基于数智健康技术的学龄前儿童肥胖综合干预的预实验研究

doi:10.11852/zgetbjzz2025-0995

摘要/Abstract

摘要： 目的探讨基于数智健康技术的“幼儿园-家庭-医疗”多方协作模式在学龄前儿童肥胖干预中的效果,为未来大规模、高质量的随机对照试验提供实践经验与科学依据。方法 2025年4月,选取山东省济南市1所幼儿园的8个中班和大班,共176名4~6岁儿童,开展为期3个月的健康体重管理干预。研究构建了“幼儿园-家庭-医疗机构”三位一体的干预体系,依托课题组开发的数智健康平台,根据儿童基线体重状况及肥胖相关行为风险,设定三级干预措施:一级(一般儿童)接受常规健康教育和生长监测;二级(高风险儿童)在此基础上增加个性化目标设定和健康行为反馈;三级(超重或肥胖儿童)进一步结合动机访谈和医生指导。通过干预前后评估儿童身体测量指标及肥胖相关行为的变化来评价干预效果。结果干预后儿童的体质量指数(BMI)与BMI Z评分下降(分别减少0.15kg/m²和0.09,P<0.01),腰围身高比和体脂百分比也降低(P<0.01)。超重率和肥胖率分别下降10.79%、5.69%,超重和肥胖儿童的身体测量指标改善效果更明显。干预后儿童达成减少油炸食品和不喝含糖饮料的目标人数增加(P<0.01),其中肥胖儿童的日均能量摄入下降286.44kCal;呈身体活动增加、静态时间减少的趋势。儿童家长对干预措施的依从性较好,数智健康平台使用率约为80%,参与项目的满意度较高。结论基于数智健康平台的肥胖综合干预模式可有效改善学龄前儿童的身体测量指标和肥胖相关行为。未来需开展更长周期及更大样本的随机对照干预试验,以验证该干预技术的效果。

关键词: 学龄前儿童, 肥胖, 干预, 数智健康

Abstract: Objective To evaluate the effectiveness of a digital-intelligence health technology-based, multi-sector collaborative model (kindergarten-family-healthcare) for obesity intervention in preschool children, in order to provide practical insights and a scientific basis for future large-scale, high-quality randomized controlled trials (RCTs). Methods A total of 176 children aged 4 - 6 years from a kindergarten in Jinan, Shandong Province, participated in a 3-month weight management intervention starting in April 2025. The study established atripartite intervention system involving kindergartens, families, and healthcare institutions, supported by a digital-intelligence health platform developed by the research team. Based on baseline weight status and obesity-related behavioral risks, three intervention levels were implemented: Level 1 (general children) received routine health education and growth monitoring; Level 2 (high-risk children) additionally received individualized goal setting and behavioral feedback; Level 3 (overweight or obese children) further incorporated motivational interviewing and physician guidance. Changes in anthropometric indicators and obesity-related behaviors were assessed before and after the intervention. Results After the intervention, children's BMI and BMI Z-scores significantly decreased (by 0.15 kg/m²and 0.09, respectively, P<0.01), along with significant reductions in waist-to-height ratio and body fat percentage (P<0.01). Rates of overweight and obesity declined by 10.79%, 5.69%, respectively. Improvements in anthropometric measures were more pronounced among overweight and obese children. The number of children achieving the goals of reducing fried food intake and avoiding sugar-sweetened beverages increased (P<0.01). Among obese children, daily energy intake decreased by 286.44 kCal. There was also a trend toward increased physical activity and reduced sedentary time. Parents showed good compliance to intervention measures, with approximately 80% utilization of the digital-intelligent health platform and high satisfaction with participation. Conclusions A comprehensive obesity intervention model supported by a digital-intelligence health platform can effectively improve anthropometric indicators and obesity-related behaviors among preschool children. Larger and longer randomized controlled trials are warranted to further validate its effectiveness.

Key words: preschool children, obesity, intervention, digital-intelligence health

中图分类号:

R179

严诗钰, 张莉, 殷春杰, 段雪霞, 李燕, 王海俊. 基于数智健康技术的学龄前儿童肥胖综合干预的预实验研究[J]. 中国儿童保健杂志, 2026, 34(1): 10-16.

YAN Shiyu, ZHANG Li, YIN Chunjie, DUAN Xuexia, LI Yan, WANG Haijun. Pilot study of a comprehensive obesity intervention for preschool children based on digital-intelligence health technology[J]. Chinese Journal of Child Health Care, 2026, 34(1): 10-16.

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