A preliminary assessment of the use of household budget survey data for the prediction of individual food consumption
A preliminary assessment of the use of household budget survey data for the prediction of individual food consumption
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DOI：
10.1079/phn2001237
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发表时间：
2001-10-01
影响因子：
3.2
通讯作者：
Trichopoulou, A
中科院分区：
文献类型：
--
作者：
Naska, A;Vasdekis, VGS;Trichopoulou, A
目的：比较个性化的家庭预算调查（HBS）数据与来自个人营养调查（INSs.Setting）的食品消费值：四个欧洲国家：比利时，1980-85和1987-88;希腊，1993-94;挪威，1992-94;和英国，1985- 88。设计：家庭预算调查数据进行个性化与非参数模型。个人营养调查数据被转换成“类似于HBS”的估计值，并应用基于食谱的计算和食物制备过程中体重变化的产量因素。为了纠正两次调查中的多报和少报或记录，14种主要食物组的数量（g天（-1））表示为总食物量（g天（-1））的分数。对于每个食物组，计算了24个研究单位的INS和HBS衍生平均值，这些研究单位由国家（涉及4个国家）、性别（男性、女性）和年龄（年轻、中年和老年）共同定义。Pearson相关系数的计算，并绘制相关图。结论：本初步分析的结果表明，从HBSs的营养信息的价值。然而，需要额外的和更复杂的工作，以获得可靠的点和区间估计个人的食物消费量的基础上HBS数据。
Objective: To compare individualised household budget survey (HBS) data with food consumption values derived from individual nutrition surveys (INSs).Setting: Four European countries: Belgium, 1980-85 and 1987-88; Greece, 1993-94; Norway, 1992-94; and the United Kingdom, 1985-88.Design: Household budget survey data were individualised with non-parametric models. Individual nutrition survey data were converted into 'HBS-like' estimates, with the application of recipe-based calculations and yield factors for weight changes during food preparation. To correct for over- and underreporting or recording in both surveys, quantities (in g day(-1)) of 14 principal food groups were expressed as fractions of total food quantity (in g day(-1)). For each food group, INS and HBS-derived mean values were calculated for 24 research units, jointly defined by country (four countries involved), gender (male, female) and age (younger, middle-aged and older). Pearson correlation coefficients were calculated and correlation diagrams were drawn.Conclusion: The results of this preliminary analysis show that there is value in the nutritional information derived from HBSs. However, additional and more sophisticated work is required, in order to derive reliable point and interval estimates of individual food consumption based on HBS data.