Establishment of database for food classification and coding in Chinese dietary exposure assessment.
- Author:
Li-wen YUE
1
;
Xiao-mei HAN
;
Jin-fang SUN
;
Hong CHEN
;
Can-nan WANG
;
Yong-ning WU
;
Pei LIU
;
Jie MIN
Author Information
- Publication Type:Journal Article
- MeSH: China; Consumer Product Safety; Databases, Factual; Diet; classification; statistics & numerical data; Diet Surveys; Humans; Vocabulary, Controlled
- From: Chinese Journal of Preventive Medicine 2010;44(3):200-203
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo establish the basis for Chinese dietary exposure assessment database by classifying and coding the data from the national dietary survey and pollutant surveillance.
METHODSThe method, which combined CODEX food classifying and coding of Codex Alimentarius Commission (CAC) with Chinese food classification of food composition table, was applied to classify and code the data of 1 810 703 Chinese dietary consumption and 487 819 pollutant surveillance. The coding system was according to the first two letters of the respective food group that represent the type or source of foods, the last four digits represent the serial number of the food in the CAC food classification. If the foods can be found in CAC food code system, its original food code is used. The new codes corresponding with the foods which are not exist in CAC food code system, is added according to CAC coding methods.
RESULTSDietary consumption data were divided into 6 major categories, 19 types, 75 groups, the agricultural products of pollutant surveillance corresponding to 499 codes. Comparing with CAC food coding system, Chinese dietary consumption data have added F (candy snacks) and G (beverages) 2 major categories, 4 types, 33 groups, 302 new codes. The additional groups most were the processing food groups with Chinese characteristics, such as canned, beverages, candy, meat products.
CONCLUSIONThe foundation of data communication to dietary exposure assessment has been established, and the connection of Chinese food classifying and coding with CAC data have been achieved.