- Volume 13 Issue 6
DOI QR Code
Comparison of Validity of Food Group Intake by Food Frequency Questionnaire Between Pre- and Post-adjustment Estimates Derived from 2-day 24-hour Recalls in Combination with the Probability of Consumption
- Kim, Dong-Woo (Cancer Epidemiology Branch, Research Institute, National Cancer Center) ;
- Oh, Se-Young (Department of Food and Nutrition, Kyung Hee University) ;
- Kwon, Sung-Ok (Department of Food and Nutrition, Kyung Hee University) ;
- Kim, Jeong-Seon (Cancer Epidemiology Branch, Research Institute, National Cancer Center)
- Published : 2012.06.30
Validation of a food frequency questionnaire (FFQ) utilising a short-term measurement method is challenging when the reference method does not accurately reflect the usual food intake. In addition, food group intake that is not consumed on daily basis is more critical when episodically consumed foods are related and compared. To overcome these challenges, several statistical approaches have been developed to determine usual food intake distributions. The Multiple Source Method (MSM) can calculate the usual food intake by combining the frequency questions of an FFQ with the short-term food intake amount data. In this study, we applied the MSM to estimate the usual food group intake and evaluate the validity of an FFQ with a group of 333 Korean children (aged 3-6 y) who completed two 24-hour recalls (24HR) and one FFQ in 2010. After adjusting the data using the MSM procedure, the true rate of non-consumption for all food groups was less than 1% except for the beans group. The median Spearman correlation coefficients against FFQ of the mean of 2-d 24HRs data and the MSM-adjusted data were 0.20 (range: 0.11 to 0.40) and 0.35 (range: 0.14 to 0.60), respectively. The weighted kappa values against FFQ ranged from 0.08 to 0.25 for the mean of 2-d 24HRs data and from 0.10 to 0.41 for the MSM-adjusted data. For most food groups, the MSM-adjusted data showed relatively stronger correlations against FFQ than raw 2-d 24HRs data, from 0.03 (beverages) to 0.34 (mushrooms). The results of this study indicated that the application of the MSM, which was a better estimate of the usual intake, could be worth considering in FFQ validation studies among Korean children.
Usual food intake;multiple source method;FFQ validation;Korean children
- Araujo MC, Yokoo EM, Pereira RA (2010). Validation and calibration of a semiquantitative food frequency questionnaire designed for adolescents. J Am Diet Assoc, 110, 1170-7. https://doi.org/10.1016/j.jada.2010.05.008
- Byers T (2001). Food frequency dietary assessment: how bad is good enough? Am J Epidemiol, 154, 1087-8. https://doi.org/10.1093/aje/154.12.1087
- Carithers TC, Talegawkar SA, Rowser ML, et al (2009). Validity and calibration of food frequency questionnaires used with African-American adults in the Jackson Heart Study. J Am Diet Assoc, 109, 1184-93. https://doi.org/10.1016/j.jada.2009.04.005
- Carriquiry AL, Camano-Garcia G (2006). Evaluation of dietary intake data using the tolerable upper intake levels. J Nutr, 136, S507-13.
- Dodd KW, Guenther PM, Freedman LS, et al (2006). Statistical methods for estimating usual intake of nutrients and foods: a review of the theory. J Am Diet Assoc, 106, 1640-1650. https://doi.org/10.1016/j.jada.2006.07.011
- Fayet F, Flood V, Petocz P, Samman S (2011). Relative and biomarker-based validity of a food frequency questionnaire that measures the intakes of vitamin B(12), folate, iron, and zinc in young women. Nutr Res, 31, 14-20. https://doi.org/10.1016/j.nutres.2010.12.004
- Field AE, Peterson KE, Gortmaker SL, et al (1999). Reproducibility and validity of a food frequency questionnaire among fourth to seventh grade inner-city school children: implications of age and day-to-day variation in dietary intake. Public Health Nutr, 2, 293-300.
- Freedman LS, Guenther PM, Krebs-Smith SM, et al (2010). A population's distribution of Healthy Eating Index-2005 component scores can be estimated when more than one 24-hour recall is available. J Nutr, 140, 1529-34. https://doi.org/10.3945/jn.110.124594
- Fumagalli F, Pontes Monteiro J, Sartorelli DS, et al (2008). Validation of a food frequency questionnaire for assessing dietary nutrients in Brazilian children 5 to 10 years of age. Nutrition, 24, 427-32. https://doi.org/10.1016/j.nut.2008.01.008
- Guenther PM, Kott PS, Carriquiry AL (1997). Development of an approach for estimating usual nutrient intake distributions at the population level. J Nutr, 127, 1106-12.
- Haubrock J, Nothlings U, Volatier JL, et al (2011). Estimating usual food intake distributions by using the Multiple Source Method in the EPIC-potsdam calibration study. J Nutr, 141, 914-20. https://doi.org/10.3945/jn.109.120394
- Hoffmann K, Boeing H, Dufour A, et al (2002). Estimating the distribution of usual dietary intake by short-term measurements. Eur J Clin Nutr, 56 Suppl 2, S53-62.
- Huybrechts I, De Bacquer D, Cox B, et al (2008). Variation in energy and nutrient intakes among pre-school children: implications for study design. Eur J Public Health, 18, 509-16. https://doi.org/10.1093/eurpub/ckn017
- Kipnis V, Midthune D, Buckman DW, et al(2009). Modeling data with excess zeros and measurement error: application to evaluating relationships between episodically consumed foods and health outcomes. Biometrics, 65, 1003-10. https://doi.org/10.1111/j.1541-0420.2009.01223.x
- Klohe DM, Clarke KK, George GC, et al (2005). Relative validity and reliability of a food frequency questionnaire for a triethnic population of 1-year-old to 3-year-old children from low-income families. J Am Diet Assoc, 105, 727-34. https://doi.org/10.1016/j.jada.2005.02.008
- Kristal AR, Peters U, Potter JD (2005). Is it time to abandon the food frequency questionnaire? Cancer Epidemiol Biomarkers Prev, 14, 2826-8. https://doi.org/10.1158/1055-9965.EPI-12-ED1
- Lee MS, Pan WH, Liu KL, et al (2006). Reproducibility and validity of a Chinese food frequency questionnaire used in Taiwan. Asia Pac J Clin Nutr, 15, 161-9.
- Lim, Y. (2001). Reliability and validity of a semi-quantitative food frequency questionnaire for Korean pre-school children. Kyung Hee University, Seoul.
- Mennen LI, Bertrais S, Galan P, et al (2002). The use of computerised 24 h dietary recalls in the French SU.VI. MAX Study: number of recalls required. Eur J Clin Nutr, 56, 659-65. https://doi.org/10.1038/sj.ejcn.1601374
- Molag ML, de Vries JH, Ocke MC, et al (2007). Design characteristics of food frequency questionnaires in relation to their validity. Am J Epidemiol, 166, 1468-78. https://doi.org/10.1093/aje/kwm236
- Mouratidou T, Ford FA, Fraser RB (2011). Reproducibility and validity of a food frequency questionnaire in assessing dietary intakes of low-income Caucasian postpartum women living in Sheffield, United Kingdom. Matern Child Nutr, 7, 128-39. https://doi.org/10.1111/j.1740-8709.2009.00221.x
- National Research Council(1986). Nutrient Adequacy: Assessment Using Food Consumption Surveys Available from http://www.nap.edu/books/0309036348/html/index.html
- Nusser SM, Carriquiry AL, Dodd KW, et al (1996). A semiparametric transformation approach to estimating usual nutrient intake distributions. J Am Stat Assoc, 91, 1440-9. https://doi.org/10.1080/01621459.1996.10476712
- Ogawa K, Tsubono Y, Nishino Y, et al (2003). Validation of a food-frequency questionnaire for cohort studies in rural Japan. Public Health Nutr, 6, 147-57.
- Oh SY, Hong MH (1999). Within- and between-person variation of nutrient intakes of older people in Korea. Eur J Clin Nutr, 53, 625-9. https://doi.org/10.1038/sj.ejcn.1600824
- Shin KO, Oh SY, Park HS (2007). Empirically derived major dietary patterns and their associations with overweight in Korean preschool children. Br J Nutr, 98, 416-21. https://doi.org/10.1017/S0007114507720226
- Shu XO, Yang G, Jin F, et al (2004). Validity and reproducibility of the food frequency questionnaire used in the Shanghai Women's Health Study. Eur J Clin Nutr, 58, 17-23. https://doi.org/10.1038/sj.ejcn.1601738
- Subar AF, Dodd KW, Guenther PM, et al (2006). The food propensity questionnaire: concept, development, and validation for use as a covariate in a model to estimate usual food intake. J Am Diet Assoc, 106, 1556-63. https://doi.org/10.1016/j.jada.2006.07.002
- Tooze JA, Kipnis V, Buckman DW, et al (2010). A mixedeffects model approach for estimating the distribution of usual intake of nutrients: the NCI method. Stat Med, 29, 2857-68. https://doi.org/10.1002/sim.4063
- Tooze JA, Midthune D, Dodd KW, et al (2006). A new statistical method for estimating the usual intake of episodically consumed foods with application to their distribution. J Am Diet Assoc, 106, 1575-87. https://doi.org/10.1016/j.jada.2006.07.003
- Waijers PM, Dekkers AL, Boer JM, et al(2006). the potential of AGE MODE, an age-dependent model, to estimate usual intakes and prevalences of inadequate intakes in a population. J Nutr, 136, 2916-20.
- Xu L, M JD, D'Este C (2004). Reliability and validity of a food-frequency questionnaire for Chinese postmenopausal women. Public Health Nutr, 7, 91-98.
- Changes in children's food group intake from age 3 to 7 years: comparison of a FFQ with an online food record vol.112, pp.02, 2014, https://doi.org/10.1017/S0007114514000762
- Identifying Critical Nutrient Intake in Groups at Risk of Poverty in Europe: The CHANCE Project Approach vol.6, pp.4, 2014, https://doi.org/10.3390/nu6041374
- Questionários de Frequência de Consumo Alimentar desenvolvidos e validados para população do Brasil: revisão da literatura vol.20, pp.9, 2015, https://doi.org/10.1590/1413-81232015209.12602014
- The e-EPIDEMIOLOGY Mobile Phone App for Dietary Intake Assessment: Comparison with a Food Frequency Questionnaire vol.5, pp.4, 2016, https://doi.org/10.2196/resprot.5782
- Associations Between Excessive Sodium Intake and Smoking and Alcohol Intake Among Korean Men: KNHANES V vol.12, pp.12, 2015, https://doi.org/10.3390/ijerph121215001