ANALISIS BIBLIOMETRIK TENTANG PENGARUH IMT TERHADAP KADAR HIGH-DENSITY LIPOPROTEIN (HDL): STUDI SELAMA DUA DEKADE
BIBLIOMETRIC ANALYSIS OF THE INFLUENCE OF BODY MASS INDEX (BMI) ON HIGH-DENSITY LIPOPROTEIN (HDL) LEVELS: A TWO-DECADE STUDY
Abstract
Indeks Massa Tubuh (IMT) dan High-Density Lipoprotein (HDL) merupakan indikator penting dalam menilai status metabolik dan risiko kardiovaskular. Penelitian ini bertujuan memetakan tren publikasi ilmiah global terkait hubungan IMT dan HDL selama 2005–2025 menggunakan pendekatan bibliometrik. Data sekunder diperoleh dari Scopus, PubMed, dan Web of Science dengan kata kunci “Body Mass Index” OR “BMI” AND “High Density Lipoprotein” OR “HDL” AND “Original”. Sebanyak 312 artikel terkumpul, terdiri atas 91 dari Scopus, 215 dari PubMed, dan 6 dari WoS. Analisis menggunakan VOSviewer untuk memvisualisasi kolaborasi penulis, kata kunci, dan tren publikasi. Hasil menunjukkan peningkatan publikasi sejak 2010, dengan puncak pada 2020–2023. Negara kontributor utama adalah Amerika Serikat, Tiongkok, dan Inggris, sementara partisipasi negara berkembang mulai terlihat. Kata kunci dominan meliputi obesity, BMI, HDL, metabolic syndrome, dan cardiovascular risk. Mayoritas penelitian menyimpulkan peningkatan IMT berkaitan dengan penurunan HDL melalui mekanisme resistensi insulin, peningkatan VLDL, gangguan enzim lipid, inflamasi kronis, dan reverse cholesterol transport. Studi ini memetakan tren global, kontribusi negara, kolaborasi penulis, serta topik utama, sekaligus menunjukkan potensi celah penelitian untuk kajian lanjutan.Body Mass Index
References
Cheng Q, Wang Z, Zhong H, et al. Association of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and gallstones among US adults aged ≤ 50 years: a cross-sectional study from NHANES 2017–2020. Lipids Health Dis. 2024;23(1). doi:10.1186/s12944-024-02262-2
Hu L, Du H, Zhou QQ, Liu C, Zhang T, Yuan M. Web of Science-Based Visualization of Metabolic Dysfunction-Associated Fatty Liver Disease in Pediatric and Adolescent Populations: A Bibliometric Study. Heal Sci Reports. 2025;8(2). doi:10.1002/hsr2.70409
WHO. NCDs at a Glance 2025 NCDs surveillance and monitoring: Noncommunicable disease mortality and risk factor prevalence in the Americas. Published online 2025.
Asztalos, B. F., Russo, G., He, L., & Diffenderfer MR. Body Mass Index and Cardiovascular Risk Markers: A Large Population Analysis. Nutrients. Published online 2025. doi:https://doi.org/10.3390/nu17050740
Zyoud SH, Shakhshir M, Koni A, et al. Mapping the global research landscape on insulin resistance: Visualization and bibliometric analysis. World J Diabetes. 2022;13(9):786-798. doi:10.4239/wjd.v13.i9.786
Lee, S. H., Yun, K. E., & Kim YH. Effects of lifestyle interventions on HDL cholesterol in overweight and obese adults: A systematic review and meta-analysis. Obesity Reviews. Published online 2017. doi:https://doi.org/https://doi.org/10.1111/obr.12503
Khanna, D., Peltzer, C., Kahar, P., & Parmar MS. Body Mass Index (BMI): A Screening Tool Analysis. Cureus https://doi.org/107759/cureus22119. Published online 2022.
Che PY, Zuo CJ, Tian J. Global trends in esophageal cancer and metabolic syndrome research: bibliometric analysis and visualization from 1995 to 2024. Discov Oncol. 2025;16(1). doi:10.1007/s12672-025-02181-3
Dou Y, Guo X, Wang X, He A, Li F, Gao K. The research progress and prospects of circadian rhythm in obesity: a bibliometric analysis. Front Nutr. 2024;11(January):1-17. doi:10.3389/fnut.2024.1499984
Jomard, A., & Osto E. High Density Lipoproteins: Metabolism, Function, and Therapeutic Potential. Front Cardiovasc Med (Vol 7). Published online 2020. doi:https://doi.org/10.3389/fcvm.2020.00039
Wang Y, Liu T, Liu W, Zhao H, Li P. Research hotspots and future trends in lipid metabolism in chronic kidney disease: a bibliometric and visualization analysis from 2004 to 2023. Front Pharmacol. 2024;15(September):1-18. doi:10.3389/fphar.2024.1401939
Tang ZJ, Yang JR, Yu CL, Dong MH, Wang R, Li CX. A Bibliometric Analysis of Global Research Trends in Psoriasis and Metabolic Syndrome. Clin Cosmet Investig Dermatol. 2024;17:365-382. doi:10.2147/CCID.S446966
Peng T, Yang Y, Ma J, et al. Dementia and metabolic syndrome: a bibliometric analysis. Front Aging Neurosci. 2024;16(June):1-15. doi:10.3389/fnagi.2024.1400589
Zyoud SH. Mapping the landscape of research on insulin resistance: a visualization analysis of randomized clinical trials. J Health Popul Nutr. 2024;43(1):6. doi:10.1186/s41043-024-00497-4
Wang J, Huang W, Sun J, et al. Global trends in research on eating behaviors among overweight/obese children and adolescents: a bibliometric study from 2003 to 2023. Front Nutr. 2025;12(April):1-21. doi:10.3389/fnut.2025.1494920
Khunti, K., Gillies, C. L., Davies, M. J., & Webb DR. Association of HDL cholesterol with cardiovascular disease and mortality in type 2 diabetes. Diabet Med. Published online 2015. doi:https://doi.org/https://doi.org/10.1111/dme.12799
Bolat S, Yerlitaş Sİ, Cephe A, et al. A Bibliometric and Visual Analysis of Publications on Low-Density Lipoprotein Cholesterol Estimating Equations. Cumhur Sci J. 2024;45(4):648-657. doi:10.17776/csj.1452125
Šuran D, Blažun Vošner H, Završnik J, et al. Lipoprotein(a) in Cardiovascular Diseases: Insight From a Bibliometric Study. Front Public Heal. 2022;10(July):1-14. doi:10.3389/fpubh.2022.923797
Cheng Q, Sun J, Zhong H, et al. Research trends in lipid-lowering therapies for coronary heart disease combined with hyperlipidemia: a bibliometric study and visual analysis. Front Pharmacol. 2024;15(May):1-20. doi:10.3389/fphar.2024.1393333
Hou Y, An Z, Hou X, Guan Y, Song G. A bibliometric analysis and visualization of literature on non-fasting lipid research from 2012 to 2022. Front Endocrinol (Lausanne). 2023;14(April):1-13. doi:10.3389/fendo.2023.1136048
Simmons S, Hagan Jr J, Srem-Sai M, Schack T. From Numbers to Insights: Bibliometric Analysis of Obesity and Heart Disease Research Output. Med Res Arch. 2024;12(8):1-14. doi:10.18103/mra.v12i8.5438
Ibarra AC, Filippin-Monteiro FB. A Bibliometric Analysis on the Association Between Pesticides and Lipoprotein. J. 2025;8(2):14. doi:10.3390/j8020014
Wang L, Wang S, Song C, et al. Bibliometric analysis of residual cardiovascular risk: trends and frontiers. J Heal Popul Nutr. 2023;42(1):1-23. doi:10.1186/s41043-023-00478-z
Pu J, Zhao Y, Wu Y, et al. Global Research Trends and Hotspots in the Role of Cholesterol in Colorectal Cancer: A Bibliometric Analysis. Hum Mutat. 2025;2025(1). doi:10.1155/humu/6546114
Liang X, He H, Zeng H, et al. The relationship between polycystic ovary syndrome and coronary heart disease: a bibliometric analysis. Front Endocrinol (Lausanne). 2023;14(May):1-13. doi:10.3389/fendo.2023.1172750
Gao H, Wu J, Sun Z, et al. Influence of lecithin cholesterol acyltransferase alteration during different pathophysiologic conditions: A 45 years bibliometrics analysis. Front Pharmacol. 2022;13(December):1-19. doi:10.3389/fphar.2022.1062249
Yuan Y, Liu T, Yao Y, Ma Q, Sun L, Zhang G. Metabolic syndrome and bladder cancer risk: a comprehensive evidence synthesis combining bibliometric and meta-analysis approaches. BMC Urol. 2025;25(1). doi:10.1186/s12894-025-01812-9
Liu S, Fan B, Li X, Sun G. Global hotspots and trends in tea anti-obesity research: a bibliometric analysis from 2004 to 2024. Front Nutr. 2024;11(November). doi:10.3389/fnut.2024.1496582
Jovicic SM. Global trend of clinical biomarkers of health and disease during the period (1913–2021): systematic review and bibliometric analysis. African J Urol. 2021;27(1). doi:10.1186/s12301-021-00239-6
Zhou X, Kang C, Hu YH, Wang XC. Study on insulin resistance and ischemic cerebrovascular disease: A bibliometric analysis via CiteSpace. Front Public Heal. 2023;11. doi:10.3389/fpubh.2023.1021378
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