预测建模用于识别儿童中衰老风险的预测模型
Siti Rahayu Nadhiroh1, Armedy Ronny Hasugian2, Allisa Nadhira Permata Arinda Putri1
1Department of Nutrition, Faculty of Public Health, Universitas Airlangga, Surabaya, Indonesia.
Food and nutrition bulletin
|January 14, 2026
概括
印度尼西亚面临着高的儿童发育迟缓率. 一个预测模型确定了年龄,出生体重和母乳养等关键风险因素,在识别有风险的儿童方面达到73.8%的准确性.
科学领域:
- 公共卫生 公共卫生
- 儿科 儿科 儿科
- 数据科学数据科学数据科学
背景情况:
- 印度尼西亚仍然面临着儿童发育迟缓的重大负担,这会给短期和长期的健康和经济造成严重后果.
- 发育迟缓的影响包括增加发病率,死亡率,增长障碍,更高的慢性疾病风险和未来生产率的降低.
研究的目的:
- 确定与印尼儿童发育迟缓相关的主要风险因素.
- 开发和评估一个预测模型,用于识别患有衰退风险的儿童.
主要方法:
- 分析2018年印度尼西亚基本健康研究数据库,包括13,106名5岁以下的儿童及其母亲.
- 两变量分析以确定显著的风险因素,其次是预测决策树模型.
- 接收器操作特征 (ROC) 曲线分析以评估模型性能.
主要成果:
- 全国发育迟缓率为25.8%. 在全国,发育迟缓率为25.8%.
- 通过决策树模型识别的关键预测因素包括年龄,性别,出生体重,出生长度,母亲教育,洗手习惯和纯母乳养.
- 预测模型实现了73.8%的准确性,ROC曲线上的曲线下的面积 (AUC) 为63.7%.
结论:
- 开发的预测模型在评估衰老风险方面表现出可接受的准确性.
- 决策树模型有效地区分了不同年龄组的缩和非缩儿童,ROC曲线分析支持这一观点.
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