skip to main content

PROFIL ANTROPOMETRI OBESITAS ANTARA MAHASISWA DENGAN METABOLIC HEALTHY OBESE (MHO) DAN METABOLIC UNHEALTHY OBESE (MUO)

Departemen Ilmu Gizi, Fakultas Kedokteran, Universitas Diponegoro, Semarang, Jawa Tengah, Indonesia

Received: 14 Oct 2025; Revised: 6 Jan 2025; Accepted: 6 Jan 2025; Available online: 28 Jan 2026; Published: 30 Jan 2026.

Citation Format:
Abstract

ABSTRACT

Background: The prevalence of obesity in Indonesia continues to increase in adolescents. The increase in obesity in adolescents increases the risk of developing metabolic syndrome at a young age. However, not all obese individuals have poor metabolism. Metabolism in obesity is categorized into Metabolically Healthy Obesity (MHO) and Metabolically Unhealthy Obesity (MUO). Anthropometric measurements can differentiate between MHO and MUO individuals.

Purpose: This study intends to analyze the differences in anthropometric profiles, including Waist Circumference (WC), Waist-to-Hip Ratio (WHR), Waist-to-Height Ratio (WHtR), and thigh circumference, between students who are Metabolically Healthy Obese (MHO) and Metabolically Unhealthy Obese (MUO).

Methode: An analytical observational study with cross-sectional design in Diponegoro University Semarang college students, 37 women with healthy obesity and 37 women with unhealthy obesity selected by purposive sampling. The collected anthropometric measurement data included WC, WHR, WHtR, and TC. The biochemical and clinical that was collected were blood pressure, triglycerides, fasting blood sugar, and High-Density Lipoprotein (HDL) in Cito Banyumanik Laboratory.

Result: All samples had pre-metabolic syndrome with at least 1 sign, which is central obesity. However, the median results of measurements of waist circumference, WHR, WHtR, and thigh circumference in the MUO group were greater than the MHO group. There was a significant difference in the results of measuring waist circumference (p<0.001), WHR (p=0.012), and WHtR (p<0.001), but there was no significant difference in thigh circumference (p=0.456)

Conclusion: There were significant differences in waist circumference, waist-hip ratio, and waist-to-height ratio in the MHO and MUO groups. There was no significant difference in thigh circumference between the MUO and MHO groups.

Keywords: Waist Circumference, WHR, WHtR, Thigh Circumference, Metabolic Phenotype

 

ABSTRAK

Latar belakang : Angka obesitas di Indonesia terus meningkat pada remaja. Peningkatan obesitas pada remaja meningkatkan risiko terjadinya sindrom metabolik pada usia muda. Namun, tidak semua individu obesitas memiliki metabolisme yang buruk. Metabolisme pada obesitas dikategorikan  menjadi  Metabolically Healthy Obesity (MHO) dan Metabolically Unhealthy Obesity (MUO). Pengukuran antropometri dapat membedakan antara individu MHO dan MUO.

Tujuan: Tujuan penelitian ini adalah untuk menganalisis perbedaan Profil antropometri antara lain Lingkar Pinggang (LP), Rasio Lingkar Pinggang-Panggul (RLPP), Rasio Lingkar Pinggang-Tinggi Badan (RLPTB) dan lingkar paha antara mahasiswa dengan Metabolic Healthy Obese (MHO) dan Metabolic Unhealthy Obese (MUO)

Metode : Penelitian analitik observasional dengan pendekatan cross-sectional pada mahasiswi UNDIP Semarang sebanyak 37 mahasiswi dengan obesitas dengan MUO dan 37 mahasiswi dengan obesitas dengan MHO dipilih secara purposive sampling. Data antropometri yang dikumpulkan berupa LP, RLPP, RLPTB, dan Lingkar Paha. Data biokimia dan klinis yang dikumpulkan yaitu Tekanan Darah (TD), Trigliserida, Gula Darah Puasa (GDP), dan High Density Lipoprotein (HDL) di laboratorium Cito Banyumanik. Analisis data menggunakan uji Mann Whitney.

Hasil : Semua subjek mengalami pre sindrom metabolik dengan minimal 1 tanda yaitu obesitas sentral. Median hasil pengukuran lingkar pinggang, RLPP, RLPTB, dan lingkar paha pada kelompok MUO lebih besar dari kelompok MHO. Terdapat perbedaan signifikan pada hasil pengukuran lingkar pinggang (p<0,001), RLPP (p=0,012), dan RLPTB (p<0,001), akan tetapi tidak ada perbedaan signifikan pada lingkar paha (p=0,456).

Simpulan : Terdapat perbedaan yang signifikan pada lingkar pinggang, rasio lingkar pinggang-panggul, dan rasio lingkar pinggang-tinggi badan pada kelompok MHO dan MUO. Tidak ada perbedaan yang signifikan pada lingkar paha antar kelompok MUO dan MHO

Kata Kunci : Lingkar Pinggang, RLPP, RLPTB, Lingkar Paha, Tipe Metabolik

Fulltext
Keywords: Lingkar Pinggang, RLPP, RLPTB, Lingkar Paha, Tipe Metabolik

Article Metrics:

  1. Lobstein T, Brinsden H, Neveux M. World Obesity Atlas 2022. World Obes. Fed.2022;19
  2. Badan Penelitian dan Pengembangan Kesehatan Kemenkes RI. Hasil Riset Kesehatan Dasar Tahun 2018. 2018
  3. Xu H, Li X, Adams H, Kubena K, Guo S. Etiology of Metabolic Syndrome and Dietary Intervention. Int J Mol Sci Internet 2019;20(1):1–19. Available from: https://doi.org/10.3390/ijms20010128
  4. Yoon YS, Oh SW. Optimal waist circumference cutoff values for the diagnosis of abdominal obesity in Korean adults. Endocrinol Metab Internet 2014;29(4):418–26. Available from: https://doi.org/10.3803/EnM.2014.29.4.418
  5. Pedersen BK, Saltin B. Exercise as Medicine - Evidence for Prescribing Exercise as Therapy in 26 Different Chronic Diseases. Scand J Med Sci Sport Internet 2015;25:1–72. Available from: https://doi.org/10.1111/sms.12581
  6. Kanagasabai T, Dhanoa R, Kuk JL, Ardern CI. Association between Sleep Habits and Metabolically Healthy Obesity in Adults: A Cross-Sectional Study. J Obes Internet 2017;2017:1–7. Available from: https://doi.org/10.1155/2017/5272984
  7. Tsatsoulis A, Paschou SA. Metabolically Healthy Obesity: Criteria, Epidemiology, Controversies, and Consequences. Curr Obes Rep Internet 2020;9(2):109–20. Available from: https://doi.org/10.1007/s13679-020-00375-0
  8. Pibriyanti K. Studi Obesitas Sentral Pada Mahasiswa Prodi Kesehatan Masyarakat Univet Bangun Nusantara Sukoharjo. J Kesehat Internet 2018;11(1):16–23. Available from: https://doi.org/10.23917/jk.v11i1.7000
  9. Prasad DS, Kabir Z, Revathi Devi K, Peter PS, Das BC. Gender Differences in Central Obesity: Implications for Cardiometabolic Health in South Asians. Indian Heart J Internet 2020;72(3):202–4. Available from: https://doi.org/10.1016/j.ihj.2020.04.008
  10. Csongová M, Volkovová K, Gajdoš M, Gurecká R, Koborová I, Líšková A, et al. Gender-Associated Differences in the Prevalence of Central Obesity Using Waist Circumference and Waist-to-Height Ratio, and that of General Obesity, in Slovak Adults. Cent Eur J Public Health Internet 2018;26(3):228–33. Available from: https://doi.org/10.21101/cejph.a4719
  11. Tian T, Zhang J, Zhu Q, Xie W, Wang Y, Dai Y. Predicting Value of Five Anthropometric Measures in Metabolic Syndrome Among Jiangsu Province, China. BMC Public Health Internet 2020;20(1):1–9. Available from: https://doi.org/10.1186/s12889-020-09423-9
  12. Laohabut I, Udol K, Phisalprapa P, Srivanichakorn W, Chaisathaphol T, Washirasaksiri C, et al. Neck Circumference as a Predictor of Metabolic Syndrome: A Cross-Sectional Study. Prim Care Diabetes Internet 2020;14(3):265–73. Available from: https://doi.org/10.1016/j.pcd.2019.08.007
  13. Raimi TH, Dele-Ojo BF, Dada SA, Ajayi DD. Neck Circumference Cut-off for Obesity and Metabolic Syndrome in Nigeria. Ethn Dis Internet 2021;31(4):501–8. Available from: https://doi.org/10.18865/ed.31.4.501
  14. Dang AK, Truong MT, Le HT, Nguyen KC, Le MB, Nguyen LT, et al. Anthropometric Cut-Off Values for Detecting the Presence of Metabolic Syndrome and Its Multiple Components among Adults in Vietnam: The Role of Novel Indices. Nutrients Internet 2022;14(19):1–14. Available from: https://doi.org/10.3390/nu14194024
  15. Jung KJ, Kimm H, Yun JE, Jee SH. Thigh Circumference and Diabetes: Obesity as a Potential Effect Modifier. J Epidemiol Internet 2013;23(5):329–36. Available from: https://doi.org/10.2188/jea.JE20120174
  16. Yoo EG. Waist-to-Height Ratio as a Screening Tool for Obesity and Cardiometabolic Risk. Korean J Pediatr Internet 2016;59(11):425–31. Available from: https://doi.org/10.3345/kjp.2016.59.11.425
  17. Carneiro Roriz AK, Santana Passos LC, Cunha De Oliveira C, Eickemberg M, De Almeida Moreira P, Barbosa Ramos L. Anthropometric Clinical Indicators in the Assessment of Visceral Obesity: An Update. Nutr Clin y Diet Hosp Internet 2016;36(2):168–79. Available from: https://doi.org/10.12873/362carneirororiz
  18. Yang YJ, Park HJ, Won KB, Chang HJ, Park GM, Kim YG, et al. Relationship Between the Optimal Cut-off Values of Anthropometric Indices for Predicting Metabolic Syndrome and Carotid Intima-Medial Thickness in a Korean Population. Medicine (Baltimore) Internet 2019;98(42):1–5. Available from: https://doi.org/10.1097/md.0000000000017620
  19. Mata AJ, Jasul G. Prevalence of Metabolic Syndrome and Its Individual Features Across Different (Normal, Overweight, Pre-Obese and Obese) Body Mass Index (BMI) Categories in a Tertiary Hospital in the Philippines. J ASEAN Fed Endocr Soc Internet 2017;32(2):117–22. Available from: https://doi.org/10.15605/jafes.032.02.04
  20. Indraswari DA, Al Ahmadi HU, Arum Sari DW, Jordan T, Puruhito B, Basyar E, et al. Body Mass Index and Waist Circumference are Associated with Visceral Fats Measured by Bioelectrical Impedance Analysis in Adolescents. Diponegoro Med J (Jurnal Kedokt Diponegoro) Internet 2021;10(5):351–6. Available from: https://doi.org/10.14710/dmj.v10i5.32040
  21. Hall JE. Endocrinology and Reproduction. In: Gyuton and Hall Textbook of Medical Physiology. Philadelphia: elsevier; 2016. page 996
  22. 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
  23. Frank, Matthew G. annis, Watkins M. Metabolically Healthy Obesity, Metabolic Syndrome, and Cardiovascular Risk. J Am Coll Cardiol Internet 2018;71(17):1857–65. Available from: https://doi.org/10.1016/j.jacc.2018.02.055
  24. Piqueras P, Ballester A, Durá-Gil J V., Martinez-Hervas S, Redón J, Real JT. Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review. Front Psychol Internet 2021;12. Available from: https://doi.org/10.3389/fpsyg.2021.631179
  25. Baioumi AYAA. Comparing Measures of Obesity: Waist Circumference, Waist-Hip, and Waist-Height Ratios Internet. In: Watson RR, editor. Nutrition in the Prevention and Treatment of Abdominal Obesity. London: Academic Press; 2019. page 29–40.Available from: http://dx.doi.org/10.1016/B978-0-12-816093-0.00003-3
  26. Widjaja NA, Arifani R, Irawan R. Value of Waist-to-Hip Ratio as a Predictor of Metabolic Syndrome in Adolescents with Obesity: Cut-off Value of Waist-to-Hip Ratio. Acta Biomed Internet 2023;94(3):1–6. Available from: https://doi.org/10.23750/abm.v94i3.13755
  27. Fernández-Verdejo R, Galgani JE. Exploring the Sequential Accumulation of Metabolic Syndrome Components in Adults. Sci Rep Internet 2022;12(1):1–9. Available from: https://doi.org/10.1038/s41598-022-19510-z
  28. She Y, Mangat R, Tsai S, Proctor SD, Richard C. The Interplay of Obesity, Dyslipidemia and Immune Dysfunction: A Brief Overview on Pathophysiology, Animal Models, and Nutritional Modulation. Front Nutr Internet 2022;9(February):1–10. Available from: https://doi.org/10.3389/fnut.2022.840209
  29. Hall JE, Mouton AJ, Da Silva AA, Wang Z, Li X, Do Carmo JM. Obesity, Kidney Dysfunction, and Inflammation: Iinteractions in Hhypertension. Cardiovasc Res Internet 2021;117(8):1859–76. Available from: https://doi.org/10.1093/Fcvr/cvaa336
  30. Stadler JT, Marsche G. Obesity‐Related Changes in High‐Density Lipoprotein Metabolism and Function. Int J Mol Sci Internet 2020;21(23):1–28. Available from: https://doi.org/10.3390/ijms21238985
  31. Ebbert JO, Jensen MD. Fat Depots, Free Fatty Acids, and Dyslipidemia. Nutrients Internet 2013;5(2):495–508. Available from: https://doi.org/10.3390/nu5020498
  32. Woessner MN, Tacey A, Levinger-Limor A, Parker AG, Levinger P, Levinger I. The Evolution of Technology and Physical Inactivity: The Good, the Bad, and the Way Forward. Front Public Heal Internet 2021;9(May):1–7. Available from: https://doi.org/10.3389/fpubh.2021.655491
  33. Maciel E da S, Silva BKR, Figueiredo FW dos S, Pontes-Silva A, Quaresma FRP, Adami F, et al. Physical Inactivity Level and Lipid Profile in Traditional Communities in the Legal Amazon: A Cross-Sectional study: Physical Inactivity Level in the Legal Amazon. BMC Public Health Internet 2022;22(1):1–9. Available from: https://doi.org/10.1186/s12889-022-12973-9
  34. Park JH, Moon JH, Kim HJ, Kong MH, Oh YH. Sedentary Lifestyle: Overview of Updated Evidence of Potential Health Risks. Korean J Fam Med Internet 2020;41(6):365–73. Available from: https://doi.org/10.4082/kjfm.20.0165
  35. Bagheri P, Khalili D, Seif M, Rezaianzadeh A. Dynamic Behavior of Metabolic Syndrome Progression: a Comprehensive Systematic Review on Recent Discoveries. BMC Endocr Disord Internet 2021;21(1):1–14. Available from: https://doi.org/10.1186/s12902-021-00716-7
  36. Alpert MA, Parker BM. Obesity and Cardiac Disease Internet. In: Ahima R, editor. Metabolic Syndrome : A Comprehensive Textbook. Switzerland: Springer International Publishing; 2015. page 663.Available from: https://doi.org/10.1007/978-3-319-12125-3_35-1
  37. Yuan Y, Sun W, Kong X. Relationship Between Metabolically Healthy Obesity and the Development of Hypertension: A Nationwide Population-Based Study. Diabetol Metab Syndr Internet 2022;14(1):1–11. Available from: https://doi.org/10.1186/s13098-022-00917-7
  38. Ahima RS. Pharmacotherapy of Obesity and Metabolic Syndrome Internet. In: Ahima RS, editor. Metabolic Syndrome : A Comprehensive Textbook. Switzerland: Springer International Publishing; 2015. page 815–30.Available from: https://doi.org/10.1007/978-3-319-12125-3_44-1
  39. Emdin CA, Anderson SG, Woodward M, Rahimi K. Usual Blood Pressure and Risk of New-Onset Diabetes Evidence from 4.1 Million Adults and a Meta-Analysis of Prospective Studies. J Am Coll Cardiol Internet 2015;66(14):1552–62. Available from: https://doi.org/10.1016/j.jacc.2015.07.059
  40. Hinton TC, Adams ZH, Baker RP, Hope KA, Paton JFR, Hart EC, et al. Investigation and Treatment of High Blood Pressure in Young People: Too Much Medicine or Appropriate Risk Reduction? Hypertens (Dallas, Tex 1979) Internet 2020;75(1):16–22. Available from: https://doi.org/10.1161/hypertensionaha.119.13820
  41. Fatima S, Mahmood S. Combatting a Silent Killer - the Importance of Self-screening of Blood Pressure from an Early Age. EXCLI J Internet 2021;20:1326–7. Available from: https://doi.org/10.17179/excli2021-4140
  42. Barus Savitri Hurriatul; Y.R. Pristya, Terry HTM. Kajian Sistematis Terhadap Faktor-Faktor yang Memengaruhi Hipertensi pada Mahasiswa. Heal Publica Internet 2020;1(Vol 1, No 02 (2020): Health Publica Jurnal Kesehatan Masyarakat):62–7. Available from: https://doi.org/10.47007/hp.v1i02.3688
  43. Kazi RNA, El-Kashif MML, Ahsan SM. Prevalence of Salt Rich Fast Food Consumption: A Focus on Physical Activity and Incidence of Hypertension Among Female Students of Saudi Arabia. Saudi J Biol Sci Internet 2020;27(10):2669–73. Available from: https://doi.org/10.1016/j.sjbs.2020.06.004
  44. Soelistijo SA. Pedoman Pengelolaan dan Pencegahan Diabetes Melitus Tipe 2 Dewasa di Indonesia 2021. Jakarta: PB Perkeni; 2021
  45. Chan DC, Pang J, Watts GF. Dyslipidemia in Obesity Internet. In: Ahima RS, editor. Metabolic Syndrome: A Comprehensive Textbook. Switzerland: Springer International Publishing; 2015. page 559–76.Available from: https://doi.org/10.1007/978-3-319-12125-3_30-1
  46. Bhupathiraju SN, Hu FB. Epidemiology of Obesity and Diabetes and Their Cardiovascular Complications. Circ Res Internet 2016;118(11):1723–35. Available from: https://doi.org/10.1161/circresaha.115.306825
  47. Shi J, Yang Z, Niu Y, Zhang W, Lin N, Li X, et al. Large Thigh Circumference is Associated with Lower Blood Pressure in Overweight and Obese Individuals: A Community-based Study. Endocr Connect Internet 2020;9(4):271–8. Available from: https://doi.org/10.1530/EC-19-0539
  48. Bando H, Kato Y, Sakamoto K, Ogawa T, Bando M, Yonei Y. Investigation for Waist Circumference (WC), Waist-to-Height Ratio (WHtR) and Thigh-to-Waist Ratio (TWaR) in Type 2 Diabetes Mellitus (T2DM). Integr Obes Diabetes Internet 2017;3(4):1–4. Available from: http://dx.doi.org/10.15761/IOD.1000183
  49. Yoon MK, Kang JG, Lee SJ, Ihm SH, Huh KB, Kim CS. Relationships between Thigh and Waist Circumference, Hemoglobin Glycation Index, and Carotid Plaque in Patients with Type 2 Diabetes. Endocrinol Metab Internet 2020;35(2):319–28. Available from: https://doi.org/10.3803/enm.2020.35.2.319
  50. Zhou Y, Hou Y, Xiang J, Dai H, Li M, Wang T, et al. Associations of Body Shapes with Insulin Resistance and Cardiometabolic Risk in Middle-Aged and Elderly Chinese. Nutr Metab Internet 2021;18(1):1–12. Available from: https://doi.org/10.1186/s12986-021-00629-1
  51. Puspitasari N. Kejadian Obesitas Sentral pada Usia Dewasa. HIGEIA (Journal Public Heal Res Dev Internet 2018;2(2):249–59. Available from: https://doi.org/10.15294/higeia.v2i2.21112
  52. Rauber F, Steele EM, da Costa Louzada ML, Millett C, Monteiro CA, Levy RB. Ultra-Processed Food Consumption and Indicators of Obesity in the United Kingdom Population (2008-2016). PLoS One Internet 2020;15(5):1–15. Available from: https://doi.org/ 10.1371/journal.pone.0232676
  53. Niovi Xenaki, Flora Bacopoulou, Kokkinos A, Nicolaides NC, Chrousos GP, Darviri C, et al. Impact of a Stress Management Program on Weight Loss, Mental Health and Lifestyle in Adults with Obesity: A Randomized Controlled Trial. J Mol Biochem 2018;7(2):78–84
  54. World Health Organization. WHO Guidelines on Physical Activity and Sedentary Behaviour : At a Glance. Geneva: WHO; 2020

Last update:

No citation recorded.

Last update:

No citation recorded.