Ayuzo Del Valle Norma Cipatli, Pérez-Treviño Perla, Cepeda Lopez Ana Carla, Murillo-Torres Regina M, Castillo Elena Cristina, Gutierrez-Cantu Diego, Tamez-Rivera Oscar, Paez Flores Mayela, Flores-Ayuzo Isabella, Luévano-Martinez Luis Alberto, Fernandez Ortiz Sergio Javier, García Noemí, Mancillas-Adame Leonardo
Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, NL, Mexico.
Tecnologico de Monterrey, The Institute for Obesity Research, Monterrey, NL, Mexico.
Front Pediatr. 2025 May 22;13:1597309. doi: 10.3389/fped.2025.1597309. eCollection 2025.
Traditional Body Mass Index based obesity classification presents limitations in pediatric populations, particularly among physically active children. The 2025 Obesity Classification Framework proposed by The Lancet Diabetes & Endocrinology Commission integrates body fat distribution and metabolic biomarkers, aiming to enhance diagnostic accuracy in pediatric obesity.
We evaluated 111 physically active children (aged 5-11 years) from the Monterrey Football League in Mexico using both the traditional BMI-based classification and the new 2025 Obesity Classification Framework, which incorporates body composition (measured by bioelectrical impedance analysis), waist-to-height ratio, and metabolic biomarkers. Each participant was classified with both frameworks, and outcomes were compared against metabolic risk markers. Normality was assessed using the Shapiro-Wilk test. Non-normally distributed variables (fat mass, visceral fat, triglycerides, creatinine, and pCr) were analyzed using non-parametric tests, while parametric tests were applied for normally distributed data. Agreement between classifications was determined using Cohen's kappa coefficient.
Agreement between classifications was moderate ( = 0.532, < 0.001). Using the new framework, 20 children previously classified as overweight by BMI were reclassified as having preclinical obesity, reflecting excess adiposity previously unrecognized. Conversely, four participants initially categorized as obese by BMI were reclassified as non-obese, reflecting elevated lean mass rather than adiposity. Participants categorized as having preclinical obesity exhibited significantly higher levels of LDL cholesterol and apolipoprotein B compared to non-obese peers.
The 2025 Obesity Classification Framework provides greater precision than traditional BMI-based assessments by effectively differentiating between excess adiposity and increased lean mass in physically active children. Although bioelectrical impedance analysis was selected due to its practicality, cost-effectiveness, and non-invasiveness, it has inherent measurement variability compared to dual-energy x-ray absorptiometry. Future research validating these results against DXA or other reference standards is recommended. Adopting this comprehensive assessment strategy may facilitate earlier and more targeted interventions for children at risk of obesity-related complications.
https://doi.org/10.1186/ISRCTN12172320, identifier ISRCTN12172320.
基于传统体重指数的肥胖分类在儿科人群中存在局限性，尤其是在身体活跃的儿童中。《柳叶刀》糖尿病与内分泌学委员会提出的2025年肥胖分类框架整合了体脂分布和代谢生物标志物，旨在提高儿科肥胖的诊断准确性。
我们使用基于传统BMI的分类方法和新的2025年肥胖分类框架对来自墨西哥蒙特雷足球联赛的111名身体活跃的儿童（5 - 11岁）进行了评估，新框架纳入了身体成分（通过生物电阻抗分析测量）、腰高比和代谢生物标志物。每个参与者都用这两种框架进行分类，并将结果与代谢风险标志物进行比较。使用夏皮罗-威尔克检验评估正态性。对非正态分布变量（脂肪量、内脏脂肪、甘油三酯、肌酐和pCr）使用非参数检验进行分析，而对正态分布数据应用参数检验。使用科恩kappa系数确定分类之间的一致性。
分类之间的一致性为中等（κ = 0.532，P < 0.001）。使用新框架，20名先前被BMI分类为超重的儿童被重新分类为患有临床前肥胖，这反映出之前未被识别的过度肥胖。相反，4名最初被BMI分类为肥胖的参与者被重新分类为非肥胖，这反映出瘦体重增加而非肥胖。与非肥胖同龄人相比，被分类为患有临床前肥胖的参与者的低密度脂蛋白胆固醇和载脂蛋白B水平显著更高。
2025年肥胖分类框架通过有效区分身体活跃儿童的过度肥胖和增加的瘦体重，比基于传统BMI的评估提供了更高的精度。尽管由于生物电阻抗分析的实用性、成本效益和非侵入性而被选用，但与双能X线吸收法相比，它具有固有的测量变异性。建议未来开展针对这些结果与双能X线吸收法或其他参考标准进行验证的研究。采用这种综合评估策略可能有助于对有肥胖相关并发症风险的儿童进行更早且更有针对性的干预。
