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Optimised Glucose “Time in Range” Using Continuous Glucose Monitors in 4,805 Non-Diabetic Individuals Is Associated With Favourable Diet and Health: The ZOE PREDICT Studies
Open accessAbstract
Continuous glucose monitoring (CGM) enables the dynamic measurement of glycemic control. In diabetic cohorts, time in range (TIR), measured by CGM, is discriminatory of future disease development. However, the value of CGM metrics in non-diabetic populations and their relationship with health outcomes is unclear. This research developed ‘optimised’ TIR targets specific to healthy populations and explored their relationship with diet and health. The ZOE PREDICT studies, one (n = 1002, UK), two (n = 987, US) and three (n = 4,500, US) collected demographic information, habitual and free-living diet data, cardiometabolic blood biomarkers and postprandial responses to standardized meals in clinic and free-living settings. TIR was calculated from CGMs (2–4 days free-living) using 1) the American Diabetes Association (ADA); 70–140 mg/dL (TIRADA) and 2) a novel optimised; 70–100 mg/dL (TIRoptimised) target. Habitual diet quality (plant-based diet indices; PDI, healthy-PDI and unhealthy-PDI), and free-living nutrient intakes (% energy) were calculated. Associations (spearman's, adjusted for age, sex and BMI) between TIR and diet were examined, and differences in diet and health outcomes between quintile 1 (Q1) and 5 (Q5) of TIR targets were assessed. Mean fasting glucose was 91 ± 10 mg/dL, HbA1c 5.3 ± 0.4%, TIRoptimised 70 ± 17% and TIRADA 91 ± 13% (n = 4805 after exclusions, 78% females, mean age 46 ± 12y). Individuals with better glycemic control (TIRoptimised Q5 vs Q1) were younger (mean ± SD) (45 ± 11 vs 49 ± 12y), had lower HbA1c (5.2 ± 0.4 vs 5.5 ± 0.5) and fasting glucose (91 ± 14 vs 97 ± 23 mg/dL) and higher HDL-cholesterol (1.7 ± 0.4 vs 1.6 ± 0.5mmol/L) (P< 0.001 for all). TIRoptimised (PREDICT 1 n = 868) was associated with a favourable diet (lower unhealthy-PDI and carbohydrate intakes and higher protein intakes) and cardiometabolic risk profile (lower HbA1c and ASCVD) (P < 0.05 for all). However, TIRADA was not associated with diet or health outcomes. We demonstrate that an optimised TIR target (70–100 mg/dL) is discriminatory of ASCVD risk despite normal fasting HbA1c. These findings demonstrate the utility of CGM's in non-diabetic populations and highlight the potential application of dietary strategies to improve TIR and subsequent metabolic complications. ZOE Ltd.
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For individuals without diabetes, a TIR of 90% or higher has been considered normal.
“For individuals without diabetes, a TIR of 90% or higher has been considered normal42.”
From Impact of digital health interventions on glycemic control and weight management. (2025) · cites this paper as [42]
The Results report a mean ADA-defined TIR of 91 ± 13% among 4,805 people without diabetes, which is consistent with a value around 90% being typical in this sample. The paper does not establish 90% or higher as a cutoff for what is considered normal; its Methods define TIR by glucose ranges, not by a percentage threshold. (LLM, conf=0.86)
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Impact of digital health interventions on glycemic control and weight management.
Veluvali, A., Dehghani Zahedani, A., Hosseinian, A., Aghaeepour, N., McLaughlin, T., Woodward, M., DiTullio, A., Hashemi, N., & Snyder, M. P. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01430-7 · Cited by 45
Multi-Horizon Glucose Prediction Across Populations With Deep Domain Generalization
Zhu, T., Afentakis, I., Li, K., Armiger, R., Hill, N. E., Oliver, N. S., & Georgiou, P. (2024) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2024.3428921 · Cited by 21
“…T1D care; it has increasingly been adopted across a diverse range of clinical scenarios,includingitsuseinhospitalsettings[8],[9],especially duringtheCOVID-19pandemic[10],[11],andamongindivid-ualswithoutdiabetes[12],suchasaidingindietarystrategies aimedatamelioratingmetaboliccomplications[13].”
Brinkmann, C. K., Bloch, W., & Mutinati, G. C. (2023) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2023.1166857 · Cited by 7
“6 mmol/ L) is associated with a more favorable cardiometabolic risk profile, while no such link was found for the time spent within the ADA’s target range (Berry et al., 2022).”
BackgroundSkroče, K., Zignoli, A., Turner, L. V., Lipman, D. J., Riddell, M. C., & Zisser, H. (2026) · Journal of Diabetes Science and Technology · doi:10.1177/19322968261426376 · Cited by 1
“18 Broader nutritional literature also emphasizes the adverse health consequences of excess dietary sugar 30 and the relevance of meal timing strategies such as early time-restricted eating for improving cardiometabolic outcomes.”
Metadata
- Authors
- Berry, S., Bermingham, K., Valdes, A., Franks, P., Wolf, J., & Spector, T.
- Affiliations
- King's College London (GB)
- University of Nottingham (GB)
- Lund University (SE)
- ZOE (United Kingdom) (GB)
- Venue
- Current Developments in Nutrition
- Publisher
- Elsevier BV
- Published
- 2022-06
- Volume
- 6
- Pages
- 1108
- ISSN
- 2475-2991 (ISSN-L)
- PMC
- PMC9194241
- OpenAlex
- W4282823632
- Cited by
- 4
- References
- 0
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 1
- FWCI
- 0.56
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Current Developments in Nutrition (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Keywords
- time in range, continuous glucose monitoring, non-diabetic individuals, glycemic control, plant-based diet, diet quality, cardiometabolic biomarkers, postprandial blood glucose, HbA1c, fasting blood glucose, HDL cholesterol, cardiovascular risk, healthy lifestyle, nutrient intake
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