ObMetrics: A Shiny app to assist in metabolic syndrome assessment in paediatric obesity.

Summary: Objective: To introduce ObMetrics, a free and user‐friendly Shiny app that simplifies the calculation, data analysis, and interpretation of Metabolic Syndrome (MetS) outcomes according to multiple definitions in epidemiological studies of paediatric populations. We illustrate its usefulness...

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Publicado en:Pediatric Obesity Vol. 20; no. 8; pp. 1 - 18
Autores principales: Torres‐Martos, Álvaro, Requena, Francisco, López‐Rodríguez, Guadalupe, Hernández‐Cabrera, Jhazmin, Galván, Marcos, Solís‐Pérez, Elizabeth, Romo‐Tello, Susana, Jasso‐Medrano, José Luis, Vilchis‐Gil, Jenny, Klünder‐Klünder, Miguel, Martínez‐Andrade, Gloria, Enríquez, María Elena Acosta, Aristizabal, Juan Carlos, Ramírez‐Mena, Alberto, Stratakis, Nikos, Bustos‐Aibar, Mireia, Gil, Ángel, Gil‐Campos, Mercedes, Bueno, Gloria, Leis, Rosaura
Formato: pictorial research tables/charts Journal Article
Publicado: Wiley-Blackwell Aug2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Aug2025
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        atl: ObMetrics: A Shiny app to assist in metabolic syndrome assessment in paediatric obesity.
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          Torres‐Martos, Álvaro
          Requena, Francisco
          López‐Rodríguez, Guadalupe
          Hernández‐Cabrera, Jhazmin
          Galván, Marcos
          Solís‐Pérez, Elizabeth
          Romo‐Tello, Susana
          Jasso‐Medrano, José Luis
          Vilchis‐Gil, Jenny
          Klünder‐Klünder, Miguel
          Martínez‐Andrade, Gloria
          Enríquez, María Elena Acosta
          Aristizabal, Juan Carlos
          Ramírez‐Mena, Alberto
          Stratakis, Nikos
          Bustos‐Aibar, Mireia
          Gil, Ángel
          Gil‐Campos, Mercedes
          Bueno, Gloria
          Leis, Rosaura
        affil: Department of Biochemistry and Molecular Biology II, Institute of Nutrition and Food Technology 'José Mataix,' Center of Biomedical Research, University of Granada, Granada, Spain
      sug:
        subj:
          Pediatric Obesity
          Metabolic Syndrome X Epidemiology
          Metabolic Syndrome X Diagnosis
          Mobile Applications Utilization
          Human
          Funding Source
          Child
          Adolescence
          Comparative Studies
          Ethnic Groups
          Case Studies
          European Americans
          Hispanic Americans
          Descriptive Statistics
          Lipids Metabolism
          Blood Pressure
          Anthropometry
          Insulin Resistance
          Child: 6-12 years
          Adolescent: 13-18 years
      ab: Summary: Objective: To introduce ObMetrics, a free and user‐friendly Shiny app that simplifies the calculation, data analysis, and interpretation of Metabolic Syndrome (MetS) outcomes according to multiple definitions in epidemiological studies of paediatric populations. We illustrate its usefulness using ethnically different populations in a comparative study of prevalence across cohorts and definitions. Methods: We conducted a case study using data from two ethnically diverse paediatric populations: a Hispanic‐American cohort (N = 1759) and a Hispanic‐European cohort (N = 2411). Using ObMetrics, we computed MetS classifications (Cook, Zimmet, Ahrens) and component‐specific z‐scores for each participant to compare prevalences. Results: The analysis revealed significant heterogeneity in MetS prevalence across different definitions and cohorts. According to Cook, Zimmet, and Ahrens's definitions, MetS prevalence in children with obesity was 25%, 12%, and 48%, respectively, in the Hispanic‐European cohort, and 38%, 27%, and 66% in the Hispanic‐American cohort. Calculating component‐specific z‐scores in each cohort also highlighted ethnic‐specific differences in lipid metabolism and blood pressure. By automating these complex calculations, ObMetrics considerably reduced analysis time and minimised the potential for errors. Conclusion: ObMetrics proved to be a powerful tool for paediatric research, generating detailed reports on the prevalence of MetS and its components based on various definitions and reference standards. Our case study further provides valuable insights into the challenges of characterising metabolic health in paediatric populations. Future efforts should focus on developing unified consensus guidelines for paediatric MetS. Meanwhile, ObMetrics enables earlier identification and targeted intervention for high‐risk children and adolescents.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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