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Dietary composition and time in range in population with type 2 diabetes mellitus-exploring the association using continuous glucose monitoring device

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Abstract

Aim

To understand the association between macronutrient composition of a diet with Time in Range (TIR), Time above Range (TAR) and Time below Range (TBR) derived using a Continuous Glucose Monitoring (CGM) device for 14 days.

Methodology

An exploratory analysis on the baseline data of 50 Type 2 Diabetes Mellitus participants with age 25–55 years, HbA1c upto 8% and on Metformin only) enrolled for an interventional clinical trial was performed.

Results

Participants consuming adequate carbohydrates (CHO) of 55 to 60% of total calories had better Average Blood Glucose of 142.0 ± 24.0 mg/dL with a significance of p = 0.03 and Glucose Management Indicator (GMI) of 6.6 ± 0.7% significant at p = 0.01, than those with high CHO intake >60% of the total calories, with Average Blood Glucose - 155.0 ± 13.4 mg/dL and GMI - 7.06 ± 0.4%. Similarly, TIR - 68.2 ± 5.1% and TAR - 23.0 ± 10.8% was significantly better (p = 0.00) among those consuming adequate protein (12–15%) as compared to low protein (≤ 10%) with TIR- 61.0 ± 5.1% & TAR- 32.9 ± 10.3%. A correlation (r = −0.482 & p = 0.00) and simple linear regression analysis (R² = 0.33, F = 7.72, p = 0.000) revealed that when CHO intake increases the TIR decreases whereas TAR increases (r = 0.380 & p = 0.006). We did not find any significant relation between fat intake and TIR, TAR or TBR.

Conclusion

Our results suggest that lowering CHO, while increasing protein in the diet may help improve TIR. Further in-depth studies are needed to confirm these findings.

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References

  1. A.B. Evert, M. Dennison, C.D. Gardner, W.T. Garvey, K.H.K. Lau, J. MacLeod et al. Nutrition Therapy for Adults With Diabetes or Prediabetes: A Consensus Report. Diabetes Care 1 42(5), 731–754 (2019). https://doi.org/10.2337/dci19-0014

    Article  Google Scholar 

  2. E. Koloverou, D.B. Panagiotakos, Macronutrient Composition and Management of Non-Insulin-Dependent Diabetes Mellitus (NIDDM): A New Paradigm for Individualized Nutritional Therapy in Diabetes Patients. Rev. Diabet. Stud. 13(1), 6–16 (2016). https://doi.org/10.1900/RDS.2016.13.6

    Article  PubMed  PubMed Central  Google Scholar 

  3. R.M. Anjana, S. Srinivasan, V. Sudha, S.R. Joshi, B. Saboo, N. Tandon et al. For the ICMR-INDIAB Collaborative Study Group; Macronutrient Recommendations for Remission and Prevention of Diabetes in Asian Indians Based on a Data-Driven Optimization Model: The ICMR-INDIAB National Study. Diabetes Care 45(12), 2883–2891 (2022). https://doi.org/10.2337/dc22-0627

    Article  CAS  Google Scholar 

  4. A. Advani, Positioning time in range in diabetes management. Diabetologia 63(2), 242–252 (2020). https://doi.org/10.1007/s00125-019-05027-0

    Article  PubMed  Google Scholar 

  5. A.E. Nuha, A. Grazia, R.A. Vanita, R.R. Bannuru, F.M. Brown, D. Bruemmer et al. on behalf of the American Diabetes Association, 6. Glycemic Targets: Standards of Care in Diabetes—2023. Diabetes Care 46(Supplement_1), S97–S110 (2023). https://doi.org/10.2337/dc23-S006

    Article  Google Scholar 

  6. A.E. Breyton, S. Lambert-Porcheron, M. Laville, S. Vinoy, J.A. Nazare, CGMS and Glycemic Variability, Relevance in Clinical Research to Evaluate Interventions in T2D, a Literature Review. Front. Endocrinol. 12, 666008 (2021). https://doi.org/10.3389/fendo.2021.666008

    Article  Google Scholar 

  7. J. Merino, I. Linenberg, K.M. Bermingham, S. Ganesh, E. Bakker, L.M. Delahanty et al. Validity of continuous glucose monitoring for categorizing glycemic responses to diet: implications for use in personalized nutrition. Am. J. Clin. Nutr. 115(6), 1569–1576 (2022). https://doi.org/10.1093/ajcn/nqac026

    Article  PubMed  PubMed Central  Google Scholar 

  8. Indian Council of Medical Research|Government of India. (2023). https://main.icmr.nic.in/sites/default/files/guidelines/ICMR_GuidelinesType2diabetes2018_0.pdf

  9. N.A. ElSayed, G. Aleppo, V.R. Aroda, R.R. Bannuru, F.M. Brown, D. Bruemmer et al. American Diabetes Association. 7. Diabetes technology: Standards of Care in Diabetes—2023. Diabetes Care 46(1), S111–S127 (2023). https://doi.org/10.2337/dc23-SDIS

    Article  PubMed  Google Scholar 

  10. S.R. Joshi, Glycemic Variability and Ambulatory Glucose Profile in Indian Diabetics. J. Assoc. Phys. India 64(4), 11–14 (2016)

    Google Scholar 

  11. American Diabetes Association, 5. Lifestyle Management: Standards of Medical Care in Diabetes—2019. Diabetes Care 42(Supplement_1), S46–S60 (2019). https://doi.org/10.2337/dc19-S005

  12. K. Osugi, Y. Kusunoki, M. Ohigashi, K. Kusunoki, C. Inoue, M. Inoue et al. Association between low‐carbohydrate diets and continuous glucose monitoring‐derived time in ranges. J. Diabetes Investig. 14(5), 659–668 (2023). https://doi.org/10.1111/jdi.13999

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. A.D. Monzon, L.B. Smith, S.W. Powers, L.M. Dolan, S.R. Patton, The Association Between Glycemic Variability and Macronutrients in Young Children with T1D. J. Pediatr. Psychol. 45(7), 749–758 (2020). https://doi.org/10.1093/jpepsy/jsaa046

    Article  PubMed  PubMed Central  Google Scholar 

  14. Y.H. Lin, Y.Y. Huang, H.Y. Chen, S.H. Hsieh, J.H. Sun, S.T. Chen et al. Impact of Carbohydrate on Glucose Variability in Patients with Type 1 Diabetes Assessed Through Professional Continuous Glucose Monitoring: A Retrospective Study. Diabetes Ther. 10(6), 2289–2304 (2019). https://doi.org/10.1007/s13300-019-00707-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. S.G. Camps, B. Kaur, J. Lim, Y.T. Loo, E. Pang, T. Ng et al. Improved Glycemic Control and Variability: Application of HealthyIngredients in Asian Staples. Nutrients 13, 3102 (2021). https://doi.org/10.3390/nu13093102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. L. Rasmussen, M.L. Christensen, C.W. Poulsen, C. Rud, A.S. Christensen, J.R. Andersen et al. Effect of High Versus Low Carbohydrate Intake in the Morning on Glycemic Variability and Glycemic Control Measured by Continuous Blood Glucose Monitoring in Women with Gestational Diabetes Mellitus-A Randomized Crossover Study. Nutrients 12(2), 475 (2020). https://doi.org/10.3390/nu12020475

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. N.F. Sheard, N.G. Clark, J.C. Brand-Miller, M.J. Franz, F.X. Pi-Sunyer, E. Mayer-Davis et al. Dietary carbohydrate (amount and type) in the prevention and management of diabetes: a statement by the American Diabetes Association. Diabetes Care. 27(9), 2266–2271 (2004). https://doi.org/10.2337/diacare.27.9.2266

    Article  CAS  PubMed  Google Scholar 

  18. B.L. Luhovyy, P. Kathirvel, Food proteins in the regulation of blood glucose control. Adv. Food Nutr. Res 102, 181–231 (2022). https://doi.org/10.1016/bs.afnr.2022.05.001

    Article  CAS  PubMed  Google Scholar 

  19. F. Tettamanzi, V. Bagnardi, P. Louca, A. Nogal, G.S. Monti, S.P. Mambrini et al. A High Protein Diet Is More Effective in Improving Insulin Resistance and Glycemic Variability Compared to a Mediterranean Diet—A Cross-OverControlled Inpatient Dietary Study. Nutrients 13, 4380 (2021). https://doi.org/10.3390/nu13124380

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. F.R. Muntis, A.E. Smith-Ryan, J. Crandell, K.R. Evenson, D.M. Maahs, M. Seid et al. A High Protein Diet Is Associated with Improved Glycemic Control Following Exercise among Adolescents with Type 1 Diabetes. Nutrients 15(8), 1981 (2023). https://doi.org/10.3390/nu15081981

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. S.H. Park, J. Yao, X.H. Chua, S.R. Chandran, D.S.L. Gardner, C.M. Khoo et al. Diet and Physical Activity as Determinants of Continuously Measured Glucose Levels in Persons at High Risk of Type 2 Diabetes. Nutrients 14, 366 (2022). https://doi.org/10.3390/nu14020366

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We acknowledge RSSDI for supporting our study.

Author contributions

Author 1: Conceptualization (equal); Formal Analysis (equal); Investigation (lead); Methodology, Software, and writing – original draft, review, and editing (equal). Author 2: Conceptualization (equal); Formal Analysis (equal); Investigation (supporting); Methodology, Software, and writing – original draft, review, and editing (equal).

Funding

This study is supported by grants from the Research Society for the Study of Diabetes in India (RSSDI).

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Authors and Affiliations

  1. Nutrition and Dietetics Department, Symbiosis International (Deemed University), Hill Base, Lavale, Pune, Maharashtra, 412115, India

    Aditi R. Deshmane & Arti S. Muley

  2. Indian Institute of Food Science and Technology, Clinical Nutrition and Dietetics, Augrangabad, Maharashtra, 431005, India

    Aditi R. Deshmane

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  1. Aditi R. Deshmane
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Correspondence to Arti S. Muley.

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The authors declare no competing interests.

Consent to participate

Informed consent was obtained from all subjects participating in the study.

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Informed consent was obtained from all subjects participating in the study for publishing their data.

Ethical approval

The data presented here are from an ongoing crossover clinical trial. The study is ethically approved by the Institutional Ethics Committee of Symbiosis International (Deemed College) (IEC-SIU Pune). The ethics approval number is IEC/SIU/325. The trial is also registered prospectively with Clinical Trials Registry- India. The Trial Registration No. is CTRI/2022/07/044356. This study was conducted in accordance with the tenets of the Declaration of Helsinki.

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Deshmane, A.R., Muley, A.S. Dietary composition and time in range in population with type 2 diabetes mellitus-exploring the association using continuous glucose monitoring device. Endocrine (2024). https://doi.org/10.1007/s12020-024-03787-3

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