Evidence map›Paper›PMID 41829883›Full record

ReviewNutrients2026

Chrono-Nutrition in Gestational Diabetes Mellitus: Implications of Meal Timing and Nutrient Distribution for Glycemic Control.

Stefania Triunfo

Abstract readReview
In one paragraph

Review in Nutrients, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Stefania TriunfoDepartment of Obstetrics and Gynecology, ASST Santi Paolo Carlo, University of Milan, 20142 Milan, Italy.ORCID 0000-0003-2405-4970

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gestational diabetes mellitus (GDM), one of the most common metabolic complications of gestation, affects approximately 10-15% of all pregnancies and represents a significant challenge for obstetricians and diabetologists aiming to reduce adverse feto-maternal outcomes. Medical nutrition therapy remains the cornerstone of GDM management, alongside lifestyle modification and pharmacological treatment in the presence of unmet glycemic targets. However, current dietary recommendations primarily emphasize nutrient composition and caloric intake, often without fully considering the temporal aspects of food intake. Chrono-nutrition is an emerging field that investigates the interaction between meal timing, circadian rhythms, and metabolic regulation. Increasing evidence indicates that glucose metabolism and insulin sensitivity exhibit marked diurnal variations, which may be further amplified in women with GDM, resulting in time-dependent differences in postprandial glycemic responses. This narrative review summarizes the current evidence on the role of chrono-nutrition in GDM by integrating mechanistic insights with findings from observational and interventional human studies. Although the available literature is limited by heterogeneity and a paucity of well-designed randomized controlled trials, the convergence of biological plausibility and emerging clinical data suggests that chrono-nutrition may represent a potential low-risk refinement of standard medical nutrition therapy. Incorporating temporal aspects of eating into dietary counseling may help frame glycemic management within a more physiologically aligned and personalized nutritional approach for pregnancies complicated by GDM.

Indexed as

Circadian RhythmDiabetes, GestationalGlycemic ControlMaternal Nutritional Physiological PhenomenaMealsBlood GlucoseFemaleHumansPregnancyBlood Glucosechrono-nutritioncircadian rhythmgestational diabetes mellitusglycemic controlmeal timingpregnancy nutrition

Identifiers

PMID41829883
PMCPMC12986806

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Registered trials

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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 OpenQuestion graph.