Validation and Calibration of Semi-Quantitative Food Frequency Questionnaire: With Participants of the Korean Health and Genome Study.
- Author:
Younjhin AHN
1
;
Ji Eun LEE
;
Nam Han CHO
;
Chol SHIN
;
Chan PARK
;
Berm Seok OH
;
Kuchan KIMM
Author Information
1. National Genome Research Institute, National Institute of Health, Korea Center for Disease Control, Seoul, Korea. k2kimm@nih.go.kr
- Publication Type:Original Article
- Keywords:
food frequency questionnaire (FFQ);
diet record (DR);
validation;
calibration
- MeSH:
Academies and Institutes;
Ascorbic Acid;
Calcium;
Calibration*;
Carotenoids;
Classification;
Cohort Studies;
Dataset;
Diet;
Diet Records;
Education;
Energy Intake;
Epidemiology;
Female;
Genome*;
Gyeonggi-do;
Humans;
Iron;
Korea;
Male;
Niacin;
Occupations;
Phosphorus;
Potassium;
Riboflavin;
Seasons;
Sodium;
Vitamin A
- From:Korean Journal of Community Nutrition
2004;9(2):173-182
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
We carried out a validation-calibration study of the food frequency questionnaire (FFQ) that we had previously developed for a community-based cohort of the Korean Genome and Health Study of the Korea National Genome Research Institute. We have collected a total of 254 3-day diet records (DRs) from 400 subjects, 200 each randomly selected from the two study cohorts of Ansung and Ansan. FFQ was administered at the time of cohort recruitment in 2001, and DRs were collected during a two month period from January through February of 2002. The mean age was 52.2 years. Farming for men and housewife for women were the most common occupations. The majority of the subjects had undergone 6~12 years of education. The general characteristics including demographic and other data were not different from the total cohort subjects. Absolute levels of consumed nutrients including total energy (energy), protein, fat, carbohydrate, calcium, phosphorus, sodium, potassium, iron, retinol, carotene, vitamin A, thiamin, riboflavin, niacin and vitamin C were compared. The average of energy intake was not significantly different between the data collected by the 2 methods. However, consumptions of protein and fat were higher in data of DRs, whereas that of carbohydrate was higher in FFQ data. Significant correlation of each nutrient consumption between the data sets was observed (p <0.05) except in the case of iron, while the average correlation coefficient between them was 0.22 ranging from 0.33 for energy to 0.11 for iron. The results of cross classification by quantile for exact classification ranged from 25.2% (carotene) to 35.0% (phosphorus), and from 64.6% (vitamin A) to 76.4% (retinol) for adjacent classification. The proportion of completely opposite classification was 8.1% in average. Calibration slope was estimated by regression and calibration parameters ranged from 0.025 for carotene to 0.423 for niacin. We conclude that the FFQ we have developed is an appropriate tool for assessing the nutrient intakes as ranking exposures in epidemiology studies in view that amounts of consumed nutrients obtained by FFQ were similar to those collected by DRs, that correlations between consumed nutrients collected by these methods were significant, and that classification results were relatively fair. The correlation coefficients, however, were lower than expected, which may be mainly due to the survey season. In fact, any short-term dietary survey cannot accurately reflect the overall dietary intakes that change heavily depending on seasons. Further studies including the analysis of chemical indices would be helpful for the studies of causal relationship between the diet and disease.
