Analysis of the risk stratification of type 2 diabetes mellitus in individuals with clinical signs of desynchronosis
https://doi.org/10.14341/DM13435
Abstract
BACKGROUND: In the context of a sustained increase in the prevalence of obesity and its associated cardiometabolic complications, the importance of identifying additional risk factors is growing, with particular emphasis on sleep disturbances and reduced sleep duration, which contribute to the development and progression of metabolic disorders.
AIM: To assess the severity of disturbances in the sleep–wake cycle in patients with overweight and class I obesity across different categories of risk for disorders of carbohydrate metabolism according to the FINDRISC scale.
MATERIALS AND METHODS: The study included 1,500 Caucasian patients of both sexes, aged 45–70 years, with a BMI ≥25 kg/m². All participants completed questionnaires: FINDRISC (to estimate the risk of developing diabetes mellitus), PSQI (Pittsburgh Sleep Quality Index, last month), and ISI (Insomnia Severity Index).
RESULTS: Retrospective analysis showed that 96.6% of patients aged 45–64 years were overweight or had class I obesity. At the second stage of the study, among 782 patients with moderate and high 10‑year risk of type 2 diabetes according to the FINDRISC, sleep disturbances were documented in 696 (89.0 %) individuals.
CONCLUSION: In patients with overweight and class I obesity who have a moderate or high 10‑year risk of type 2 diabetes according to the FINDRISC, disturbances of the sleep–wake cycle should be additionally considered as a modifiable predictor of metabolic disorders.
About the Authors
Yu. V. NelaevaRussian Federation
Yulia V. Nelaeva, MD, PhD
Tyumen
Competing Interests:
none
A. A. Nelaeva
Russian Federation
Alsu A. Nelaeva, MD, PhD, Professor
Tyumen
Competing Interests:
none
S. A. Vedernikova
Russian Federation
Sofya A. Vedernikova, MD
Tyumen
Competing Interests:
none
M. A. Arkhipova
Russian Federation
Marina S. Arkhipova, MD
Tyumen
Competing Interests:
none
E. A. Likhacheva
Russian Federation
Elizaveta А. Likhacheva, MD
Tyumen
Competing Interests:
none
References
1. Zhang X, Ha S, Lau HC, Yu J. Excess body weight: Novel insights into its roles in obesity comorbidities. Semin Cancer Biol. 2023;92:16–27. doi: https://doi.org/10.1016/j.semcancer.2023.03.008
2. Kade AK, Chabanets EA, Zanin SA, et al. Sick fat (adiposopathy) as the main contributor to metabolic syndrome. Voprosy pitaniia. 2022;91(1):27–36. (in Russ.) doi: https://doi.org/10.33029/0042-8833-2022-91-1-27-36
3. Fahed G, Aoun L, Bou Zerdan M, et al. Metabolic Syndrome: Updates on Pathophysiology and Management in 2021. Int J Mol Sci. 2022;23(2):786. doi: https://doi.org/10.3390/ijms23020786
4. Lim HM, Chia YC, Koay ZL. Performance of the Finnish Diabetes Risk Score (FINDRISC) and Modified Asian FINDRISC (ModAsian FINDRISC) for screening of undiagnosed type 2 diabetes mellitus and dysglycaemia in primary care. Prim Care Diabetes. 2020;14(5):494–500. doi: https://doi.org/10.1016/j.pcd.2020.02.008
5. Saaristo T, Peltonen M, Lindström J, et al. Cross-sectional evaluation of the Finnish Diabetes Risk Score: a tool to identify undetected type 2 diabetes, abnormal glucose tolerance and metabolic syndrome. Diab Vasc Dis Res. 2005;2(2):67–72. doi: https://doi.org/10.3132/dvdr.2005.011
6. Chaudhry BA, Brian MS, Morrell JS. The Relationship between Sleep Duration and Metabolic Syndrome Severity Scores in Emerging Adults. Nutrients. 2023;15(4):1046. doi: https://doi.org/10.3390/nu15041046
7. Ai S, Zhang J, Zhao G, et al. Causal associations of short and long sleep durations with 12 cardiovascular diseases: linear and nonlinear Mendelian randomization analyses in UK Biobank. Eur Heart J. 2021;42(34):3349–3357. doi: https://doi.org/10.1093/eurheartj/ehab170
8. Zimmet P, Alberti KGMM, Stern N, et al. The Circadian Syndrome: is the Metabolic Syndrome and much more!. J Intern Med. 2019;286(2):181–191. doi: https://doi.org/10.1111/joim.12924
9. Shi Z, Tuomilehto J, Kronfeld-Schor N, et al. The circadian syndrome predicts cardiovascular disease better than metabolic syndrome in Chinese adults. J Intern Med. 2021;289(6):851–860. doi: https://doi.org/10.1111/joim.13204
10. Ostroumova OD, Kochetkov AI, Ebzeeva EYu, Pereverzev AP. Insomnia and polymorbidity: a study guide. Moscow: Russian Medical Academy of Continuous Professional Education, Ministry of Health of Russia; 2021. (In Russ.)
11. Morin CM, Belleville G, Bélanger L, Ivers H. The Insomnia Severity Index: psychometric indicators to detect insomnia cases and evaluate treatment response. Sleep. 2011;34(5):601-8. doi: https://doi.org/10.1093/sleep/34.5.601
12. Zhelyabina OV, Eliseev MS, Glukhova SI, et al. Risk factors for type 2 diabetes mellitus in patients with gout: results from a prospective study. Sovremennaya Revmatologiya. 2022;16(1):52–59 (In Russ.) doi: https://doi.org/10.14412/1996-7012-2022-1-52-59
13. Riise HKR, Graue M, Igland J, et al. Prevalence of increased risk of type 2 diabetes in general practice: a crosssectional study in Norway. BMC Prim Care. 2023;24(1):151. doi: https://doi.org/10.1186/s12875-023-02100-x
14. Dedov II, Shestakova MV, Vikulova OK, et.al. Epidemiological characteristics of diabetes mellitus in the Russian Federation: clinical and statistical analysis according to the Federal diabetes register data of 01.01.2021. Diabetes mellitus. 2021;24(3):204–221. (In Russ.)] doi: https://doi.org/10.14341/DM12759
15. Suplotova LA, Belchikova LN, Rozhnova NA, Sudnitsyna AS. Epidemiological characteristics of diabetes type 2 in Tyumen region for over 10-year period (2012–2022). Medical science and education of Ural. 2023;24(3):79–83. (In Russ.) doi: https://doi.org/10.36361/18148999_2023_24_3_79
16. Drapkina ОM, Kotova MB, Maksimov SA, et al. Adherence to a healthy lifestyle in Russia according to the ESSE-RF study: is there a COVID-19 trace? Cardiovascular Therapy and Prevention. 2023;22(8S):8–19. (In Russ.) doi: https://doi.org/10.15829/1728-8800-2023-3788.
17. Rohm TV, Meier DT, Olefsky JM, et al. Inflammation in obesity, diabetes, and related disorders. Immunity. 2022;55(1):31–55. doi: https://doi.org/10.1016/j.immuni.2021.12.013
18. Strizheletskiy VV, Gomon YM, Spichakova EA, et al. Obesity grade I: a study of real clinical practice in the Russian Federation. Medical Technologies. Assessment and Choice. 2024;46(1):83–90. (In Russ.) doi: https://doi.org/10.17116/medtech20244601183
19. Dhadse R, Yadav D, Thakur L, et al. Clinical Profile, Risk Factors, and Complications in Young-Onset Type 2 Diabetes Mellitus. Cureus. 2024;16(9):e68497. doi: https://doi.org/10.7759/cureus.68497
20. Chasens ER, Imes CC, Kariuki JK, et al. Sleep and Metabolic Syndrome. Nurs Clin North Am. 2021;56(2):203–217. doi: https://doi.org/10.1016/j.cnur.2020.10.012
21. Smiley A, King D, Bidulescu A. The Association between Sleep Duration and Metabolic Syndrome: The NHANES 2013/2014. Nutrients. 2019;11(11):2582. doi: https://doi.org/10.3390/nu11112582
22. Che Y, Shimizu Y, Hayashi T, et al. Chronic circadian rhythm disorder induces heart failure with preserved ejection fraction-like phenotype through the Clock-sGC-cGMP-PKG1 signaling pathway. Sci Rep. 2024;14(1):10777. doi: https://doi.org/10.1038/s41598-024-61710-2
Supplementary files
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1. Рисунок 1. Дизайн исследования. | |
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2. Рисунок 2. Структура выборки в соответствии с суммарно набранными баллами (FINDRISC) (n=1500). | |
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3. Рисунок 3. Структура нарушений сна у пациентов с избыточной массой тела и ожирением I степени с умеренным и высоким риском (FINDRISC) по данным опросника «Индекс тяжести инсомнии» (n=782). | |
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| Type | Исследовательские инструменты | |
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Review
For citations:
Nelaeva Yu.V., Nelaeva A.A., Vedernikova S.A., Arkhipova M.A., Likhacheva E.A. Analysis of the risk stratification of type 2 diabetes mellitus in individuals with clinical signs of desynchronosis. Diabetes mellitus. 2026;29(3):237-244. (In Russ.) https://doi.org/10.14341/DM13435
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