Trial reportThe American journal of clinical nutrition2023
A randomized clinical trial comparing low-fat with precision nutrition-based diets for weight loss: impact on glycemic variability and HbA1c.
Trial report in The American journal of clinical nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03336411 (Personalized Technology-Supported Counseling to Reduce Glycemic Response in Dietary Weight Loss), which is not on this map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Personalized Technology-Supported Counseling to Reduce Glycemic Response in Dietary Weight Loss: The Personal Diet Study
Who cites it
16 citing papers in PubMed, 25 citations in OpenAlex.
- Inflammatory markers and blood glucose are higher after morning vs afternoon exercise in type 2 diabetes.Diabetologia · 2025Trial
- Baseline Characteristics of Weight-Loss Success in a Personalized Nutrition Intervention: A Secondary Analysis.Nutrients · 2025Trial
- Imprecision nutrition? Intraindividual variability of glucose responses to duplicate presented meals in adults without diabetes.The American journal of clinical nutrition · 2025Trial
- From association to causation: a decision-aware framework for reproducible biomarker discovery and precision intervention design in the human gut microbiome.Briefings in bioinformatics · 2026Article
- Impact of fat and protein on postprandial glycemia in gestational diabetes: A randomized pilot crossover trial.Pregnancy (Hoboken, N.J.) · 2026Article
- Nutrigenomics meets multi-omics: integrating genetic, metabolic, and microbiome data for personalized nutrition strategies.Genes & nutrition · 2025Review
- From omics to AI-mapping the pathogenic pathways in type 2 diabetes.FEBS letters · 2025Review
- Characterising the design and methods of continuous glucose monitoring used in behavioural interventions to inform future research in prediabetes.The Lancet. Digital health · 2025Review
- Weight loss is associated with improved daytime time in range in adults with prediabetes and non-insulin-treated type 2 diabetes undergoing dietary intervention.Diabetic medicine : a journal of the British Diabetic Association · 2025Article
- Applications of Artificial Intelligence and Machine Learning in Prediabetes: A Scoping Review.Journal of diabetes science and technology · 2025Review
- Predictive models of post-prandial glucose response in persons with prediabetes and early onset type 2 diabetes: A pilot study.Diabetes, obesity & metabolism · 2025Article
- Effectiveness of Personalized Nutrition on Management Diabetes Mellitus Type 2 and Prediabetes in Adults: A Systematic Review.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Review
- Personalized nutrition: aligning science, regulation, and marketing.Health affairs scholar · 2024Article
- Big data and personalized nutrition: the key evidence gaps.Nature metabolism · 2024Article
- Imprecision nutrition? Duplicate meals result in unreliable individual glycemic responses measured by continuous glucose monitors across four dietary patterns in adults without diabetes.medRxiv : the preprint server for health sciences · 2023Article
- Exploring a novel therapeutic strategy: the interplay between gut microbiota and high-fat diet in the pathogenesis of metabolic disorders.Frontiers in nutrition · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 6 institutions in 2 countries.
Funding
Abstract
backgroundRecent 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.
objectiveThis 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.
methodsThe 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.
resultsWe 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.
conclusionsPersonalized 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.