METABOLIC AND CARDIOVASCULAR RISK FACTORS IN YOUNG ADULTS WITH TYPE 2 DIABETES: THE ROLE OF LIPID ABNORMALITIES AND FAMILY HISTORY
DOI:
https://doi.org/10.22159/ajpcr.2025v18i9.55139Keywords:
Diabetes, lipid abnormalities, cardiovascular risk, family historyAbstract
Objective: Cardiovascular diseases (CVDs) are a major cause of illness and death worldwide, with dyslipidemia and insulin resistance contributing significantly to their development. Although these metabolic conditions were once considered prevalent mainly in older adults, these conditions are increasingly seen in younger populations due to lifestyle changes, obesity, and genetics. Early identification of high-risk individuals is crucial, yet research on these conditions in young adults is limited.
Objective: This study aimed to investigate the relationship between lipid profiles, insulin resistance, and cardiovascular risk factors in young adults, especially those with a family history of diabetes.
Methods: A cross-sectional case–control study involved 200 participants (aged 25–35 years), including 70 diabetic patients with a family history, 70 without, and 60 healthy controls. Cardiovascular and metabolic parameters, including waist circumference, body mass index, blood pressure, triglycerides (TG), high-density lipoprotein (HDL), total cholesterol, fasting blood sugar (FBS), hemoglobin A1c (HbA1c), and TG/HDL ratio, were measured. Insulin resistance was assessed using the homeostatic model assessment of insulin resistance (HOMA-IR).
Results: Significant differences in metabolic and cardiovascular parameters were observed between diabetic patients and controls, especially in those with a family history. Diabetic patients with a family history had systolic blood pressure (131.5±12.90 vs. 121±16.9), TG (183.4±114.9 vs. 114±54.3), FBS (128.9±31.14 vs. 97.4±21.6), HbA1c (6.06±0.8 vs. 5.39±0.44), and TG/HDL ratio (4.22±2.42 vs. 1.04±0.28). A positive correlation was found between HOMA-IR and FBS, HbA1c, insulin levels, and TG, indicating a strong link between insulin resistance and these metabolic disturbances.
Conclusion: The findings highlight the importance of early metabolic health assessments and interventions, particularly for young adults with a family history of diabetes, to reduce CVD risk. Further research is needed to explore the long-term cardiovascular impacts of early metabolic dysfunction.
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References
1. Jyotsna F, Ahmed A, Kumar K, Kaur P, Chaudhary MH, Kumar S, et al. Exploring the complex connection between diabetes and cardiovascular disease: Analyzing approaches to mitigate cardiovascular risk in patients with diabetes. Cureus. 2023 Aug 21;15(8):e43882. doi: 10.7759/cureus.43882, PMID 37746454
2. Behera BP, Sen RK. A study on the prevalence of thyroid dysfunction in patients with type 2 diabetes mellitus in a tertiary centre in a tribal population of Eastern India. Int J Pharm Pharm Sci. 2023;15(6):29-34. doi: 10.22159/ijpps.2023v15i6.48019
3. Kamalesh DR, Geetha KM. A review on role of markers in diabetes mellitus and associated micro and macrovascular complications. Int J Curr Pharm Res. 2022;14(1):20-6.
4. Jacobsen AP, Whelton SP, Blumenthal RS, Mcevoy JW. Dyslipidemia. In: Hypertension. Netherlands: Elsevier; 2024. p. 476-88.
5. Courtney CH, Olefsky JM. Insulin Resistance. In: Mechanisms of
Insulin Action. New York: Springer New York; 2007. p. 185-209. Available from: https://link.springer.com/10.1007/978-0-387-72204- 7_10 [Last accessed on 2024 Nov 19].
6. Sarkar S, Sadhu S, Roy R, Tarafdar S, Mukherjee N, Sil M, et al. Contemporary drifts in diabetes management. Int J App Pharm. 2023;15(2):1-9. doi: 10.22159/ijap.2023v15i2.46792
7. Mithal A, Kotwal N, Joshi S. Diabetes Surging among India’s Young Adults: Here’s How to Navigate with Ease and Confidence; ET Special. Available from: https://economictimes.indiatimes.com/industry/ healthcare/biotech/diabetes/surging/among/indias/young/adults/heres/ how/to/navigate/with/ease/and/confidence/articleshow/107206226. cms?utm_source=contentofinterest&utm_medium=text&utm_ campaign=cppst [Last accessed on 2024 Jan 29].
8. Van Sluijs EM, Ekelund U, Crochemore-Silva I, Guthold R, Ha A, Lubans D, et al. Physical activity behaviours in adolescence: Current evidence and opportunities for intervention. Lancet. 2021 Jul;398(10298):429-42. doi: 10.1016/S0140-6736(21)01259-9, PMID 34302767
9. ElSayed NA, Aleppo G, Bannuru RR, Bruemmer D, Collins BS, Ekhlaspour L, et al. 2. Diagnosis and classification of diabetes: Standards of care in diabetes-2024. Diabetes Care. 2024 Jan 1;47 Suppl 1:S20-42. doi: 10.2337/dc23-S002.
10. Ramesh R, Pandurangan V, Madhavan S, Srinivasan D, Bhaskar E, Marappa L, et al. Comparison of fasting insulin level, homeostatic model of insulin resistance, and lipid levels between patients with primary hypertension and normotensive subjects. Rambam Maimonides Med J. 2022 Apr 26;13(2):e0009. doi: 10.5041/RMMJ.10468, PMID 35482462
11. Espinoza ZM, Ruiz FN, Barrios E, Reigosa A, Leal HU, González JC. Perfilmetabólico de riesgo cardiovascular y resistencia a la insulinasegúníndice de masa corporal. Rev Méd Chile. 2009 Sep;137(9):1179-86.
12. Pannacciulli N, Giorgino F, Martina RA, Resta O, Giorgino R, De Pergola G. Effect of family history of type 2 diabetes on white blood cell count in adult women. Obes Res. 2003 Oct;11(10):1232-7. doi: 10.1038/oby.2003.169, PMID 14569049
13. Bethelli S, Oroszi T. Role of LDL and triglycerides in hyperlipidemia in diabetes mellitus. J Fam Med Dis Prev. 2023;10(1):155. doi: 10.23937/2469-5793/1510155
14. Yadav SK, Pathak R, Singh RK, Mahato RV. Correlation of body mass index with waist circumference, random blood sugar and dietary pattern as predictors of diabetes mellitus. Int J Appl Sci Biotechnol. 2018 Oct 1;6(3):274-8. doi: 10.3126/IJASBT.V6I3.21177
15. Rashad NM, Abdelsamad MA, Amer AM, Sitohy MZ, Mousa MM. The impact of stevioside supplementation on glycemic control and lipid profile in patients with type 2 diabetes: A controlled clinical trial. Egypt J Intern Med. 2019 Mar;31(1):22-30. doi: 10.4103/ejim.ejim_68_18
16. Jha BK, Sherpa ML, Imran M, Mohammed Y, Jha LA, Paudel KR, et al. Progress in understanding metabolic syndrome and knowledge of its complex pathophysiology. Diabetology. 2023;4(2):134-59. doi: 10.3390/diabetology4020015
17. Taiwo EO, Thanni LO, Taiwo OP. Variations in anthropometric parameters in offspring of type 2 diabetes patients. Hosp Pract Res. 2022 Sep;7(3):119-22. doi: 10.34172/hpr.2022.24
18. Iqbal J, Chandio K, Memon AH, Hussain A, Talpur RA, Ali AA. Exploring the relationship between family history of type 2 diabetes mellitus and anthropometric, blood sugar, and lipid parameters in normal individuals: A comparative study. Prof Med J. 2023 Oct 5;30(10):1309-16. doi: 10.29309/TPMJ/2023.30.10.7561
19. Telles S, Pal S, Sharma SK, Singh A, Kala N, Balkrishna A. The association between the lipid profile and fasting blood glucose with weight related outcomes in healthy obese adults. BMC Res Notes. 2018 Dec;11(1):383. doi: 10.1186/s13104-018-3485-4, PMID 29898771
20. Hassani SS, Fallahi Arezodar FF, Esmaeili SS, Gholami-Fesharaki M. Effect of fenugreek use on fasting blood glucose, glycosylated hemoglobin, body mass index, waist circumference, blood pressure and quality of life in patients with type 2 diabetes mellitus: A randomized, double-blinded, placebo-controlled clinical trials. Galen Med J. 2019 Mar 30;8:e1432. doi: 10.31661/gmj.v8i0.1432, PMID 34466512
21. Sergi D, Spaggiari R, Dalla Nora E, Angelini S, Castaldo F, Omenetto A, et al. HOMA-IR and TyG index differ for their relationship with dietary, anthropometric, inflammatory factors and capacity to predict cardiovascular risk. Diabetes Res Clin Pract. 2025;222:112103. doi: 10.1016/j.diabres.2025.112103
22. Hsieh MH, Lin WY, Chien HH, Chien LH, Huang CK, Yang JF, et al. Waist circumference, Body mass index, serum uric acid, blood sugar, and triglyceride levels are important risk factors for abnormal liver function tests in the Taiwanese population. Kaohsiung J Med Sci. 2012 Sep;28(9):470-6. doi: 10.1016/j.kjms.2012.04.003, PMID 22974665
23. Nevill AM, Duncan MJ, Myers T. BMI is dead; Long live waist-circumference indices: But which index should we choose to predict cardio-metabolic risk? Nutr Metab Cardiovasc Dis. 2022 Jul;32(7):1642- 50. doi: 10.1016/j.numecd.2022.04.003, PMID 35525679
24. Amini S, Shirali S, Jafarirad S, Ehsani H, Mohseni H, Bargard MS. Are lipid profile, body mass index, waist circumference, and blood pressure of depressed elderly patients different from healthy subjects? Int J Prev Med. 2019;10(1):185. doi: 10.4103/ijpvm.IJPVM_372_17, PMID 32133103
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