KSCN
Articles
- Page Path
- HOME > Korean J Community Nutr > Volume 22(6); 2017 > Article
-
Research Article
-
Korean Journal of Community Nutrition 2017;22(6):507-519.
DOI: https://doi.org/10.5720/kjcn.2017.22.6.507
Published online: January 20, 2017
1)Department of Food Science & Nutrition, The Catholic University of Korea, Bucheon, Korea
- †Corresponding author Sook Mee Son Department of Food and Nutrition, 43, Jibong-ro, Bucheon-si, Gyeonggi-do 14662, Korea Tel: (02) 2164-4318 Fax: (02) 02-2164-4310 E-mail: sonsm@catholic.ac.kr ORCID: 0000-0002-7578-2882
• Received: September 29, 2017 • Revised: December 19, 2017 • Accepted: December 19, 2017
Copyright © 2017 Journal of the Korean Society of Community Nutrition
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.
- 945 Views
- 1 Download
- 3 Crossref
Abstract
-
Objectives
- The objective of this study was to examine the relations between total vegetable and Kimchi intakes and the risk of metabolic syndrome (Mets) in Korean adults.
-
Methods
- This study used dietary intake and health data of 6668 subjects aged 20 years and over from the 2010–2011 Korea National Health and Nutrition Examination Survey (KNHANES). Daily intakes of total vegetables and Kimchi were assessed by 24-hour recall data. The odds ratio of Mets risk according to daily intake of vegetables and Kimchi was analyzed, respectively.
-
Results
- The highest consumption of total vegetables was associated with a lower risk of abdominal obesity (multivariable adjusted OR=0.56, 95% CI: 0.33, 0.93) in men and lower risk of Mets (multivariable adjusted OR=0.67, 95% CI: 0.47, 0.94) in women. Kimchi consumption was not related to the risk of Mets in both men and in women. However, a higher intake of Kimchi was associated with an increased risk of elevated blood pressure (Q1 vs Q5, multivariable adjusted OR=1.34, 95% CI: 0.95, 1.90, P for trend= 0.0261) in women.
-
Conclusions
- A higher intake of vegetables was associated with decreased risk of abdominal obesity and Mets in both men and women, respectively. A higher consumption of Kimchi was not related to the risk of Mets in both in men and in women. However, a higher intake of Kimchi was associated with an increased risk of elevated blood pressure in women.
Table 1.General characteristics of Korean adults according to quintiles of total vegetable intake
Values are expressed as mean ± SE for continuous variables and percentage for categorical variables.
Q1, Q3, Q5 are the lowest, middle, and highest quintiles, respectively
1) P value is P for trend determined by GLM for continuous variables and P for difference by Chi-square test for categorical variables.
2) High was defined as Quatile 4 evaluated with monthly household income.
3) Regular exercise was defined as walking at least 30 minutes a day, more than 5 times per week.
Table 2.General characteristics of Korean adults participants according to quintiles of Kimchi intake
Values are expressed as mean°æSE for continuous variables and percentage for categorical variables. Q1, Q3, Q5 are the lowest, middle, and highest quintiles, respectively. 1) P value is P for trend determined by GLM for continuous variables and P for difference by Chi-square test for categorical variables. 2) High was defined as Quatile 4 evaluated with monthly household income. 3) Regular exercise was defined as walking at least 30 minutes a day, more than 5 times per week.
Table 3.Energy and energy adjusted nutrient intake according to quintiles of total vegetable intake in Korean adults
Table 4.Energy and energy adjutsetd nutrient intake according to quintiles of Kimchi intake in Korean adults.
Table 5.Parameters according to quintiles of total vegetable intake in Korean adults
Table 6.Parameters according to quintiles of Kimchi intake in Korean adults.
Table 7.The odds ratios and 95% confidence intervals for metabolic syndrome and its components according to quintiles of total vegetable intake in Korea adults
1)Adjustment for age, BMI, household income (>high), education (>college or higher), regular exercise (walking at least 30 minutes a day, more than 5 times) (yes/no), current smoking status (current smoker) (yes/no), monthly alcohol consumption (≥1 cups per month) (yes/no), eating out times (≥1 time/week) (yes/no), frequency of fast food intake (≥1 time/week) (yes/no), energy intake 2) P for trend from GLM
Table 8.The odd ratios and 95% confidence intervals for metabolic syndrome and its components according to quintiles of Kimchi intake in Korea adults
1)Adjustment for age, BMI, household income (>high), education (>college or higher), regular exercise (walking at least 30 minutes a day, more than 5 times) (yes/no), current smoking status (current smoker) (yes/no), monthly alcohol consumption (≥1 cups per month) (yes/no), eating out times (≥1 time/week) (yes/no), frequency of fast food intake (≥1 time/week) (yes/no), energy intake 2) P for trend from GLM
- 1. 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.ArticlePubMed
- 2. Isomaa B, Almgren P, Tuomi T, Forsen B, Lahti K, Nissen M, et al. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 2001; 24(4): 683-689.ArticlePubMedPDF
- 3. Haffner SM, Valdez RA, Hazuda HP, Mitchell BD, Morales PA, Stern MP. Prospective analysis of the insulin resistance syndrome (syndrome X). Diabetes 1992; 41(6): 715-722.ArticlePubMed
- 4. Han JH, Park HS, Shin CI, Chang HM, Yun KE, Cho SH, et al. Metabolic syndrome and quality of life (QOL) using generalised and obesity?specific QOL scales. Int J Clin Pract 2009; 63(5): 735-741.ArticlePubMed
- 5. Lim S, Shin H, Song JH, Kwak SH, Kang SM, Yoon JW, et al. 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.PubMedPMC
- 6. Bazzano LA, He J, Ogden LG, Loria CM, Vupputuri S, Myers L, et al. Fruit and vegetable intake and risk of cardiovascular disease in US adults: the first National Health and Nutrition Examination Survey Epidemiologic Follow-up Study. Am J Clin Nutr 2002; 76(1): 93-99.ArticlePubMed
- 7. Bazzano LA, Serdula MK, Liu S. Dietary intake of fruit and vegetable and risk of cardiovascular disease. Curr Atheroscler Rep 2003; 5(6): 492-499.ArticlePubMedPDF
- 8. 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(1): 111-118.ArticlePubMed
- 9. Bian S, Gao Y, Zhang M, Wang X, Liu W, Zhang D, et al. Dietary nutrient intake and metabolic syndrome risk in Chinese adults: a case?control study. Nutr J 2013; 12(1): 106-122.ArticlePubMedPMCPDF
- 10. Li Y, Guo H, Wu M, Liu M. Serum and dietary antioxidant status is associated with lower prevalence of the metabolic syndrome in a study in Shanghai, China. Asia Pac J Clin Nutr 2013; 22(1): 60-68.PubMed
- 11. 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.ArticlePubMed
- 12. Agudo A, Cabrera L, Amiano P, Ardanaz E, Barricarte A, Berenguer T et al Fruit and vegetable intakes, dietary antioxidant nutrients, and total mortality in Spanish adults: findings from the Spanish cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC-Spain). Am J Clin Nutr 2007; 85(6): 1634-1642.
- 13. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention. Korea Health Statistics 2012: Korea National Health and Nutrition Examination Survey (KNHANESV-3). Cheongju: Korea Centers for Disease Control and Prevention; 2013.
- 14. Son SM, Park Y, Lim H, Kim S, Jeong Y. Sodium intakes of Korean adults with 24-hour urine analysis and dish frequency questionnaire and comparison of sodium intakes according to the regional area and dish group. Korean J Community Nutr 2007; 12(5): 545-558.
- 15. Kwon JH, Shim JE, Park MK, Paik HY. Evaluation of fruits and vegetables intake for prevention of chronic disease in Korean adults aged 30 years and over: using the third Korea National Health and Nutrition Examination Survey (KNHANES III), 2005. Korean J Nutr 2009; 42(2): 146-157.Article
- 16. Lee JS, Heo GY, Lee JW, OH YJ, Park JA, Park YH, et al. Analysis of Kimchi microflora using denaturing gradient gel electrophoresis. In J Food Microbiol 2005; 102(2): 143-150.Article
- 17. Kim EK, An SY, Lee MS, Kim TH, Lee HK, Hwang WS, et al. Fermented Kimchi reduces body weight and improves metabolic parameters in overweight and obese patients. Nutr Res 2011; 31(6): 436-443.ArticlePubMed
- 18. Choi SH, Kim HJ, Kwon MJ, Baeck YH, Song YO. The effect of Kimchi pill supplementation on plasma lipid concentration in healthy people. J Korean Soc Food Sci Nutr 2001; 30(5): 913-920.
- 19. Lee SM, Cho Y, Chung HK, Shin DH, Ha WK, Lee SC, et al. Effects of Kimchi supplementation on blood pressure and cardiac hypertrophy with varying sodium content in spontaneously hypertensive rats. Nutr Res Pract 2012; 6(4): 315-321.ArticlePubMedPMC
- 20. Kim MK, Kim K, Shin MH, Shin DH, Lee YH, Chun BY, et al. The relationship of dietary sodium, potassium, fruits, and vegetables intake with blood pressure among Korean adults aged 40 and elder. Nutr Res Pract 2014; 8(4): 453-462.ArticlePubMedPMC
- 21. Ford ES, Mokdad AH, Giles WH, Brown DW. The metabolic syndrome and antioxidant concentrations: findings from the third National Health and Nutrition Examination Survey. Diabetes 2003; 52(9): 2346-2352.PubMed
- 22. Navia B, Aparicio A, Perea JM, Perez-Farinos N, Villar-Villalba C, Labrado E, et al. Sodium intake may promote weight gain; results of the FANPE study in a representative sample of the adult Spanish population. Nutr Hosp 2014; 29(6): 1283-1289.PubMed
- 23. Cocores JA, Gold MS. The salted food addiction hypothesis may explain overeating and the obesity epidemic. Med Hypotheses 2009; 73(6): 892-899.ArticlePubMed
- 24. McKeown NM, Meigs JB, Liu S, Saltzman E, Wilson PW, Jacques PF. Carbohydrate nutrition, insulin resistance, and the prevalence of the metabolic syndrome in the Framingham Offspring Cohort. Diabetes Care 2004; 27(2): 538-546.ArticlePubMedPDF
- 25. Hosseinpour-Niazi S, Mirmiran P, Sohrab G, Hosseini-Esfahani F, Azizi F. Inverse association between fruit, legume, and cereal fiber and the risk of metabolic syndrome: Tehran Lipid and Glucose Study. Diabetes Res Clin Pract 2011; 94(2): 276-283.ArticlePubMed
- 26. Hosseinpour-Niazi S, Mirmiran P, Mirzaei S, Azizi F. Cereal, fruit and vegetable fibre intake and the risk of the metabolic syndrome: a prospective study in the Tehran Lipid and Glucose Study. J Hum Nutr Diet 2015; 28(3): 236-245.ArticlePubMedPDF
- 27. Hermsdorff HHM, Zulet MA, PuchauB , Martinez JA. Fruit and vegetable consumption and proinflammatory gene expression from peripheral blood mononuclear cells in young adults: a translational study. Nutr Metab(Lond) 2010; 7(1): 42-52.ArticlePubMedPMCPDF
- 28. Oh HY, Kim MK, Lee M, Kim YO. Macronutrient composition and sodium intake of diet are associated with risk of metabolic syndrome and hypertension in Korean women. PLoS ONE 2013; 8(10): e78088.ArticlePubMedPMC
- 29. Misra A, Khurana L, Isharwal S, Bhardwaj S. South Asian diets and insulin resistance. Br J Nutr 2009; 101(4): 465-473.ArticlePubMed
- 30. Son SM, Huh GY. Dietary risk factors associated with hypertension in patients. Korean J Community Nutr 2006; 11(5): 661-672.
- 31. Kang M, Joung H, 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.Article
- 32. Miura K, Okuda N, Turin TC, Takashima N, Nakagawa H, Nakamura K, et al. Dietary salt intake and blood pressure in a representative Japanese population: baseline analyses of NIPPON DATA80. J Epidemiol 2010; 20(S3): S524-S530.ArticlePubMedPMC
- 33. Ishibashi K, Oshima T, Matsuura H, Watanabe M, Ishida M, Ishida T, et al. Effects of age and sex on sodium chloride sensitivity: association with plasma renin activity. Clin Nephrol 1994; 42(6): 376-380.PubMed
REFERENCES
Figure & Data
REFERENCES
Citations
Citations to this article as recorded by 
- Association between Phthalate Exposure and Frailty among Community-Dwelling Older Adults: A Repeated Panel Data Study
Hongsoo Kim, Seyune Lee, Young-Il Jung, Yun-Chul Hong
International Journal of Environmental Research and Public Health.2021; 18(4): 1985. CrossRef - Association of Korean fermented cabbage kimchi consumption with an incidence of metabolic syndrome: 10-year follow-up results of the Korean Genome and Epidemiology Study
Suk Hyeon Seo, Jiyoun Hong, Im Huei Son, Young Hee Han, Taisun Hyun
Journal of Nutrition and Health.2019; 52(6): 569. CrossRef - Risk of Metabolic Syndrome according to Intake of White Rice and Kimchi in Korean Adults: based on the 6th Korea National Health and Nutrition Examination Survey, 2013–2015
Jin-Su Kim, So Hyun Ahn, Sook Mee Son
Korean Journal of Community Nutrition.2018; 23(6): 525. CrossRef
Cite
XML Download- We recommend
- Related articles
-
- Self-reported weight change and diet quality in relation to metabolic syndrome among Korean cancer survivors: a cross-sectional study using the Korea National Health and Nutrition Examination Survey 2019–2021
- Analysis of the relationship between sugar intake and cancer prevalence: a cross-sectional study using the 8th Korea National Health and Nutrition Examination Survey
- Trends in growth and nutritional status of Korean toddlers and preschoolers: a cross-sectional study using 2010–2021 Korea National Health and Nutrition Examination Survey data
- Total sugar intake and its contributed foods by age groups in Koreans using the 8th (2019–2021) Korea National Health and Nutrition Examination Survey: a cross-sectional study
- Estimating and evaluating usual total fat and fatty acid intake in the Korean population using data from the 2019–2021 Korea National Health and Nutrition Examination Surveys: a cross-sectional study
Risk of Metabolic Syndrome according to Intakes of Vegetables and Kimchi in Korean Adults: Using the 5th Korea National Health and Nutrition Examination Survey, 2010–2011
Risk of Metabolic Syndrome according to Intakes of Vegetables and Kimchi in Korean Adults: Using the 5th Korea National Health and Nutrition Examination Survey, 2010–2011
General characteristics of Korean adults according to quintiles of total vegetable intake
| Men (n=2628) | P1) | Women (n=4040) | P1) | |||||
|---|---|---|---|---|---|---|---|---|
| Quintiles of total vegetable intake | Quintiles of total vegetable intake | |||||||
| Q1 | Q3 | Q5 | Q1 | Q3 | Q5 | |||
| N | 525 | 526 | 525 | 808 | 808 | 808 | ||
| Total vegetable intake (g/day) | 132.2 ± 3.4 | 341.7 ± 1.4 | 741.4 ± 10.7 | <0.0001 | 86.5 ± 1.7 | 251.7 ± 1.1 | 617.0 ± 8.4 | <0.0001 |
| Kimchi intake (g/day) | 49.2 ± 2.9 | 136.9 ± 4.6 | 270.1 ± 59.8 | <0.0001 | 30.7 ± 1.6 | 101.6 ± 2.9 | 190.8 ± 6.6 | <0.0001 |
| Age (years) | 38.0 ± 0.8 | 41.4 ± 0.6 | 41.9 ± 50.6 | <0.0001 | 39.2 ± 0.6 | 40.8 ± 0.5 | 43.3 ± 0.5 | <0.0001 |
| Household income status | ||||||||
| High (%)2) | 24.3 | 29.2 | 32.3 | 0.0208 | 25.1 | 26.8 | 33.6 | 0.0156 |
| Education | ||||||||
| College or higher(%) | 37.5 | 40.9 | 45.1 | 0.2183 | 37.8 | 38.1 | 36.5 | 0.4827 |
| Regular exercise | ||||||||
| Yes (%)3) | 41.8 | 44.7 | 46.3 | 0.2741 | 38.6 | 36.3 | 37.8 | 0.9051 |
| Smoking status | ||||||||
| Current smoker (%) | 49.3 | 47.0 | 46.8 | 0.9344 | 8.1 | 7.6 | 4.1 | 0.1248 |
| Monthly alcohol consumption | ||||||||
| ≥1 cup (%) | 77.4 | 79.9 | 79.9 | 0.6850 | 46.0 | 47.7 | 43.3 | 0.7475 |
| Frequency of eating out | ||||||||
| ≥1/day (%) | 39.4 | 44.8 | 43.4 | 0.4231 | 18.0 | 16.6 | 14.6 | 0.7442 |
| Frequency of fast food intake | ||||||||
| ≥1/week (%) | 3.3 | 2.7 | 3.3 | 0.9787 | 2.4 | 0.9 | 1.5 | 0.0167 |
Values are expressed as mean ± SE for continuous variables and percentage for categorical variables.
Q1, Q3, Q5 are the lowest, middle, and highest quintiles, respectively
1) P value is P for trend determined by GLM for continuous variables and P for difference by Chi-square test for categorical variables.
2) High was defined as Quatile 4 evaluated with monthly household income.
3) Regular exercise was defined as walking at least 30 minutes a day, more than 5 times per week.
General characteristics of Korean adults participants according to quintiles of Kimchi intake
| Men (n=2628) | P1) | Women (n=4040) | P1) | |||||
|---|---|---|---|---|---|---|---|---|
| Quintiles of Kimchi intake | Quintiles of Kimchi intake | |||||||
| Q1 | Q3 | Q5 | Q1 | Q3 | Q5 | |||
| N | 525 | 526 | 524 | 808 | 805 | 808 | ||
| Kimchi intake (g/day) | 18.0 ± 0.9 | 118.9 ± 0.8 | 344.4 ± 56.3 | <0.0001 | 7.0 ± 0.4 | 75.1 ± 0.5 | 260.5 ± 4.0 | <0.0001 |
| Total vegetable intake(g/day | y) 247.5 ± 8.7 | 352.4 ± 8.4 | 576.1 ± 10.8 | <0.0001 | 201.9 ± 8.9 | 260.3 ± 9.0 | 444.9 ± 8.4 | <0.0001 |
| Age (years) | 37.6 ± 0.7 | 40.7 ± 0.6 | 43.7 ± 50.6 | <0.0001 | 38.8 ± 0.6 | 39.8 ± 0.5 | 43.1 ± 0.6 | <0.0001 |
| Household income status | ||||||||
| High (%)2) | 27.3 | 24.1 | 25.8 | 0.4225 | 32.6 | 30.8 | 26.4 | 0.0942 |
| Education | ||||||||
| College or higher (%) | 42.7 | 40.6 | 41.7 | 0.9790 | 40.2 | 42.7 | 33.0 | 0.0238 |
| Regular exercise | ||||||||
| Yes (%)3) | 47.9 | 41.9 | 44.8 | 0.0620 | 35.2 | 39.3 | 36.2 | 0.3402 |
| Smoking status | ||||||||
| Current smoker (%) | 48.2 | 48.6 | 50.2 | 0.5757 | 8.3 | 8.3 | 5.2 | 0.1896 |
| Monthly alcohol consumption | ||||||||
| ≥1 cup (%) | 79.4 | 79.0 | 76.0 | 0.7898 | 46.7 | 47.0 | 41.9 | 0.3518 |
| Frequency of eating out | ||||||||
| ≥1/day (%) | 41.5 | 48.7 | 37.3 | 0.0344 | 18.5 | 19.1 | 11.8 | 0.0092 |
| Frequency of fast food intake | ||||||||
| ≥1/week (%) | 4.4 | 1.9 | 3.3 | 0.5477 | 3.4 | 1.7 | 0.8 | 0.0089 |
Values are expressed as mean°æSE for continuous variables and percentage for categorical variables. Q1, Q3, Q5 are the lowest, middle, and highest quintiles, respectively. 1) P value is P for trend determined by GLM for continuous variables and P for difference by Chi-square test for categorical variables. 2) High was defined as Quatile 4 evaluated with monthly household income. 3) Regular exercise was defined as walking at least 30 minutes a day, more than 5 times per week.
Energy and energy adjusted nutrient intake according to quintiles of total vegetable intake in Korean adults
| Men (n=2628) | P for trend1) | Women (n=4040) | P for trend1) | |||||
|---|---|---|---|---|---|---|---|---|
| Quintiles of total vegetable intake | Quintiles of total vegetable intake | |||||||
| Q1 | Q3 | Q5 | Q1 | Q3 | Q5 | |||
| N | 525 | 526 | 525 | 808 | 808 | 808 | ||
| Nutrient intake | ||||||||
| Energy (kcal/day) | 1,998.2±532.53) | 2,374.8±345.3 | 2,894.9±536.8 | <0.0001 | 1,442.6± 519.9 | 1,731.5±519.3 | 2,160.1±524.5 | <0.0001 |
| Carbohydrate (g) | 340.5±554.93) | 370.4±554.4 | 377.9±555.4 | <0.0001 | 283.8± 552.5 | 293.0±552.7 | 298.4±553.3 | 0.0019 |
| Protein (g) | 86.4±551.93) | 88.5±551.3 | 94.1±551.8 | 0.0698 | 59.8±550.8 | 64.7±550.8 | 68.9±551.0 | <0.0001 |
| Fat (g) | 57.3± 551.43) | 51.8± 551.4 | 50.8±551.4 | 0.0139 | 42.1±550.9 | 37.1±550.9 | 37.0± 551.1 | <0.0001 |
| Calcium (mg) | 485.7± 517.53) | 565.5±513.1 | 767.7± 521.4 | <0.0001 | 405.8±510.7 | 462.3±559.2 | 613.6±513.2 | <0.0001 |
| Iron (mg) | 13.4±550.43) | 17.5±550.5 | 22.7±550.7 | <0.0001 | 10.8±550.3 | 12.9±550.3 | 18.2±550.8 | <0.0001 |
| Sodium (mg) | 4,277.7±100.03) | 5,837.4±108.6 | 8,527.5±201.6 | <0.0001 | 3,196.9±561.1 | 4,302.7±583.5 | 6,200.2±161.6 | <0.0001 |
| Potassium (mg) | 2,824.1±554.43) | 3,449.3±545.5 | 4,491.6±562.1 | <0.0001 | 2,265.2±547.1 | 2761.3± 534.1 | 3,725.9±560.5 | <0.0001 |
| Sodium/Potassium | 1.6±550.03) | 1.8±550.0 | 2.0±550.0 | <0.0001 | 1.6± 550.0 | 1.7±550.0 | 1.7±550.0 | <0.0001 |
| Potassium/Sodium | 0.8±550.03) | 0.7±550.0 | 0.6±550.0 | <0.0001 | 0.9±550.0 | 0.7±550.0 | 0.8± 550.0 | <0.0001 |
| VitaminA (μgRE) | 770.4± 591.33) | 981.4±548.5 | 1319.6±549.2 | <0.0001 | 548.0±526.6 | 700.5±524.2 | 1,293.9±546.7 | <0.0001 |
| Carotine (μg) | 3,543.1±534.13) | 4,974.8±264.7 | 7,205.8±274.1 | <0.0001 | 2,431.8±141.5 | 3,493.5±134.6 | 7,058.0±276.2 | <0.0001 |
| Retinol (μg) | 188.4± 514.73) | 204.5±558.9 | 97.2± 513.2 | <0.0001 | 115.7± 555.0 | 108.2± 512.0 | 97.6± 559.1 | 0.0586 |
| Thiamine (mg) | 1.5±550.03) | 1.6± 550.0 | 1.8±550.0 | <0.0001 | 1.1±550.0 | 1.2± 550.0 | 1.4± 550.0 | <0.0001 |
| Riboflavin (mg) | 1.5±550.03) | 1.5±550.0 | 1.7± 550.0 | 0.0002 | 1.1±550.0 | 1.1±550.0 | 1.3±550.0 | <0.0001 |
| Niacin (mg) | 19.6±550.43) | 20.9±550.3 | 23.1±550.5 | <0.0001 | 13.3±550.2 | 14.9± 550.2 | 17.2±550.3 | <0.0001 |
| VitaminC (mg) | 81.8±554.13) | 112.7±554.0 | 170.1±554.7 | <0.0001 | 78.5±553.8 | 106.0±554.4 | 155.3± 554.6 | <0.0001 |
Values are presented as mean ± SE. Q1, Q3, Q5 are the lowest, middle, and highest quintiles, respectively. 1) P for trend from GLM unadjusted for energy intake and adjusted for energy for other nutrients.
Energy and energy adjutsetd nutrient intake according to quintiles of Kimchi intake in Korean adults.
| Men (n=2628) | P for trend1) | Women (n=4040) | P for trend1) | |||||
|---|---|---|---|---|---|---|---|---|
| Quintiles of Kimchi intake | Quintiles of Kimchi intake | |||||||
| Q1 | Q3 | Q5 | Q1 | Q3 | Q5 | |||
| N | 525 | 526 | 524 | 808 | 805 | 808 | ||
| Nutrient intake | ||||||||
| Energy (kcal/day) | 2,304.8 ± 36.3 | 2,369.1 ± 35.9 | 2,610.5 ± 36.3 | <0.0001 | 1,633.1 ± 22.9 | 1,755.5 ± 22.4 | 1,910.3 ± 22.1 | <0.0001 |
| Carbohydrate (g) | 341.0 ± 5.5 | 357.6 ± 4.2 | 383.4 ± 4.7 | <0.0001 | 278.8 ± 3.0 | 289.1 ± 2.2 | 302.3 ± 2.4 | <0.0001 |
| Protein (g) | 89.2 ± 1.8 | 91.4 ± 2.2 | 88.3 ± 1.3 | 0.6300 | 64.1 ± 0.8 | 64.5 ± 0.8 | 65.6 ± 0.9 | 0.0342 |
| Fat (g) | 58.3 ± 1.4 | 52.9 ± 1.3 | 48.1 ± 1.2 | <0.0001 | 41.9 ± 0.9 | 39.4 ± 0.8 | 35.2 ± 0.8 | <0.0001 |
| Calcium (mg) | 535.1 ± 18.5 | 569.5 ± 15.0 | 670.0 ± 18.1 | <0.0001 | 449.1 ± 10.7 | 481.0 ± 13.2 | 540.3 ± 10.9 | <0.0001 |
| Iron (mg) | 15.4 ± 0.5 | 18.2 ± 0.6 | 20.0 ± 0.8 | <0.0001 | 12.6 ± 0.3 | 13.4 ± 0.3 | 15.4 ± 0.7 | 0.0004 |
| Sodium (mg) | 4,687.5 ± 135.8 | 6,042.9 ± 117.1 | 8,388.1 ± 189.8 | <0.0001 | 3,377.3 ± 73.5 | 4,023.1 ± 83.0 | 6,296.1 ± 117.9 | <0.0001 |
| Potassium (mg) | 3,100.3 ± 52.8 | 3,472.0 ± 55.1 | 3,958.7 ± 56.1 | <0.0001 | 2,605.8 ± 51.9 | 2,772.9 ± 43.8 | 3,261.7 ± 54.1 | <0.0001 |
| Sodium/ Potassium | 1.6 ± 0.0 | 1.8 ± 0.0 | 2.2 ± 0.0 | <0.0001 | 1.4 ± 0.0 | 1.6 ± 0.0 | 2.0 ± 0.0 | <0.0001 |
| Potassium/ Sodium | 0.8 ± 0.0 | 0.6 ± 0.0 | 0.5 ± 0.0 | <0.0001 | 1.0 ± 0.0 | 0.8 ± 0.0 | 0.6 ± 0.0 | <0.0001 |
| Vitamin A (µgRE) | 901.5 ± 62.7 | 971.0 ± 83.2 | 1,045.5 ± 46.0 | 0.1650 | 704.7 ± 33.5 | 776.3 ± 27.4 | 899.3 ± 32.5 | 0.0016 |
| Carotine (µg) | 4,349.2 ± 356.3 | 4,972.7 ± 490.6 | 5,557.1 ± 244.2 | 0.0066 | 3,377.9 ± 182.1 | 3,836.4 ± 151.2 | 4,740.9 ± 193.7 | <0.0001 |
| Retinol (µg) | 184.8 ± 19.7 | 188.8 ± 57.0 | 104.6 ± 14.1 | 0.0144 | 116.1 ± 8.7 | 128.7 ± 14.3 | 91.1 ± 6.3 | 0.0035 |
| Thiamine (mg) | 1.5 ± 0.0 | 1.6 ± 0.0 | 1.7 ± 0.0 | 0.0026 | 1.1 ± 0.0 | 1.2 ± 0.0 | 1.3 ± 0.0 | <0.0001 |
| Riboflavin (mg) | 1.5 ± 0.1 | 1.5 ± 0.0 | 1.5 ± 0.0 | 0.9826 | 1.1 ± 0.0 | 1.2 ± 0.0 | 1.2 ± 0.0 | 0.0119 |
| Niacin (mg) | 20.4 ± 0.4 | 20.8 ± 0.4 | 21.4 ± 0.4 | 0.2541 | 14.8 ± 0.2 | 15.2 ± 0.2 | 15.7 ± 0.3 | 0.0470 |
| VitaminC (mg) | 92.2 ± 3.5 | 105.0 ± 3.3 | 142.1 ± 4.2 | <0.0001 | 95.2 ± 4.2 | 102.9 ± 3.5 | 132.3 ± 4.4 | <0.0001 |
Values are presented as mean ± SE. Q1, Q3, Q5 are the lowest, middle, and highest quintiles, respectively. 1) P for trend from GLM unadjusted for energy intake and adjusted for energy intake for other nutrients.
Parameters according to quintiles of total vegetable intake in Korean adults
| Men (n=2628) | P for trend1) | Women (n=4040) | P for trend1) | |||||
|---|---|---|---|---|---|---|---|---|
| Quintiles of total vegetable intake | Quintiles of total vegetable intake | |||||||
| Q1 | Q3 | Q5 | Q1 | Q3 | Q5 | |||
| N | 525 | 526 | 525 | 808 | 808 | 808 | ||
| Parameters | ||||||||
| Body mass index | 23.3 ± 0.2 | 23.9 ± 0.2 | 24.2 ± 0.2 | 0.0025 | 22.5 ± 0.2 | 23.0 ± 0.1 | 23.1 ± 0.1 | 0.1251 |
| Waist circumference (cm) | 83.3 ± 0.2 | 83.6 ± 0.2 | 82.5 ± 0.3 | 0.0026 | 76.4 ± 0.2 | 76.6 ± 0.2 | 76.3 ± 0.2 | 0.0212 |
| Systolic blood pressure (mmHg) | 120.3 ± 0.7 | 119.2 ± 0.7 | 119.5 ± 0.7 | 0.2344 | 113.4 ± 0.5 | 112.4 ± 0.5 | 112.3 ± 0.6 | 0.2981 |
| Diastolic blood pressure (mmHg) | 79.3 ± 0.5 | 79.1 ± 0.5 | 79.7 ± 0.5 | 0.0110 | 72.7 ± 0.4 | 72.8 ± 0.4 | 73.3 ± 0.4 | 0.0933 |
| Fasting plasma glucose (mg/dl) | 96.7 ± 0.9 | 95.4 ± 0.6 | 95.8 ± 1.4 | 0.1817 | 90.9 ± 0.4 | 90.6 ± 0.3 | 91.6 ± 0.6 | 0.1024 |
| Triglyceride (mg/dl) | 150.8 ± 4.8 | 153.4 ± 5.6 | 146.4 ± 7.2 | 0.0497 | 104.5 ± 2.8 | 100.3 ± 2.5 | 100.1 ± 2.8 | 0.9750 |
| HDL-cholesterol (mg/dl) | 50.9 ± 0.6 | 51.1 ± 0.6 | 49.6 ± 0.6 | 0.3594 | 56.9 ± 0.5 | 56.2 ± 0.4 | 56.9 ± 0.5 | 0.2779 |
Values are presented as mean ± SE. Q1, Q3, Q5 are the lowest, middle, and highest quintiles, respectively. 1) P for trend from GLM.
Parameters according to quintiles of Kimchi intake in Korean adults.
| Men (n=2628) | P for trend1) | Women (n=4040) | P for trend1) | |||||
|---|---|---|---|---|---|---|---|---|
| Quintiles of Kimchi intake | Quintiles of Kimchi intake | |||||||
| Q1 | Q3 | Q5 | Q1 | Q3 | Q5 | |||
| N | 525 | 526 | 524 | 808 | 805 | 808 | ||
| Parameters | ||||||||
| Body mass index | 23.4 ± 0.24) | 23.5 ± 0.2 | 24.0 ± 0.2 | 0.0358 | 22.5 ± 0.1 | 22.8 ± 0.1 | 22.9 ± 0.2 | 0.0010 |
| Waist circumference (cm) | 83.5 ± 0.2 | 83.3 ± 0.2 | 82.8 ± 0.3 | 0.0000 | 76.3 ± 0.2 | 76.3 ± 0.2 | 76.1 ± 0.2 | 0.0002 |
| Systolic blood pressure (mmHg) | 119.7 ± 0.7 | 119.4 ± 0.7 | 120.6 ± 0.8 | 0.0145 | 113.0 ± 0.5 | 113.9 ± 0.6 | 112.5 ± 0.6 | 0.0241 |
| Diastolic blood pressure (mmHg) | 78.7 ± 0.6 | 79.9 ± 0.5 | 79.6 ± 0.6 | 0.0234 | 72.5 ± 0.4 | 73.6 ± 0.4 | 73.6 ± 0.4 | 0.0039 |
| Fasting plasma glucose (mg/dl) | 95.1 ± 0.8 | 96.3 ± 0.8 | 95.2 ± 1.2 | 0.1257 | 90.4 ± 0.4 | 90.9 ± 0.4 | 91.3 ± 0.5 | 0.0122 |
| Triglyceride (mg/dl) | 141.4 ± 4.2 | 162.5 ± 6.7 | 152.5 ± 6.5 | 0.0012 | 100.5 ± 2.3 | 100.2 ± 2.4 | 103.4 ± 2.4 | 0.1294 |
| HDL-cholesterol (mg/dl) | 50.6 ± 0.6 | 49.3 ± 0.5 | 50.6 ± 0.5 | 0.3732 | 57.2 ± 0.5 | 57.4 ± 0.5 | 56.7 ± 0.5 | 0.1905 |
Values are presented as mean ± SE Q1, Q3, Q5 are the lowest, middle, and highest quintiles, respectively. 1) P for trend from GLM.
The odds ratios and 95% confidence intervals for metabolic syndrome and its components according to quintiles of total vegetable intake in Korea adults
