, Center for Healthful Behavior Change, Department of Population Health, NYU Langone Health, New York, New York
                [2 ]Division of Biostatistics, Department of Population Health, NYU Langone Health, New York, New York
                [3 ]Department of Nutrition, University of Nevada, Reno
                [4 ]Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
                [5 ]Department of Mathematical Sciences, United States Military Academy, West Point, New York
                [6 ]Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, NYU Langone Health, New York, New York
                [7 ]Diabetes Research Program, Department of Medicine, NYU Langone Health, New York, New York
                Author notes
                Article Information
                Accepted for Publication: August 3, 2022.
                Published: September 28, 2022. doi:10.1001/jamanetworkopen.2022.33760
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Popp CJ et al. JAMA Network Open.
                Corresponding Author: Collin J. Popp, PhD, MS, RDN, Institute for Excellence in Health Equity, Center for Healthful Behavior Change, Department of Population Health, NYU Langone Health, 180 Madison Ave, Seventh Floor, Cubicle 7-25, New York, NY 10016 ( collin.popp@ 123456nyulangone.org ).
                Author Contributions: Drs Popp and Sevick had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Popp, Hu, Curran, St-Jules, Segal, Schmidt, Sevick.
                Acquisition, analysis, or interpretation of data: Popp, Hu, Kharmats, Curran, Berube, Wang, Pompeii, Illiano, St-Jules, Mottern, Li, Williams, Schoenthaler, Segal, Godneva, Thomas, Bergman, Sevick.
                Drafting of the manuscript: Popp, Hu, Kharmats, Curran, Pompeii, Illiano, Li, Schoenthaler, Segal, Sevick.
                Critical revision of the manuscript for important intellectual content: Popp, Hu, Kharmats, Curran, Berube, Wang, St-Jules, Mottern, Li, Williams, Segal, Godneva, Thomas, Bergman, Schmidt, Sevick.
                Statistical analysis: Kharmats, Berube, Wang, Li, Segal, Godneva.
                Obtained funding: St-Jules, Segal, Schmidt, Sevick.
                Administrative, technical, or material support: Popp, Hu, Mottern, Williams, Segal, Godneva, Thomas, Bergman, Schmidt.
                Supervision: Popp, Hu, Schoenthaler, Segal, Sevick.
                Conflict of Interest Disclosures: Dr Popp reported serving as a sports nutrition consultant for Renaissance Periodization, LLC, outside the submitted work. Dr Segal reported serving as a consultant for DayTwo. No other disclosures were reported.
                Funding/Support: This study was supported by grant 17SFRN33490004 from the American Heart Association; the National Center for Advancing Translational Sciences; grant UL1TR001445 from the National Institutes of Health; grants K99MD012811, R00MD012811, U54MD000538-15 pilot award, and P30DK111022 pilot award from the NIH (Dr Hu); grant 5T32HL129953-04 from the NIH (Dr Kharmats); and grant T32HP22238 from the Health Resources and Services Administration (Dr Berube).
                Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Disclaimer: The contents of this article are solely the responsibility of the authors and do not necessarily reflect the official views of the American Heart Association.
                Data Sharing Statement: See Supplement 3.
                Additional Contributions: Antonia Polyn, MS, Shirley Chen, BS, and Katherine Perdomo, BS (all from NYU Grossman School of Medicine) contributed to the administrative, technical and material support of the trial. We thank our study participants, without whom this study would not have been completed.
                Article
                zoi220963
                10.1001/jamanetworkopen.2022.33760
                9520362
                36169954
                c6b7241c-d2fc-4ee9-9a09-6cf98d53eeda
                Copyright 2022 Popp CJ et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 14 May 2022
                : 3 August 2022
                Categories
                Research
                Original Investigation
                Online Only
                Nutrition, Obesity, and Exercise

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