Penentuan titik potong skor sindroma metabolik remaja dan penilaian validitas diagnostik parameter antropometri: analisis Riskesdas 2013

https://doi.org/10.22146/ijcn.25590

Zahra Anggita Pratiwi(1*), Mubasysyir Hasanbasri(2), Emy Huriyati(3)

(1) Departemen Biostatistik, Epidemiologi, dan Kesehatan Populasi, Fakultas Kedokteran Universitas Gadjah Mada
(2) Departemen Biostatistik, Epidemiologi, dan Kesehatan Populasi, Fakultas Kedokteran Universitas Gadjah Mada
(3) Departemen Gizi Kesehatan, Fakultas Kedokteran, Universitas Gadjah Mada
(*) Corresponding Author

Abstract


Background: The risk of death caused by non-communicable diseases is related to metabolic syndrome. Metabolic syndrome not only occurs in adults, but also occurs in adolescents. The problem of metabolic syndrome in adolescents shows the importance of early detection and management. Early detection of metabolic syndrome in adolescents can be done through non-invasive approaches such as anthropometric measurements. However, the definition of metabolic syndrome has so far not reached an agreement.

Objective: This study aims 1) To know the intersection points of adolescent metabolic syndrome 2) To know the best anthropometry parameters for detecting metabolic syndrome in adolescents.

Method: This study used cross sectional design, using Riskesdas 2013 survey data. The sample size of this study was 3273 adolescents aged 15-24 years. The analysis using receiver operating characteristic curve (ROC) indicated the accuracy of the score to diagnose metabolic syndrome, supported by area under the curve (AUC) results. The best parameters were seen from the largest AUC values, taking into account the sensitivity and specificity values.

Results: The metabolic syndrome scores in general for Indonesian adolescents=2.21 (sensitivity=83%, specificity=84%). Specific cutoff point for women=2.02 (sensitivity=84%, specificity=85%), and for males=2.40 (sensitivity=86%, specificity=82%). The best anthropometric parameters for detecting metabolic syndrome in adolescents are abdominal circumference (AUC=0.77; sensitivity=71%, specificity=67%).

Conclusion: Abdominal circumference has the best validity and can be used for early detection of the risk of metabolic syndrome in adolescents


Keywords


anthropometric parameter; cut off point; Indonesian adolescent; metabolic syndrome score

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References

  1. Alberti KGMM, Zimmet P, Shaw J. The metabolic syndrome - a new worldwide definition. Lancet 2005;366(9491):1059–62.
  2. Bray GA, Ryan D. Overweight and the metabolic syndrome: from bench to bedside. USA: Springer; 2006.
  3. De Ferranti SD, Gauvreau K, Ludwig DS, Newburger JW, Rifai N. Inflammation and changes in metabolic syndrome abnormalities in US adolescents: findings from the 1988-1994 and 1999-2000 National Health and Nutrition Examination Surveys. Clin Chem 2006;52(7):1325–30.
  4. You M-A, Son Y-J. Prevalence of metabolic syndrome and associated risk factors among Korean adolescents: analysis from the Korean national survey. Asia-Pacific J Public Heal 2012;24(3):464–71.
  5. Bantas K. Perbedaan gender pada kejadian sindrom metabolik pada penduduk perkotaan di Indonesia. Kesmas, Jurnal Kesehatan Masyarakat Nasional 2012;7(5):219–26.
  6. Wang J, Zhu Y, Cai L, Jing J, Chen Y, Mai J, et al. Metabolic syndrome and its associated early-life factors in children and adolescents: a cross-sectional study in Guangzhou, China. Public Health Nutr 2015;19(13):1–8.
  7. Rini S. Sindrom metabolik. J Major 2015;4(4):88–93.
  8. Kahn R, Buse J, Ferrannini E, Stern M. The metabolic syndrome: time for a critical appraisal. Diabetes Cares 2005;28(9):2289–304.
  9. Okosun IS, Boltri JM, Lyn R, Davis-Smith M. Continuous metabolic syndrome risk score, body mass index percentile, and leisure time physical activity in American children. J Clin Hypertens (Greenwich) 2010;12(8):636–44.
  10. Sastroasmoro S, Ismael S. Dasar-dasar metodologi penelitian klinis. edisi ke-4. Jakarta: Sagung seto; 2011.
  11. Hosseini M, Sarrafzadegan N, Kelishadi R, Monajemi M, Asgary S, Vardanjani HM. Population-based metabolic syndrome risk score and its determinants: The Isfahan Healthy Heart Program. J Res Med Sci 2014;9(12):1167-74.
  12. Pandit D, Chiplonkar S, Khadilkar A, Kinare A, Khadilkar V. Efficacy of a continuous metabolic syndrome score in Indian children for detecting subclinical atherosclerotic risk. Int J Obes (Lond) 2011;35(10):1318–24.
  13. Villa JKD, e Silva AR, Santos TSS, Ribeiro AQ, Sant’Ana LFDR. Metabolic syndrome risk assessment in children: use of a single score. Rev Paul Pediatr 2015;33(2):187–93.
  14. Hsiung D-Y, Liu C-W, Cheng P-C, Ma W-F. Using non-invasive assessment methods to predict the risk of metabolic syndrome. Appl Nurs Res 2014;28(2):72–7.
  15. Kamso S, Dharmayati P, Lubis U, Juwita R, Kurnia Y, Besral R. Prevalensi dan determinan sindrom metabolik pada kelompok eksekutif di Jakarta dan sekitarnya. Kesmas, Jurnal Kesehatan Masyarakat Nasional 2011;6(2):85–90.
  16. Kementerian Kesehatan. Riset Kesehatan Dasar 2013. Jakarta; Kemenkes RI; 2013.
  17. Kassi E, Pervanidou P, Kaltsas G, Chrousos G. Metabolic syndrome: definitions and controversies. BMC Med 2011;9(1):48.
  18. Moy FM, Bulgiba A. The modified NCEP ATP III criteria maybe better than the IDF criteria in diagnosing metabolic syndrome among Malays in Kuala Lumpur. BMC Public Health 2010;10(678):2–7.
  19. Soewondo P, Purnamasari D, Oemardi M, Waspadji S, Soegondo S. Prevalence of metabolic syndrome using NCEP/ATP III criteria in Jakarta, Indonesia: the Jakarta primary non-communicable disease risk factors surveillance 2006. Acta Med Indones 2010;42(4):199–203.
  20. Eisenmann JC. On the use of a continuous metabolic syndrome score in pediatric research. Cardiovasc Diabetol 2008;7:17.
  21. Eisenmann JC, Laurson KR, DuBose KD, Smith BK, Donnelly JE. Construct validity of a continuous metabolic syndrome score in children. Diabetol Metab Syndr 2010;2:8.
  22. Stabelini Neto A, de Campos W, Dos Santos GC, Mazzardo Junior O. Metabolic syndrome risk score and time expended in moderate to vigorous physical activity in adolescents. BMC Pediatr 2014;14:42.
  23. Velásquez-villa M, Gómez-ocampo L, Bermúdez-cardona J. Abdominal obesity and low physical activity are associated with insulin resistance in overweight adolescents : a cross-sectional study. BMC Pediatr 2014;14(52):1–9.
  24. Hillier TA, Rousseau A, Lange C, Lépinay P, Cailleau M, Balkau B, et al. Practical way to assess metabolic syndrome using a continuous score obtained from principal components analysis. Diabetologia 2006;49(7):1528–35.
  25. Benmohammed K, Valensi P, Benlatreche M, Nguyen MT, Benmohammed F, Pariès J, et al. Anthropometric markers for detection of the metabolic syndrome in adolescents. Diabetes Metab 2015;41(2):138–44.
  26. Sihombing M, Tjandrarini DH. Faktor risiko sindrom metabolik pada orang dewasa di Kota Bogor. Penel Gizi dan Makanan 2015;38(1):21–30.
  27. Kelsey MM, Zeitler PS. Insulin resistance of puberty. Curr Diab Rep 2016;16(7):64.
  28. Neinstein LS. Handbook of adolescent health care. United States: Lippincott Williams & Wilkins; 2009.
  29. Susilawati MD, Bantas K, Jahari AB. Nilai batas dan indikator obesitas terhadap terjadinya diabetes mellitus tipe 2. Penel Gizi Makanan 2014;2(1):11–20.
  30. Gharipour M, Sadeghi M, Dianatkhah M, Bidmeshgi S, Ahmadi A, Tahri M, et al. The cut-off values of anthropometric indices for identifying subjects at risk for metabolic syndrome in Iranian elderly men. J Obes 2014;2014.
  31. Brambilla P, Bedogni G, Heo M, Pietrobelli A. Waist circumference-to-height ratio predicts adiposity better than body mass index in children and adolescents. Int J Obes 2013;37(7):943–6.
  32. Nambiar S, Hughes I, Davies PS. Developing waist-to-height ratio cut-offs to define overweight and obesity in children and adolescents. Public Health Nutr 2010;13(10):1566–74.
  33. Carr SNUTP-M. An introduction to public health and epidemiology. second edition. New York: Open University Press; 2007.



DOI: https://doi.org/10.22146/ijcn.25590

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