Paulo Francisco de Almeida-Neto, Adam Dominic George Baxter-Jones, Ricardo Fernando Arrais, Jenner Christian Veríssimo de Azevedo, Paulo Moreira Silva Dantas, Breno Guilherme de Araújo Tinôco Cabral, Radamés Maciel Vitor Medeiros
{"title":"增强预测男孩青春期阶段的数学模型：一项横断面研究","authors":"Paulo Francisco de Almeida-Neto, Adam Dominic George Baxter-Jones, Ricardo Fernando Arrais, Jenner Christian Veríssimo de Azevedo, Paulo Moreira Silva Dantas, Breno Guilherme de Araújo Tinôco Cabral, Radamés Maciel Vitor Medeiros","doi":"10.1002/ajhb.24193","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Previously, we developed a mathematical model capable of predicting pubertal development (PD) through seven anthropometric variables, with an accuracy of 75%. We believe that it is possible to develop a similar model that uses fewer anthropometric measurements and provides greater precision.</p><p><strong>Objective: </strong>Develop a mathematical model capable of predicting PD through anthropometric variables.</p><p><strong>Methods: </strong>We evaluated the anthropometric profile and PD by medical analysis in 203 boys (Age = 12.6 ± 2.6). Subsequently, we divided the boys into groups: development (n = 121) and cross-validation (n = 82). Data from the development group were subjected to discriminant analysis to identify which anthropometric indicators would be potential predictors of PD. We subsequently developed an equation based on the indicated indicators and tested its validation using data from the cross-validation group.</p><p><strong>Results: </strong>Discriminant analyses showed that age and sitting-height were the variables with the greatest power to predict PD (p < 0.05). Consequently, the mathematical model was developed: Puberty-score = -17.357 + (0.603 × Age [years]) + (0.127 × Sitting-height [cm]). Based on the scores generated, we classified PD into stage-I (score ≤ -1.815), stage-II (score = -1.816 to -0.605), stage-III (score = -0.606 to 0.695), stage-IV (score = 0.696-3.410), and stage-V (score > 3.410). No differences were found between PD assessments performed by doctors and assessments using the mathematical model (p > 0.5). The prediction model showed high agreement (R<sup>2</sup> = 0.867; CCC = 0.899; ICC = 0.900; Kappa = 0.922; α-Krippendorff = 0.885; Bland-Altman LoAs = -2.0, 2.0; pure error = 0.0009) with accuracy of 82.8% and precision of 82%. Analyses in the cross-validation group confirmed the reliability of the prediction model.</p><p><strong>Conclusion: </strong>The developed mathematical model presents high reliability, validity and accuracy and precision above 80% for determining PD in boys.</p>","PeriodicalId":50809,"journal":{"name":"American Journal of Human Biology","volume":" ","pages":"e24193"},"PeriodicalIF":1.6000,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhancement of a Mathematical Model for Predicting Puberty Stage in Boys: A Cross-Sectional Study.\",\"authors\":\"Paulo Francisco de Almeida-Neto, Adam Dominic George Baxter-Jones, Ricardo Fernando Arrais, Jenner Christian Veríssimo de Azevedo, Paulo Moreira Silva Dantas, Breno Guilherme de Araújo Tinôco Cabral, Radamés Maciel Vitor Medeiros\",\"doi\":\"10.1002/ajhb.24193\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Previously, we developed a mathematical model capable of predicting pubertal development (PD) through seven anthropometric variables, with an accuracy of 75%. We believe that it is possible to develop a similar model that uses fewer anthropometric measurements and provides greater precision.</p><p><strong>Objective: </strong>Develop a mathematical model capable of predicting PD through anthropometric variables.</p><p><strong>Methods: </strong>We evaluated the anthropometric profile and PD by medical analysis in 203 boys (Age = 12.6 ± 2.6). Subsequently, we divided the boys into groups: development (n = 121) and cross-validation (n = 82). Data from the development group were subjected to discriminant analysis to identify which anthropometric indicators would be potential predictors of PD. We subsequently developed an equation based on the indicated indicators and tested its validation using data from the cross-validation group.</p><p><strong>Results: </strong>Discriminant analyses showed that age and sitting-height were the variables with the greatest power to predict PD (p < 0.05). Consequently, the mathematical model was developed: Puberty-score = -17.357 + (0.603 × Age [years]) + (0.127 × Sitting-height [cm]). Based on the scores generated, we classified PD into stage-I (score ≤ -1.815), stage-II (score = -1.816 to -0.605), stage-III (score = -0.606 to 0.695), stage-IV (score = 0.696-3.410), and stage-V (score > 3.410). No differences were found between PD assessments performed by doctors and assessments using the mathematical model (p > 0.5). The prediction model showed high agreement (R<sup>2</sup> = 0.867; CCC = 0.899; ICC = 0.900; Kappa = 0.922; α-Krippendorff = 0.885; Bland-Altman LoAs = -2.0, 2.0; pure error = 0.0009) with accuracy of 82.8% and precision of 82%. Analyses in the cross-validation group confirmed the reliability of the prediction model.</p><p><strong>Conclusion: </strong>The developed mathematical model presents high reliability, validity and accuracy and precision above 80% for determining PD in boys.</p>\",\"PeriodicalId\":50809,\"journal\":{\"name\":\"American Journal of Human Biology\",\"volume\":\" \",\"pages\":\"e24193\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Human Biology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/ajhb.24193\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ANTHROPOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Human Biology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/ajhb.24193","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ANTHROPOLOGY","Score":null,"Total":0}
Enhancement of a Mathematical Model for Predicting Puberty Stage in Boys: A Cross-Sectional Study.
Background: Previously, we developed a mathematical model capable of predicting pubertal development (PD) through seven anthropometric variables, with an accuracy of 75%. We believe that it is possible to develop a similar model that uses fewer anthropometric measurements and provides greater precision.
Objective: Develop a mathematical model capable of predicting PD through anthropometric variables.
Methods: We evaluated the anthropometric profile and PD by medical analysis in 203 boys (Age = 12.6 ± 2.6). Subsequently, we divided the boys into groups: development (n = 121) and cross-validation (n = 82). Data from the development group were subjected to discriminant analysis to identify which anthropometric indicators would be potential predictors of PD. We subsequently developed an equation based on the indicated indicators and tested its validation using data from the cross-validation group.
Results: Discriminant analyses showed that age and sitting-height were the variables with the greatest power to predict PD (p < 0.05). Consequently, the mathematical model was developed: Puberty-score = -17.357 + (0.603 × Age [years]) + (0.127 × Sitting-height [cm]). Based on the scores generated, we classified PD into stage-I (score ≤ -1.815), stage-II (score = -1.816 to -0.605), stage-III (score = -0.606 to 0.695), stage-IV (score = 0.696-3.410), and stage-V (score > 3.410). No differences were found between PD assessments performed by doctors and assessments using the mathematical model (p > 0.5). The prediction model showed high agreement (R2 = 0.867; CCC = 0.899; ICC = 0.900; Kappa = 0.922; α-Krippendorff = 0.885; Bland-Altman LoAs = -2.0, 2.0; pure error = 0.0009) with accuracy of 82.8% and precision of 82%. Analyses in the cross-validation group confirmed the reliability of the prediction model.
Conclusion: The developed mathematical model presents high reliability, validity and accuracy and precision above 80% for determining PD in boys.
期刊介绍：
The American Journal of Human Biology is the Official Journal of the Human Biology Association.
The American Journal of Human Biology is a bimonthly, peer-reviewed, internationally circulated journal that publishes reports of original research, theoretical articles and timely reviews, and brief communications in the interdisciplinary field of human biology. As the official journal of the Human Biology Association, the Journal also publishes abstracts of research presented at its annual scientific meeting and book reviews relevant to the field.
The Journal seeks scholarly manuscripts that address all aspects of human biology, health, and disease, particularly those that stress comparative, developmental, ecological, or evolutionary perspectives. The transdisciplinary areas covered in the Journal include, but are not limited to, epidemiology, genetic variation, population biology and demography, physiology, anatomy, nutrition, growth and aging, physical performance, physical activity and fitness, ecology, and evolution, along with their interactions. The Journal publishes basic, applied, and methodologically oriented research from all areas, including measurement, analytical techniques and strategies, and computer applications in human biology.
Like many other biologically oriented disciplines, the field of human biology has undergone considerable growth and diversification in recent years, and the expansion of the aims and scope of the Journal is a reflection of this growth and membership diversification.
The Journal is committed to prompt review, and priority publication is given to manuscripts with novel or timely findings, and to manuscripts of unusual interest.
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