Comparing the validity of continuous metabolic syndrome risk scores for predicting pediatric metabolic syndrome: the CASPIAN-V study
-
Mehri Khoshhali
,
Ramin Heshmat
and
Roya Kelishadi
Abstract
Background
The aim of this study was to compare the validity of various approaches to pediatric continuous metabolic syndrome (cMetS) scores including siMS scores (2 waist/height + fasting blood glucose [FBG]/5.6 + triglycerides [TG]/1.7 + systolic blood pressure [BP]/130 + high-density lipoprotein [HDL]/1.02), Z-scores, principal component analysis (PCA) and confirmatory factor analysis (CFA) for predicting metabolic syndrome (MetS).
Methods
This nationwide cross-sectional study was conducted on 4200 Iranian children and adolescents aged 7–18 years. The cMetS was computed using data on HDL, cholesterol, TGs, FBG, mean arterial pressure (MAP) and waist circumference (WC). The areas under the receiver operating characteristic curves (AUCs) were used to compare the performances of different cMetS scores.
Results
Data of 3843 participants (52.4% boys) were available for the current study. The mean (standard deviation [SD]) age was 12.6 (3) and 12.3 (3.1) years for boys and girls, respectively. The differences in AUC values of cMetS scores were significant based on the Delong method. The AUCs (95% confidence interval [CI]) were for Z-scores, 0.94 (0.93, 0.95); first PCA, 0.91 (0.89, 0.93); sum PCA, 0.90 (0.88, 0.92), CFA, 0.79 (0.76, 0.3) and also for siMS scores 1 to 3 as 0.93 (0.91, 0.94), 0.92 (0.90, 0.93), and 0.91 (0.90, 0.93), respectively.
Conclusions
The results of our study indicated that the validity of all approaches for cMetS scores for predicting MetS was high. Given that the siMS scores are simple and practical, it might be used in clinical and research practice.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Conflict of interest: None to declare.
Research funding: This study was conducted as part of a national surveillance program.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
References
1. Bruce KD, Byrne CD. The metabolic syndrome: common origins of a multifactorial disorder. Postgrad Med J 2009;85:614–21.10.1136/pgmj.2008.078014Search in Google Scholar PubMed
2. Lusis AJ, Attie AD, Reue K. Metabolic syndrome: from epidemiology to systems biology. Nat Rev Genet 2008;9:819–30.10.1038/nrg2468Search in Google Scholar PubMed PubMed Central
3. Wu Y-E, Zhang C-L, Zhen Q. Metabolic syndrome in children. Exp Ther Med 2016;12:2390–4.10.3892/etm.2016.3632Search in Google Scholar PubMed PubMed Central
4. Olza J, Gil-Campos M, Leis R, Bueno G, Aguilera CM, et al. Presence of the metabolic syndrome in obese children at prepubertal age. Ann Nutr Metab 2011;58:343–50.10.1159/000331996Search in Google Scholar PubMed
5. Daniels SR, Greer FR, Srinivasan S, Berenson G, Mercat I, et al. Lipid screening and cardiovascular health in childhood. Pediatrics 2008;122:198–208.10.1542/peds.2008-1349Search in Google Scholar PubMed
6. Ahrens W, Moreno LA, Mårild S, Molnár D, Siani A, et al. Metabolic syndrome in young children: definitions and results of the IDEFICS study. Int J Obes 2014;38:S4–14.10.1038/ijo.2014.130Search in Google Scholar PubMed
7. Friend A, Craig L, Turner S. The prevalence of metabolic syndrome in children: a systematic review of the literature. Metab Syndr Relat Disord 2013;11:71–80.10.1089/met.2012.0122Search in Google Scholar PubMed
8. Khashayar P, Heshmat R, Qorbani M, Motlagh ME, Aminaee T, et al. Metabolic syndrome and cardiovascular risk factors in a national sample of adolescent population in the Middle East and North Africa: the CASPIAN III study. Int J Endocrinol 2013;2013:1–8.10.1155/2013/702095Search in Google Scholar PubMed PubMed Central
9. Qorbani M, Mehrkash M, Kelishadi R, Mohammadian S, Mousavinasab F, et al. Obesity and metabolic syndrome among a representative sample of Iranian adolescents. Southeast Asian J Trop Med Public Heal 2012;43:756–63.Search in Google Scholar
10. Mirhosseini N-Z, Yusoff NA, Shahar S, Parizadeh SM, Mobarhen MG, et al. Prevalence of the metabolic syndrome and its influencing factors among adolescent girls in Mashhad, Iran. Asia Pac J Clin Nutr 2009;18:131–6.Search in Google Scholar
11. Ostovaneh MR, Zamani F, Sharafkhah M, Ansari-Moghaddam A, Akhavan Khaleghi N, et al. Prevalence of metabolic syndrome in Amol and Zahedan, Iran: a population based study. Arch Iran Med 2014;17:477–82.Search in Google Scholar
12. Kelishadi R, Hovsepian S, Djalalinia S, Jamshidi F, Qorbani M. A systematic review on the prevalence of metabolic syndrome in Iranian children and adolescents. J Res Med Sci 2016;21:1–9.Search in Google Scholar
13. Eisenmann JC. On the use of a continuous metabolic syndrome score in pediatric research. Cardiovasc Diabetol 2008;7:17.10.1186/1475-2840-7-17Search in Google Scholar PubMed PubMed Central
14. Shi P, Goodson JM, Hartman M-L, Hasturk H, Yaskell T, et al. Continuous metabolic syndrome scores for children using salivary biomarkers. PLoS One 2015;10:e0138979.10.1371/journal.pone.0138979Search in Google Scholar PubMed PubMed Central
15. Eisenmann JC, Laurson KR, DuBose KD, Smith BK, Donnelly JE. Construct validity of a continuous metabolic syndrome score in children. Diabetol Metab Syndr 2010;2:8.10.1186/1758-5996-2-8Search in Google Scholar PubMed PubMed Central
16. Heshmat R, Heidari M, Ejtahed H-S, Motlagh ME, Mahdavi-Gorab A, et al. Validity of a continuous metabolic syndrome score as an index for modeling metabolic syndrome in children and adolescents: the CASPIAN-V study. Diabetol Metab Syndr 2017;9:89.10.1186/s13098-017-0291-4Search in Google Scholar PubMed PubMed Central
17. Shen B, Goldberg RB, Llabre MM, Schneiderman N. Is the factor structure of the metabolic syndrome comparable between men and women and across three ethnic groups: the Miami Community Health study. Ann Epidemiol 2006;16:131–7.10.1016/j.annepidem.2005.06.049Search in Google Scholar PubMed
18. Pladevall M, Singal B, Williams LK, Brotons C, Guyer H, et al. A single factor underlies the metabolic syndrome: a confirmatory factor analysis. Diabetes Care 2006;29:113–22.10.2337/dc06-0800Search in Google Scholar
19. Shafiee G, Kelishadi R, Heshmat R, Qorbani M, Motlagh ME, et al. First report on the validity of a continuous metabolic syndrome score as an indicator for metabolic syndrome in a national sample of paediatric population – the CASPIAN-III study. Endokrynol Pol 2013;64:278–84.10.5603/EP.2013.0006Search in Google Scholar PubMed
20. Martínez-Vizcaíno V, Martínez MS, Aguilar FS, Martínez SS, Gutiérrez RF, et al. Validity of a single-factor model underlying the metabolic syndrome in children: a confirmatory factor analysis. Diabetes Care 2010;33:1370–2.10.2337/dc09-2049Search in Google Scholar PubMed PubMed Central
21. Gurka MJ, Ice CL, Sun SS, Deboer MD. A confirmatory factor analysis of the metabolic syndrome in adolescents: an examination of sex and racial/ethnic differences. Cardiovasc Diabetol 2012;11:1–10.10.1186/1475-2840-11-128Search in Google Scholar PubMed PubMed Central
22. Soldatovic I, Vukovic R, Culafic D, Gajic M, Dimitrijevic-Sreckovic V. siMS Score: Simple method for quantifying metabolic syndrome. PLoS One 2016;11:e0146143.10.1371/journal.pone.0146143Search in Google Scholar PubMed PubMed Central
23. Vukovic R, Milenkovic T, Stojan G, Vukovic A, Mitrovic K, et al. Pediatric siMS score: a new, simple and accurate continuous metabolic syndrome score for everyday use in pediatrics. PLoS One 2017;12:e0189232.10.1371/journal.pone.0189232Search in Google Scholar PubMed PubMed Central
24. Motlagh M, Ziaodini H, Qorbani M, Taheri M, Aminaei T, et al. Methodology and early findings of the fifth survey of childhood and adolescence surveillance and prevention of adult noncommunicable disease: the caspian-v study. Int J Prev Med 2017;8:1–9.Search in Google Scholar
25. WHO. Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser 1995;854:1–452.Search in Google Scholar
26. Knowles KM, Paiva LL, Sanchez SE, Revilla L, Lopez T, et al. Waist circumference, body mass index, and other measures of adiposity in predicting cardiovascular disease risk factors among Peruvian adults. Int J Hypertens 2011;2011:1–10.10.4061/2011/931402Search in Google Scholar PubMed PubMed Central
27. National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and Adolescents. The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Pediatrics 2004;114:555–76.10.1542/peds.114.S2.555Search in Google Scholar
28. McNamara JR, Schaefer EJ. Automated enzymatic standardized lipid analyses for plasma and lipoprotein fractions. Clin Chim Acta 1987;166:1–8.10.1016/0009-8981(87)90188-4Search in Google Scholar
29. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18:499–502.10.1093/clinchem/18.6.499Search in Google Scholar
30. Banerjee S. Final report, Vol. 21. Golden, CO, CO: Public Health, 2005.Search in Google Scholar
31. Li C, Ford ES, Mokdad AH, Cook S. Recent trends in waist circumference and waist-height ratio among US children and adolescents. Pediatrics 2006;118:e1390–8.10.1542/peds.2006-1062Search in Google Scholar PubMed
32. Zimmet P, Alberti KG, Kaufman F, Tajima N, Silink M, et al. The metabolic syndrome in children and adolescents – an IDF consensus report. Pediatr Diabetes 2007;8:299–306.10.1111/j.1399-5448.2007.00271.xSearch in Google Scholar PubMed
33. Swets JA. Measuring the accuracy of diagnostic systems. Science 1988;240:1285–93.10.1126/science.3287615Search in Google Scholar PubMed
34. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988;44:837.10.2307/2531595Search in Google Scholar
35. Magnussen CG, Koskinen J, Chen W, Schmidt MD, Srinivasan SR, et al. Pediatric metabolic syndrome predicts adulthood metabolic syndrome, subclinical atherosclerosis, and type 2 diabetes mellitus but is no better than body mass index alone. Circulation 2010;122:1604–11.10.1161/CIRCULATIONAHA.110.940809Search in Google Scholar PubMed PubMed Central
36. Magnussen CG, Cheriyan S, Sabin MA, Juonala M, Koskinen J, et al. Continuous and dichotomous metabolic syndrome definitions in youth predict adult type 2 diabetes and carotid artery intima media thickness: the cardiovascular risk in young finns study. J Pediatr 2016;171:97–103.10.1016/j.jpeds.2015.10.093Search in Google Scholar PubMed
37. Magnussen CG, Koskinen J, Juonala M, Chen W, SrinivasanSR, et al. A diagnosis of the metabolic syndrome in youth that resolves by adult life is associated with a normalization of high carotid intima-media thickness and type 2 diabetes mellitus risk. The Bogalusa heart and cardiovascular risk in young finns studies. J Am Coll Cardiol 2012;60:1631–9.10.1016/j.jacc.2012.05.056Search in Google Scholar PubMed
38. Kelly AS, Steinberger J, Jacobs DR, Hong CP, Moran A, et al. Predicting cardiovascular risk in young adulthood from metabolic syndrome, its component risk factors, and a cluster score in childhood. Int J Pediatr Obes 2011;6:283–9.10.3109/17477166.2010.528765Search in Google Scholar PubMed PubMed Central
39. Brage S, Wedderkopp N, Ekelund U, Franks PW, Wareham NJ, et al. Features of the metabolic syndrome are associated with objectively measured physical activity and fitness in Danish children: the European Youth Heart Study (EYHS). Diabetes Care 2004;27:2141–8.10.2337/diacare.27.9.2141Search in Google Scholar PubMed
40. Okosun IS, Lyn R, Davis-Smith M, Eriksen M, Seale P. Validity of a continuous metabolic risk score as an index for modeling metabolic syndrome in adolescents. Ann Epidemiol 2010;20:843–51.10.1016/j.annepidem.2010.08.001Search in Google Scholar PubMed
41. 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;35:1318–24.10.1038/ijo.2011.138Search in Google Scholar PubMed
42. Hesse MB, Young G, Murray RD. Evaluating health risk using a continuous metabolic syndrome score in obese children. J Pediatr Endocrinol Metab 2016;29:451–8.10.1515/jpem-2015-0271Search in Google Scholar PubMed
©2019 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Review
- The importance of anthropological methods in the diagnosis of rare diseases
- Original Articles
- PON1 arylesterase activity, HDL functionality and their correlation in malnourished children
- Prevalence of dyslipidemia and factors affecting dyslipidemia in young adults with type 1 diabetes: evaluation of statin prescribing
- Myocardial dysfunction in relation to serum thiamine levels in children with diabetic ketoacidosis
- Evaluation of long-term follow-up and methimazole therapy outcomes of pediatric Graves’ disease: a single-center experience
- Endocrine consequences of neuroblastoma treatment in children: 20 years’ experience of a single center
- Analysis of diabetes-associated autoantibodies in children and adolescents with autoimmune thyroid diseases
- Adrenal function of extremely premature infants in the first 5 days after birth
- Atypical presentation of Leydig cell tumour in three prepubertal patients: diagnosis, treatment and outcomes
- The diagnosis of cystinosis in patients reveals new CTNS gene mutations in the Chinese population
- Comparing the validity of continuous metabolic syndrome risk scores for predicting pediatric metabolic syndrome: the CASPIAN-V study
- Primary pigmented nodular adrenocortical disease (PPNAD): single centre experience
- Short Communication
- Classical galactosemia patients can achieve high IQ scores
- Case Reports
- Idiopathic gonadotropin-independent precocious puberty – is regular surveillance required?
- MYT1L mutation in a patient causes intellectual disability and early onset of obesity: a case report and review of the literature
- A case report and literature review of monoallelic mutation of GHR
- Pitfalls in the diagnosis of insulin autoimmune syndrome (Hirata’s disease) in a hypoglycemic child: a case report and review of the literature
Articles in the same Issue
- Frontmatter
- Review
- The importance of anthropological methods in the diagnosis of rare diseases
- Original Articles
- PON1 arylesterase activity, HDL functionality and their correlation in malnourished children
- Prevalence of dyslipidemia and factors affecting dyslipidemia in young adults with type 1 diabetes: evaluation of statin prescribing
- Myocardial dysfunction in relation to serum thiamine levels in children with diabetic ketoacidosis
- Evaluation of long-term follow-up and methimazole therapy outcomes of pediatric Graves’ disease: a single-center experience
- Endocrine consequences of neuroblastoma treatment in children: 20 years’ experience of a single center
- Analysis of diabetes-associated autoantibodies in children and adolescents with autoimmune thyroid diseases
- Adrenal function of extremely premature infants in the first 5 days after birth
- Atypical presentation of Leydig cell tumour in three prepubertal patients: diagnosis, treatment and outcomes
- The diagnosis of cystinosis in patients reveals new CTNS gene mutations in the Chinese population
- Comparing the validity of continuous metabolic syndrome risk scores for predicting pediatric metabolic syndrome: the CASPIAN-V study
- Primary pigmented nodular adrenocortical disease (PPNAD): single centre experience
- Short Communication
- Classical galactosemia patients can achieve high IQ scores
- Case Reports
- Idiopathic gonadotropin-independent precocious puberty – is regular surveillance required?
- MYT1L mutation in a patient causes intellectual disability and early onset of obesity: a case report and review of the literature
- A case report and literature review of monoallelic mutation of GHR
- Pitfalls in the diagnosis of insulin autoimmune syndrome (Hirata’s disease) in a hypoglycemic child: a case report and review of the literature
