International Journal of Pediatrics Research
International Journal of Pediatrics Research. 2024; 4: (2) ; 10.12208/j.ijped.20240014 .
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浙江树人学院 浙江杭州
*通讯作者： 李英,单位：浙江树人学院 浙江杭州；
近年来，儿童肥胖已成为全球公共卫生领域的重要挑战，其与代谢综合征（Metabolic Syndrome, MetS）的密切关联更是引发了广泛关注。代谢综合征以中心性肥胖、胰岛素抵抗、高血压、血脂异常及糖代谢紊乱为主要特征，显著增加儿童远期心血管疾病和2型糖尿病的风险。大量流行病学研究表明，肥胖儿童中MetS的患病率高达15%-30%，且呈现逐年上升趋势。这一现象不仅与遗传易感性相关，更受到环境因素、生活方式及社会心理因素的共同影响。从病理机制来看，儿童肥胖与MetS的核心关联在于胰岛素抵抗和慢性低度炎症状态。过量的内脏脂肪组织释放游离脂肪酸和促炎细胞因子，干扰胰岛素信号通路，进而导致糖脂代谢紊乱。此外，肥胖儿童常伴随下丘脑-垂体轴功能失调，进一步加剧代谢异常。近年来，神经内分泌研究还发现，肥胖与注意缺陷多动障碍（ADHD）等神经发育问题可能存在共同的生物学基础，提示多系统交互影响的复杂性。在临床评估方面，目前国际上有多个儿童MetS诊断标准，如国际糖尿病联盟（IDF）和美国国家胆固醇教育计划（NCEP-ATPⅢ）的标准，但其适用性仍存在争议。新兴生物标志物（如瘦素、脂联素）的引入为早期筛查提供了新思路。在干预策略上，综合管理模式展现出显著优势。生活方式干预（如运动处方、膳食调整）是基础，其中结构化运动（如有氧结合抗阻训练）和低升糖指数饮食被证实能有效改善代谢指标。心理行为干预（如认知行为疗法）和家庭-学校协同支持同样不可或缺。值得注意的是，多学科协作模式（如法国ADHD诊疗经验）为儿童肥胖-MetS的长期管理提供了可借鉴的框架。尽管现有研究取得了重要进展，但仍存在若干挑战，如长期随访数据的缺乏、干预措施的个体化优化等。未来研究需结合基因组学、代谢组学等前沿技术，探索精准防控路径。综上所述，儿童肥胖与代谢综合征的防治亟需从生物-心理-社会医学模式出发，构建早期筛查、科学干预和全程管理的综合体系。
In recent years, childhood obesity has become an important challenge in the field of global public health, and its close association with metabolic syndrome (MetS) has aroused widespread concern. Metabolic syndrome is characterized by central obesity, insulin resistance, hypertension, dyslipidemia and glucose metabolism disorders, which significantly increase the risk of long-term cardiovascular disease and type 2 diabetes in children. A large number of epidemiological studies have shown that the prevalence of MetS in obese children is as high as 15%-30%, and presents an increasing trend year by year. This phenomenon is not only related to genetic susceptibility, but also affected by environmental factors, lifestyle and social psychological factors. From the pathological point of view, the core association between childhood obesity and MetS lies in insulin resistance and chronic low-grade inflammatory state. Excess visceral adipose tissue releases free fatty acids and pro-inflammatory cytokines that interfere with insulin signaling pathways, resulting in disorders of glycolipid metabolism. In addition, obese children are often associated with hypothalamic-pituitary axis dysfunction, further exacerbating metabolic abnormalities. In recent years, neuroendocrine studies have also found that obesity and neurodevelopmental problems such as attention deficit hyperactivity disorder (ADHD) may have a common biological basis, suggesting the complexity of multisystem interactions. In terms of clinical evaluation, there are currently several international diagnostic criteria for MetS in children, such as the International Diabetes Federation (IDF) and the National Cholesterol Education Program (NCEP-ATP III), but their applicability is still controversial. The introduction of emerging biomarkers such as leptin and adiponectin provides new ideas for early screening. In the intervention strategy, the integrated management model showed significant advantages. Lifestyle interventions (such as exercise prescriptions and dietary adjustments) are the foundation, among which structured exercise (such as aerobic combined with resistance training) and a low glycemic index diet have been proven to be effective in improving metabolic indicators. Psychobehavioral interventions such as cognitive behavioral therapy and collaborative family-school support are also essential. It is worth noting that multidisciplinary collaborative models, such as the French ADHD experience, provide a framework for the long-term management of childhood obesity-MetS. Despite important advances in existing studies, several challenges remain, such as lack of long-term follow-up data and individualized optimization of interventions. Future research needs to combine genomics, metabolomics and other cutting-edge technologies to explore precise prevention and control paths. To sum up, the prevention and treatment of childhood obesity and metabolic syndrome urgently needs to construct a comprehensive system of early screening, scientific intervention and overall management from the bio-psychological-social medical model.
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