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Associations of continuous glucose monitor derived time in range and glycaemic variability with diet lifestyle and demographics
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  • Published: 27 March 2026

Associations of continuous glucose monitor derived time in range and glycaemic variability with diet lifestyle and demographics

  • Kate M. Bermingham1,2 na1,
  • Harry A. Smith1,2 na1,
  • Emma L. Duncan  ORCID: orcid.org/0000-0002-8143-44033,4,
  • Javier T. Gonzalez5,
  • Ana M. Valdes  ORCID: orcid.org/0000-0003-1141-44716,7,
  • Paul W. Franks  ORCID: orcid.org/0000-0002-0520-76048,9,
  • Linda Delahanty  ORCID: orcid.org/0000-0002-1525-355910,11,
  • Hassan S. Dashti  ORCID: orcid.org/0000-0002-1650-679X10,
  • Richard Davies  ORCID: orcid.org/0000-0003-2050-39942,
  • George Hadjigeorgiou  ORCID: orcid.org/0000-0001-7647-84712,
  • Jonathan Wolf  ORCID: orcid.org/0000-0002-0530-22572,
  • Andrew T. Chan  ORCID: orcid.org/0000-0001-7284-676712,
  • Tim D. Spector  ORCID: orcid.org/0000-0002-9795-03651,2 &
  • …
  • Sarah E. Berry  ORCID: orcid.org/0000-0002-5819-51091 na1 

Nature Communications (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Homeostasis
  • Risk factors
  • Systems biology

Abstract

Continuous glucose monitors (CGMs) provide detailed glucose profiles, but their relevance to health outcomes in individuals without diabetes remains unclear. Here we assess time in range (TIR3.9–5.6 and TITR3.9-7.8) and glycaemic variability in individuals (N = 3,634; age 46 ± 12 y; 83% female; BMI 27 ± 6 kg/m²) from PREDICT 1 (NCT03479866), PREDICT 2 (NCT03983733), and PREDICT 3 (NCT04735835) without diabetes or prediabetes, and explore associations with demographic, diet, lifestyle, cardiometabolic markers, and predicted cardiovascular risk. Outcomes are non-pre-defined exploratory analyses. Higher TIR3.9–5.6 is associated with lower HbA1c, OGTT glucose, carbohydrate intake, and higher protein intake. Sleep duration is inversely correlated with mean glucose. TIR3.9–5.6 provided moderate discrimination for predicted ASCVD 10-year risk (AUC = 0.75). While CGM metrics show potential to capture some components of glycaemic physiology, longer-term health outcomes are required to demonstrate whether CGM monitoring has utility for health management in euglycaemic individuals.

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Data availability

The study data can be released to bona fide researchers who submit a research proposal to data.papers@joinzoe.com. All proposals will be reviewed by a sub-panel of the ZOE Scientific Advisory Board within four working weeks. To protect participant privacy, individual participant clinical data are not publicly available and cannot be deposited in public repositories. Proposals, researchers or institutions requesting data will be approved if they meet the standard criteria related to ethics, privacy and data protection regulations. Approved researchers are required to enter into a data-sharing agreement with ZOE.

Code availability

The scripts for the statistical analysis are freely available upon request to ZOE Ltd. Code will be made available within 2 months of the request. Code requests should be sent to data.papers@joinzoe.com.

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Acknowledgements

This work was supported by ZOE Ltd and TwinsUK, which is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), ZOE Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London. H.S.D. is supported by the National Institute of Health [grant number R00HL153795].

Author information

Author notes

  1. These authors contributed equally: Kate M. Bermingham, Harry A. Smith, Sarah E. Berry.

Authors and Affiliations

  1. Department of Nutritional Sciences, King’s College London, London, UK

    Kate M. Bermingham, Harry A. Smith, Tim D. Spector & Sarah E. Berry

  2. Zoe Ltd, London, UK

    Kate M. Bermingham, Harry A. Smith, Richard Davies, George Hadjigeorgiou, Jonathan Wolf & Tim D. Spector

  3. Department of Endocrinology, Guy’s and St Thomas’ NHS Foundation Trust, London, UK

    Emma L. Duncan

  4. Department of Twin Research and Genetic Epidemiology, School of Life Course and Population Sciences, Faculty of Life Sciences & Medicine, King’s College London, London, UK

    Emma L. Duncan

  5. Centre for Nutrition, Exercise, and Metabolism, Department for Health, University of Bath, Bath, UK

    Javier T. Gonzalez

  6. School of Medicine, University of Nottingham, Nottingham, UK

    Ana M. Valdes

  7. Nottingham NIHR Biomedical Research Centre, Nottingham, UK

    Ana M. Valdes

  8. Department of Clinical Sciences, Lund University, Lund, Sweden

    Paul W. Franks

  9. Department of Nutrition, Harvard Chan School of Public Health, Boston, MA, USA

    Paul W. Franks

  10. Diabetes Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA

    Linda Delahanty & Hassan S. Dashti

  11. Department of Medicine, Harvard Medical School, Boston, MA, USA

    Linda Delahanty

  12. Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA

    Andrew T. Chan

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Contributions

K.M.B., H.A.S., and S.E.B. contributed equally to the conception, design, analysis, and drafting of the manuscript. S.E.B. and T.D.S. contributed to all aspects of the study except software development, including study design, data interpretation, and manuscript revision. R.D., G.H., and J.W. developed and provided the software and infrastructure that hosted the PREDICT data. E.L.D., J.T.G., A.M.V., P.W.F., L.M.D., H.S.D., and A.T.C. contributed to data interpretation and revisions of the manuscript.

Corresponding author

Correspondence to Sarah E. Berry.

Ethics declarations

Competing interests

T.D.S., J.W. and G.H. are co-founders of ZOE Ltd. A.M.V., P.W.F., L.M.D., A.T.C. and T.D.S. are consultants to ZOE Ltd. K.M.B., H.A.S., R.D., G.H., S.E.B. and J.W. are or have been employees of ZOE Ltd. K.M.B., H.A.S., A.M.V., L.M.D., R.D., G.H., J.W., T.D.S. and S.E.B. also receive options in ZOE Ltd. The remaining authors declare no competing interests.

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Bermingham, K.M., Smith, H.A., Duncan, E.L. et al. Associations of continuous glucose monitor derived time in range and glycaemic variability with diet lifestyle and demographics. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70308-3

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  • Received: 23 April 2024

  • Accepted: 09 February 2026

  • Published: 27 March 2026

  • DOI: https://doi.org/10.1038/s41467-026-70308-3

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