Table 2 Epidemiological studies investigating the prevalence of metabolic syndrome in children and adolescents based on the diagnostic criteria from the IDF, Cook et al. [6], Ford et al. [26], and de Ferranti et al. [27].

From: The prevalence of pediatric metabolic syndrome—a critical look on the discrepancies between definitions and its clinical importance

Author	Year	Country	Study cohort		Study design	IDF criteria	Modified NCEP criteria
Author	Year	Country	N	Age (years)	Study design	IDF criteria	Modified NCEP criteria
Europe
Ostrihoňová et al. [58]	2017	Slovak Republic	1294	10–17.99	Visitors of Health Advice Centers no randomization	♂2.7% ♀2.8%
Vanlancker et al. [18]	2017	10 European Countries	1004	12.5–17	Randomized multicenter study not population-representative	2.7%	Cook 3.5%
Galera-martínez et al. [48]	2015	Spain	379	12–16.9	Population-based sample of adolescents living in Almería	3.8%	Ford 5.7%
Ahrens et al. [40]	2014	8 European Countries	12,319	2–10.9	Population-based not nationally representative	0.4%	Cook 1.4%
North America
Reina et al. [64]	2017	USA	1137	10–16	Population-based study of Latino/Hispanic people living in the US; SOL youth^a	3.1% (10–15) ♂2.8% (16) ♀6.3% (16)
Rodríguez et al. [37]	2016	USA	1623	12–19	Nationally representative sample of adolescents; NHANES^b 2005–2012	5.4%
MacPherson et al. [46]	2016	Canada	1228	10–18	Population representative survey; CHMS^c 2007–2009, 2009–2011	2.1%
Miller et al. [20]	2014	USA	3495	12–19	Nationally representative sample of adolescents; NHANES 2001–2010		Ford 10.1%
South America
Reuter et al. [80]	2018	Brazil	1200	12–17	Population representative sample of adolescents from Southern Brazil	2.1%	Cook 1.9% de Ferranti 5.0%
Ramírez-Vélez et al. [32]	2016	Colombia	1922	9–17.9	Population-based sample of school children in Bogota; FUPRECOL^d study 2014–2015	0.3%	Cook 6.2% Ford 7.8% de Ferranti 11.0%
Suarez-Ortegón et al. [50]	2016	Colombia	494	5–9	Cross-sectional study of the scholar population in the city of Cali; IFRECNTEC^e study		de Ferranti 8.7%
Kuschnir et al. [31]	2016	Brazil	37,504	12–19	Representative of adolescents from medium- and large-sized cities; ERICA^f Study	2.6%
Burrows et al. [38]	2015	Chile	667	12–17	Adolescents of low to middle SE-status residing in the city of Santiago not population representative	9.5%
Villalobos Reyes et al. [43]	2014	Venezuela	916	9–18	Representative sample in the city of Mérida; CREDEFAR^g Study 2010–2011	1.5%	Cook 2.2%
Dias Pitangueira et al. [41]	2014	Brazil	540	7–14	Random sample from the municipality of Mutuípe, Brazil		de Ferranti12.8%
Agudelo et al. [51]	2014	Colombia	851	10–18	Beneficiaries of a health-promotion company in the city of Medellín no randomization	0.9%	Cook 3.8% Ford 4.1% de Ferranti 11.4%
Asia
Song et al. [42]	2017	China	831	7–18	“National household-based study in nine Chinese provinces;” CHNS^h 2009	1.4% (10–18)	Cook 3.4% (7–18) 3.6% (10–18)
Xu et al. [57]	2017	China	11,174	10–17	Population survey conducted in six provinces in 2007–2011		Cook 3.8%
Lee et al. [60]	2017	South Korea	623	10–18	Population representative; KNHANESⁱ	1.0%
Asghari et al. [33]	2017	Iran	1424	11–18	Randomly selected, population representative; TLGS^j, baseline 1999	8.4%	Cook 13.1% de Ferranti 26.4%
Bahrani et al. [35]	2016	Iran	538	14–18	Random sampling procedure. 12 high schools in Shiraz, Iran		Cook 6.1%
Kim et al. [52]	2016	Korea	2330	10–18	Population representative; KNHANES 2010–2012	2.1%	Ford 5.7%
Wang et al. [44]	2015	China	1770	7–17	Random sample of 10 schools in urban area of Guangzhou, China	1.1% (10–17)	Cook 2.5% (7–17)
Al-Hussein et al. [36]	2014	Saudi Arabia	2 149	6–17	Random sample of students in Riyadh; S.Ch.O.O.Ls^k study	2.0%	Cook and Ford 4.9% de Ferranti 17.5%
Fadzlina et al. [49]	2014	Malaysia	1014	13	Population-based study; students from urban and rural schools	2.6%
Li et al. [39]	2014	China	910	11–16	Students from 30 high-school classes in North East China	7.6%
Hosseinpanah et al. [34]	2013	Iran	1424	11–18	Randomized, population representative; TLGS, baseline 1999–2001		Cook 13.3%
Australia
Huang et al. [81]	2013	Australia	964	17	Representative sample of adolescents from Western Australia	2.7%
Africa
Sekokotla et al. [30]	2017	South Africa	371	13–18	Selected high schools in Mthatha, South Africa		Cook ♂6.0% ♀3.1%
Benmohammed et al. [47]	2015	Algeria	989	12–18	Randomized recruitment of school children in the city of Constantine	♂ 1.3% ♀ 0.5%	Cook ♂2.6% ♀0.6% de Ferranti ♂4.0% ♀2.0%
Matsha et al. [45]	2013	South Africa	1272	10–16	Randomly selected from primary schools 2007–2008	1.9%

^aStudy of Latino Youth.
^bNational Health and Nutrition Examination Survey.
^cCanadian Health Measures Survey.
^dIn Spanish Associación de la Fuerza Prensil con Manifestaciones de Riesgo Cardiovascular Tempranas en Niños y Adolescentes Colombianos.
^eIdentification of risk factors for adult non-communicable chronic disease in schooled population.
^fEstudo de Riscos Cardiovasculares em Adolescentes (study of cardiovascular risk in adolescents).
^gEvaluation of growth, development, and cardio-metabolic risk factors in school children and adolescents from Mérida, Venezuela.
^hChina Health and Nutrition Survey.
ⁱKorea National Health and Nutrition Examination Survey.
^jTeheran Lipid and Glucose Study.
^kSaudi Children’s Overweight, Obesity and Lifestyles Study.

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Table 2 Epidemiological studies investigating the prevalence of metabolic syndrome in children and adolescents based on the diagnostic criteria from the IDF, Cook et al. [6], Ford et al. [26], and de Ferranti et al. [27].

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