Dekkers Arnold L M, Verkaik-Kloosterman Janneke, van Rossum Caroline T M, Ocké Marga C
National Institute for Public Health and the Environment, Bilthoven, The Netherlands
National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
J Nutr. 2014 Dec;144(12):2083-91. doi: 10.3945/jn.114.191288. Epub 2014 Oct 15.
For the evaluation of both the adequacy of intakes and the risk of excessive intakes of micronutrients, all potential sources should be included. In addition to micronutrients naturally present in foods, micronutrients can also be derived from fortified foods and dietary supplements. In the estimation of the habitual intake, this may cause specific challenges such as multimodal distributions and heterogeneous variances between the sources.
We present the Statistical Program to Assess Dietary Exposure (SPADE) that was developed to cope with these challenges in one single program.
Similar to other methods, SPADE can model habitual intake of daily and episodically consumed dietary components. In addition, SPADE has the option to model habitual intake from dietary supplements. Moreover, SPADE offers models to estimate habitual intake distributions from different sources (e.g., foods and dietary supplements) separately and adds these habitual intakes to get the overall habitual intake distribution. The habitual intake distribution is modeled as a function of age, and this distribution can directly be compared with cutoff values to estimate the proportion above or below. Uncertainty in the habitual intake distribution and in the proportion below or above a cutoff value is quantified with ready-for-use bootstrap and provides 95% CIs.
SPADE is implemented in R and is freely available as an R package called SPADE.RIVM. The various features of SPADE are illustrated by the estimation of the habitual intake distribution of folate and folic acid for women by using data from the Dutch National Food Consumption Survey 2007-2010. The results correspond well with the results of existing programs.
SPADE offers new features to existing programs to estimate the habitual intake distribution because it can handle many different types of modeling with the first-shrink-then-add approach.
为了评估微量营养素摄入的充足性和过量摄入的风险，应纳入所有潜在来源。除了食物中天然存在的微量营养素外，微量营养素也可来源于强化食品和膳食补充剂。在估计习惯性摄入量时，这可能会带来一些特殊挑战，如多峰分布以及不同来源之间的异质方差。
我们介绍了膳食暴露评估统计程序（SPADE），该程序旨在在一个程序中应对这些挑战。
与其他方法类似，SPADE可以对日常和偶尔食用的膳食成分的习惯性摄入量进行建模。此外，SPADE还可以选择对膳食补充剂的习惯性摄入量进行建模。此外，SPADE提供模型分别估计来自不同来源（如食物和膳食补充剂）的习惯性摄入量分布，并将这些习惯性摄入量相加，以获得总体习惯性摄入量分布。习惯性摄入量分布被建模为年龄的函数，该分布可直接与临界值进行比较，以估计高于或低于临界值的比例。习惯性摄入量分布以及低于或高于临界值的比例的不确定性通过现成的自助法进行量化，并提供95%置信区间。
SPADE是用R语言实现的，可作为名为SPADE.RIVM的R包免费获取。通过使用2007 - 2010年荷兰国家食品消费调查的数据，对女性叶酸和叶酸的习惯性摄入量分布进行估计，说明了SPADE的各种功能。结果与现有程序的结果吻合良好。
SPADE为现有程序提供了新的功能来估计习惯性摄入量分布，因为它可以通过先收缩后相加的方法处理许多不同类型的建模。
