Suppr超能文献

复合婴幼儿喂养指数(CCFI)对儿童营养状况的预测效用:构建最佳 CCFI 最适用公式的比较分析。

Predictive Utility of Composite Child Feeding Indices (CCFIs) for Child Nutritional Status: Comparative Analyses for the Most Suitable Formula for Constructing an Optimum CCFI.

机构信息

School of Public Health, Bielefeld University, Universitätsstraße 25, 33615 Bielefeld, Germany.

Department of Industrial and Health Sciences, Faculty of Applied Sciences, Takoradi Technical University, Takoradi P.O. Box 256, Ghana.

出版信息

Int J Environ Res Public Health. 2022 May 29;19(11):6621. doi: 10.3390/ijerph19116621.

Abstract

Composite child feeding indices (CCFIs) developed from various relevant measures of dietary intake by infants and young children have several potential applications in nutritional epidemiological studies for the development and deployment of precise public health nutrition interventions against child undernutrition. The predictive utility of some CCFIs (computed from varying formulation components) for child nutritional status (stunting, wasting, and underweight) were compared. The purpose of the study was to identify the most suitable among them for possible standardization, validation, and adoption by nutritional health researchers. Using cluster sampling, data from 581 mother-child pairs were collected. Multivariable regression analyses were applied to the data obtained through a community-based analytical cross-sectional survey design. Three of the CCFIs were found to be significantly associated with only wasting (WHZ) from the linear regression models after adjusting for potential confounders and/or correlates. None of the CCFIs (whether in the continuous nor categorical form) was consistently predictive of all three measures of child nutritional status, after controlling for potential confounders and/or correlates, irrespective of the choice of regression method. CCFI 5 was constructed using a dimension reduction technique-namely principal component analysis (PCA)-as the most optimal summary index in terms of predictiveness for child wasting status, validity, and reliability (Cronbach's α = 0.80) that captured relevant dimensions of optimal child food intake. The dimension reduction approach that was used in constructing CCFI 5 is recommended for standardization, validation, and possible adoption for wider applicability across heterogeneous population settings as an optimum CCFI usable for nutritional epidemiological studies among children under five years.

摘要

复合婴幼儿喂养指数(CCFI)由婴幼儿各种相关饮食摄入量的测量方法组成,在针对儿童营养不足制定和实施精确公共卫生营养干预措施的营养流行病学研究中有多种潜在应用。一些 CCFI(由不同配方成分计算得出)对儿童营养状况(发育迟缓、消瘦和体重不足)的预测效果进行了比较。该研究的目的是确定其中最适合的指数,以便可能进行标准化、验证和被营养健康研究人员采用。研究采用聚类抽样,收集了 581 对母婴数据。通过基于社区的分析性横断面调查设计,对获得的数据进行多变量回归分析。经过调整潜在混杂因素和/或关联因素后,在多元线性回归模型中发现,有 3 种 CCFI 仅与消瘦(WHZ)显著相关。在控制潜在混杂因素和/或关联因素后,无论选择何种回归方法,没有任何 CCFI(无论是连续的还是分类的)能够一致预测所有三种儿童营养状况的测量指标。CCFI5 是使用降维技术——主成分分析(PCA)构建的,是针对儿童消瘦状况预测性、有效性和可靠性(Cronbach'sα=0.80)的最佳综合指数,它捕捉了最佳儿童饮食摄入的相关维度。建议使用降维方法构建 CCFI5,以便在不同人群中进行标准化、验证和可能采用,作为适用于五岁以下儿童营养流行病学研究的最佳 CCFI。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a45/9180453/d4839e6e7835/ijerph-19-06621-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验