Validation and Calibration of Semi-Quantitative Food Frequency Questionnaire - With Participants of the Korean Health and Genome Study -

반정량식품섭취빈도조사지의 타당성 검증 및 보정 - 지역사회 유전체 코호트 참여자를 대상으로 -

  • Ahn, Youn-Jhin (National Genome Research Institute, National Institute of Health, Korea Center for Disease Control) ;
  • Lee, Ji-Eun (National Genome Research Institute, National Institute of Health, Korea Center for Disease Control) ;
  • Cho, Nam-Han (Department of Preventive Medicine, Ajou University School of Medicine & Hospital) ;
  • Shin, Chol (Department of Respiratory Internal Medicine, Ansan Hospital, Korea University Medical Center) ;
  • Park, Chan (National Genome Research Institute, National Institute of Health, Korea Center for Disease Control) ;
  • Oh, Berm-Seok (National Genome Research Institute, National Institute of Health, Korea Center for Disease Control) ;
  • Kimm, Ku-Chan (National Genome Research Institute, National Institute of Health, Korea Center for Disease Control)
  • 안윤진 (국립보건연구원 유전체연구부) ;
  • 이지은 (국립보건연구원 유전체연구부) ;
  • 조남한 (아주대학교 의과대학 예방의학교실) ;
  • 신철 (고려대학교 의과대학 안산병원 호흡기내과학교실) ;
  • 박찬 (국립보건연구원 유전체연구부) ;
  • 오범석 (국립보건연구원 유전체연구부) ;
  • 김규찬 (국립보건연구원 유전체연구부)
  • Published : 2004.04.01

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.

Keywords

References

  1. Ahn Y, Lee JE, Paik HY, Lee HK, Jo I, Kimm K (2003): Development of a semi-quantitative food frequency questionnaire based on dietary data from the Korea national health and nutrition examination sur-vey. Nutr Sci 6(3): 173-184
  2. Choi MS, Han KY, Park KS (2001): Comparison of dietary intakes by 24-hr dietary recall, dietary record and food frequency questionnaire among elderly people. Korean J Nutr 34(6): 688-700
  3. Hunter D (1998): Biochemical indicators of dietary intake. In: Willett WC, ed. Nutritional Epidemiology, pp174-243, Oxford University Press, New York
  4. Jain MG, Rohan TE, Soskolne CL, Kreiger N (2003): Calibration of the dietary questionnaire for the Canadian study of diet, lifestyle and health cohort. Pubc Health Nutr 6(1) : 79-86
  5. Johansson I, Hallmans G, Wikman $\AA$, Biessy C, Riboli E, Kaaks R(2002): Validation and calibration of food frequency questionnaire measurements in the Northern Sweden Health and Diseases cohort. Pubc Health Nutr 5: 487-496
  6. Kabagambe EK, Baylin A, Allan DA, Siles X, Spiegelman D, Campos H (2001): Application of the methods of triads to evaluate the perfor-mance of food frequency questionnaires and biomarkers as indicators of long-term dietary intake. Am J Epidemiol 154: 1126-1135
  7. Kim MK, Lee SS, Ahn YO (1996): Reproducibility and validity of a self-administered food frequency questionnaire. Korean J Comm Nutr 1(3): 376-394
  8. Kim WY, Yang EJ (1998): A study on development and validation of food frequency questionnaire for Koreans. Korean J Nutr 31: 220-230
  9. Korean Dietitian Association & Samsung Medical Center (1999): Portion size with picture, Seoul
  10. Lee HJ, Park SJ, Kim JH, Kim CI, Chang KJ, Yim KS, Kim KW, Choi H (2002): Development and validation of a computerized semiquan-titative food frequency questionnaire program for evaluating the nu-tritional status of the Korean elderly. Korean J Comm Nutr 7(2): 277-285
  11. McKeown NM, Day NE, Welch AA, Runswick SA, Luben RN, Mulligan AA, McTaggart A, Bingham SA (2001): Use of biological markers to validate self-reported dietary intake in a random sample of the European Prospective Investigation into Cancer United Kingdon Norfolk cohort. Am J Clin Nutr 71: 188-196
  12. Ocke MC, Kaaks RJ (1997): Biochemical markers as additional measu-rements in dietary validity studies: application of the method of triads with examples from the European Prospective Investigation into Cancer and Nutrition. Am J Clin Nutr 65(4 Suppl): 1240S-1245S https://doi.org/10.1093/ajcn/65.4.1240S
  13. Ogawa K, Tsubono Y, Nishino Y, Watanabe Y, Ohkubo T, Watanabe T, Nakatsuka H, Takahashi N, Kawamura M, Tsuji I, Hisamichi S (2003): Validation of a food-frequency questionnaire for cohort studies in rural Japan. Pubc Health Nutr 6: 147-157
  14. Paik HY, Ryu JY, Choi JS, Ahn Y, Moon HK, Park YS, Lee HK, Kim YI(1995): Development and validation of food frequency question-naire for dietary assessment of Korean adults in rural area. Korean J Nutr 28: 914-922
  15. Riboli E, Kaaks R (2000): The challenge of multi-center cohort studies in the search for diet and cancer links. Am J Epidemiol 151: 371-374
  16. Rimm EB, Giovannucci EL, Stampfer MJ, Colditz GA, Litin LB, Willett WC (1992) : Reproducibility and validity of a expanded self-admi-nistered semiquantitative food frequency questionnaire among male health professionals. Am J Epidemiol 135: 1114-1126 https://doi.org/10.1093/oxfordjournals.aje.a116211
  17. Rodriguez MM, Mendez H, Torun B, Schroeder D, Stein A (2000): Va-lidation of a semi-quantitative food frequency questionnaire for use among adults in Guatemala. Public Health Nutr 5: 691-698
  18. Rosner B, Spiegelman D, Willett WC (1990): Correction of logistic re-gression relative risk estimates and confidence intervals for measu-rement error: the case of multiple covariates measured with error. Am J Epidemiol 132(4): 734-745 https://doi.org/10.1093/oxfordjournals.aje.a115715
  19. Rosner B, Spiegelman D, Willett WC (1992): Correction of logistic reg-ression relative risk estimates and confidence intervals for random wi-thin- person measurement error. Am J Epidemiol 136(11): 1400-1413 https://doi.org/10.1093/oxfordjournals.aje.a116453
  20. Shim JE, Ryu 1Y, Paik HY (1997): Contribution of seasonings to nutrient intake assessed by food frequency questionnaire in adults in rural area of Korea. Korean J Nutr 30: 1211-1218
  21. Shim JS, Oh KW, Suh I, Kim MY, Sohn CY, Lee EJ, Nam CM (2002): A study on validity of a semi-quantitative food frequency question-naire for Korean adults. Korean J Comm Nutr 7: 484-494
  22. Stram DO, Hankin JH, Wilkens LR, Pike MC, Monroe KR, Park S, Hen-derson BE, Nomura AMY, Earle ME, Nagamine FS, Kolonel LN (2000): Calibration of the dietary questionnaire for a multiethnic cohort in Hawaii and Los Angeles. Am J Epidemiol 151: 358-370
  23. The Korean Nutrition Society (2000): Food composition table. In: Re-commended dietary allowances for Koreans 7th Ed. Seoul
  24. Willett W, Sampson L, Stampfer MJ, Rosner B, Bain C, Witschi J, Hen-nekens CH, Speizer FE (1985): Reproducibility and validity of a semiquantitative food frequency questionnaire. Am J Epidemiol 122(1): 51-65 https://doi.org/10.1093/oxfordjournals.aje.a114086
  25. Willett W (1998): Nutritional epidemiology 2nd Ed. Oxford University Press, New York
  26. Won HS, Kim WY (2000): Development and validation of a semi-quantitative food frequency questionnaire to evaluate nutrition status of Korean elderly. Korean J Nutr 33(3): 314-323