Evidence map›Paper›PMID 42942995›Full record

ReviewNutrients2026

Precision Nutrition and Health Outcomes Across the Lifespan.

Yang Scarlet Shi, Alison G M Brown, Shilpy Dixit, Eric J Shiroma, Nicole Farmer, Qing Lu, Beena Sood, Debbie Vitalis, Maliha Ilias, Marrah Lachowicz-Scroggins and 1 more

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Yang Scarlet ShiNational Heart, Lung, and Blood Institute, National Institutes of Health, 6705 Rockledge Drive, Bethesda, MD 20892, USA.ORCID 0000-0002-1862-4706
Alison G M BrownNational Heart, Lung, and Blood Institute, National Institutes of Health, 6705 Rockledge Drive, Bethesda, MD 20892, USA.
Shilpy DixitNational Heart, Lung, and Blood Institute, National Institutes of Health, 6705 Rockledge Drive, Bethesda, MD 20892, USA.
Eric J ShiromaNational Heart, Lung, and Blood Institute, National Institutes of Health, 6705 Rockledge Drive, Bethesda, MD 20892, USA.
Nicole FarmerNational Heart, Lung, and Blood Institute, National Institutes of Health, 6705 Rockledge Drive, Bethesda, MD 20892, USA.ORCID 0000-0003-3250-8688
Qing LuNational Heart, Lung, and Blood Institute, National Institutes of Health, 6705 Rockledge Drive, Bethesda, MD 20892, USA.
Beena SoodNational Heart, Lung, and Blood Institute, National Institutes of Health, 6705 Rockledge Drive, Bethesda, MD 20892, USA.ORCID 0000-0002-1433-6811
Debbie VitalisNational Heart, Lung, and Blood Institute, National Institutes of Health, 6705 Rockledge Drive, Bethesda, MD 20892, USA.
Maliha IliasNational Heart, Lung, and Blood Institute, National Institutes of Health, 6705 Rockledge Drive, Bethesda, MD 20892, USA.
Marrah Lachowicz-ScrogginsNational Heart, Lung, and Blood Institute, National Institutes of Health, 6705 Rockledge Drive, Bethesda, MD 20892, USA.ORCID 0000-0002-3173-5662
Charlotte A PrattNational Heart, Lung, and Blood Institute, National Institutes of Health, 6705 Rockledge Drive, Bethesda, MD 20892, USA.ORCID 0000-0002-6580-9500

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precision nutrition is an emerging paradigm that seeks to tailor dietary recommendations and interventions based on individual and population characteristics. Although advances in multi-omics, wearable sensors, and artificial intelligence/machine learning (AI/ML) have accelerated discovery, translation into practice remains limited by fragmented evidence across life stages and insufficient integration of knowledge regarding systems biology and other influences on health. Nutritional needs, vulnerabilities, intervention opportunities, and response heterogeneity evolve dynamically from preconception and pregnancy through infancy, childhood, adolescence, adulthood, and older age. These life stage-specific processes intersect with (epi)genetic, metabolic and microbiome factors, as well as social, psychological, behavioral, and environmental/geographic influences, contributing to heterogeneity in health outcomes. Addressing this complexity requires not only multimodal predictive models but also frameworks that integrate data standards and harmonization, systems biology, implementation science, and community engagement. To provide a structured approach to this complexity, we developed a seven-pillar Precision Nutrition Framework encompassing prevention for all, data sources, quantitative sciences, qualitative sciences, intervention implementation, communities, and education and workforce training. Using this framework and a lifespan perspective, we examine opportunities for promoting cardiovascular, pulmonary, hematologic, and circadian/sleep health, synthesize evidence on key nutrients, dietary patterns, and emerging biomarkers, and adapt and expand the "precision nutrition plate" for implementation research in clinical and community settings. We highlight critical research gaps, including the need for phenotype-guided trials, standardized data integration, and scalable implementation strategies. By integrating biological, behavioral, and broader environmental dimensions across the life course, precision nutrition can advance more effective, accessible, and sustainable approaches for disease prevention and health promotion.

Indexed as

Nutritional StatusPrecision MedicineAdolescentAdultChildDietFemaleHealth StatusHumansInfantPregnancybloodchrononutritiondata harmonizationheartimplementationlifespanlungphysical activityprecision nutritionsleep

Identifiers

PMID42942995
PMCPMC13708180

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.