Ji Soo Oh; Mi Jin Ahn; Han Chan Jung; Kim Hyesook; Oran Kwon; Hye Won Chung; Namsoo Chang

doi:10.4163/jnh.2014.47.1.176

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Oh, Ahn, Jung, Hyesook, Kwon, Chung, and Chang: Relationship between flavonoids intake and metabolic syndrome in Korean women with polycystic ovary syndrome∗

Research Article

J Nutr Health 2014;47(3):176-185.

Published online: 20 January 2014

DOI: https://doi.org/10.4163/jnh.2014.47.1.176

Relationship between flavonoids intake and metabolic syndrome in Korean women with polycystic ovary syndrome∗

Ji Soo Oh¹, Mi Jin Ahn¹, Han Chan Jung¹, Kim Hyesook¹, Oran Kwon¹, Hye Won Chung², Namsoo Chang¹

¹Department of Nutritional Science and Food Management, Ewha Womans University, Seoul 120–750, Korea

²Department of Obstetrics and Gynecology, Ewha Womans University College of Medicine, Seoul 158–710, Korea

Received 17 March 2014 Revised 3 April 2014 Accepted 3 June 2014

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

Purpose

The purpose of this study was to investigate the relationship between dietary flavonoids intake and metabolic syndrome (MetS) in Korean women with polycystic ovary syndrome (PCOS). Methods: A total of 223 subjects (mean age; 27.3 ± 4.2 yrs, range; 17–38 yrs) were divided into the MetS group (n = 27) and non-MetS group (n = 196). Dietary intake data were assessed by 24-hour recall method for two non-consecutive days and the average of the two days was used to estimate the usual dietary intake. Dietary habits were assessed using the Mini Dietary Assessment (MDA) score. We analyzed the intakes of six flavonoid classes (anthocyanidins, flavan-3-ols, flavanones, flavones, flavonols, and isoflavones) using a flavonoids database. Results: After adjustment for age, total energy intake, alcohol consumption, smoking, regular exercise, and oral contraceptive use, dietary flavonols intake was significantly lower in the MetS group (5.1 ± 2.4 mg/d) than in the non-MetS group (8.9 ± 2.8 mg/d) (p = 0.0472). Intakes of other flavonoids except for flavonols did not differ between the two groups. In MDA scores, significant differences were observed only for that related to daily consumption of fruit or fruit juice (p = 0.0180). A significant inverse relationship was observed between flavonols intake and the risk of MetS (4th vs. 1st quartile, OR = 0.11, 95% CI = 0.02–0.62, p for trend = 0.0131). Conclusion: These results suggest that higher intake of flavonols may be beneficial for MetS in PCOS women.

Keywords: PCOS, metabolic syndrome, dietary flavonoids intake.

References

1. Azziz R, Woods KS, Reyna R, Key TJ, Knochenhauer ES, Yildiz BO. The prevalence and features of the polycystic ovary syndrome in an unselected population. J Clin Endocrinol Metab. 2004; 89(6):2745–2749.

2. Goodarzi MO, Dumesic DA, Chazenbalk G, Azziz R. Polycystic ovary syndrome: etiology, pathogenesis and diagnosis. Nat Rev Endocrinol. 2011; 7(4):219–231.

3. Boudreaux MY, Talbott EO, Kip KE, Brooks MM, Witchel SF. Risk of T2DM and impaired fasting glucose among PCOS subjects: results of an 8-year follow-up. Curr Diab Rep. 2006; 6(1):77–83.

4. Wild RA, Carmina E, Diamanti-Kandarakis E, Dokras A, Escobar-Morreale HF, Futterweit W, Lobo R, Norman RJ, Talbott E, Dumesic DA. Assessment of cardiovascular risk and prevention of cardiovascular disease in women with the polycystic ovary syndrome: a consensus statement by the Androgen Excess and Polycystic Ovary Syndrome (AE-PCOS) Society. J Clin Endocrinol Metab. 2010; 95(5):2038–2049.

5. Hahn S, Tan S, Sack S, Kimmig R, Quadbeck B, Mann K, Janssen OE. Prevalence of the metabolic syndrome in German women with polycystic ovary syndrome. Exp Clin Endocrinol Diabetes. 2007; 115(2):130–135.

6. Cussons AJ, Watts GF, Burke V, Shaw JE, Zimmet PZ, Stuckey BG. Cardiometabolic risk in polycystic ovary syndrome: a comparison of different approaches to defining the metabolic syndrome. Hum Reprod. 2008; 23(10):2352–2358.

7. Gambineri A, Repaci A, Patton L, Grassi I, Pocognoli P, Cognig-ni GE, Pasqui F, Pagotto U, Pasquali R. Prominent role of low HDL-cholesterol in explaining the high prevalence of the metabolic syndrome in polycystic ovary syndrome. Nutr Metab Cardiovasc Dis. 2009; 19(11):797–804.

8. Lee H, Oh JY, Hong Y, Sung YA, Chung H. Prevalence of metabolic syndrome in young Korean women with polycystic ovary syndrome. J Korean Diabetes Assoc. 2006; 30(4):285–291.

9. Kouki R, Schwab U, Hassinen M, Komulainen P, Heikkilä H, Lakka TA, Rauramaa R. Food consumption, nutrient intake and the risk of having metabolic syndrome: the DR's EXTRA Study. Eur J Clin Nutr. 2011; 65(3):368–377.

10. Martínez-González MÁ. Martín-Calvo N. The major European dietary patterns and metabolic syndrome. Rev Endocr Metab Disord. 2013; 14(3):265–271.

11. Almoosawi S, Tsang C, Ostertag LM, Fyfe L, Al-Dujaili EA. Differential effect of polyphenol-rich dark chocolate on biomarkers of glucose metabolism and cardiovascular risk factors in healthy, overweight and obese subjects: a randomized clinical trial. Food Funct. 2012; 3(10):1035–1043.

12. Barona J, Aristizabal JC, Blesso CN, Volek JS, Fernandez ML. Grape polyphenols reduce blood pressure and increase flow-mediated vasodilation in men with metabolic syndrome. J Nutr. 2012; 142(9):1626–1632.

13. Sohrab G, Hosseinpour-Niazi S, Hejazi J, Yuzbashian E, Mirmiran P, Azizi F. Dietary polyphenols and metabolic syndrome among Iranian adults. Int J Food Sci Nutr. 2013; 64(6):661–667.

14. Steffen Y, Gruber C, Schewe T, Sies H. Mono-O-methylated fla-vanols and other flavonoids as inhibitors of endothelial NADPH oxidase. Arch Biochem Biophys. 2008; 469(2):209–219.

15. Xiao ZP, Peng ZY, Peng MJ, Yan WB, Ouyang YZ, Zhu HL. Flavonoids health benefits and their molecular mechanism. Mini Rev Med Chem. 2011; 11(2):169–177.

16. Fauser BC, Tarlatzis BC, Rebar RW, Legro RS, Balen AH, Lobo R, Carmina E, Chang J, Yildiz BO, Laven JS, Boivin J, Petraglia F, Wijeyeratne CN, Norman RJ, Dunaif A, Franks S, Wild RA, Dumesic D, Barnhart K. Consensus on women's health aspects of polycystic ovary syndrome (PCOS): the Amsterdam ESHRE/AS-RM-Sponsored 3rd PCOS Consensus Workshop Group. Fertil Steril. 2012; 97(1):28–38.e25.

17. Korean Diabetes Association. Treatment guideline for diabetes. the. 4th edition.Seoul: Korean Diabetes Association;2011.

18. The Korean Nutrition Society. Nutritional assessment program ‘CAN-Pro 4.0' [CD-ROM]. Seoul: The Korean Nutrition Society;2011.

19. Yang YK, Kim JY, Kwon O. Development of flavonoid database for commonly consumed foods by Koreans. Korean J Nutr. 2012; 45(3):283–292.

20. Kim WY, Cho MS, Lee HS. Development and validation of mini dietary assessment index for Koreans. Korean J Nutr. 2003; 36(1):83–92.

21. Edwards RL, Lyon T, Litwin SE, Rabovsky A, Symons JD, Jalili T. Quercetin reduces blood pressure in hypertensive subjects. J Nutr. 2007; 137(11):2405–2411.

22. Jacques PF, Cassidy A, Rogers G, Peterson JJ, Meigs JB, Dwyer JT. Higher dietary flavonol intake is associated with lower incidence of type 2 diabetes. J Nutr. 2013; 143(9):1474–1480.

23. Holden JM, Bhagwat SA, Haytowitz DB, Gebhardt SE, Dwyer JT, Peterson J, Beecher GR, Eldridge AL, Balentine D. Development of a database of critically evaluated flavonoids data: application of USDA's data quality evaluation system. J Food Compost Anal. 2005; 18(8):829–844.

24. Erdman JW Jr, Balentine D, Arab L, Beecher G, Dwyer JT, Folts J, Harnly J, Hollman P, Keen CL, Mazza G, Messina M, Scalbert A, Vita J, Williamson G, Burrowes J. Flavonoids and heart health: proceedings of the ILSI North America Flavonoids Workshop, May 31-June 1, 2005, Washington, DC. J Nutr. 2007; 137(3 Suppl 1):718S–737S.

25. Kim JY, Kwon O. Culinary plants and their potential impact on metabolic overload. Ann N Y Acad Sci. 2011; 1229:133–139.

26. Galleano M, Calabro V, Prince PD, Litterio MC, Piotrkowski B, Vazquez-Prieto MA, Miatello RM, Oteiza PI, Fraga CG. Flavonoids and metabolic syndrome. Ann N Y Acad Sci. 2012; 1259:87–94.

27. van Dam RM, Naidoo N, Landberg R. Dietary flavonoids and the development of type 2 diabetes and cardiovascular diseases: review of recent findings. Curr Opin Lipidol. 2013; 24(1):25–33.

28. Siasos G, Tousoulis D, Tsigkou V, Kokkou E, Oikonomou E, Va-vuranakis M, Basdra EK, Papavassiliou AG, Stefanadis C. Flavonoids in atherosclerosis: an overview of their mechanisms of action. Curr Med Chem. 2013; 20(21):2641–2660.

29. Landberg R, Sun Q, Rimm EB, Cassidy A, Scalbert A, Mantzoros CS, Hu FB, van Dam RM. Selected dietary flavonoids are associated with markers of inflammation and endothelial dysfunction in U.S. women. J Nutr. 2011; 141(4):618–625.

30. Coskun O, Kanter M, Korkmaz A, Oter S. Quercetin, a flavonoid antioxidant, prevents and protects streptozotocin-induced oxidative stress and beta-cell damage in rat pancreas. Pharmacol Res. 2005; 51(2):117–123.

31. Mahesh T, Menon VP. Quercetin allievates oxidative stress in streptozotocin-induced diabetic rats. Phytother Res. 2004; 18(2):123–127.

32. Kobori M, Masumoto S, Akimoto Y, Takahashi Y. Dietary quercetin alleviates diabetic symptoms and reduces streptozotocin-induced disturbance of hepatic gene expression in mice. Mol Nutr Food Res. 2009; 53(7):859–868.

33. Vessal M, Hemmati M, Vasei M. Antidiabetic effects of quercetin in streptozocin-induced diabetic rats. Comp Biochem Physiol C Toxicol Pharmacol. 2003; 135C(3):357–364.

34. Yang YK. Construction of flavonoid database for the estimation of flavonoid intake in Korean [Dissertation]. Seoul: Ewha Womans University;2011.

35. Yoo S, Nicklas T, Baranowski T, Zakeri IF, Yang SJ, Srinivasan SR, Berenson GS. Comparison of dietary intakes associated with metabolic syndrome risk factors in young adults: the Bogalusa Heart Study. Am J Clin Nutr. 2004; 80(4):841–848.

36. Yang YJ, Kim YJ, Yang YK, Kim JY, Kwon O. Dietary flavan-3-ols intake and metabolic syndrome risk in Korean adults. Nutr Res Pract. 2012; 6(1):68–77.

37. U.S. Department of Health and Human Services; U.S. Department of Agriculture. Dietary guidelines for Americans 2005. 6th edition.Washington, D.C.: U.S. Government Printing Office;2005.

38. Estaquio C, Castetbon K, Kesse-Guyot E, Bertrais S, Deschamps V, Dauchet L, Péneau S, Galan P, Hercberg S. The French National Nutrition and Health Program score is associated with nutritional status and risk of major chronic diseases. J Nutr. 2008; 138(5):946–953.

39. World Cancer Research Fund; American Institute for Cancer Research. Food, nutrition, physical activity, and the prevention of cancer: a global perspective. Washington D.C.: American Institute for Cancer Research;2007.

40. Lee HS, Cho YH, Park J, Shin HR, Sung MK. Dietary intake of phytonutrients in relation to fruit and vegetable consumption in Korea. J Acad Nutr Diet. 2013; 113(9):1194–1199.

41. The Korean Nutrition Society. Dietary reference intakes for Koreans, 1st revision. Seoul: The Korean Nutrition Society;2010.

42. Vural B, Caliskan E, Turkoz E, Kilic T, Demirci A. Evaluation of metabolic syndrome frequency and premature carotid atherosclerosis in young women with polycystic ovary syndrome. Hum Reprod. 2005; 20(9):2409–2413.

43. Fox CS, Massaro JM, Hoffmann U, Pou KM, Maurovich-Hor-vat P, Liu CY, Vasan RS, Murabito JM, Meigs JB, Cupples LA, D'Agostino RB Sr, O'Donnell CJ. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation. 2007; 116(1):39–48.

44. Ganie MA, Kalra S. Polycystic ovary syndrome – A metabolic malady, the mother of all lifestyle disorders in women – Can Indian health budget tackle it in future? Indian J Endocrinol Metab. 2011; 15(4):239–241.

Table 1.

General characteristics according to MetS in subjects 1)

	All (n = 223)	Non-MetS²⁾ (n = 196)	MetS³⁾ (n = 27)	p value⁴⁾
Age (yr)	27.3 ± 4.20	27.0 ± 3.90	29.4 ± 5.50	< 0.0401
Height (cm)	161.5 ± 5.500	161.1 ± 5.300	164.4 ± 5.600	< 0.0034
Weight (kg)	59.0 ± 12.8	56.2 ± 10.0	79.4 ± 12.8	< 0.0001
BMI (kg/m ²)	22.5 ± 4.40	21.6 ± 3.50	29.3 ± 4.10	< 0.0001
Waist (cm)	76.5 ± 10.8	74.0 ± 8.40	94.7 ± 9.10	< 0.0001
Hip (cm)	91.4 ± 8.10	89.9 ± 6.90	102.5 ± 7.600	< 0.0001
Waist-to hip ratio (WHR)	0.83 ± 0.06	0.82 ± 0.06	0.92 ± 0.04	< 0.0001
Occupation				< 0.0771⁵⁾
Students	58 (26.0)	54 (27.6)	4 (14.8)
Employed	127 (57.0)	113 (57.6)	14 (51.9)
Househwives	10 (04.5)	8 (04.1)	2 (07.4)
Others	28 (12.5)	21 (10.7)	7 (25.9)
Nutritional supplement use	40 (17.9)	37 (18.8)	3 (11.1)	< 0.4284⁵⁾
Oral contraceptive use	105 (47.1)	92 (46.9)	13 (48.2)	< 0.7099
Smoking				< 0.0032⁵⁾
Current smoker	26 (11.7)	17 (08.7)	9 (33.3)
Ex smoker	11 (04.9)	9 (04.6)	2 (07.4)
Non smoker	184 (82.5)	168 (85.7)	16 (59.3)
Current alcohol drinking	157 (70.4)	139 (70.9)	18 (66.7)	< 0.8969
Regular exercise	106 (47.5)	94 (48.0)	32 (44.4)	< 0.8058

¹⁾ Values are mean ± SD or number (%).

²⁾ Non-MetS: non metabolic syndrome group

³⁾ MetS: metabolic syndrome group

⁴⁾ From chi-square tests for categorical variables and Student's t-test for continuous variables

⁵⁾ From Fisher's exact test

Table 2.

Blood profiles according to MetS in subjects 1)

	All (n = 223) N	Non-MetS²⁾ (n = 196)	MetS³⁾ (n = 27)	p value⁵⁾
	All (n = 223) N	Non-MetS²⁾ (n = 196)	MetS³⁾ (n = 27)	Unadjusted	Adjusted⁶⁾
Systolic blood pressure (mmHg)	113.8 ± 15.6⁴⁾	111.3 ± 14.2	131.5 ± 14.7	< 0.0001	< 0.0001
Diastolic blood pressure (mmHg)	068.5 ± 11.4	066.7 ± 10.3	081.4 ± 10.8	< 0.0001	< 0.0001
Total cholesterol (mg/dl)	178.8 ± 1.20	176.7 ± 1.20	194.9 ± 1.20	< 0.0053	< 0.0044
Triglyceride (mg/dl)	079.6 ± 1.6	71.6 ± 1.5	172.9 ± 1.40	< 0.0001	< 0.0001
HDL cholesterol (mg/dl)	057.4 ± 1.3	60.3 ± 1.2	40.0 ± 1.2	< 0.0001	< 0.0001
LDL cholesterol (mg/dl)	100.2 ± 1.30	97.1 ± 1.3	124.7 ± 1.30	< 0.0001	< 0.0001
Glucose₀ (mg/dl)⁷⁾	087.6 ± 1.1	86.5 ± 1.1	96.1 ± 1.1	< 0.0001	< 0.0001
Glucose₁₂₀ (mg/dl)⁸⁾	100.3 ± 1.20	97.3 ± 1.2	125.1 ± 1.20	< 0.0001	< 0.0001

¹⁾ Data are log-transformed before analysis except blood pressure data.

²⁾ Non-MetS: non metabolic syndrome group

³⁾ MetS: metabolic syndrome group

⁴⁾ Values are GM ± GSD except for blood pressure (mean ± SD).

⁵⁾ From Student's t-test

⁶⁾ Adjusted for age, log-transformed total energy intake, current alcohol drinking, smoking, regular exercise, oral contraceptives us

⁷⁾ Glucose₀; blood glucose at fasting

⁸⁾ Glucose₁₂₀; blood glucose at 120 minute after a 75 g oral glucose tolerance test

Table 3.

Dietary plant foods, nutrients and flavonoids intakes according to MetS in subjects 1)

	All (n = 223) N	Non-MetS²⁾ (n = 196)	MetS³⁾ (n = 27)	p value⁴⁾
	All (n = 223) N	Non-MetS²⁾ (n = 196)	MetS³⁾ (n = 27)	Unadjusted	adjusted⁶⁾
Plants foods (g/d)	742.1 ± 1.4	748.9 ± 1.5	694.4 ± 1.4	0.3152	0.3180
Cereals/potatoes products	228.2 ± 1.5	226.8 ± 1.5	238.2 ± 1.5	0.5584	0.0132
Sugars	6.9 ± 2.9	7.2 ± 2.8	9.8 ± 8.0	0.1255	0.2949
Beans/nuts	17.7 ± 5.7	19.2 ± 5.3	5.1 ± 3.5	0.0770	0.1538
Fruits/vegetables/mushrooms/seaweeds	251.8 ± 1.9	253.5 ± 1.9	240.0 ± 1.6	0.5748	0.8543
Oils	6.3 ± 2.3	6.3 ± 2.3	6.5 ± 1.8	0.7970	0.2018
Beverages	111.9 ± 4.6	108.3 ± 4.8	146.4 ± 3.0	0.4083	0.7534
Nutrients
Energy (kcal/d)	1,414.4 ± 1.3	1,429.2 ± 1.3	1,311.5 ± 1.4	0.1369	0.2567
Carbohydrate (g/d)	202.3 ± 1.4	202.8 ± 1.4	199.0 ± 1.4	0.7609	0.0037
Protein (g/d)	52.9 ± 1.4	53.5 ± 1.4	48.5 ± 1.5	0.1551	0.3599
Fat (g)	41.3 ± 1.5	42.4 ± 1.5	34.0 ± 1.6	0.0073	0.0045
Cholesterol (mg/d)	216.3 ± 1.9	226.0 ± 1.8	157.5 ± 2.2	0.0323	0.0112
Fiber (g/d)	13.7 ± 1.5	13.8 ± 1.5	13.0 ± 1.5	0.4373	0.7123
Calcium (mg/d)	398.8 ± 1.6	403.8 ± 1.6	364.2 ± 1.5	0.2655	0.8027
Iron (mg/d)	9.9 ± 1.5	10.1 ± 1.5	8.9 ± 1.5	0.1332	0.4926
Zinc (mg/d)	7.3 ± 1.4	7.5 ± 1.4	6.5 ± 1.4	0.0438	0.1314
Flavonoids (mg/d)
Anthocyanidins	5.6 ± 5.2	5.7 ± 5.6	4.7 ± 2.7	0.4772	0.9798
Flavan-3-ols	2.0 ± 24.3⁵⁾	2.0 ± 23.2	1.7 ± 41.1	0.8435	0.5523
Flavanones	5.2 ± 12.7⁵⁾	5.2 ± 12.8	5.1 ± 13.9	0.9893	0.7857
Flavones	0.3 ± 3.3	0.3 ± 3.2	0.3 ± 3.9	0.7950	0.8802
Flavonols	8.3 ± 2.7	8.9 ± 2.8	5.1 ± 2.4	0.0090	0.0472
Isoflavones	1.4 ± 21.6⁵⁾	1.5 ± 21.4	1.1 ± 24.2	0.5937	0.9145
Total	39.8 ± 3.1	41.5 ± 2.8	29.2 ± 4.9	0.2676	0.1827

¹⁾ Data are log-transformed before analysis.

²⁾ Non-MetS: non metabolic syndrome group

³⁾ MetS: metabolic syndrome grou

⁴⁾ From Student's t-test

⁵⁾ Values are GM ± GSD.

⁶⁾ Adjusted for age, log-transformed total energy intake, current alcohol drink ing, smoking, regular exercise, oral contraceptives use

Table 4.

Mini dietary assessment (MDA) scores¹⁾ of the subjects according to MetS in subjects ²⁾

Component of MDA		All (n = 223)	Non-MetS (n = 196)³⁾	MetS⁴⁾ (n = 27)	p value⁵⁾
I drink 1 or more bottles of milk or its products (yogurt, yoplait, etc.) daily.	Always	58 (26.01)	51 (26.02)	7 (25.93)	0.7411
	Generally	71 (31.84)	64 (32.65)	7 (25.93)
	Seldom	94 (42.15)	81 (41.33)	13 (48.15)
For each meal, I consume foods made up of a combination of meat, fish, eggs, beans, tobu, etc.	Always	48 (21.52)	39 (19.90)	9 (33.33)	0.2537
	Generally	97 (43.50)	88 (44.90)	9 (33.33)
	Seldom	78 (34.98)	69 (35.20)	9 (33.33)
For each meal, I consume vegetables other than Kimchi.	Always	57 (25.56)	51 (26.02)	6 (22.22)	0.2208
	Generally	99 (44.39)	83 (42.35)	16 (59.26)
	Seldom	67 (30.04)	62 (31.63)	5 (18.52)
I consume at least 1 fruit or fruit juice (1 glass) daily.	Always	53 (23.77)	47 (23.98)	6 (22.22)	0.0180
	Generally	81 (36.32)	77 (39.29)	4 (14.81)
	Seldom	89 (39.91)	72 (36.73)	17 (62.96)
I consume fried or stir-fried foods at least 2 times per week.	Always	31 (13.90)	26 (13.27)	9 (33.33)	0.4676
	Generally	94 (42.15)	81 (41.33)	13 (48.15)
	Seldom	98 (43.95)	89 (45.41)	5 (18.52)
I consume high fat content eats (bacon, ribs, eel, etc.) at least 2 times per week.	Always	19 (08.52)	17 (08.67)	2 (07.41)	0.9144
	Generally	67 (30.04)	58 (29.59)	9 (33.33)
	Seldom	137 (61.43)	121 (61.73)	16 (59.26)
I tent to add extra salt or soy sauce while taking my meal.	Always	9 (04.05)	8 (04.10)	1 (03.70)	0.5682
	Generally	34 (15.32)	28 (14.36)	6 (22.22)
	Seldom	179 (80.63)	159 (81.54)	20 (74.07)
I have three regular meals a day.	Always	48 (21.52)	44 (22.45)	4 (14.81)	0.3579
	Generally	66 (29.60)	55 (28.06)	11 (40.74)
	Seldom	109 (48.88)	97 (22.45)	12 (44.44)
I consume ice cream, cake, biscuit varieties, carbonated beverages, etc. as snack at least 2 times per week.	Always	23 (10.31)	17 (08.67)	6 (22.22)	0.0786
	Generally	60 (26.91)	55 (28.06)	5 (18.52)
	Seldom	140 (62.78)	124 (63.27)	16 (59.26)
I tend to consume a wide range of foods evenly (I have a balanced diet.).	Always	67 (30.04)	60 (30.61)	7 (25.93)	0.8089
	Generally	100 (44.84)	88 (44.90)	12 (44.44)
	Seldom	56 (25.11)	48 (24.49)	8 (29.63)
Total score of MDA⁶⁾		32.7 ± 6.4	32.9 ± 6.4	31.6 ± 6.5	0.3343⁷⁾

¹⁾ Minimum and maximum scores for each component are 1 and 5. The total score can be up to 50.

²⁾ Values are number (%).

³⁾ Non-MetS: non metabolic syndrome group

⁴⁾ MetS: metabolic syndrome group

⁵⁾ From chi-square tests

⁶⁾ Values are mean ± SD.

⁷⁾ From Student's t-test

Table 5.

Odds ratio (OR) and 95% confidence interval (CI) of MetS by quartiles of dietary flavonols intakes ¹⁾

Quartiles
	Q1 (< 4.14 mg/d)	Q2 (4.14–8.87 mg/d)	Q3 (8.88–15.8 mg/d)	Q4 (> 15.8 mg/d)	p for trend
Unadjusted	1.00 (ref)	0.40 (0.14, 1.13)	0.41 (0.14, 1.16)	0.12 (0.03, 0.57)	0.0084
Adjusted	1.00 (ref)	0.41 (0.13, 1.36)	0.44 (0.14, 1.39)	0.11 (0.02, 0.62)	0.0131

¹⁾ Adjusted for age, log-transformed total energy intake, current alcohol drinking, smoking, regular exercise, oral contraceptives use

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