J Korean Med Sci.  2017 Sep;32(9):1474-1483. 10.3346/jkms.2017.32.9.1474.

Carbohydrate Intake Exhibited a Positive Association with the Risk of Metabolic Syndrome in Both Semi-Quantitative Food Frequency Questionnaires and 24-Hour Recall in Women

• Ahn J
• Kim NS
• Lee BK
• Park S

• KMID: 2385954
• DOI: http://doi.org/10.3346/jkms.2017.32.9.1474

Abstract

We compared the usual nutrient intake in both the semi-quantitative food frequency questionnaire (SQFFQ) and 24-hour recall methods and determined the association between metabolic syndrome (MetS) risk and nutrient intake calculated by both methods in Korea National Health and Nutrition Examination Survey (KNHANES; 2012-2014) data. Adjusted odds ratios for MetS were calculated according to the intake of macronutrients, measured by the 2 methods in 10,286 adults, while controlling for covariates associated with MetS. Fat and carbohydrate intake (energy percent) calculated by 24-hour recall and SQFFQ was significantly different between the MetS and non-MetS groups, particularly in women. The differences in other nutrient intakes determined by both methods were mainly non-significant. The correlation coefficients between the 2 methods were about 0.4 for most nutrients except total vitamin A and iron (Fe). Energy intake according to gender and MetS presence was similar between the 2 methods. Carbohydrate intake exhibited a positive association with the MetS risk, while fat intake showed a negative association in both methods. The association exhibited a gender interaction with carbohydrate and fat intake calculated by 24-hour recall: women exhibited a significant association. However, for the SQFFQ a gender interaction was evident only for carbohydrate intake. In diet quality index of SQFFQ the adequacy of vegetables and total fat intake was higher in the non-MetS than the MetS. In conclusion, the MetS prevalence exhibited a positive association with carbohydrate intake only in women, as assessed by 24-hour recall and SQFFQ. The SQFFQ can be used to assess the association between usual food intake and MetS risk in large population studies.

Keyword

24-hour Recall; Semi-quantitative Food Frequency Questionnaires; Metabolic Syndrome; Fat Intake; Carbohydrate Intake

MeSH Terms

Adult
Diet
Eating
Energy Intake
Female
Humans
Iron
Korea
Nutrition Surveys
Odds Ratio
Prevalence
Vegetables
Vitamin A
Iron
Vitamin A

Reference

1. Rhee SY, Park SY, Hwang JK, Son JI, Chin SO, Kim YS, Woo JT. Metabolic syndrome as an indicator of high cardiovascular risk in patients with diabetes: analyses based on Korea National Health and Nutrition Examination Survey (KNHANES) 2008. Diabetol Metab Syndr. 2014; 6:98.

2. Gami AS, Witt BJ, Howard DE, Erwin PJ, Gami LA, Somers VK, Montori VM. Metabolic syndrome and risk of incident cardiovascular events and death: a systematic review and meta-analysis of longitudinal studies. J Am Coll Cardiol. 2007; 49:403–414.

3. Nestel P, Lyu R, Low LP, Sheu WH, Nitiyanant W, Saito I, Tan CE. Metabolic syndrome: recent prevalence in East and Southeast Asian populations. Asia Pac J Clin Nutr. 2007; 16:362–367.

4. Calton EK, James AP, Pannu PK, Soares MJ. Certain dietary patterns are beneficial for the metabolic syndrome: reviewing the evidence. Nutr Res. 2014; 34:559–568.

5. Shin H, Yoon YS, Lee Y, Kim CI, Oh SW. Dairy product intake is inversely associated with metabolic syndrome in Korean adults: Anseong and Ansan cohort of the Korean Genome and Epidemiology Study. J Korean Med Sci. 2013; 28:1482–1488.

6. Griel AE, Kris-Etherton PM. Beyond saturated fat: the importance of the dietary fatty acid profile on cardiovascular disease. Nutr Rev. 2006; 64:257–262.

7. Schwab U, Lauritzen L, Tholstrup T, Haldorssoni T, Riserus U, Uusitupa M, Becker W. Effect of the amount and type of dietary fat on cardiometabolic risk factors and risk of developing type 2 diabetes, cardiovascular diseases, and cancer: a systematic review. Food Nutr Res. 2014; 58:25145.

8. Siri-Tarino PW, Sun Q, Hu FB, Krauss RM. Saturated fatty acids and risk of coronary heart disease: modulation by replacement nutrients. Curr Atheroscler Rep. 2010; 12:384–390.

9. Park S, Ahn J, Lee BK. Very-low-fat diets may be associated with increased risk of metabolic syndrome in the adult population. Clin Nutr. 2016; 35:1159–1167.

10. Willett WC. Nutritional Epidemiology. 2nd ed. New York, NY: Oxford University Press;1998.

11. Maruyama K, Kokubo Y, Yamanaka T, Watanabe M, Iso H, Okamura T, Miyamoto Y. The reasonable reliability of a self-administered food frequency questionnaire for an urban, Japanese, middle-aged population: the Suita study. Nutr Res. 2015; 35:14–22.

12. Kim DW, Song S, Lee JE, Oh K, Shim J, Kweon S, Paik HY, Joung H. Reproducibility and validity of an FFQ developed for the Korea National Health and Nutrition Examination Survey (KNHANES). Public Health Nutr. 2015; 18:1369–1377.

13. Korea Centers for Disease Control and Prevention. Guideline for the Evaluation of the Fourth Korea National Health and Nutrition Survey. Cheongwon: Korea Centers for Disease Control and Prevention;2014.

14. Park S, Ham JO, Lee BK. Effects of total vitamin A, vitamin C, and fruit intake on risk for metabolic syndrome in Korean women and men. Nutrition. 2015; 31:111–118.

15. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004; 363:157–163.

16. Kim S, Haines PS, Siega-Riz AM, Popkin BM. The Diet Quality Index-International (DQI-I) provides an effective tool for cross-national comparison of diet quality as illustrated by China and the United States. J Nutr. 2003; 133:3476–3484.

17. Takahara M, Shimomura I. Metabolic syndrome and lifestyle modification. Rev Endocr Metab Disord. 2014; 15:317–327.

18. Macedo-Ojeda G, Vizmanos-Lamotte B, Márquez-Sandoval YF, Rodríguez-Rocha NP, López-Uriarte PJ, Fernández-Ballart JD. Validation of a semi-quantitative food frequency questionnaire to assess food groups and nutrient intake. Nutr Hosp. 2013; 28:2212–2220.

19. Dehghan M, del Cerro S, Zhang X, Cuneo JM, Linetzky B, Diaz R, Merchant AT. Validation of a semi-quantitative Food Frequency Questionnaire for Argentinean adults. PLoS One. 2012; 7:e37958.

20. Ahn Y, Kwon E, Shim JE, Park MK, Joo Y, Kimm K, Park C, Kim DH. Validation and reproducibility of food frequency questionnaire for Korean genome epidemiologic study. Eur J Clin Nutr. 2007; 61:1435–1441.

21. Schröder H, Covas MI, Marrugat J, Vila J, Pena A, Alcántara M, Masiá R. Use of a three-day estimated food record, a 72-hour recall and a food-frequency questionnaire for dietary assessment in a Mediterranean Spanish population. Clin Nutr. 2001; 20:429–437.

22. Cade J, Thompson R, Burley V, Warm D. Development, validation and utilisation of food-frequency questionnaires - a review. Public Health Nutr. 2002; 5:567–587.

23. Brunner E, Stallone D, Juneja M, Bingham S, Marmot M. Dietary assessment in Whitehall II: comparison of 7 d diet diary and food-frequency questionnaire and validity against biomarkers. Br J Nutr. 2001; 86:405–414.

24. Shirani F, Esmaillzadeh A, Keshteli AH, Adibi P, Azadbakht L. Low-carbohydrate-diet score and metabolic syndrome: an epidemiologic study among Iranian women. Nutrition. 2015; 31:1124–1130.

25. Choi H, Song S, Kim J, Chung J, Yoon J, Paik HY, Song Y. High carbohydrate intake was inversely associated with high-density lipoprotein cholesterol among Korean adults. Nutr Res. 2012; 32(9):–. 100–106.

26. 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; 100:576–584.

27. Aekplakorn W, Satheannoppakao W, Putwatana P, Taneepanichskul S, Kessomboon P, Chongsuvivatwong V, Chariyalertsak S. Dietary pattern and metabolic syndrome in Thai adults. J Nutr Metab. 2015; 2015:468759.