EVALUATION OF THE PREVALENCE OF CARBOHYDRATE METABOLISM DISORDERS AND TYPE 2 DIABETES MELLITUS BASED ON THE FILLING OF THE DIAXATAR QUESTIONNAIRE
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Keywords

diabetes mellitus, prediabetes, glucose tolerance, fasting glycemia, Diaxatar, carbohydrate metabolism disorders

Abstract

Relevance of the topic: the spread of type 2 diabetes mellitus (DM2) around the world has reached the level of an epidemic and continues to grow steadily. According to experts from the International Diabetes Federation (IDF), 79 million adults between the ages of 537 and 20 suffer from diabetes around the world (10.5% of all adults in this age group) and their number is growing. On the other hand, 541 million people suffer from disorders of carbohydrate metabolism. It is estimated that people aged 643 million by 2030 and 783 million aged 20 to 79 years by 2045 will be living with diabetes [1].
Purpose: to identify high-risk groups for the development of carbohydrate metabolism disorders and type 2 diabetes mellitus on the basis of filling out a Diaxatar questionnaire among the population living in Marhamat District of Andijan region.
Materials and methods: 18 residents over the age of 2112 living in the Marhamat District of Andijan region underwent a violation of carbohydrate metabolism and a screening examination of the DM2 type. All participants completed a Diaxatar questionnaire and their blood sugar levels were measured, a glucose tolerance test was performed.
Results obtained: during the study, 2,112 people were examined, of which 1,356 (64.2%) did not disrupt carbohydrate metabolism. Different levels of carbohydrate metabolism disorder have been found in the remaining 669 (31.6%) people: 87 (4.1%) people were first diagnosed with Type 2 diabetes, 243 (11.5%) people had fasting glycemia disorder (FGD), 267 (12.6%) people had impaired glucose tolerance (IGT), and 159 (7.5%) people had FGD and IGT.
Filling out the Diaxatar questionnaire increases the chances of early detection of DM2-type disorders and carbohydrate metabolism. The survey showed that type 2 diabetes and carbohydrate metabolism disorders increased with an increase in scores.
Conclusion. The active use of the Diaxatar questionnaire makes it possible to identify type 2 diabetes and carbohydrate metabolism disorders among the population at an early stage, prevent complications resulting from the disease, and reduce the risk of death.

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References

International Diabetes Federation. IDF Diabetes Atlas. 10th edition. Available at: http://www.idf.org/diabetesatlas

Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM; Diabetes Prevention Program Research Group . Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin . N Engl J Med. 2002;346(6):393–403.

Dreval AV, Misnikova IV, Dzebisashvili TG. Risk razvitiya sakharnogo diabetesa 2 tipa i ostroy cardiovaskuyarnoi patologii u lits s rannimi narusheniyami uglevodnogo obmena. Clinical medicine. 2012; 80(11): 30–3.

Schulze MB , Hoffmann K , Boeing H , Linseisen J , Rohrmann S , Mohlig M , Pfeiffer AF , Spranger J , Thamer C , Haring HU , Fritsche A , Joost HG . Accurate risk score based on anthropometric, dietary , and lifestyle factors to predict the development of type 2 diabetes. Diabetes Care. 2007;30(3):510–5.

Griffin SJ, Little PS, Hales CN, Kinmonth AL, Wareham NJ. Diabetes risk score: towards earlier detection of type 2 diabetes in general practice. Diabetes Metab Res Rev 2000;16(3):164–71.6.

Implementation of Type 2 Diabetes Prevention Plan in Pirkanmaa, South Ostrobothnia, North Ostrobothnia, Northern Savo and Central Finland Hospital districts. Tampere: Finnish Diabetes Association; 2006. 62 p.

Herman WH, Smith PJ, Thompson TJ, Engelgau MM, Aubert RE. A new and simple questionnaire to identify people at increased risk for undiagnosed diabetes. Diabetes Care. 1995;18(3):382–7.

Burnett RW, D'Orazio P, Fogh -Andersen N, Kuwa K, Kulpmann WR, Larsson L, LewnstamA , Maas AH, Mager G, Spichiger -Keller U; Scientific Division, Working Group on Selective Electrodes. IFCC recommendation on reporting results for blood glucose. Clin Chim Acta. 2001;307(1–2):205–9.

World Health Organization. Definition, diagnosis, and classification of Diabetes Mellitus and its complications. Geneva: World Health Organization; 1999/2006.

Andes LJ, Cheng YJ, Rolka DB et al. Prevalence of Prediabetes Among Adolescents and Young Adults in the United States, 2005-2016.

Konnov M.V., Deev A.D. Own and parental histories of prediabetes in children of individuals with early coronary heart disease. Cardiology. 2017; 57(6): 16-21. doi : 10.18087/cardio.2019.7.10266.

Konnov MV, Deev AD Own and parental predictors of prediabetes in children of individuals with early coronary heart disease. Cardiology. 2017; 57(6): 16-21. doi : 10.18087/cardio.2019.7.10266 [in Russian].

Liu YS, Kim SY, Bae HY et al. Prevalence and Risk Factors for Undiagnosed Glucose Intolerance Status in Apparently Healthy Young Adults Aged <40 Years: The Korean National Health and Nutrition Examination Survey 2014-2017. Int J Environ Res Public Health. 2019; 16(13). pi : E2393. doi: 10.3390/ijerph16132393.

Wang L., Gao P., Zhang M. et al. Prevalence and Ethnic Pattern of Diabetes and Prediabetes in China in 2013. JAMA. 2017; 27:2515-2523. doi: 10.1001/jama.2017.7596.

Younes N., Atallah M., Alam R. et al. HbA1c and blood pressure measurements: relationship with gender, body mass index, study field and lifestyle in Lebanese students. Endocr Practice. 2019; 25(11): 1101-1108. doi: 10.4158/EP-2019-0163.

Fazli GS, Moineddin R., Bierman AS et al. Ethnic differences in prediabetes incidence among immigrants to Canada: a population-based cohort study. BMC Med. 2019; 17(1): 100. doi: 10.1186/s12916-019-1337-2.

Dedov I.I., Shestakova M.V., Galstyan G.R. The prevalence of type 2 diabetes mellitus in the adult population of Russia (NATION study). diabetes mellitus. 2016; 19(2): 104-112. doi:10.1016/ j.diabres . 2016.02.010.

Dedov I., Shestakova M., Galstyan G. The prevalence of type 2 diabetes mellitus in the adult population of Russia (NATION study). Diabetes. 2016; 19(2): 104-112. doi:10.1016/j.diabres.2016.02.010 [in Russian].

Breyer MK, Offenheimer A., Altziebler J. et al. Marked differences in prediabetes and diabetes associated comorbidities between men and women — epidemiological results from a general population-based cohort aged 6-80 years — the LEAD (Lung, heart, social, body) study. Eur J Clin Invest. 2020:e13207. doi: 10.1111/eci.13207.

Al Amri T., Bahijri S., Al- Raddadi R. et al. The Association Between Prediabetes and Dyslipidemia Among Attendants of Primary Care Health Centers in Jeddah, Saudi Arabia. Diabetes Metab Syndr Obese. 2019; 12: 2735-2743. doi: 10.2147/DMSO.S233717.