Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 May 14;16(10):1479.
doi: 10.3390/nu16101479.

Do Precision and Personalised Nutrition Interventions Improve Risk Factors in Adults with Prediabetes or Metabolic Syndrome? A Systematic Review of Randomised Controlled Trials

Affiliations

Do Precision and Personalised Nutrition Interventions Improve Risk Factors in Adults with Prediabetes or Metabolic Syndrome? A Systematic Review of Randomised Controlled Trials

Seaton Robertson et al. Nutrients. .

Abstract

This review aimed to synthesise existing literature on the efficacy of personalised or precision nutrition (PPN) interventions, including medical nutrition therapy (MNT), in improving outcomes related to glycaemic control (HbA1c, post-prandial glucose [PPG], and fasting blood glucose), anthropometry (weight, BMI, and waist circumference [WC]), blood lipids, blood pressure (BP), and dietary intake among adults with prediabetes or metabolic syndrome (MetS). Six databases were systematically searched (Scopus, Medline, Embase, CINAHL, PsycINFO, and Cochrane) for randomised controlled trials (RCTs) published from January 2000 to 16 April 2023. The Academy of Nutrition and Dietetics Quality Criteria were used to assess the risk of bias. Seven RCTs (n = 873), comprising five PPN and two MNT interventions, lasting 3-24 months were included. Consistent and significant improvements favouring PPN and MNT interventions were reported across studies that examined outcomes like HbA1c, PPG, and waist circumference. Results for other measures, including fasting blood glucose, HOMA-IR, blood lipids, BP, and diet, were inconsistent. Longer, more frequent interventions yielded greater improvements, especially for HbA1c and WC. However, more research in studies with larger sample sizes and standardised PPN definitions is needed. Future studies should also investigate combining MNT with contemporary PPN factors, including genetic, epigenetic, metabolomic, and metagenomic data.

Keywords: medical nutrition therapy; metabolic syndrome; personalized nutrition; precision nutrition; prediabetes; randomized controlled trial; systematic review.

PubMed Disclaimer

Conflict of interest statement

C.E.C. is funded by an Australian National Health and Medical Research Council Leadership Investigator Grant (APP2009340). The authors declare that they have no conflicts of interest to disclose.

Figures

Figure 1
Figure 1
PRISMA flow diagram for the literature search and the study selection process [30].
Figure 2
Figure 2
Number of studies that reported statistically significant differences between the intervention and comparison groups for each outcome of interest. The blue bars represent reported increases in the intervention group compared to the control group, while the red bars denote decreases. Studies that examined the outcome but did not report a significant between-group difference are not included in this figure (see Table S3 for further information). Esposito et al. [25] did not specify if blood/plasma glucose levels (counted under BGL outcome) were measured in a fasted state. Pimentel et al. [29] did not report the timing for when post-prandial glucose or insulin were measured, while Ben-Yacov et al. [24] calculated post-prandial glucose from continuous glucose monitor (CGM) data. BGL (Blood Glucose Level), BMI (Body Mass Index), HbA1c (Glycated Haemoglobin), HOMA-IR (Homeostatic Model Assessment of Insulin Resistance).

References

    1. Tabák A.G., Herder C., Rathmann W., Brunner E.J., Kivimäki M. Prediabetes: A high-risk state for diabetes development. Lancet. 2012;379:2279–2290. doi: 10.1016/S0140-6736(12)60283-9. - DOI - PMC - PubMed
    1. Stefan N., Schulze M.B. Metabolic health and cardiometabolic risk clusters: Implications for prediction, prevention, and treatment. Lancet Diabetes Endocrinol. 2023;11:426–440. doi: 10.1016/S2213-8587(23)00086-4. - DOI - PubMed
    1. Abdul-Ghani M.A., Tripathy D., DeFronzo R.A. Contributions of β-Cell Dysfunction and Insulin Resistance to the Pathogenesis of Impaired Glucose Tolerance and Impaired Fasting Glucose. Diabetes Care. 2006;29:1130–1139. doi: 10.2337/dc05-2179. - DOI - PubMed
    1. Zimmet P., Magliano D., Matsuzawa Y., Alberti G., Shaw J. The metabolic syndrome: A global public health problem and a new definition. J. Atheroscler. Thromb. 2005;12:295–300. doi: 10.5551/jat.12.295. - DOI - PubMed
    1. Nathan D.M., Davidson M.B., DeFronzo R.A., Heine R.J., Henry R.R., Pratley R., Zinman B. Impaired Fasting Glucose and Impaired Glucose Tolerance: Implications for care. Diabetes Care. 2007;30:753–759. doi: 10.2337/dc07-9920. - DOI - PubMed

Publication types

MeSH terms