A randomized clinical trial comparing low-fat with precision nutrition-based diets for weight loss: impact on glycemic variability and HbA1c.


Journal

The American journal of clinical nutrition
ISSN: 1938-3207
Titre abrégé: Am J Clin Nutr
Pays: United States
ID NLM: 0376027

Informations de publication

Date de publication:
08 2023
Historique:
received: 09 06 2022
revised: 16 05 2023
accepted: 23 05 2023
pmc-release: 14 06 2024
medline: 7 8 2023
pubmed: 27 5 2023
entrez: 26 5 2023
Statut: ppublish

Résumé

Recent studies have demonstrated considerable interindividual variability in postprandial glucose response (PPGR) to the same foods, suggesting the need for more precise methods for predicting and controlling PPGR. In the Personal Nutrition Project, the investigators tested a precision nutrition algorithm for predicting an individual's PPGR. This study aimed to compare changes in glycemic variability (GV) and HbA1c in 2 calorie-restricted weight loss diets in adults with prediabetes or moderately controlled type 2 diabetes (T2D), which were tertiary outcomes of the Personal Diet Study. The Personal Diet Study was a randomized clinical trial to compare a 1-size-fits-all low-fat diet (hereafter, standardized) with a personalized diet (hereafter, personalized). Both groups received behavioral weight loss counseling and were instructed to self-monitor diets using a smartphone application. The personalized arm received personalized feedback through the application to reduce their PPGR. Continuous glucose monitoring (CGM) data were collected at baseline, 3 mo and 6 mo. Changes in mean amplitude of glycemic excursions (MAGEs) and HbA1c at 6 mo were assessed. We performed an intention-to-treat analysis using linear mixed regressions. We included 156 participants [66.5% women, 55.7% White, 24.1% Black, mean age 59.1 y (standard deviation (SD) = 10.7 y)] in these analyses (standardized = 75, personalized = 81). MAGE decreased by 0.83 mg/dL per month for standardized (95% CI: 0.21, 1.46 mg/dL; P = 0.009) and 0.79 mg/dL per month for personalized (95% CI: 0.19, 1.39 mg/dL; P = 0.010) diet, with no between-group differences (P = 0.92). Trends were similar for HbA1c values. Personalized diet did not result in an increased reduction in GV or HbA1c in patients with prediabetes and moderately controlled T2D, compared with a standardized diet. Additional subgroup analyses may help to identify patients who are more likely to benefit from this personalized intervention. This trial was registered at clinicaltrials.gov as NCT03336411.

Sections du résumé

BACKGROUND
Recent studies have demonstrated considerable interindividual variability in postprandial glucose response (PPGR) to the same foods, suggesting the need for more precise methods for predicting and controlling PPGR. In the Personal Nutrition Project, the investigators tested a precision nutrition algorithm for predicting an individual's PPGR.
OBJECTIVE
This study aimed to compare changes in glycemic variability (GV) and HbA1c in 2 calorie-restricted weight loss diets in adults with prediabetes or moderately controlled type 2 diabetes (T2D), which were tertiary outcomes of the Personal Diet Study.
METHODS
The Personal Diet Study was a randomized clinical trial to compare a 1-size-fits-all low-fat diet (hereafter, standardized) with a personalized diet (hereafter, personalized). Both groups received behavioral weight loss counseling and were instructed to self-monitor diets using a smartphone application. The personalized arm received personalized feedback through the application to reduce their PPGR. Continuous glucose monitoring (CGM) data were collected at baseline, 3 mo and 6 mo. Changes in mean amplitude of glycemic excursions (MAGEs) and HbA1c at 6 mo were assessed. We performed an intention-to-treat analysis using linear mixed regressions.
RESULTS
We included 156 participants [66.5% women, 55.7% White, 24.1% Black, mean age 59.1 y (standard deviation (SD) = 10.7 y)] in these analyses (standardized = 75, personalized = 81). MAGE decreased by 0.83 mg/dL per month for standardized (95% CI: 0.21, 1.46 mg/dL; P = 0.009) and 0.79 mg/dL per month for personalized (95% CI: 0.19, 1.39 mg/dL; P = 0.010) diet, with no between-group differences (P = 0.92). Trends were similar for HbA1c values.
CONCLUSIONS
Personalized diet did not result in an increased reduction in GV or HbA1c in patients with prediabetes and moderately controlled T2D, compared with a standardized diet. Additional subgroup analyses may help to identify patients who are more likely to benefit from this personalized intervention. This trial was registered at clinicaltrials.gov as NCT03336411.

Identifiants

pubmed: 37236549
pii: S0002-9165(23)63950-4
doi: 10.1016/j.ajcnut.2023.05.026
pmc: PMC10447469
pii:
doi:

Substances chimiques

Glycated Hemoglobin 0
Blood Glucose 0

Banques de données

ClinicalTrials.gov
['NCT03336411']

Types de publication

Randomized Controlled Trial Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

443-451

Subventions

Organisme : NHLBI NIH HHS
ID : T32 HL129953
Pays : United States
Organisme : NIMHD NIH HHS
ID : K99 MD012811
Pays : United States
Organisme : NIMHD NIH HHS
ID : R00 MD012811
Pays : United States
Organisme : NIDDK NIH HHS
ID : P30 DK111022
Pays : United States

Informations de copyright

Copyright © 2023 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.

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Auteurs

Anna Y Kharmats (AY)

Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States.

Collin Popp (C)

Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States.

Lu Hu (L)

Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States.

Lauren Berube (L)

Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States. Electronic address: lauren.thomas@nyulangone.org.

Margaret Curran (M)

Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States.

Chan Wang (C)

Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States.

Mary Lou Pompeii (ML)

Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States.

Huilin Li (H)

Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States.

Michael Bergman (M)

Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States; Division of Endocrinology, Diabetes and Metabolism, New York University Grossman School of Medicine, New York, NY, United States.

David E St-Jules (DE)

Department of Nutrition, University of Nevada, Reno, Reno, NV, United States.

Eran Segal (E)

Department of Computer Science and Applied Math, Weizmann Institute of Science, Rehovot, Israel.

Antoinette Schoenthaler (A)

Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States.

Natasha Williams (N)

Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States.

Ann Marie Schmidt (AM)

Diabetes Research Program, Department of Medicine, New York University Langone Health, New York, NY, United States.

Souptik Barua (S)

Division of Precision Medicine, Department of Medicine, New York University Langone Health, New York, NY, United States.

Mary Ann Sevick (MA)

Center for Healthful Behavior Change, Institute for Excellence in Health Equity, New York University Langone Health, New York, NY, United States; Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States; Division of Endocrinology, Diabetes and Metabolism, New York University Grossman School of Medicine, New York, NY, United States.

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