Correlation of lipid profile, glucose, and body composition on insulin resistance in overweight and obese subjects

Fatmayanti Nawai -  Department of Nutrition, Gorontalo Polytechnic of Health of Ministry of Health, Indonesia
Ahmad Syauqy* -  Department of Nutrition Science, Faculty of Medicine, Diponegoro University, Indonesia
Adriyan Pramono -  Department of Nutrition Science, Faculty of Medicine, Diponegoro University, Indonesia
DOI : 10.30867/action.v9i1.1571

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Indonesia has the highest prevalence of obesity in the Asia-Pacific region. Insulin resistance is a form of obesity that causes damage to the liver, heart, and pancreatic tissue as we age. This study aimed to determine the correlation among lipid profiles, glucose levels, body composition, and insulin resistance. Methods: This study used a pre-experimental design and was conducted at the Gorontalo Ministry of Health Polytechnic in February 2023 on 31 obese people whose venous blood was collected for examination of insulin resistance variables. Data were collected by purposive sampling with data analysis using Pearson Correlation and Spearman Rank statistical tests at a 95% confidence interval (CI). Results: Insulin resistance status based on sex, using the TyG index, was dominated by women (55%) among the 20 people who experienced insulin resistance. Men are more likely to be aged <30 years than women, according to the HOMA-IR index. The Pearson triglyceride test value (p= 0,000, r= 0,974) shows that the relationship between triglycerides and the TyG index was very strong, whereas when the HOMA-IR index was used, fasting insulin (p= 0,000, r= 0,985) had a very strong relationship. In conclusion, lipid profile (triglycerides, total cholesterol, LDL), fasting glucose, fasting insulin, and visceral fat percentage correlated with insulin resistance.

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Keywords : Insulin resistance, lipid profile, glucose blood, and body composition

  1. Abdurrosidi, A., Novitasari, D., & Khasanah, S. (2021). Hubungan Aktifitas Fisik dengan Kestabilan Tekanan Darah pada Penderita Hipertensi di UPTD Puskesmas I Kembaran Kabupaten Banyumas. https://prosiding.uhb.ac.id/index.php/SNPPKM/article/view/806
  2. Abenavoli, L., Scarpellini, E., Colica, C., Boccuto, L., Salehi, B., Sharifi-Rad, J., Aiello, V., Romano, B., De Lorenzo, A., Izzo, A. A., & Capasso, R. (2019). Gut microbiota and obesity: A role for probiotics. Nutrients, 11(11), 1–27. https://doi.org/10.3390/nu11112690
  3. Al Rahmad, A. H. (2021). Hubungan Indeks Massa Tubuh dengan kolesterol, LDL, dan Trigliserida pada pasien jantung koroner di Kota Banda Aceh. Jurnal Kesehatan, 9(1), 1–8. https://doi.org/10.25047/jkes.v9i1.161
  4. Al-Thani, M. H., Al-Mutawa, K. A., Alyafei, S. A., Ijaz, M. A., Khalifa, S. A. H., Kokku, S. B., Mishra, A. C. M., Poovelil, B. V., Soussi, M. B., Toumi, A. A., Dargham, S. R., Awad, S. F., & Abu-Raddad, L. J. (2021). Characterizing epidemiology of prediabetes, diabetes, and hypertension in Qataris: A cross-sectional study. PLoS ONE, 16(10), 1–16. https://doi.org/10.1371/journal.pone.0259152
  5. Anggraeny, O., Ridhanti, D., & Nugroho, F. (2018). Tidak ada korelasi antara asupan karbohidrat sederhana, lemak jenuh, dan tingkat aktivitas fisik dengan status gizi pada remaja dengan kegemukan dan obesitas. AcTion: Aceh Nutrition Journal, 3(1), 1-8. http://dx.doi.org/10.30867/action.v3i1.89
  6. Anyanwu, O. A., Folta, S. C., Zhang, F. F., Chui, K., Chomitz, V. R., Kartasurya, M. I., & Naumova, E. N. (2022). A Cross-Sectional Assessment of Dietary Patterns and Their Relationship to Hypertension and Obesity in Indonesia. Current Developments in Nutrition, 6(6), nzac091. https://doi.org/10.1093/cdn/nzac091
  7. Apidechkul, T., Chomchiei, C., Upala, P., & Tamornpark, R. (2022). Epidemiology of prediabetes mellitus among hill tribe adults in Thailand. PLoS ONE, 17(7), 1–13. https://doi.org/10.1371/journal.pone.0271900
  8. Apovian, C. M. (2016). Obesity: definition, comorbidities, causes, and burden. The American Journal of Managed Care, 22(7), s176–s185. https://pubmed.ncbi.nlm.nih.gov/27356115/
  9. Atlas, I. D. F. D. (2019). IDF Diabetes Atlas Ninth edition 2019. In International Diabetes Federation, 266(6881). https://doi.org/10.1016/S0140-6736(55)92135-8
  10. Aydo, O., & Kutlutu, S. (2023). Physical literacy as a determinant of physical activity level among late adolescents. PLoS ONE, 28(4), 1–11. https://doi.org/10.1371/journal.pone.0285032
  11. Chan, M. (2016). Global Report on Diabetes. In WHO Global report on diabetes: A summary. https://www.who.int/publications/i/item/9789241565257
  12. Chang, C., Jian, D., Lin, M., Zhao, J., & Ho, L. (2015). Evidence in obese children: Contribution of hyperlipidemia, obesity-inflammation, and insulin sensitivity. PLoS ONE, 26(5), 1–12. https://doi.org/10.1371/journal.pone.0125935
  13. Chen, L. W., Chen, P. H., & Yen, J. H. (2021). Inhibiting adipose tissue M1 cytokine expression decreases DPP4 activity and insulin resistance in a type 2 diabetes mellitus mouse model. PLoS ONE, 16(5), 1–21. https://doi.org/10.1371/journal.pone.0252153
  14. Dahlan M. Sopiyudin. (2016). Statistik Untuk Kedokteran dan Kesehatan. Penerbit Salemba Medika.
  15. de Cassia da Silva, C., Zambon, M. P., Vasques, A. C. J., Camilo, D. F., De Bernardi Rodrigues, A. M., de Góes Monteiro Antonio, M. Â. R., Dâmaso, A. R., Tufik, S., de Mello, M. T., da Silveira Campos, R. M., & Geloneze, B. (2019). Homeostatic model assessment of adiponectin (HOMA-Adiponectin) as a surrogate measure of insulin resistance in adolescents: Comparison with the hyperglycaemic clamp and homeostatic model assessment of insulin resistance. PLoS ONE, 14(3), 1–12. https://doi.org/10.1371/journal.pone.0214081
  16. Dornelles, A. (2019). Impact of multiple food environments on body mass index. PLoS ONE, 7(8), 1–14. https://doi.org/10.1371/journal.pone.0219365
  17. Er, L. K., Wu, S., Chou, H. H., Hsu, L. A., Teng, M. S., Sun, Y. C., & Ko, Y. L. (2016). Triglyceride glucose-body mass index is a simple and clinically useful surrogate marker for insulin resistance in nondiabetic individuals. PLoS ONE, 11(3), 1–12. https://doi.org/10.1371/journal.pone.0149731
  18. Ge, Y., Wei, C., Rajavel Arumugam, U., Wu, Y., & Cao, L. K. (2023). Quinoa bran insoluble dietary fiber-zinc chelate mediates intestinal flora structure to regulate glucose and lipid metabolism in obese rats. Journal of Functional Foods, 108(105765), 1–12. https://doi.org/10.1016/j.jff.2023.105765
  19. Han, T., Yuan, T., Liang, X., Chen, N., Song, J., Zhao, X., Weng, Y., & Hu, Y. (2022). Sarcopenic obesity with normal body size may have higher insulin resistance in elderly patients with type 2 diabetes mellitus. Diabetes, Metabolic Syndrome and Obesity, 15(April), 1197–1206. https://doi.org/10.2147/DMSO.S360942
  20. Jung, S. H., Ha, K. H., & Kim, D. J. (2016). Visceral fat mass has stronger associations with diabetes and prediabetes than other anthropometric obesity indicators among Korean adults. Yonsei Medical Journal, 57(3), 674–680. https://doi.org/10.3349/ymj.2016.57.3.674
  21. Kemenkes RI. (2018). Hasil Riset Kesehatan Dasar Tahun 2018. Kementrian Kesehatan RI, 53(9), 1689–1699.
  22. Kim, K. A., Gu, W., Lee, I. A., Joh, E. H., & Kim, D. H. (2012). High fat diet-induced gut microbiota exacerbates inflammation and obesity in mice via the TLR4 Signaling pathway. PLoS ONE, 7(10), 1–11. https://doi.org/10.1371/journal.pone.0047713
  23. Kim, S. J., Ye, S., Ha, E., & Chun, E. M. (2018). Association of body mass index with incident tuberculosis in Korea. PLoS ONE, 18(April), 1–12. https://doi.org/10.1371/journal.pone.0195104
  24. Krol, H., Gozdz, S., & Zak, M. (2020). Optimal body fat percentage cut-off values in predicting the obesity-related cardiovascular risk factors : A cross-sectional cohort study. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, 13, 1587–1597.
  25. Labatjo, R., Tumenggung, I., & Rahmad, A. H. Al. (2023). Insulin resistance, visceral fat, and vitamin D in overweight and obesity adolescents. Universal Journal of Public Health, 11(4), 463–471. https://doi.org/10.13189/ujph.2023.110411
  26. Liang, X., Chen, X., Li, J., Yan, M., & Yang, Y. (2018). Study on body composition and its correlation with obesity. Medicine (United Kingdom), 97(21), 1–6. https://doi.org/10.1097/MD.0000000000010722
  27. Liberty, I. A., Kodim, N., Sartika, R. A. D., Trihandini, I., Tjekyan, R. M. S., Zulkarnain, Pane, M., Pratisthita, L. B., Tahapary, D. L., & Soewondo, P. (2021). Triglyceride/Glucose Index (TyG Index) as a marker of glucose status conversion among reproductive-aged women in Jakarta, Indonesia: The Bogor cohort study (2011–2016). Diabetes and Metabolic Syndrome: Clinical Research and Reviews, 15(6), 1–19. https://doi.org/10.1016/j.dsx.2021.102280
  28. Lisnawati, N., Kusmiyati, F., Herwibawa, B., Kristanto, B. A., & Rizkika, A. (2023). Hubungan indeks massa tubuh, persen lemak tubuh, dan aktivitas fisik dengan kadar gula darah remaja. Journal of Nutrition College, 12(4), 168–178.
  29. Liu, C., Shao, M., Lu, L., Zhao, C., Qiu, L., & Liu, Z. (2021). Obesity, insulin resistance and their interaction on liver enzymes. PLoS ONE, 16(4 April), 1–9. https://doi.org/10.1371/journal.pone.0249299
  30. Ludwig, D. S., & Ebbeling, C. B. (2018). The carbohydrate-insulin model of obesity: Beyond “calories in, calories out.” JAMA Internal Medicine, 178(8), 1098–1103. https://doi.org/10.1001/jamainternmed.2018.2933
  31. Michille, Situmorang, S., & Hanida, W. (2022). Hubungan Karakteristik pasien diabetes melitus tipe 2 dengan lipid profile di RS Royal Prima tahun 2021. Jambura Journal of Health Science and Research, 5(1), 42–50. https://doi.org/10.35971/jjhsr.v5i1.16828
  32. Mishra, A., Ruano, S. H., Saha, P. K., & Pennington, K. A. (2022). A novel model of gestational diabetes: Acute high fat high sugar diet results in insulin resistance and beta cell dysfunction during pregnancy in mice. PLoS ONE, 17(12 December), 1–16. https://doi.org/10.1371/journal.pone.0279041
  33. Molli, A. E. I., Panero, J., Dos Santos, P. C., González, C. D., Vilariño, J., Sereday, M., Cerrone, G. E., Slavutsky, I., & Frechtel, G. D. (2017). Metabolically healthy obese women have longer telomere length than obese women with metabolic syndrome. PLoS ONE, 12(4), 1–13. https://doi.org/10.1371/journal.pone.0174945
  34. Paleva, R., Dokter, P., Kedokteran, F., & Lampung, U. (2019). Literatur review mekanisme resistensi insulin terkait obesitas pendahuluan metode hasil dan pembahasan. Jurnal Kesehatan Sandi Husada, 10(2), 354–358. https://doi.org/10.35816/jiskh.v10i2.190
  35. Perkin, O. J., Mcguigan, P. M., Thompson, D., & Stokes, K. A. (2018). Habitual physical activity levels do not predict leg strength and power in healthy, active older adults. PLoS ONE, 2(July), 1–12.
  36. Rahmad, A. H. Al. (2020). Korelasi IMT dengan peningkatan profil lipid darah pada pasien jantung koroner. Jurnal Vokasi Kesehatan, 6(2), 94–99. https://doi.org/10.30602/jvk.v6i2.563
  37. Ramdas, N. V. K., Nayak, K. R., Vidyasagar, S., & Kamath, A. (2018). Body composition analysis, anthropometric indices and lipid profile markers as predictors for prediabetes. PLoS ONE, 13(8), 1–14. https://doi.org/10.1371/journal.pone.0200775
  38. Singh, R. K., Kumar, P., & Mahalingam, K. (2017). Molecular genetics of human obesity: A comprehensive review. Comptes Rendus - Biologies, 340(2), 87–108. https://doi.org/10.1016/j.crvi.2016.11.007
  39. Sun, A. R. J., Panchal, S. K., Friis, T., Sekar, S., Crawford, R., Brown, L., Xiao, Y., & Prasadam, I. (2017). Obesity-associated metabolic syndrome spontaneously induces infiltration of pro-inflammatory macrophage in synovium and promotes osteoarthritis. PLoS ONE, 12(8), 1–22. https://doi.org/10.1371/journal.pone.0183693
  40. Téllez-Rojo, M. M., Trejo-Valdivia, B., Roberts, E., Muñoz-Rocha, T. V., Bautista-Arredondo, L. F., Peterson, K. E., & Cantoral, A. (2019). Influence of post-partum BMI change on childhood obesity and energy intake. PLoS ONE, 14(12), 1–16. https://doi.org/10.1371/journal.pone.0224830
  41. Tjandrawinata, R. R. (2016). Patogenesis Diabetes Tipe 2 : Resistensi Insulin dan Defisiensi Insulin. Dlbs, February, 1–4. https://doi.org/https://www.researchgate.net/publication/292615802 Patogenesis
  42. Wang, L., Lv, S., Li, F., Yu, X., Bai, E., & Yang, X. (2020). Vitamin D deficiency is associated with metabolic risk factors in women with polycystic ovary syndrome: A Cross-sectional study in Shaanxi China. Frontiers in Endocrinology, 11(March), 1–7. https://doi.org/10.3389/fendo.2020.00171

Open Access Copyright (c) 2024 Fatmayanti Nawai, Ahmad Syauqy, Adriyan Pramono
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AcTion: Aceh Nutrition Journal
Published by: Department of Nutrition at the Health Polytechnic of Aceh, Ministry of Health.
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