과제정보
This research was supported by Korea National Open University Research Fund.
참고문헌
- Getz GS, Reardon CA. Nutrition and cardiovascular disease. Arterioscler Thromb Vasc Biol 2007; 27(12): 2499-2506. https://doi.org/10.1161/ATVBAHA.107.155853
- Kim K, Yun SH, Choi BY, Kim MK. Cross-sectional relationship between dietary carbohydrate, glycaemic index, glycaemic load and risk of the metabolic syndrome in a Korean population. Br J Nutr 2008; 100(3): 576-584. https://doi.org/10.1017/S0007114508904372
- World Health Organization, Food and Agriculture Organization of the United Nations. Diet, nutrition and the prevention of chronic diseases. Geneva: World Health Organization; 2003.
- Kim S, Lee JS, Hong KH, Yeom HS, Nam YS, Kim JY et al. Development and relative validity of semi-quantitative food frequency questionnaire for Korean adults. J Nutr Health 2018; 51(1): 103-119. https://doi.org/10.4163/jnh.2018.51.1.103
- Choe JS. Evaluation of long-term dietary intakes of housewives. Korean J Community Living Sci 2004; 15(1): 91-104.
- Nusser SM, Fuller WA, Guenther PM. Estimating usual dietary intake distributions: Adjusting for measurement error and nonnormality in 24-hour food intake data. New York: Wiley; 1997.
- Dodd KW, Guenther PM, Freedman LS, Subar AF, Kipnis V, Midthune D et al. Statistical methods for estimating usual intake of nutrients and foods: A review of the theory. J Am Diet Assoc 2006; 106(10): 1640-1650. https://doi.org/10.1016/j.jada.2006.07.011
- Zhang S, Midthune D, Guenther PM, Krebs-Smith SM, Kipnis V, Dodd KW et al. A new multivariate measurement error model with zero inflated dietary data, and its application to dietary assessment. Ann Appl Stat 2011; 5(2B): 1456-1487.
- Carriquiry AL. Estimation of usual intake distributions of nutrients and foods. J Nutr 2003; 133(2): 601S-608S. https://doi.org/10.1093/jn/133.2.601S
- Tooze JA, Midthune D, Dodd KW, Freedman LS, Krebs-Smith SM, Subar AF et al. A new statistical method for estimating the usual intake of episodically consumed foods with application to their distribution. J Am Diet Assoc 2006; 106(10): 1575-1587. https://doi.org/10.1016/j.jada.2006.07.003
- Pereira JL, de Castro MA, Crispim SP, Fisberg RM, Isasi CR, Mossavar-Rahmani Y et al. Comparing methods from the National Cancer Institute vs Multiple Source Method for estimating usual intake of nutrients in the Hispanic community health study/study of Latino youth. J Acad Nutr Diet 2021; 121(1): 59-73. https://doi.org/10.1016/j.jand.2020.03.010
- Haubrock J, Nothlings U, Volatier JL, Dekkers A, Ocke M, Harttig U, Illner AK, Knuppel S, Andersen LF, Boeing H; European Food Consumption Validation Consortium. Estimating usual food intake distributions by using the multiple source method in the EPIC-Potsdam Calibration Study. J Nutr. 2011; 141(5): 914-20. https://doi.org/10.3945/jn.109.120394
- Hoffmann K, Boeing H, Dufour A, Volatier JL, Telman J, Virtanen M et al. Estimating the distribution of usual dietary intake by short-term measurements. Eur J Clin Nutr 2002; 56(2): S53-S62.
- Shamah-Levy T, Rodriguez-Ramirez S, Gaona-Pineda EB, Cuevas-Nasu L, Carriquiry AL, Rivera JA. Three 24-hour recalls in comparison with one improve the estimates of energy and nutrient intakes in an urban Mexican population. J Nutr. 2016; 146(5): 1043-50. https://doi.org/10.3945/jn.115.219683
- Harttig U, Haubrock J, Knuppel S, Boeing H. The MSM program: Web-based statistics package for estimating usual dietary intake using the Multiple Source Method. Eur J Clin Nutr 2011; 65(1): S87-S91. https://doi.org/10.1038/ejcn.2011.92
- Biro G, Hulshof K, Ovesen L, Cruz JA. Selection of methodology to assess food intake. Eur J Clin Nutr 2002; 56(2): S25-S32.
- Zhang S, Krebs-Smith SM, Midthune D, Perez A, Buckman DW, Kipnis V, Freedman LS, Dodd KW, Carroll RJ. Fitting a bivariate measurement error model for episodically consumed dietary components. Int J Biostat. 2011; 7(1): 1. https://doi.org/10.2202/1557-4679.1322
- Lee JY, Kim DW. Validation of food intake frequency from food frequency questionnaire for use as a covariate in a model to estimate usual food intake. Culin Sci Hosp Res 2017; 23(2): 64-73. https://doi.org/10.20878/cshr.2017.23.2.007
- Subar AF, Dodd KW, Guenther PM, Kipnis V, Midthune D, McDowell M et al. 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 2006; 106(10): 1556-1563. https://doi.org/10.1016/j.jada.2006.07.002
- Hartman AM, Brown CC, Palmgren J, Pietinen P, Verkasalo M, Myer D et al. Variability in nutrient and food intakes among older middle-aged men: Implications for design of epidemiologic and validation studies using food recording. Am J Epidemiol 1990; 132(5): 999-1012. https://doi.org/10.1093/oxfordjournals.aje.a115743
- Carroll RJ, Midthune D, Subar AF, Shumakovich M, Freedman LS, Thompson FE et al. Taking advantage of the strengths of 2 different dietary assessment instruments to improve intake estimates for nutritional epidemiology. Am J Epidemiol 2012; 175(4): 340-347. https://doi.org/10.1093/aje/kwr317
- Kipnis V, Midthune D, Buckman DW, Dodd KW, Guenther PM, Krebs-Smith SM et al. Modeling data with excess zeros and measurement error: Application to evaluating relationships between episodically consumed foods and health outcomes. Biometrics 2009; 65(4): 1003-1010. https://doi.org/10.1111/j.1541-0420.2009.01223.x