• Cochrane Db Syst Rev · Jan 2025

    Review Meta Analysis

    Precision nutrition-based interventions for the management of obesity in children and adolescents up to the age of 19 years.

    • Samantha L Huey, Neel H Mehta, Ruth S Steinhouse, Yue Jin, Matthew Kibbee, Rebecca Kuriyan, Julia L Finkelstein, and Saurabh Mehta.
    • Cornell Joan Klein Jacobs Center for Precision Nutrition and Health, Cornell University, Ithaca, NY, USA.
    • Cochrane Db Syst Rev. 2025 Jan 30; 1: CD015877CD015877.

    BackgroundPrecision nutrition-based methods develop tailored interventions and/or recommendations accounting for determinants of intra- and inter-individual variation in response to the same diet, compared to current 'one-size-fits-all' population-level approaches. Determinants may include genetics, current dietary habits and eating patterns, circadian rhythms, health status, gut microbiome, socioeconomic and psychosocial characteristics, and physical activity. ​​​​In this systematic review, we examined the evidence base for the effect of interventions based on precision nutrition approaches on overweight and obesity in children and adolescents to help inform future research and global guidelines.ObjectivesTo examine the impact of precision nutrition-based interventions for the management of obesity in children and adolescents in all their diversity.Search MethodsWe searched CENTRAL, MEDLINE, CINAHL, Web of Science Core Collection, BIOSIS Previews, Global Index Medicus (all regions), IBECS, SciELO, PAHO, PAHO IRIS, WHO IRIS, WHOLIS, Bibliomap, and TRoPHI, as well as the WHO ICTRP and ClinicalTrials.gov. We last searched the databases on 23 July 2024. We did not apply any language restrictions.Selection CriteriaWe included randomised or quasi-randomised controlled trials that evaluated precision nutrition-based interventions (accounting for 'omics' such as phenotyping, genotyping, gut microbiome; clinical data, baseline dietary intake, postprandial glucose response, etc., and/or including artificial intelligence such as machine learning methods) compared to general or one-size-fits-all interventions or no intervention in children and adolescents aged 0 to 9 years or 10 to 19 years with overweight or obesity.Data Collection And AnalysisTwo review authors independently conducted study screening, data extraction, and risk of bias and GRADE assessments. We used fixed-effect analyses. Our outcomes of interest were physical and mental well-being, physical activity, health-related quality of life, obesity-associated disability, and adverse events associated with the interventions as defined or measured by trialists, and weight change (reduction, stabilisation or maintenance).Main ResultsTwo studies (3 references, 105 participants) conducted in Ukraine and Greece met our eligibility criteria. One study reported nonprofit funding sources, whilst the other did not report funding, and the certainty of evidence ranged from very low to low across outcomes (all measured at endpoint). Only one trial (65 participants) contributed data on our primary outcomes of interest. Precision nutrition-based intervention versus one-size-fits-all intervention or standard of care In children 0 to 9 years of age, evidence is very uncertain about the effect of a precision nutrition-based intervention (a computerised Decision Support Tool (DST) that incorporates a variety of participant data and provides personalised diet recommendations based on decision-tree algorithms) on body mass index (BMI) (mean difference (MD) -1.40 kg/m2, 95% confidence interval (CI) -3.48 to 0.68; 1 study, 35 participants; very low-certainty evidence) and on weight (MD -2.60 kg, 95% CI -8.42 to 3.22; 1 study, 35 participants; very low-certainty evidence) compared with a one-size-fits-all control intervention. In children and adolescents 10 to 19 years of age, evidence is very uncertain about the effect of a precision nutrition-based intervention (computerised DST) on BMI (MD 3.00 kg/m2, 95% CI -0.26 to 6.26; 1 study, 30 participants; very low-certainty evidence) and on weight (MD 11.40 kg, 95% CI -0.47 to 23.27; 1 study, 30 participants; very low-certainty evidence) compared with a one-size-fits-all control intervention.Authors' ConclusionsBased on data from two small studies with a total of 105 participants, the evidence is very uncertain about the effect of precision nutrition-based interventions on body weight or BMI. This review was limited by the number of available randomised controlled trials in this relatively nascent field. Given these limitations, the two studies do not provide sufficient evidence to adequately inform practice. Future research should report participant outcome data, including outcomes related to mental, emotional, and functional well-being, in addition to biochemical and physical measures, stratified by World Health Organization-defined age groups (children (0 to 9 years), and children and adolescents (10 to 19 years)). Future studies should also report methods related to randomisation, blinding, and compliance, as well as include prespecified analysis plans.Copyright © 2025 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.

      Pubmed     Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…