Influence of Family History of Diabetes Mellitus, Menopausal Status, and Physical Activity on Insulin Resistance in Indonesian Non-diabetic Women: A Cross-sectional Study
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Abstract
Background: Insulin resistance (IR) is a common complication of type 2 diabetes mellitus (T2DM). Women's risk of IR increases significantly after menopause. This Study aimed to determine the risk of IR and related risk variables in non- diabetic women. Methods: This cross-sectional study was conducted in East Java, Indonesia, between June - August 2024. Participants were 196 nondiabetic women selected using consecutive method. This study used a questionnaire and the FINDRISC tool. Results: The average FINDRISC score of respondents was 10.4. There were five risk categories for IR: low (24.3%), moderate (15.5%), high (24.3%), slightly increased (33.7%), and extremely high (2.2%). The FINDRISC score was significantly correlated with menopausal status, smoking, history of hypertension, and family history of DM (p-value = 0.000, p < α). Multivariate test results showed that age, menopausal status, waist circumference (WC), body mass index (BMI), physical activity, and family history of DM can significantly be used to predict the risk of insulin resistance (p-value = 0.000, p < α). Menopausal status (Coef. B = 3.489), lack of physical activity (Coef. B = 1.262), and family history of DM (Coef. B = 3.715) were the three factors that were most significant in predicting the likelihood of IR. Conclusion: The risk of IR is projected to increase with age, WC, BMI, and family history of DM and to decrease with increasing physical activity.
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Rosenberg M, Tomioka S, Barber SL. Research to inform health systems’ responses to rapid population ageing: a collection of studies funded by the WHO Centre for Health Development in Kobe, Japan. Heal Res Policy Syst [Internet]. 2022;20(1):1–6. Available from: https://doi.org/10.1186/s12961-022-00917-z
Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract [Internet]. 2019;157:107843. Available from: https://doi.org/10.1016/j.diabres.2019.107843
Hotta N, Hori A, Okamura Y, Baba R, Watanabe H, Sugawara J, et al. Insulin resistance is associated with an exaggerated blood pressure response to ischemic rhythmic handgrip exercise in nondiabetic older adults. J Appl Physiol. 2020;129(1):144–51.
Zhao W, Diao H, Chen X, Xu S, Jiang S, Cao H, et al. The serum oestradiol/progesterone ratio on the day of OPU + 7, but not the day of OPU + 5, affects the rates of live birth in fresh blastocyst embryo transfer cycles. J Ovarian Res [Internet]. 2023;16(1):1–10. Available from: https://doi.org/10.1186/s13048-023-01096-3
Magliano D, Boyko E. IDF diabetes atlas [Internet]. 10th editi. International Diabetes Federation; 2021. Available from: https://diabetesatlas.org/atlas/tenthedition/
Goh LPW, Sani SA, Sabullah MK, Gansau JA. The Prevalence of Insulin Resistance in Malaysia and Indonesia: An Updated Systematic Review and Meta-Analysis. Med. 2022;58(6).
Ciarambino T, Crispino P, Guarisco G, Giordano M. Gender Differences in Insulin Resistance: New Knowledge and Perspectives. Curr Issues Mol Biol. 2023;45(10):7845–61.
Lee SH, Park SY, Choi CS. Insulin Resistance: From Mechanisms to Therapeutic Strategies. Diabetes Metab J. 2022;46(1):15–37.
Sigit FS, Tahapary DL, Trompet S, Sartono E, Willems Van Dijk K, Rosendaal FR, et al. The prevalence of metabolic syndrome and its association with body fat distribution in middle-aged individuals from Indonesia and the Netherlands: A cross-sectional analysis of two population-based studies. Diabetol Metab Syndr [Internet]. 2020;12(1):1–11. Available from: https://doi.org/10.1186/s13098-019-0503-1
Verma A, Malhotra A, Ranjan P, Kumari A, Chopra S, Khan MA, et al. A comprehensive evaluation of predictors of obesity in women during the perimenopausal period: A systematic review and narrative synthesis. Diabetes Metab Syndr Clin Res Rev [Internet]. 2024;18(1):102933. Available from: https://doi.org/10.1016/j.dsx.2023.102933
Numao S, Katayama Y, Nakata Y, Matsuo T, Nakagaichi M, Tanaka K. Association of abdominal fat with metabolic syndrome components in overweight women: Effect of menopausal status. J Physiol Anthropol. 2020;39(1):1–8.
Elsayed MM, El Refaye GE, Rabiee A, Abouzeid S, Elsisi HF. Aerobic exercise with diet induces hormonal, metabolic, and psychological changes in postmenopausal obese women. Heliyon [Internet]. 2022;8(3):e09165. Available from: https://doi.org/10.1016/j.heliyon.2022.e09165
Lee SM, Ryu KJ, Son S, Lee YJ, Park H, Kim T. Body fat distribution and insulin resistance among Korean middle-aged women: a Korean National Health and Nutrition Examination Survey. Obstet Gynecol Sci. 2022;65(5):468–76.
Zhao X, An X, Yang C, Sun W, Ji H, Lian F. The crucial role and mechanism of insulin resistance in metabolic disease. Front Endocrinol (Lausanne). 2023;14(March).
Abdallah M, Sharbaji S, Sharbaji M, Daher Z, Faour T, Mansour Z, et al. Diagnostic accuracy of the Finnish Diabetes Risk Score for the prediction of undiagnosed type 2 diabetes, prediabetes, and metabolic syndrome in the Lebanese University. Diabetol Metab Syndr [Internet]. 2020;12(1):1–11. Available from: https://doi.org/10.1186/s13098-020-00590-8
Mohammed Saleem S, Salim Khan SM, Sumaya Jan S. Finnish Diabetic Risk Score- A Tool For Predicting Risk Of Undiagnosed Type 2 Diabetes Mellitus. Ann Med Heal Sci Res [Internet]. 2017;9(3):39–42. Available from: https://www.amhsr.org/articles/finnish-diabetic-risk-score-a-tool-for-predicting-risk-of-undiagnosed-type-2-diabetes-mellitus.pdf
Jølle A, Midthjell K, Holmen J, Carlsen SM, Tuomilehto J, Bjørngaard JH, et al. Validity of the FINDRISC as a prediction tool for diabetes in a contemporary Norwegian population: A 10-year follow-up of the HUNT study. BMJ Open Diabetes Res Care. 2019;7(1):1–9.
Tarigan M, Setiawan, Tarigan R, Imelda F, Jongudomkarn D. Identifying diabetes risks among Indonesians: A cross-sectional study in a community setting. Belitung Nurs J. 2024;10(1):41–7.
Kehm R, Kluth O, Schürmann A, Grune T, Höhn A. The role of aging and senescence on pancreatic β-cell function and proliferation. Free Radic Biol Med. 2017;108:S71.
De Tata V. Age-related impairment of pancreatic beta-cell function: Pathophysiological and cellular mechanisms. Front Endocrinol (Lausanne). 2014;5(SEP):1–8.
Shou J, Chen PJ, Xiao WH. Mechanism of increased risk of insulin resistance in aging skeletal muscle. Diabetol Metab Syndr [Internet]. 2020;12(1):1–10. Available from: https://doi.org/10.1186/s13098-020-0523-x
Freitas RDS, Maria C, Silva DS, Fratelli CF, Lima LR De, Stival MM, et al. Syndrome : Insights into Older Adults ’ Clinical Characteristics. 2024;16(1241):1–13.
Zhang Y, Xu L, Liu X, Wang Y. Evaluation of insulin sensitivity by hyperinsulinemic-euglycemic clamps using stable isotope-labeled glucose. Cell Discov [Internet]. 2018;4(1):4–7. Available from: http://dx.doi.org/10.1038/s41421-018-0016-3
Chia CW, Egan JM, Ferrucci L. Age-related changes in glucose metabolism, hyperglycemia, and cardiovascular risk. Circ Res. 2018;123(7):886–904.
Abildgaard J, Tingstedt J, Zhao Y, Hartling HJ, Pedersen AT, Lindegaard B, et al. Increased systemic inflammation and altered distribution of T-cell subsets in postmenopausal women. PLoS One. 2020;15(6).
De Paoli M, Zakharia A, Werstuck GH. The Role of Estrogen in Insulin Resistance: A Review of Clinical and Preclinical Data. Am J Pathol [Internet]. 2021;191(9):1490–8. Available from: https://doi.org/10.1016/j.ajpath.2021.05.011
Ntikoudi A, Spyrou A, Evangelou E, Dokoutsidou E, Mastorakos G. The Effect of Menopausal Status, Insulin Resistance and Body Mass Index on the Prevalence of Non-Alcoholic Fatty Liver Disease. Healthc. 2024;12(1081):1–17.
Biteli P, Barbalho SM, Detregiachi CRP, dos Santos Haber JF, Chagas EFB. Dyslipidemia influences the effect of physical exercise on inflammatory markers on obese women in post-menopause: A randomized clinical trial. Exp Gerontol. 2021;150(111355):1–6.
Kamińska MS, Lubkowska A, Panczyk M, Walaszek I, Grochans S, Grochans E, et al. Relationships of Body Mass Index, Relative Fat Mass Index, and Waist Circumference with Serum Concentrations of Parameters of Chronic Inflammation. Nutrients. 2023;15(2789).
Mohallem R, Aryal UK. Regulators of TNFα mediated insulin resistance elucidated by quantitative proteomics. Sci Rep [Internet]. 2020;10(1):1–15. Available from: https://doi.org/10.1038/s41598-020-77914-1
Sethi JK, Hotamisligil GS. Metabolic Messengers: tumour necrosis factor. Nat Metab. 2021;3(10):1302–12.
Sasaki R, Yano Y, Yasuma T, Onishi Y, Suzuki T, Maruyama-Furuta N, et al. Association of waist circumference and body fat weight with insulin resistance in male subjects with normal body mass index and normal glucose tolerance. Intern Med. 2016;55(11):1425–32.
Chait A, den Hartigh LJ. Adipose Tissue Distribution, Inflammation and Its Metabolic Consequences, Including Diabetes and Cardiovascular Disease. Front Cardiovasc Med. 2020;7(22):1–41.
Deusdará R, Souza A de M, Szklo M. Association between Obesity, Overweight, Elevated Waist Circumference, and Insulin Resistance Markers among Brazilian Adolescent Students. Nutrients [Internet]. 2022;14(3487):1–11. Available from: https://www.mdpi.com/2072-6643/14/17/3487
Lin Y, Fan R, Hao Z, Li J, Yang X, Zhang Y, et al. The Association Between Physical Activity and Insulin Level Under Different Levels of Lipid Indices and Serum Uric Acid. Front Physiol. 2022;13(February).
Kjøbsted R, Roll JLW, Jørgensen NO, Birk JB, Foretz M, Viollet B, et al. AMPK and TBC1D1 regulate muscle glucose uptake after, but not during, exercise and contraction. Diabetes. 2019;68(7):1427–40.
Esquejo RM, Albuquerque B, Sher A, Blatnik M, Wald K, Peloquin M, et al. AMPK activation is sufficient to increase skeletal muscle glucose uptake and glycogen synthesis but is not required for contraction-mediated increases in glucose metabolism. Heliyon [Internet]. 2022;8(10):e11091. Available from: https://doi.org/10.1016/j.heliyon.2022.e11091
Friedenreich CM, Neilson HK, Wang Q, Stanczyk FZ, Yasui Y, Brenner DR, et al. Exercise Dose Effects on Insulin Resistance Indicators in Postmenopausal Women: A Randomized Trial. J Endocrinol Metab. 2016;6(2):35–45.
Lloyd JW, Evans KA, Zerfass KM, Holmstrup ME, Kanaley JA, Keslacy S. Effect of an acute bout of aerobic exercise on chemerin levels in obese adults [Internet]. Vol. 10, Diabetes & Metabolic Syndrome: Clinical Research & Reviews. Elsevier BV; 2016. p. 37–42. Available from: http://dx.doi.org/10.1016/j.dsx.2015.04.010
Bird SR, Hawley JA. Update on the effects of physical activity on insulin sensitivity in humans. BMJ Open Sport Exerc Med. 2017;2(1):1–26.
Syeda USA, Battillo D, Visaria A, Malin SK. The importance of exercise for glycemic control in type 2 diabetes. Am J Med Open. 2023;9(April 2022):100031.
Bennet L, Franks PW, Zöller B, Groop L. Family history of diabetes and its relationship with insulin secretion and insulin sensitivity in Iraqi immigrants and native Swedes: a population-based cohort study. Acta Diabetol [Internet]. 2018;55(3):233–42. Available from: https://doi.org/10.1007/s00592-017-1088-5
Gościk J, Bauer W, Wawrusiewicz‑Kurylonek N, Paczkowska‑Abdulsalam M, Niemira M, Citko A, et al. Efficacy of family history, genetic risk score, and physical activity in assessing the prevalence of type 2 diabetes. Polish Arch Intern Med. 2019;129(7–8):442–50.
Van Gemert WA, Monninkhof EM, May AM, Peeters PH, Schuit AJ. Effect of exercise on insulin sensitivity in healthy postmenopausal women: The SHAPE study. Cancer Epidemiol Biomarkers Prev. 2015;24(1):81–7.
Tremblay J, Hamet P. Environmental and genetic contributions to diabetes. Metabolism. 2019;100:1–6.
Brown AE, Walker M. Genetics of Insulin Resistance and the Metabolic Syndrome. Curr Cardiol Rep [Internet]. 2016;18(8). Available from: http://dx.doi.org/10.1007/s11886-016-0755-4