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

Shafiee, Gita; Kelishadi, Roya; Heshmat, Ramin; Qorbani, Mostafa; Motlagh, Mohammad Esmaeil; Aminaee, Tahereh; Ardalan, Gelayol; Taslimi, Mahnaz; Poursafa, Parinaz; Larijani, Bagher

doi:10.5603/ep.2013.0006

Cited by 39 publications

(30 citation statements)

References 43 publications

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“…Otro país es Turquía, donde se ha reportado una prevalencia del SM de 2.3% en adolescentes de 10-19 años 39 o de 2.5-4.4% en niños de primaria y secundaria dependiendo del método de diagnóstico utilizado40 . De igual manera, Irán tiene una prevalencia del SM de 5.3% en niños de 6 a 11 años 41 , de 6.5% en adolescentes entre 15 a 18 años 42 , y de 4.4% en adolescentes de 10-18 años43 . Mientras que las prevalencias del SM altas han sido reportadas en países como Italia (niños y adolescentes de 6 a 14 años con 13.0%)44 .…”

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Prevalencia De Síndrome Metabólico en Niños Y Adolescentes De América

Pierlot

Cuevas-Romero

Rodríguez-Antolín

et al. 2017

TIP

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Nota: Artículo recibido el 09 de abril de 2016 y aceptado el 25 de octubre de 2016. ARTÍCULO DE REVISIÓN reSumen Objetivo: Analizar la prevalencia del Síndrome Metabólico (SM) y sus componentes en niños y adolescentes del continente Americano. Método: La recopilación de la información se tomó de artículos científicos de los años 2008 al 2016 que aparecen en las bases de datos PubMed, Europe PMC y SciELO. Se incluyeron estudios que muestran datos cuantitativos de los componentes del SM en niños y/o adolescentes entre 4 y 19 años de edad. Resultados: Se analizaron 23 estudios realizados en 12 países del continente americano, de los cuales sólo 3 consideraron el factor edad. Los componentes del SM más prevalentes fueron la obesidad y las dislipidemias. Mientras que los menos prevalentes fueron hiperglicemia e hipertensión. La hipoαlipoproteinemia, la hipertensión y el SM fueron más frecuentes en hombres que en mujeres. Pocos estudios analizaron factores de riesgo para el SM. Conclusión: La presencia del SM y sus componentes en niños y adolescentes americanos es variable. La variabilidad es también observada en países de otros continentes. Esta revisión evidencia la necesidad de definir los criterios de diagnóstico del SM en niños y jóvenes, y la urgencia de diseñar estrategias de prevención de las alteraciones metabólicas en edades tempranas, involucrando la participación de la familia, la sociedad y las instituciones públicas.

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Prevalencia De Síndrome Metabólico en Niños Y Adolescentes De América

Pierlot

Cuevas-Romero

Rodríguez-Antolín

et al. 2017

TIP

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“…Of these 24 papers, 22 report about the development of one or more risk model or score [24][25][26][27][28][29][30][31][32][33][34][35]37,38,[40][41][42][43][44][45][46][47], and 2 studies report about the development and external validation of one or more risk model or scores on an external population [36,39].Overall, the 24 studies reported 40 models, out of which 24 models were selected for full data extraction. The rest (16 models) were not selected, either because they were judged to be minimally different from the reported ones or they were not the preferred models by the authors or they were significantly deficient in details or statistical reporting.…”

Section: Resultsmentioning

confidence: 99%

“…Regarding the age of the sample, more risk scores were reported in adults than in children or adolescent. Of the 24 included models, 15 risk models were focused on adult subjects [24,25,29,[31][32][33][34][35][36][37][38][41][42][43][44]47], while 8 targets children and adolescents [26][27][28]30,39,40,45,46]. Table 4.0 shows the details of the components of the included 24 risk models or scores as well as their statistical properties-which includes (where available) their "sensitivity, specificity, discrimination, calibration, positive and negative predictive values, AUROC".…”

Section: Resultsmentioning

confidence: 99%

Risk models and scores for metabolic syndrome: a systematic review

Ibrahim

Pang

Pappas

et al. 2020

Preprint

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Background:Metabolic syndrome is linked with increased risk of cardiovascular disease, diabetes and all-cause mortality. Despite the high number of models and scores for assessing the risk of developing MetS, there is hardly any used in practical setting. Hence, we conducted a systematic review to determine the performance of risk models and scores for predicting metabolic syndrome.Methods:We systematically searched MEDLINE, CINAHL, PUBMED and Web of Science to identify studies that either derive or validate risk prediction models or scores for predicting the risk of metabolic syndrome. Data concerning models’ statistical properties as well as details of internal or external validations were extracted. Tables were used to compare various components of models and statistical properties. Finally, PROBAST was used to assess the methodological quality (risk of bias) of included studies.Results:A total of 15102 titles were scanned, 29 full papers were analysed in detail and 24 papers were included. The studies reported about the development, validation or both of 40 MetS risk models; out of these, 24 models were studied in details. There is significant heterogeneity between studies in terms of geography/demographics, data type and methodological approach. Majority of the models or risk scores were developed or validated using data from cross-sectional studies, or routine data that were often assembled for other reasons. Various combinations of risk factors (predictors) were considered significant in the respective final model. Similarly, different criteria were used in the diagnosis of MetS, but, NCEP criteria including its modified versions were by far the most widely used (32.5%). There is generally poor reporting quality across the studies, especially concerning statistical data. Any form of internal validation is either not conducted, or not reported in nearly a fifth of the studies. Only two (2) risk models or scores were externally validatedConclusions:There is an abundance of MetS models in the literature. But, their usefulness is doubtful, due to limitations in methodology, poor reporting and lack of external validation and impact studies. Therefore, researchers in the future should focus more on externally validating/ applying such models in a different setting.Protocol: The protocol of this study can be found at https://bmjopen.bmj.com/content/9/9/e027326PROSPERO registration number CRD42019139326

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“…We have previously published the methodology of the cMetS score calculation in detail [ 29 ]. In brief, the cMetS score was computed by standardizing the residuals (z-scores) of WC, MAP, HDL-C, TG, and FBG by regressing them according to age and sex to account for age and gender-related differences.…”

Section: Methodsmentioning

confidence: 99%

Is the association of continuous metabolic syndrome risk score with body mass index independent of physical activity? The CASPIAN-III study

et al. 2015

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BACKGROUND/OBJECTIVESAlthough the association of body mass index (BMI) with metabolic syndrome (MetS) is well documented, there is little knowledge on the independent and joint associations of BMI and physical activity with MetS risk based on a continuous scoring system. This study was designed to explore the effect of physical activity on interactions between excess body weight and continuous metabolic syndrome (cMetS) in a nationwide survey of Iranian children and adolescents.SUBJECTS/METHODSData on 5,625 school students between 10 and 18 years of age were analyzed. BMI percentiles, screen time activity (STA), leisure time physical activity (LTPA) levels, and components of cMetS risk score were extracted. Standardized residuals (z-scores) were calculated for MetS components. Linear regression models were used to study the interactions between different combinations of cMetS, LTPA, and BMI percentiles.RESULTSOverall, 984 (17.5%) subjects were underweight, whereas 501 (8.9%) and 451 (8%) participants were overweight and obese, respectively. All standardized values for cMetS components, except fasting blood glucose level, were directly correlated with BMI percentiles in all models (P-trend < 0.001); these associations were independent of STA and LTPA levels. Linear associations were also observed among LTPA and standardized residuals for blood pressure, high-density lipoprotein, and waist circumference (P-trend < 0.01).CONCLUSIONSOur findings suggest that BMI percentiles are associated with cMetS risk score independent of LTPA and STA levels.

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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

Cited by 39 publications

References 43 publications

Prevalencia De Síndrome Metabólico en Niños Y Adolescentes De América

Prevalencia De Síndrome Metabólico en Niños Y Adolescentes De América

Risk models and scores for metabolic syndrome: a systematic review

Is the association of continuous metabolic syndrome risk score with body mass index independent of physical activity? The CASPIAN-III study

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