[探索回归计算在估计中国地区食物摄入量的适用性]
Yiyao Lian1, Yuehui Fang1, Zhihan Xu1
1NHC Key Laboratory of Public Nutrition and Health, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Wei sheng yan jiu = Journal of hygiene research
|March 12, 2026
概括
回归策略有效地估计了未经调查的中国地区的食物摄入量,支持国家营养监测. 这种空间归算方法显示了各种食品类型和人口群体的可靠结果.
科学领域:
- 营养流行病学 营养流行病学
- 地质统计学 在地质统计学
- 空间分析是一种空间分析.
背景情况:
- 国家营养监测需要准确的食物摄入数据,即使在未经调查的地区.
- 空间归算方法对于填补大规模调查中的数据缺口至关重要.
- 以前的方法可能缺乏详细的营养评估所需的空间分辨率.
研究的目的:
- 开发和验证回归试验方法,以估计中国未经调查的地区的成年人食物摄入量.
- 为国家营养监测系统中的空间归算提供方法支持.
- 评估回归计算对食物摄入量估计的区域适用性.
主要方法:
- 通过使用中国营养和慢性疾病监测 (2015) 数据结合逐步回归和普通 kriging 来构建回归 kriging 模型.
- 该模型被应用到县级,以计算不同年龄和性别群体在未经调查的地区的食物摄入量.
- 使用R2,RMSE和MAE评估模型性能,采用离开一个缺席的交叉验证.
主要成果:
- 性别和教育水平显著影响了食物摄入量;人均GDP的影响最小.
- 全谷物模型显示最佳匹配 (R2=0.479),而豆类模型则产生了最低的RMSE和MAE.
- 国家一级估计差异很小 (男性:2.08%,女性:1.80%),红肉和全谷物显示出最小的误差. 省级差异差异很大,从天津的1.74%到西藏的37.40%.
结论:
- 回归战争是一种有效的方法,用于在国家监测期间在未经调查的地区归算食物摄入数据.
- 对于具有均样本分布和残留物强大的空间自相关性的食品类型,该方法的准确性得到了提高.
- 这种方法为改善国家营养监测的空间覆盖和准确性提供了有价值的方法支持.
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