EVALUASI PARAMETER ANTROPOMETRI DAN BIOKIMIA SEBAGAI PREDIKTOR KOMPOSISI LEMAK TUBUH PADA LAKI-LAKI DEWASA
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Latar Belakang: Peningkatan prevalensi obesitas dan gangguan metabolik menekankan perlunya pendekatan skrining yang praktis, efektif, dan berbasis risiko. Peningkatan lemak subkutan berpotensi meningkatkan risiko penyakit-penyakit tidak menular seperti diabetes dan hipertensi, sehingga evaluasi parameter antropometri dan biokimia pada laki-laki dewasa memiliki nilai penting dalam memprediksi lemak subkutan Tujuan: Evaluasi antropometri dan biokimia darah metabolik dengan komposisi lemak tubuh pada laki-laki dewasa. Metode: Penelitian ini menggunakan desain observasional analitik dengan pendekatan potong lintang. Data dikumpulkan dari laki-laki dewasa yang menjalani pemeriksaan kesehatan rutin di Ujung Menteng, Cengkareng Timur, Grogol, Duri Kosambi, Tanjung Duren Selatan, dan Menteng Dalam periode Juni 2024 – Juni 2025. Parameter yang dinilai meliputi lingkar perut, lingkar panggul, rasio pinggang-pinggul (waist-to-hip ratio/WHR), tekanan darah, serta parameter biokimia seperti trigliserida, asam urat, HDL, dan LDL. Komposisi lemak subkutan diukur berdasarkan segmentasi tubuh melalui metode antropometri standar. Analisis korelasi Pearson digunakan untuk mengevaluasi hubungan antarvariabel. Hasil: Lingkar perut menunjukkan korelasi yang sangat kuat terhadap total lemak subkutan (r = 0,783; p < 0,001), menegaskan perannya sebagai indikator utama akumulasi lemak perifer. WHR dan lingkar panggul juga menunjukkan korelasi signifikan terhadap distribusi lemak tubuh. Parameter biokimia seperti kadar trigliserida menunjukkan korelasi positif terhadap seluruh area lemak subkutan (r = 0,280; p = 0,002), sedangkan tekanan darah diastolik berasosiasi signifikan dengan semua segmen lemak subkutan. Sebaliknya, asam urat, HDL, dan LDL tidak menunjukkan hubungan bermakna. Kesimpulan: Lingkar perut dan parameter biokimia dapat digunakan sebagai prediktor praktis terhadap komposisi lemak subkutan pada laki-laki dewasa. Implementasi skrining multifaktorial berbasis antropometri dan biokimia dapat menjadi pendekatan klinis yang efektif dalam deteksi dini risiko metabolik.
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Andersson, D. P., & Arner, P. (2025). Decreased Adipose Lipid Turnover Associates With Cardiometabolic Risk and the Metabolic Syndrome. Arteriosclerosis, Thrombosis, and Vascular Biology, 45(2), 277–284. https://doi.org/10.1161/ATVBAHA.124.321760
Bibi, S., Naeem, M., Mahmoud Mousa, M. F., Bahls, M., Dörr, M., Friedrich, N., Nauck, M., Bülow, R., Völzke, H., Markus, M. R., & Ittermann, T. (2024). Body composition markers are associated with changes in inflammatory markers but not vice versa: A bi-directional longitudinal analysis in a population-based sample. Nutrition, Metabolism and Cardiovascular Diseases, 34(5), 1166–1174. https://doi.org/10.1016/j.numecd.2024.01.008
Bogdanova, O. G., & Myl’nikova, I. V. (2020). Metabolic syndrome: situation in the world, clinical-diagnostic criteria and risk factors (review of literature). Hygiene and Sanitation, 99(10), 1165–1169. https://doi.org/10.47470/0016-9900-2020-99-10-1165-1169
da Cunha de Sá-Caputo, D., Sonza, A., Coelho-Oliveira, A. C., Pessanha-Freitas, J., Reis, A. S., Francisca-Santos, A., dos Anjos, E. M., Paineiras-Domingos, L. L., de Rezende Bessa Guerra, T., da Silva Franco, A., Xavier, V. L., Barbosa e Silva, C. J., Moura-Fernandes, M. C., Mendonça, V. A., Rodrigues Lacerda, A. C., da Rocha Pinheiro Mulder, A., Seixas, A., Sartorio, A., Taiar, R., & Bernardo-Filho, M. (2021). Evaluation of the Relationships between Simple Anthropometric Measures and Bioelectrical Impedance Assessment Variables with Multivariate Linear Regression Models to Estimate Body Composition and Fat Distribution in Adults: Preliminary Results. Biology, 10(11), 1209. https://doi.org/10.3390/biology10111209
Dhondge, R. H., Agrawal, S., Patil, R., Kadu, A., & Kothari, M. (2024). A Comprehensive Review of Metabolic Syndrome and Its Role in Cardiovascular Disease and Type 2 Diabetes Mellitus: Mechanisms, Risk Factors, and Management. Cureus. https://doi.org/10.7759/cureus.67428
Elguezabal Rodelo, R. G., Porchia, L. M., Torres‐Rasgado, E., López-Bayghen, E., & Gonzalez-Mejia, M. E. (2024). Viseral and subcutaneous abdominal fat is associated with non-alcoholic fatty liver disease while augmenting Metabolic Syndrome’s effect on non-alcoholic fatty liver disease: A cross-sectional study of NHANES 2017–2018. PLOS ONE, 19(2), e0298662. https://doi.org/10.1371/journal.pone.0298662
Goel, K., Misra, A., Vikram, N. K., Poddar, P., & Gupta, N. (2010). Subcutaneous abdominal adipose tissue is associated with the metabolic syndrome in Asian Indians independent of intra-abdominal and total body fat. Heart, 96(8), 579–583. https://doi.org/10.1136/hrt.2009.183236
Guo, L., Wei, C., Yi, L., Yang, W., Geng, Z., & Chen, X. (2021). Transcriptional Insights into Key Genes and Pathways Underlying Muscovy Duck Subcutaneous Fat Deposition at Different Developmental Stages. Animals, 11(7), 2099. https://doi.org/10.3390/ani11072099
Hassler, E. M., Deutschmann, H., Almer, G., Renner, W., Mangge, H., Herrmann, M., Leber, S., Michenthaler, M., Staszewski, A., Gunzer, F., Partl, R., & Reishofer, G. (2021). Distribution of subcutaneous and intermuscular fatty tissue of the mid-thigh measured by MRI—A putative indicator of serum adiponectin level and individual factors of cardio-metabolic risk. PLOS ONE, 16(11), e0259952. https://doi.org/10.1371/journal.pone.0259952
Jialal, I., & Devaraj, S. (2018). Subcutaneous adipose tissue biology in metabolic syndrome. Hormone Molecular Biology and Clinical Investigation, 33(1). https://doi.org/10.1515/hmbci-2017-0074
Kim, J. Y., Choi, J., Vella, C. A., Criqui, M. H., Allison, M. A., & Kim, N. H. (2022). Associations between Weight-Adjusted Waist Index and Abdominal Fat and Muscle Mass: Multi-Ethnic Study of Atherosclerosis. Diabetes & Metabolism Journal, 46(5), 747–755. https://doi.org/10.4093/dmj.2021.0294
Klimontov, V. V, Tyan, N. V, Fazullina, O. N., Myakina, N. E., Lykov, A. P., & Konenkov, V. I. (2016). Clinical and metabolic factors associated with chronic low-grade inflammation in type 2 diabetic patients. Diabetes Mellitus, 19(4), 295–302. https://doi.org/10.14341/DM7928
Kohir, D. S., Murhan, A., & Sulastri, S. (2024). Skrining Faktor Risiko Obesitas Usia Produktif. Jurnal Wacana Kesehatan, 9(2), 97. https://doi.org/10.52822/jwk.v9i2.673
Limareva, L. V, Ginzburg, M. M., Sazonova, O. V, Galitskaya, A. V, Danil’chenko, O. P., Bogush, V. V, & Yakunova, E. M. (2017). Assessment of the relationship of inflammation markers, adipokines and parameters of lipid metabolism in patient. Voprosy Pitaniia, 86(1), 41–47. https://doi.org/10.24411/0042-8833-2017-00019
Maqoud, F., Calabrese, F. M., Celano, G., Mallardi, D., Goscilo, F., D’Attoma, B., Ignazzi, A., Linsalata, M., Bitetto, G., Di Chito, M., Pesole, P. L., Diciolla, A., Apa, C. A., De Pergola, G., Giannelli, G., De Angelis, M., & Russo, F. (2024). Role of Increasing Body Mass Index in Gut Barrier Dysfunction, Systemic Inflammation, and Metabolic Dysregulation in Obesity. Nutrients, 17(1), 72. https://doi.org/10.3390/nu17010072
Mecherques-Carini, M., Albaladejo-Saura, M., Esparza-Ros, F., Baglietto, N., & Vaquero-Cristóbal, R. (2025). Validity between dual-energy x-ray absorptiometry and bioelectrical impedance for segmental fat analysis and a novel low-cost model developed using anthropometry in young adults. Journal of Translational Medicine, 23(1), 40. https://doi.org/10.1186/s12967-024-06062-1
Miyagi, T., Otagiri, K., Okawa, K., Oyama, Y., Sakai, T., & Kitabayashi, H. (2024). Abstract 4136677: High Viseral-to-Subcutaneous Fat Ratio is Correlated with Increased Cardiovascular Events in Patients with Low Waist Circumference Suspected of Coronary Artery Disease. Circulation, 150(Suppl_1). https://doi.org/10.1161/circ.150.suppl_1.4136677
Oliveira, B. R. de, Magalhães, E. I. da S., Bragança, M. L. B. M., Coelho, C. C. N. da S., Lima, N. P., Bettiol, H., Barbieri, M. A., Cardoso, V. C., Santos, A. M. dos, Horta, B. L., & Silva, A. A. M. da. (2023). Performance of Body Fat Percentage, Fat Mass Index and Body Mass Index for Detecting Cardiometabolic Outcomes in Brazilian Adults. Nutrients, 15(13), 2974. https://doi.org/10.3390/nu15132974
Oyama, Y., Otagiri, K., Miyagi, T., Sakai, T., & Kitabayashi, H. (2024). Impact of waist circumference and abdominal fat distribution on coronary artery disease severity stratified by computed tomography-derived SYNTAX score. European Heart Journal, 45(Supplement_1). https://doi.org/10.1093/eurheartj/ehae666.2885
Pereira-Junior, S. A. G., Costa, R. V, Rodrigues, J. L., Torrecilhas, J. A., Chiaratti, M. R., Lanna, D. P. D., das Chagas, J. C., Nociti, R. P., Meirelles, F. V, Ferraz, J. B. S., Fernandes, M. H. M. R., Almeida, M. T. C., & Ezequiel, J. M. B. (2024). Soybean molasses increases subcutaneous fat deposition while reducing lipid oxidation in the meat of castrated lambs. Journal of Animal Science, 102. https://doi.org/10.1093/jas/skae130
R Hithesh Sri, V., Ulavala, P., & Sravanthi, N. (2023). Understanding Metabolic Syndrome: Causes Symptoms and Risk Factors. International Journal of Science and Research (IJSR), 12(9), 1846–1848. https://doi.org/10.21275/MR23924092909
Raji, C. A., Meysami, S., Hashemi, S., Garg, S., Akbari, N., Gouda, A., Chodakiewitz, Y. G., Nguyen, T. D., Niotis, K., Merrill, D. A., & Attariwala, R. (2023). Viseral and Subcutaneous Abdominal Fat Predict Brain Volume Loss at Midlife in 10,001 Individuals. Aging and Disease. https://doi.org/10.14336/AD.2023.0820
Sattar, N., McGuire, D. K., & Gill, J. M. R. (2022). High Circulating Triglycerides Are Most Commonly a Marker of Ectopic Fat Accumulation: Connecting the Clues to Advance Lifestyle Interventions. Circulation, 146(2), 77–79. https://doi.org/10.1161/CIRCULATIONAHA.122.060411
Senyigit, A. (2025). General Aspects of Metabolic Syndrome: An Update on Diagnostic Criteria, Pathophysiology, and Management. In Metabolic Syndrome: A Comprehensive Update with New Insights (pp. 1–28). BENTHAM SCIENCE PUBLISHERS. https://doi.org/10.2174/9789815322132125010004
Torres, A. N., Tavares, L., Pereira, M. J., Eriksson, J. W., & Jones, J. G. (2023). Positional and compositional analysis of saturated, monounsaturated, and polyunsaturated fatty acids in human adipose tissue triglyceride by 13 C nuclear magnetic resonance. NMR in Biomedicine, 36(4). https://doi.org/10.1002/nbm.4632
Tsukagoshi‐Yamaguchi, A. (2023). Metabolomic Analysis of Serum Samples From a Clinical Study on Ipragliflozin and Metformin Treatment in Japanese Patients With Type 2 Diabetes: Exploring Human Metabolites Associated With Viseral Fat Reduction. Pharmacotherapy the Journal of Human Pharmacology and Drug Therapy. https://doi.org/10.1002/phar.2884
van Niekerk, E., Botha-Le Roux, S., Mels, C. M. C., Swanepoel, M., Delles, C., Welsh, P., & Kruger, R. (2024). Twenty-four-hour ambulatory, but not clinic blood pressure associates with leptin in young adults with overweight or obesity: The African-PREDICT study. Hypertension Research, 47(2), 478–486. https://doi.org/10.1038/s41440-023-01477-7
Wrammert, J., Koutsonanos, D., Li, G.-M., Edupuganti, S., Sui, J., Morrissey, M., McCausland, M., Skountzou, I., Hornig, M., Lipkin, W. I., Mehta, A., Razavi, B., Del Rio, C., Zheng, N.-Y., Lee, J.-H., Huang, M., Ali, Z., Kaur, K., Andrews, S., … Wilson, P. C. (2011). Broadly cross-reactive antibodies dominate the human B cell response against 2009 pandemic H1N1 influenza virus infection. Journal of Experimental Medicine, 208(1), 181–193. https://doi.org/10.1084/jem.20101352
Xiong, L., Pei, J., Bao, P., Wang, X., Guo, S., Cao, M., Kang, Y., Yan, P., & Guo, X. (2023). The Effect of the Feeding System on Fat Deposition in Yak Subcutaneous Fat. International Journal of Molecular Sciences, 24(8), 7381. https://doi.org/10.3390/ijms24087381
Yang, Q., Xu, H., Zhang, H., Li, Y., Chen, S., He, D., Yang, G., Ban, B., Zhang, M., & Liu, F. (2023). Serum triglyceride glucose index is a valuable predictor for viseral obesity in patients with type 2 diabetes: a cross-sectional study. Cardiovascular Diabetology, 22(1), 98. https://doi.org/10.1186/s12933-023-01834-3
You, W., Liu, S., Li, J., Tu, Y., & Shan, T. (2023). GADD45A regulates subcutaneous fat deposition and lipid metabolism by interacting with Stat1. BMC Biology, 21(1), 212. https://doi.org/10.1186/s12915-023-01713-z
Yu, S., Zhao, S., Zhang, Y., & Xu, Y. (2023). PS-P06-13: THE IMPACT OF BODY COMPOSITION AND ADIPOSE DISTRIBUTION ON BLOOD PRESSURE IN YOUNG AND MIDDLE-AGED ADULTS. Journal of Hypertension, 41(Suppl 1), e256. https://doi.org/10.1097/01.hjh.0000915340.07987.49
Zhao, S., Tang, J., Zhao, Y., Xu, C., Xu, Y., Yu, S., & Zhang, Y. (2022). The impact of body composition and fat distribution on blood pressure in young and middle-aged adults. Frontiers in Nutrition, 9. https://doi.org/10.3389/fnut.2022.979042
Zheleznova, E. A., Zhernakova, Y. V., Shariya, M. A., Blinova, N. V., Azimova, M. O., Sharf, T. V., Konosova, I. D., Masenko, V. P., & Chazova, I. E. (2023). Distribution of fat stores in young adults with different metabolic phenotypes. Systemic Hypertension, 19(4), 17–25. https://doi.org/10.38109/2075-082X-2022-4-17-25