Journal List > Korean J Community Nutr > v.19(6) > 1038485

TOOLS
Lee, Lee, and Lee: The Risk of Metabolic Syndrome by Dietary Patterns of Middle-aged Adults in Gyeonggi Province
Research Article

Korean Journal of Community Nutrition 2014; 19(6): 527-536.

Published online: 31 December 2014

DOI: https://doi.org/10.5720/kjcn.2014.19.6.527

The Risk of Metabolic Syndrome by Dietary Patterns of Middle-aged Adults in Gyeonggi Province

You-Sin Lee1, Moo-Yong Lee2, Sim-Yeol Lee1

1Department of Home Economics Education, Dongguk University, Seoul, Korea.

2Cardiovascular Center, Dongguk University Ilsan Hospital, Goyang, Korea.

Corresponding author: Sim-Yeol Lee. Department of Home Economics Education, Dongguk University, Seoul 110-715, Korea. Tel: (02) 2260-3413, Fax: (02) 2265-1170, slee@dongguk.edu

Received 27 November 2014       Revised 23 December 2014       Accepted 30 December 2014

Copyright © 2014 The Korean Society of Community Nutrition

(open-access):

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objectives

The aim of this study was to assess how nutrient intakes are related to risk factors for metabolic syndrome according to dietary patterns in the middle-aged adults.

Methods

The subjects (n = 187; 47 men, 140 women) consisted of middle-aged adults over 30 years old in Ilsan area. The metabolic syndrome was diagnosed according to the data collected from each subject, including anthropometric measurements and blood analyses. The dietary patterns were derived from the average of two-day dietary intake data.

Results

Factor analysis identified three major dietary patterns which were "Meats and alcohol", "Mixed grains, vegetables and fruits", and "Rice, Kimchi and fish & shellfish". The daily intakes of energy, protein, and sodium increased across quartiles of "Meats and alcohol" pattern scores (p < 0.05), whereas the intakes of carbohydrates, potassium, calcium, and fiber increased across quartiles of "Mixed grains, vegetables and fruits" pattern scores (p < 0.001). The "Meats and alcohol" pattern scores were positively correlated with protein and sodium intakes but inversely correlated with carbohydrates, fiber and potassium intakes which were adjusted for age, sex and energy (p < 0.05). The highest quartile pattern score of "Meats and alcohol" pattern had elevated odds ratio of abdominal obesity and metabolic syndrome (p < 0.05). The risk of hypertriglyceridemia decreased in the highest quartile of "Mixed grains, vegetables and fruits" pattern (OR 0.35, 95% CI 0.12-1.00).

Conclusions

Our results suggested that reducing the consumption of meat and alcohol along with increasing fruits, vegetables and mixed grains would be helpful for preventing the metabolic syndrome and chronic diseases.

Keywords: Metabolic syndrome, dietary patterns, middle-aged adults

Figures and Tables

Table 1
Factor loading matrix for the 3 major dietary patterns according to intake amounts of food or food groups
kjcn-19-527-i001

Factor loadings less than ±0.20 are not shown for simplicity.

Table 2
Comparison of characteristics by quartile scores of dietary patterns1)
kjcn-19-527-i002

BMI: Body mass index

1) Factor score of each subject for a given factor was obtained by the sum of products of factor loading and standardized score of each variable, 2) Mean±SD, tested by linear trend test using generalized linear model, 3) %, tested by chi-square test, 4) Physical activity was assigned "Yes" if subjects engaged in physical activity at least 2 days or more per week.

*: p < 0.05, **: p < 0.01, ***: p < 0.001

Table 3
Nutrient intakes by quartile scores of dietary patterns
kjcn-19-527-i003

1) Mean±SD, 2) Adjusted for age, sex, 3) Adjusted for age, sex and energy intake

Table 4
Correlation coefficients between nutrient intakes and scores of dietary patterns
kjcn-19-527-i004

1) Adjusted for age, sex and energy intake.

*: p < 0.05, **: p < 0.01, ***: p < 0.001

Table 5
Odds ratios for metabolic syndrome and its components by quartile scores of dietary patterns
kjcn-19-527-i005

1) Odds ratios were adjusted by age, sex using logistic regression.

2) Serum fasting blood glucose ≥ 100 mg/dL; Systolic blood pressure ≥ 130 mm Hg or diastolic blood pressure ≥ 85 mm Hg; Low serum HDL cholesterol < 50 mg/dL for women or < 40 mg/dL for men; Serum TG ≥ 150 mg/dL; Waist circumference ≥ 85 cm for women or ≥ 90 cm for men.

Notes

This work was supported by the research program of Dongguk University

References

1. Buyck JF, Blacher J, Kesse-Guyot E, Castetbon K, Galan P, Safar M, Hercberg S, Czernichow S. Differential associations of dietary sodium and potassium intake with blood pressure: a focus on pulse pressure. J Hypertens. 2009; 27(6):1158–1164.
2. Esmaillzadeh A, Kimiagar M, Mehrabi Y, Azadbakht L, Hu FB, Willett WC. Fruit and vegetable intakes, C-reactive protein, and the metabolic syndrome. Am J Clin Nutr. 2006; 84(6):1489–1497.
3. Flint AJ, Hu FB, Glyn RJ, Jensen MK, Franz M, Sampson L, Rimm EB. Whole grains and incident hypertension in men. Am J Clin Nutr. 2009; 90(3):493–498.
4. Han BK, Kang YM, Ju SH, Shin MY, Kim JM, Rha SY, Joung KH, Lee JH, Kim KS, Kim HJ, Ku BJ. Effects of green whole grain mixed diet on body weight and waist circumference in patients with type 2 diabetes. Korean J Obes. 2014; 23(1):41–49.
5. Hoffmann IS, Cubeddu LX. Salt and the metabolic syndrome. Nutr Metab Cardiovasc Dis. 2009; 19(2):123–128.
6. Hong SY, Song YJ, Lee KH, Lee HS, Lee MS, Jee SH, Joung HJ. A fruit and dairy dietary pattern is associated with a reduced risk of metabolic syndrome. Metabolism. 2012; 61(6):883–890.
7. Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol. 2002; 13(1):3–9.
8. Jones JM, Reicks M, Adams J, Fulcher G, Weaver G, Kanter M, Marquart L. The importance of promoting a whole grain foods message. J Am coll nutr. 2002; 21(4):293–297.
9. Kang M, Joumg HJ, Lim JH, Lee YS, Song YJ. Secular trend in dietary patterns in a Korean adult population, using the 1998, 2001, and 2005 Korean National Health and Nutrition Examination Survey. Korean J Nutr. 2011; 44(2):152–161.
10. Kant AK. Dietary patterns and health outcomes. J Am Diet Assoc. 2004; 104(4):615–635.
11. Kim JH, JO IH. Grains, vegetables, and fish dietary pattern is inversely associated with the risk of metabolic syndrome in South Korean adults. J Am Diet Assoc. 2011; 111(8):1141–1149.
12. Lee S, Park HS, Kim SM, Kwon HS, Kim DY, Kim DJ, Cho GJ, Han JH, Kim SR, Park CY, Oh SJ, Lee CB, Kim KS, Oh SW, Kim YS, Choi WH, Yoo HJ. Cut-off Points of waist circumference for defining abdominal obesity in the Korean population. Korean J Obes. 2006; 15(1):1–9.
13. Lee SY, Park HS, Kim DJ, Han JH, Kim SM, Cho GJ, Kim DY, Kwon HS, Kim SR, Lee CB, Oh SJ, Park CY, Yook HJ. Appropriate waist circumference cutoff points for central obesity in Korean adults. Diabetes Res Clin Pract. 2007; 75(1):72–80.
14. Lee TY, Yoo HJ, Joo NS. Daily calcium intake and obesity in middle-aged Koreans. Korean J Obes. 2009; 18(2):59–64.
15. Lim HJ. A study on the sodium and potassium intakes and urinary excretion of adults in Busan. Korean J Community Nutr. 2012; 17(6):737–751.
16. Lim S, Shin H, Song JH, Kwak SH, Kang SM, Yoon JW, Choi SH, Cho SI, Park KS, Lee HK, Jang HC, Koh KK. Increasing prevalence of metabolic syndrome in Korea: the Korean National Health and Nutrition Examination Survey for 1998-2007. Diabetes care. 2011; 34(6):1323–1328.
17. Moon HK, Kong JE. Assessment of nutrient intake for middle aged with and without metabolic syndrome using 2005 and 2007 Korean National Health and Nutrition Survey. Korean J Nutr. 2010; 43(1):69–78.
18. Mozumdar A, Liguori G. Persistent increase of prevalence of metabolic syndrome among U.S. adult: NHANES III to NHANES 1999-2006. Diabetes Care. 2011; 34(1):216–219.
19. Muzio F, Mondazzi L, Harris WS, Sommariva D. Effects of moderate variations in the macronutrient content of the diet on cardiovascular disease risk factors in obese patients with the metabolic syndrome. Am J Clin Nutr. 2007; 86(4):946–951.
20. National Cholesterol Education Program (NCEP), Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III) final report. Circulation. 2002; 106(25):3143–3421.
21. Newby PK, Tucker KL. Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev. 2004; 62(5):177–203.
22. Park YW, Zhu S, Palaniappan L, Heshka S, Carnethon MR, Heymsfield SB. The metabolic syndrome: prevalence and associated risk factor findings in the US population from the Third National Health and Nutrition Examination Survey, 1988-1994. Arch Intern Med. 2003; 163(4):427–436.
23. Riccardi G, Giacco R, Rivellese AA. Dietary fat, insulin sensitivity and the metabolic syndrome. Clin Nutr. 2004; 23(4):447–456.
24. Rizzo NS, Sabaté J, Jaceldo-Siegl K, Fraser GE. Vegetarian dietary patterns are associated with a lower risk of metabolic syndrome: the adventist health study 2. Diabetes care. 2011; 34(5):1225–1227.
25. Rumawas ME, Meigs JB, Dwyer JT, McKeown NM, Jacques PF. Mediterranean-style dietary pattern, reduced risk of metabolic syndrome traits, and incidence in the Framingham Offspring Cohort. Am J Clin Nutr. 2009; 90(6):1608–1614.
26. Sacks FM, Svetkey LP, Vollmer WM, Appel LJ, Bray GA, Harsha D, Obarzanek E, Conlin PR, Miller ER, Simons-Morton DG, Karanja N, Lin PH. Effects on blood pressure of reduced dietary sodium and the dietary approaches to stop hypertension (DASH) diet. N Engl J Med. 2001; 344(1):3–10.
27. Sahyoun NR, Jacques PF, Zhang XL, Juan W, McKeown NM. Whole-grain intake is inversely associated with the metabolic syndrome and mortality in older adults. Am J Clin Nutr. 2006; 83(1):124–131.
28. Shin KO, Oh SY, Park HS. Empirically derived major dietary patterns and their associations with overweight in Korean preschool children. Br J Nutr. 2007; 98(2):416–421.
29. Son SH, Lee HJ, Park K, Ha TY, Seo JS. Nutritional evaluation and its relation to the risk of metabolic syndrome according to the consumption of cooked rice and cooked rice with multi-grains in Korean adults: based on 2007-2008 Korean National Health and Nutrition Examination Survey. Korean J Community Nutr. 2013; 18(1):77–87.
30. Song YJ, Joung HJ, Paik HY. Socioeconomic, nutrient, and health risk factors associated with dietary patterns in adult populations from 2001 Korean National Health and Nutrition Survey. Korean J Nutr. 2005; 38(3):219–225.
31. Statistics Korea. The statistics of mortality and the causes. 2013. cited November 25, 2014. Available from http://www.kostat.go.kr.
32. The Korean Nutrition Society. Computer Aided Nutritional Analysis Program 4.0 for Professionals. 2011.
33. Van dam RM, Rimm EB, Willett WC, Stampfer MJ, Hu FB. Dietary patterns and risk for type 2 diabetes mellitus in U.S. men. Ann Intern Med. 2002; 136(3):201–209.
34. Wirfält E, Hedblad B, Gullberg B, Mattisson I, Andrén C, Rosander U, Janzon L, Berglund G. Food patterns and components of the metabolic syndrome in men and women: a cross-sectional study within the malmö diet and cancer cohort. Am J Epidemiol. 2001; 154(12):1150–1159.
35. Yang EJ, Kerver JM, Song WO. Dietary patterns of Korean Americans described by factor analysis. J Am Coll Nutr. 2005; 24(2):115–121.
36. Yoo H, Kim YH. A study on the characteristics of nutrient intake in metabolic syndrome subjects. Korean J Nutr. 2008; 41(6):510–517.
TOOLS
Similar articles