Álvaro Torres-Martos, Francisco Requena, Guadalupe López-Rodríguez, Jhazmin Hernández-Cabrera, Marcos Galván, Elizabeth Solís-Pérez, Susana Romo-Tello, José Luis Jasso-Medrano, Jenny Vilchis-Gil, Miguel Klünder-Klünder, Gloria Martínez-Andrade, María Elena Acosta Enríquez, Juan Carlos Aristizabal, Alberto Ramírez-Mena, Nikos Stratakis, Mireia Bustos-Aibar, Ángel Gil, Mercedes Gil-Campos, Gloria Bueno, Rosaura Leis, Jesús Alcalá-Fdez, Concepción María Aguilera, Augusto Anguita-Ruiz
{"title":"ObMetrics:一个闪亮的应用程序,以协助代谢综合征评估在儿童肥胖。","authors":"Álvaro Torres-Martos, Francisco Requena, Guadalupe López-Rodríguez, Jhazmin Hernández-Cabrera, Marcos Galván, Elizabeth Solís-Pérez, Susana Romo-Tello, José Luis Jasso-Medrano, Jenny Vilchis-Gil, Miguel Klünder-Klünder, Gloria Martínez-Andrade, María Elena Acosta Enríquez, Juan Carlos Aristizabal, Alberto Ramírez-Mena, Nikos Stratakis, Mireia Bustos-Aibar, Ángel Gil, Mercedes Gil-Campos, Gloria Bueno, Rosaura Leis, Jesús Alcalá-Fdez, Concepción María Aguilera, Augusto Anguita-Ruiz","doi":"10.1111/ijpo.70016","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":217,"journal":{"name":"Pediatric Obesity","volume":" ","pages":"e70016"},"PeriodicalIF":2.7000,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ObMetrics: A Shiny app to assist in metabolic syndrome assessment in paediatric obesity.\",\"authors\":\"Álvaro Torres-Martos, Francisco Requena, Guadalupe López-Rodríguez, Jhazmin Hernández-Cabrera, Marcos Galván, Elizabeth Solís-Pérez, Susana Romo-Tello, José Luis Jasso-Medrano, Jenny Vilchis-Gil, Miguel Klünder-Klünder, Gloria Martínez-Andrade, María Elena Acosta Enríquez, Juan Carlos Aristizabal, Alberto Ramírez-Mena, Nikos Stratakis, Mireia Bustos-Aibar, Ángel Gil, Mercedes Gil-Campos, Gloria Bueno, Rosaura Leis, Jesús Alcalá-Fdez, Concepción María Aguilera, Augusto Anguita-Ruiz\",\"doi\":\"10.1111/ijpo.70016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>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. 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ObMetrics: A Shiny app to assist in metabolic syndrome assessment in paediatric obesity.
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.
期刊介绍:
Pediatric Obesity is a peer-reviewed, monthly journal devoted to research into obesity during childhood and adolescence. The topic is currently at the centre of intense interest in the scientific community, and is of increasing concern to health policy-makers and the public at large.
Pediatric Obesity has established itself as the leading journal for high quality papers in this field, including, but not limited to, the following:
Genetic, molecular, biochemical and physiological aspects of obesity – basic, applied and clinical studies relating to mechanisms of the development of obesity throughout the life course and the consequent effects of obesity on health outcomes
Metabolic consequences of child and adolescent obesity
Epidemiological and population-based studies of child and adolescent overweight and obesity
Measurement and diagnostic issues in assessing child and adolescent adiposity, physical activity and nutrition
Clinical management of children and adolescents with obesity including studies of treatment and prevention
Co-morbidities linked to child and adolescent obesity – mechanisms, assessment, and treatment
Life-cycle factors eg familial, intrauterine and developmental aspects of child and adolescent obesity
Nutrition security and the "double burden" of obesity and malnutrition
Health promotion strategies around the issues of obesity, nutrition and physical activity in children and adolescents
Community and public health measures to prevent overweight and obesity in children and adolescents.