Relation between the Total Diet Quality based on Korean Healthy Eating Index and the Incidence of Metabolic Syndrome Constituents and Metabolic Syndrome among a Prospective Cohort of Korean Adults

Saerom Shin; Seungmin Lee

doi:10.5720/kjcn.2020.25.1.61

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Research Article: Korean Journal of Community Nutrition 2020;25(1):61-70.
DOI: https://doi.org/10.5720/kjcn.2020.25.1.61
Published online: January 20, 2020

¹⁾Department of Food and Nutrition, Graduate School, Sungshin Women's University, Seoul, Korea, Master's graduate

²⁾Department of Food and Nutrition, Sungshin Women's University, Seoul, Korea, Associate Professor

†Corresponding author Seungmin Lee Department of Food and Nutrition, Sungshin Women's University, 55, Dobong-ro 76ga-gil, Gangbuk-gu, Seoul 01133, Korea Tel: (02) 920-7671 Fax: (02) 920-2076 E-mail: smlee@sungshin.ac.kr

• Received: February 10, 2020 • Revised: February 17, 2020 • Accepted: February 19, 2020

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.

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Abstract
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Abstract

Objectives
This study examined the association of the total diet quality with the incidence risk of metabolic syndrome constituents and metabolic syndrome among Korean adults.
Methods
Based on a community-based cohort of the Korean Genome and Epidemiology Study (KoGES) from 2001 to 2014, data from a total of 5,549 subjects (2,805 men & 2,744 women) aged 40∼69 years at the baseline with a total follow-up period of 38,166 person-years were analyzed. The criteria of the National Cholesterol Education Program Adult Treatment Panel was employed to define metabolic syndrome. The total diet quality was estimated using the Korean Healthy Eating Index (KHEI). Hazard ratios (HR) and 95% confidence intervals (CI) for risk of metabolic syndrome constituents and metabolic syndrome in relation to KHEI quintile groups was calculated by multivariate Cox proportional hazards regression model.
Results
After adjusting for age, energy intake, income, education, physical activity, smoking, and drinking, the incidence of abdominal obesity and high blood pressure was significantly lower, by approximately 29.7% (P < 0.01) and 25.2% (P < 0.01), respectively, in the fifth KHEI quintile compared to the first quintile in men. A significant decreasing trend of the metabolic syndrome incidence was observed across the improving levels of KHEI (HRq5vs.q1: 0.775, 95% CIq5vs.q1: 0.619∼0.971, P for trend<0.01). In women, the incidence of abdominal obesity and metabolic syndrome was significantly lower, by approximately 29.8% (P < 0.01) and 22.5% (P < 0.05), respectively, in the fifth KHEI quintile compared to the first quintile adjusting for multiple covariates. On the other hand, the linear trend of metabolic syndrome risk across the KHEI levels did not reach the significance level.
Conclusions
A better diet quality can prevent future metabolic syndrome and its certain risk factors among Korean men and women.
Keywords: diet quality; Korean Healthy Eating Index; metabolic syndrome; prospective cohort

Table 1.

Subjects' general characteristics at baseline

Characteristics	Men (N=2,805)	Women (N=2,744)	P-value¹⁾
Age group
40∼49 (year)	1,535 (54.7)	1,594 (58.1)	0.007
50∼59 (year)	679 (24.2)	631 (23.0)
60∼69 (year)	591 (21.1)	519 (18.9)
Education			< 0.001
Elementary school graduate or less	547 (19.6)	980 (35.9)
Middle school graduate	631 (22.6)	697 (25.6)
High school graduate	1,022 (36.6)	854 (31.3)
College graduate or more Income (10,000 won)	594 (21.3)	197 (97.2)	< 0.001
< 100	751 (27.0)	899 (33.5)	< 0.001
100∼199	862 (31.0)	830 (30.9)
200∼399	920 (33.1)	774 (28.8)
≥ 400	250 (99.0)	182 (96.8)
Drinking status
Non-drinker	791 (28.2)	1,913 (69.7)
Drinker	2,014 (71.8)	831 (30.3)
Alcohol intake (g/day)	17.6 ± 27.9	1.6 ± 5.8	< 0.001
Smoking status			< 0.001
Non-smoker	1,354 (48.3)	2,639 (96.2)	< 0.001
Smoker	1,451 (51.7)	105 (93.8)
Cumulative smoking (pack-year)	18.0 ± 17.6	0.4 ± 2.6
Physical activity			< 0.001
METs²⁾ < 20	1,560 (57.3)	1,787 (66.9)
20 ≤ METs < 40	536 (19.7)	425 (15.9)
40 ≤ METs	627 (23.0)	458 (17.2)

n (%) or Mean ± SD 1) Calculated from chi-square test or student t-test 2) Metabolic equivalents

Table 2.

Nutrient and food group intakes for first and fifth quintiles of Korean Healthy Eating Index scores

Dietary component	Men (N=2,805)			Women (N=2,744)
			Quintiles of KHEI scores		P-value
	1st	5th	P-value¹⁾ 1st	5th	P-value
Total KHEI⁴⁾ score	1,943.79 ± 1,995.19¹⁾	1,977.72 ± 1,994.61	< 0.001 1,949.13 ± 1,996.03	1,984.47 ± 1,993.68	< 0.001
Nutrients
Energy (kcal/day)²⁾	1,650.96 ± 1,467.96	2,312.56 ± 1,558.42	< 0.001 1,546.58 ± 1,519.37	2,159.27 ± 1,618.44	< 0.001
Energy from carbohydrates (%)²⁾	1,973.83 ±1,99 8.27	1,966.58 ±1,99 4.54	< 0.001 1,976.04 ± 1,997.84	1,967.69 ± 1,994.32	< 0.001
Energy from fat (%)²⁾	1,912.36 ±1,99 6.58	1,917.78 ± 1,993.35	< 0.001 1,910.71 ± 1,996.35	1,916.72 ± 1,993.32	< 0.001
Dietary fiber (g/day)³⁾	1,995.21 ± 1,992.44	1,998.50 ± 1,993.15	< 0.001 1,995.15 ± 1,992.55	1,998.44 ± 1,993.33	< 0.001
Alcohol (g/day)³⁾	1,932.68 ± 1,931.70	1,917.64 ± 1,926.22	< 0.001 1,998.18 ± 1,913.49	1,992.49 ± 1,992.63	< 0.001
Sodium (mg/day)³⁾	2,967.20 ± 1,617.31	3,686.14 ± 1,632.86	0.009 2,564.25 ± 1,333.82	3,392.21 ± 1,671.25	0.064
Food groups
Fruits (servings/day)³⁾	1,990.94 ± 1,991.37	1,992.67 ± 1,992.20	< 0.001 1,991.44 ± 1,992.20	1,992.87 ±1,99 2.49	0.103
Vegetables (servings/day)³⁾	1,992.46 ± 1,991.80	1,995.33 ±1,99 2.61	< 0.001 1,992.67 ± 1,992.24	1,995.90 ± 1,993.32	< 0.001
Dairy products (servings/day)³⁾	1,990.17 ±1,99 0.48	1,991.08 ±1,99 0.80	< 0.001 1,990.21 ±1,99 0.49	1,991.34 ±1,99 0.99	< 0.001
Protein foods (servings/day)³⁾	1,991.77 ±1,99 1.37	1,994.11 ± 1,991.63	< 0.001 1,991.52 ±1,99 1.25	1,993.99 ±1,99 1.68	< 0.001
Empty calorie foods (servings/day)	)³⁾ 1,994.47 ±1,99 3.86	1,992.94 ± 1,992.89	< 0.001 1,991.38 ±1,99 1.62	1,991.20 ±1,99 0.95	< 0.001
Whole grains (servings/day)³⁾	1,990.53 ±1,99 1.04	1,991.87 ± 1,991.37	< 0.001 1,990.80 ± 1,991.27	1,992.25 ±1,99 1.21	< 0.001
Refined grains (servings/day)³⁾	1,992.58 ± 1,991.23	1,991.37 ± 1,991.40	< 0.001 1,992.20 ± 1,991.33	1,990.79 ± 1,991.13	< 0.001

Mean ± SD 1) Calculated from general linear model adjusted for age (year) or adjusted for age (year) and energy intake (kcal/day) 2) Adjusted for age (year) 3) Adjusted for age (year) and energy intake (kcal/day) 4) Korean Healthy Eating Index

Table 3.

Incidence risk of metabolic syndrome components for first and fifth quintiles of Korean Healthy Eating Index scores in men (N=2,805)

Metabolic syndrome components	Quintiles of	No. of	Total		Crude			Model 1²⁾			Model 2³⁾
Metabolic syndrome components	KHEI⁴⁾ scores	cases	person-years	HR⁴⁾	95% CI⁴⁾	P-value¹⁾	HR	95% CI	P-value	HR	95% CI	P-value
Abdominal obesity	1st	183	3,884	1.000	–		1.000	–		1.000
Abdominal obesity	5th	156	4,231	0.796	0.643∼0.985	0.036	0.665	0.528∼0.837	< 0.001	0.703	0.553∼0.895	0.004
Hypertriglyceridemia	1st	287	2,964	1.000	–		1.000	–		1.000	–
Hypertriglyceridemia	5th	273	3,383	0.866	0.733∼1.022	0.088	0.813	0.680∼0.972	0.023	0.931	0.773∼1.122	0.453
Low HDL-cholesterolemia	1st	477	3,009	1.000	–		1.000	–		1.000
Low HDL-cholesterolemia	5th	464	3,039	1.009	0.882∼1.156	0.893	1.017	0.879∼1.177	0.817	1.001	0.858∼1.166	0.995
High blood pressure	1st	317	2,978	1.000	–		1.000	–		1.000	–
High blood pressure	5th	265	3,513	0.725	0.616∼0.853	< 0.001	0.662	0.555∼0.789	< 0.001	0.748	0.623∼0.897	0.002
Hyperglycemia	1st	244	3,507	1.000	–		1.000	–		1.000	–
Hyperglycemia	5th	202	3,935	0.746	0.619∼0.899	0.002	0.669	0.548∼0.818	< 0.001	0.811	0.657∼1.000	0.051

¹⁾ Calculated from Cox proportional hazards model 2) Adjusted for adjusted for age (year) and energy intake (kcal/day) 3) Adjusted for age (year), energy intake (kcal/day), income (< 100; 100∼199; 200∼3990; ≥ 400 (10,000 won)), education (elementary school graduate or less; middle school graduate; high school graduate; college graduate or more), physical activity (METs), smoking (pack-years), and alcohol intake (g/day) 4) KHEI: Korean Healthy Eating Index, HR: hazard ratio, CI: confidence interval

Table 4.

Incidence risk of metabolic syndrome components for first and fifth quintiles of Korean Healthy Eating Index scores in women (N=2,744)

Metabolic syndrome components	Quintiles of KHEI⁴⁾ scores	No. of cases	Total person-years	Crude			Model 1²⁾			Model 2³⁾
Metabolic syndrome components	Quintiles of KHEI⁴⁾ scores	No. of cases	Total person-years	HR⁴⁾	95% CI⁴⁾	P-value¹⁾	HR	95% CI	P-value	HR	95% CI	P-value
Abdominal obesity	1st	263	3,073	1.000	–		1.000	–		1.000	–
Abdominal obesity	5th	179	4,066	0.547	0.452∼0.661	< 0.001	0.526	0.430∼0.643	< 0.001	0.702	0.569∼0.867	0.001
Hypertriglyceridemia	1st	243	3,535	1.000	–		1.000	–		1.000	–
Hypertriglyceridemia	5th	226	3,958	0.828	0.691∼0.993	0.041	0.934	0.772∼1.131	0.486	0.952	0.780∼1.163	0.631
Low HDL-cholesterolemia	1st	524	1,613	1.000	–		1.000	–		1.000	–
Low HDL-cholesterolemia	5th	509	2,013	0.822	0.722∼0.935	0.003	0.834	0.726∼0.957	0.009	0.869	0.753∼1.004	0.056
High blood pressure	1st	242	3,448	1.000	–		1.000	–		1.000	–
High blood pressure	5th	183	3,941	0.672	0.554∼0.814	< 0.001	0.768	0.627∼0.941	0.011	0.898	0.725∼1.112	0.325
Hyperglycemia	1st	143	4,115	1.000	–		1.000	–		1.000	–
Hyperglycemia	5th	122	4,430	0.792	0.622∼1.008	0.058	0.843	0.653∼1.089	0.190	0.992	0.757∼1.299	0.953

Table 5.

Incidence risk of metabolic syndrome across quintiles of Korean Healthy Eating Index scores in men (N=2,805)

Quintiles of KHEI⁵⁾ scores	No. of cases	Crude			Model 1³⁾				Model 2⁴⁾
Quintiles of KHEI⁵⁾ scores	No. of cases	Total person-years	HR⁵⁾	95% CI⁵⁾	P-value¹⁾	HR	95% CI	P-value	HR	95% CI	P-value
1st	208	3,738	1.000	–		1.000	–		1.000	–
2nd	202	3,696	0.985	0.811∼1.195	0.876	0.945	0.777∼1.150	0.574	0.952	0.781∼1.161	0.628
3rd	180	3,800	0.851	0.697∼1.039	0.113	0.792	0.645∼0.972	0.026	0.840	0.681∼1.037	0.105
4th	178	3,984	0.801	0.656∼0.979	0.030	0.727	0.590∼0.897	0.003	0.791	0.637∼0.984	0.035
5th	180	4,040	0.799	0.655∼0.976	0.028	0.691	0.557∼0.858	< 0.001	0.775	0.619∼0.971	0.027
P-value for trend^1),2)				0.005			< 0.001			0.009

¹⁾ Calculated from Cox proportional hazards model 2) P-value for trend was calculated by treating the KHEI quintile as a continuous variable after substitution each quintile value with its medium value 3) Adjusted for adjusted for age (year) and energy intake (kcal/day) 4) Adjusted for age (year), energy intake (kcal/day), income (< 100; 100∼199; 200∼3990; ≥ 400 (10,000 won)), education (elementary school graduate or less; middle school graduate; high school graduate; college graduate or more), physical activity (METs), smoking (pack-years), and alcohol intake (g/day) 5) KHEI: Korean Healthy Eating Index, HR: hazard ratio, CI: confidence interval

Table 6.

Incidence risk of metabolic syndrome across quintiles of Korean Healthy Eating Index scores in women (N=2,744)

Quintiles of KHEI⁵⁾ scores	⁾ No. of cases	Crude				Model 1³⁾			Model 2⁴⁾
Quintiles of KHEI⁵⁾ scores	⁾ No. of cases	Total person-years	HR⁵⁾	95% CI⁵⁾	P-value¹⁾	HR	95% CI	P-value	HR	95% CI	P-value
1st	218	3,556	1.000	–		1.000	–		1.000	–
2nd	191	3,752	0.829	0.683∼1.007	0.059	0.839	0.689∼1.021	0.080	0.931	0.759∼1.142	0.492
3rd	203	3,671	0.905	0.747∼1.095	0.305	0.898	0.739∼1.093	0.283	1.036	0.846∼1.268	0.734
4th	180	3,781	0.781	0.641∼0.952	0.014	0.799	0.650∼0.981	0.032	0.976	0.787∼1.211	0.825
5th	151	4,148	0.593	0.482∼0.729	< 0.001	0.606	0.486∼0.755	< 0.001	0.774	0.615∼0.975	0.030
P-value for trend^1),2)			< 0.001			< 0.001			0.093

¹⁾ Calculated from Cox proportional hazards model 2) P for trend was calculated by treating the KHEI quintile as a continuous variable after substitution each quintile value with its medium value 3) Adjusted for adjusted for age (year) and energy intake (kcal/day) 4) Adjusted for age (year), energy intake (kcal/day), income (< 100; 100∼199; 200∼3990; ≥ 400 (10,000 won)), education (elementary school graduate or less; middle school graduate; high school graduate; college graduate or more), physical activity (METs), smoking (pack-years), and alcohol intake (g/day) 5) KHEI: Korean Healthy Eating Index, HR: hazard ratio, CI: confidence interval

REFERENCES

1. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention. Korea Health Statistics 2016: Korea National Health and Nutrition Examination Survey (KNHANES VII-1). Cheongju: Korea Centers for Disease Control and Prevention; 2017.
2. Korean Society of Cardiometabolic Syndrome. Metabolic syndrome fact sheet in Korea 2018 [Internet]. Korean Society of Cardiometabolic Syndrome;. 2018; [cited 2020 Feb 13]. Available from:. http://kscms.org/en/uploads/Metabolic_Syndrome.pdf.
3. Galassi A, Reynolds K, He J. Metabolic syndrome and risk of cardiovascular disease: a metaanalysis. Am J Med 2006; 119(10): 812-819.Article PubMed
4. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005; 112(17): 2735-2752.Article PubMed
5. Ministry of Health and Welfare. The 4th health plan (2016∼2020) [Internet]. Sejong: Ministry of Health and Welfare; 2016. [updated 2016 Mar 15; cited 2017 Feb 30]. Available from:. http://www.mohw.go.kr/react/jb/sjb030301vw.jsp?PAR_MENU_ID=03&MENU_ID=0319&CONT_SEQ=330479&page=1.
6. Mirmiran P, Moslehi N, Mahmoudof H, Sadeghi M, Azizi F. A longitudinal study of adherence to the Mediterranean dietary pattern and metabolic syndrome in a non-Mediterranean population. Int J Endocrinol Metab 2015; 13(3): e26128.Article PubMed PMC
7. Sadykova K, Shalkharova Z, Nuskabayeva G, Zhunissova M, Madenbay K. Relation between adherence to Mediterranean diet and components of the metabolic syndrome in the Kajakhastani population. Georgian Med News 2018; 274:97-102.
8. Fung TT, Hu FB, Wu K, Chiuve SE, Fuchs CS, Giovannucci E. The Mediterranean and Dietary Approaches to Stop Hypertension (DASH) diets and colorectal cancer. Am J Clin Nutr 2010; 92(6): 1429-1435.Article PubMed PMC
9. Kant AK, Schatzkin A, Graubard BI, Schairer C. A prospective study of diet quality and mortality in women. JAMA 2000; 283(16): 2109-2115.Article PubMed
10. Mai V, Kant AK, Flood A, Lacey JV Jr, Schairer C, Schatzkin A. Diet quality and subsequent cancer incidence and mortality in a prospective cohort of women. Int J Epidemiol 2005; 34(1): 54-60.Article PubMed
11. Ahn S, Jun S, Kang M, Shin S, Wie GA, Baik HW, et al. Association between intake of antioxidant vitamins and metabolic syndrome risk among Korean adults. J Nutr Health 2017; 50(4): 313-324.Article PDF
12. Kim M, Kim J, Bae W, Kim S, Lee Y, Na W, et al. Relationship between nutrients intakes, dietary quality, and serum concentrations of inflammatory markers in metabolic syndrome patients. Korean J Community Nutr 2011; 16(1): 51-61.Article
13. 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(10): 1482-1488.Article PubMed PMC PDF
14. Baik I, Abbott RD, Curb JD, Shin C. Intake of fish and n-3 fatty acids and future risk of metabolic syndrome. J Am Diet Assoc 2010; 110(7): 1018-1026.Article PubMed
15. Baik I, Shin C. Prospective study of alcohol consumption and metabolic syndrome. Am J Clin Nutr 2008; 87(5): 1455-1463.Article PubMed
16. Oh SM, Kim HC, Ahn SV, Chi HJ, Suh I. Association between meat consumption and carotid intima-media thickness in Korean adults with metabolic syndrome. J Prev Med Public Health 2010; 43(6): 486-495.Article PubMed
17. Kim YJ, Hwang JY, Kim H, Park S, Kwon O. Diet quality, physical activity, and their association with metabolic syndrome in Korean adults. Nutrition 2019; 59:138-144.Article PubMed
18. Shin S, Lee S. Association between total diet quality and metabolic syndrome incidence risk in a prospective cohort of Korean adults. Clin Nutr Res 2019; 8(1): 46-54.Article PubMed PMC PDF
19. National Institute of Health, Korean Centers for Disease Control and Prevention. Examination and survey quality control of the Korean Genome and Epidemiology Study [Internet]. National Institute of Health; 2019. [updated 2019 Aug 8; cited 2019 Oct 30]. Available from:. http://nih.go.kr/contents.es?mid=a40504040200.
20. Lee SY, Park HS, Kim DJ, Han JH, Kim SM, Cho GJ, et al. Appropriate waist circumference cutoff points for central obesity in Korean adults. Diabetes Res Clin Pract 2007; 75(1): 72-80.Article PubMed
21. Yook SM, Park S, Moon HK, Kim K, Shim JE, Hwang JY. Development of Korean Healthy Eating Index for adults using the Korea National Health and Nutrition Examination Survey data. J Nutr Health 2015; 48(5): 419-428.Article
22. Ministry of Health and Welfare. Dietary guidelines for Korean adults [Internet]. Ministry of Health and Welfare; 2009. [updated 2009 Dec 8; cited 2014 Mar 27]. Available from:. http://www.mw.go.kr/front_new/jb/sjb030301vw.jsp?PAR_MENU_ID=03&MENU_ID=0320&CONT_SEQ=224044&page=1.
23. The Korean Nutrition Society. Dietary reference intakes for Koreans. 1st revision. Seoul: The Korean Nutrition Society; 2010.
24. Guenther PM, Reedy J, Krebs-Smith SM. Development of the healthy eating index-2005. J Am Diet Assoc 2008; 108(11): 1896-1901.Article PubMed
25. Fogli-Cawley JJ, Dwyer JT, Saltzman E, McCullough ML, Troy LM, Meigs JB, et al. The 2005 Dietary Guidelines for Americans and risk of the metabolic syndrome. Am J Clin Nutr 2007; 86(4): 1193-1201.Article PubMed
26. Kesse-Guyot E, Ahluwalia N, Lassale C, Hercberg S, Fezeu L, Lairon D. Adherence to Mediterranean diet reduces the risk of metabolic syndrome: a 6-year prospective study. Nutr Metab Cardiovasc Dis 2013; 23(7): 677-683.Article PubMed

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Relation between the Total Diet Quality based on Korean Healthy Eating Index and the Incidence of Metabolic Syndrome Constituents and Metabolic Syndrome among a Prospective Cohort of Korean Adults

Korean J Community Nutr. 2020;25(1):61-70. Published online February 29, 2020

DOI: https://doi.org/10.5720/kjcn.2020.25.1.61

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Relation between the Total Diet Quality based on Korean Healthy Eating Index and the Incidence of Metabolic Syndrome Constituents and Metabolic Syndrome among a Prospective Cohort of Korean Adults

Table 1.

Subjects' general characteristics at baseline

Characteristics	Men (N=2,805)	Women (N=2,744)	P-value¹⁾
Age group
40∼49 (year)	1,535 (54.7)	1,594 (58.1)	0.007
50∼59 (year)	679 (24.2)	631 (23.0)
60∼69 (year)	591 (21.1)	519 (18.9)
Education			< 0.001
Elementary school graduate or less	547 (19.6)	980 (35.9)
Middle school graduate	631 (22.6)	697 (25.6)
High school graduate	1,022 (36.6)	854 (31.3)
College graduate or more Income (10,000 won)	594 (21.3)	197 (97.2)	< 0.001
< 100	751 (27.0)	899 (33.5)	< 0.001
100∼199	862 (31.0)	830 (30.9)
200∼399	920 (33.1)	774 (28.8)
≥ 400	250 (99.0)	182 (96.8)
Drinking status
Non-drinker	791 (28.2)	1,913 (69.7)
Drinker	2,014 (71.8)	831 (30.3)
Alcohol intake (g/day)	17.6 ± 27.9	1.6 ± 5.8	< 0.001
Smoking status			< 0.001
Non-smoker	1,354 (48.3)	2,639 (96.2)	< 0.001
Smoker	1,451 (51.7)	105 (93.8)
Cumulative smoking (pack-year)	18.0 ± 17.6	0.4 ± 2.6
Physical activity			< 0.001
METs²⁾ < 20	1,560 (57.3)	1,787 (66.9)
20 ≤ METs < 40	536 (19.7)	425 (15.9)
40 ≤ METs	627 (23.0)	458 (17.2)

n (%) or Mean ± SD 1) Calculated from chi-square test or student t-test 2) Metabolic equivalents

Table 2.

Nutrient and food group intakes for first and fifth quintiles of Korean Healthy Eating Index scores

Dietary component	Men (N=2,805)			Women (N=2,744)
			Quintiles of KHEI scores		P-value
	1st	5th	P-value¹⁾ 1st	5th	P-value
Total KHEI⁴⁾ score	1,943.79 ± 1,995.19¹⁾	1,977.72 ± 1,994.61	< 0.001 1,949.13 ± 1,996.03	1,984.47 ± 1,993.68	< 0.001
Nutrients
Energy (kcal/day)²⁾	1,650.96 ± 1,467.96	2,312.56 ± 1,558.42	< 0.001 1,546.58 ± 1,519.37	2,159.27 ± 1,618.44	< 0.001
Energy from carbohydrates (%)²⁾	1,973.83 ±1,99 8.27	1,966.58 ±1,99 4.54	< 0.001 1,976.04 ± 1,997.84	1,967.69 ± 1,994.32	< 0.001
Energy from fat (%)²⁾	1,912.36 ±1,99 6.58	1,917.78 ± 1,993.35	< 0.001 1,910.71 ± 1,996.35	1,916.72 ± 1,993.32	< 0.001
Dietary fiber (g/day)³⁾	1,995.21 ± 1,992.44	1,998.50 ± 1,993.15	< 0.001 1,995.15 ± 1,992.55	1,998.44 ± 1,993.33	< 0.001
Alcohol (g/day)³⁾	1,932.68 ± 1,931.70	1,917.64 ± 1,926.22	< 0.001 1,998.18 ± 1,913.49	1,992.49 ± 1,992.63	< 0.001
Sodium (mg/day)³⁾	2,967.20 ± 1,617.31	3,686.14 ± 1,632.86	0.009 2,564.25 ± 1,333.82	3,392.21 ± 1,671.25	0.064
Food groups
Fruits (servings/day)³⁾	1,990.94 ± 1,991.37	1,992.67 ± 1,992.20	< 0.001 1,991.44 ± 1,992.20	1,992.87 ±1,99 2.49	0.103
Vegetables (servings/day)³⁾	1,992.46 ± 1,991.80	1,995.33 ±1,99 2.61	< 0.001 1,992.67 ± 1,992.24	1,995.90 ± 1,993.32	< 0.001
Dairy products (servings/day)³⁾	1,990.17 ±1,99 0.48	1,991.08 ±1,99 0.80	< 0.001 1,990.21 ±1,99 0.49	1,991.34 ±1,99 0.99	< 0.001
Protein foods (servings/day)³⁾	1,991.77 ±1,99 1.37	1,994.11 ± 1,991.63	< 0.001 1,991.52 ±1,99 1.25	1,993.99 ±1,99 1.68	< 0.001
Empty calorie foods (servings/day)	)³⁾ 1,994.47 ±1,99 3.86	1,992.94 ± 1,992.89	< 0.001 1,991.38 ±1,99 1.62	1,991.20 ±1,99 0.95	< 0.001
Whole grains (servings/day)³⁾	1,990.53 ±1,99 1.04	1,991.87 ± 1,991.37	< 0.001 1,990.80 ± 1,991.27	1,992.25 ±1,99 1.21	< 0.001
Refined grains (servings/day)³⁾	1,992.58 ± 1,991.23	1,991.37 ± 1,991.40	< 0.001 1,992.20 ± 1,991.33	1,990.79 ± 1,991.13	< 0.001

Table 3.

Incidence risk of metabolic syndrome components for first and fifth quintiles of Korean Healthy Eating Index scores in men (N=2,805)

Metabolic syndrome components	Quintiles of	No. of	Total		Crude			Model 1²⁾			Model 2³⁾
Metabolic syndrome components	KHEI⁴⁾ scores	cases	person-years	HR⁴⁾	95% CI⁴⁾	P-value¹⁾	HR	95% CI	P-value	HR	95% CI	P-value
Abdominal obesity	1st	183	3,884	1.000	–		1.000	–		1.000
Abdominal obesity	5th	156	4,231	0.796	0.643∼0.985	0.036	0.665	0.528∼0.837	< 0.001	0.703	0.553∼0.895	0.004
Hypertriglyceridemia	1st	287	2,964	1.000	–		1.000	–		1.000	–
Hypertriglyceridemia	5th	273	3,383	0.866	0.733∼1.022	0.088	0.813	0.680∼0.972	0.023	0.931	0.773∼1.122	0.453
Low HDL-cholesterolemia	1st	477	3,009	1.000	–		1.000	–		1.000
Low HDL-cholesterolemia	5th	464	3,039	1.009	0.882∼1.156	0.893	1.017	0.879∼1.177	0.817	1.001	0.858∼1.166	0.995
High blood pressure	1st	317	2,978	1.000	–		1.000	–		1.000	–
High blood pressure	5th	265	3,513	0.725	0.616∼0.853	< 0.001	0.662	0.555∼0.789	< 0.001	0.748	0.623∼0.897	0.002
Hyperglycemia	1st	244	3,507	1.000	–		1.000	–		1.000	–
Hyperglycemia	5th	202	3,935	0.746	0.619∼0.899	0.002	0.669	0.548∼0.818	< 0.001	0.811	0.657∼1.000	0.051

¹⁾Calculated from Cox proportional hazards model 2) Adjusted for adjusted for age (year) and energy intake (kcal/day) 3) Adjusted for age (year), energy intake (kcal/day), income (< 100; 100∼199; 200∼3990; ≥ 400 (10,000 won)), education (elementary school graduate or less; middle school graduate; high school graduate; college graduate or more), physical activity (METs), smoking (pack-years), and alcohol intake (g/day) 4) KHEI: Korean Healthy Eating Index, HR: hazard ratio, CI: confidence interval

Table 4.

Incidence risk of metabolic syndrome components for first and fifth quintiles of Korean Healthy Eating Index scores in women (N=2,744)

Metabolic syndrome components	Quintiles of KHEI⁴⁾ scores	No. of cases	Total person-years	Crude			Model 1²⁾			Model 2³⁾
Metabolic syndrome components	Quintiles of KHEI⁴⁾ scores	No. of cases	Total person-years	HR⁴⁾	95% CI⁴⁾	P-value¹⁾	HR	95% CI	P-value	HR	95% CI	P-value
Abdominal obesity	1st	263	3,073	1.000	–		1.000	–		1.000	–
Abdominal obesity	5th	179	4,066	0.547	0.452∼0.661	< 0.001	0.526	0.430∼0.643	< 0.001	0.702	0.569∼0.867	0.001
Hypertriglyceridemia	1st	243	3,535	1.000	–		1.000	–		1.000	–
Hypertriglyceridemia	5th	226	3,958	0.828	0.691∼0.993	0.041	0.934	0.772∼1.131	0.486	0.952	0.780∼1.163	0.631
Low HDL-cholesterolemia	1st	524	1,613	1.000	–		1.000	–		1.000	–
Low HDL-cholesterolemia	5th	509	2,013	0.822	0.722∼0.935	0.003	0.834	0.726∼0.957	0.009	0.869	0.753∼1.004	0.056
High blood pressure	1st	242	3,448	1.000	–		1.000	–		1.000	–
High blood pressure	5th	183	3,941	0.672	0.554∼0.814	< 0.001	0.768	0.627∼0.941	0.011	0.898	0.725∼1.112	0.325
Hyperglycemia	1st	143	4,115	1.000	–		1.000	–		1.000	–
Hyperglycemia	5th	122	4,430	0.792	0.622∼1.008	0.058	0.843	0.653∼1.089	0.190	0.992	0.757∼1.299	0.953

¹⁾Calculated from Cox proportional hazards model 2) Adjusted for adjusted for age (year) and energy intake (kcal/day) 3) Adjusted for age (year), energy intake (kcal/day), income (< 100; 100∼199; 200∼3990; ≥ 400 (10,000 won)), education (elementary school graduate or less; middle school graduate; high school graduate; college graduate or more), physical activity (METs), smoking (pack-years), and alcohol intake (g/day) 4) KHEI: Korean Healthy Eating Index, HR: hazard ratio, CI: confidence interval

Table 5.

Incidence risk of metabolic syndrome across quintiles of Korean Healthy Eating Index scores in men (N=2,805)

Quintiles of KHEI⁵⁾ scores	No. of cases	Crude			Model 1³⁾				Model 2⁴⁾
Quintiles of KHEI⁵⁾ scores	No. of cases	Total person-years	HR⁵⁾	95% CI⁵⁾	P-value¹⁾	HR	95% CI	P-value	HR	95% CI	P-value
1st	208	3,738	1.000	–		1.000	–		1.000	–
2nd	202	3,696	0.985	0.811∼1.195	0.876	0.945	0.777∼1.150	0.574	0.952	0.781∼1.161	0.628
3rd	180	3,800	0.851	0.697∼1.039	0.113	0.792	0.645∼0.972	0.026	0.840	0.681∼1.037	0.105
4th	178	3,984	0.801	0.656∼0.979	0.030	0.727	0.590∼0.897	0.003	0.791	0.637∼0.984	0.035
5th	180	4,040	0.799	0.655∼0.976	0.028	0.691	0.557∼0.858	< 0.001	0.775	0.619∼0.971	0.027
P-value for trend^1),2)				0.005			< 0.001			0.009

¹⁾Calculated from Cox proportional hazards model 2) P-value for trend was calculated by treating the KHEI quintile as a continuous variable after substitution each quintile value with its medium value 3) Adjusted for adjusted for age (year) and energy intake (kcal/day) 4) Adjusted for age (year), energy intake (kcal/day), income (< 100; 100∼199; 200∼3990; ≥ 400 (10,000 won)), education (elementary school graduate or less; middle school graduate; high school graduate; college graduate or more), physical activity (METs), smoking (pack-years), and alcohol intake (g/day) 5) KHEI: Korean Healthy Eating Index, HR: hazard ratio, CI: confidence interval

Table 6.

Incidence risk of metabolic syndrome across quintiles of Korean Healthy Eating Index scores in women (N=2,744)