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Kim, Jun, Hong, and Joung: Estimated macronutrients and antioxidant vitamins intake according to Hansik consumption rate among Korean adults: Based on the Korea National Health and Nutrition Examination Survey 2007~2012
Research Article

Journal of Nutrition and Health 2016; 49(5): 323-334.

Published online: 31 October 2016

DOI: https://doi.org/10.4163/jnh.2016.49.5.323

Estimated macronutrients and antioxidant vitamins intake according to Hansik consumption rate among Korean adults: Based on the Korea National Health and Nutrition Examination Survey 2007~2012

Seong-Ah Kim1, Shinyoung Jun2, Eunju Hong3, Hyojee Joung1, 2

1Department of Public Health, Graduate School of Public Health, Seoul National University, Seoul 08826, Korea.

2Institute of Health and Environment, Seoul National University, Seoul 08826, Korea.

3Department of Economics and Finance, Hanyang Cyber University, Seoul 04763, Korea.

To whom correspondence should be addressed. tel: +82-2-880-2781, hjjoung@snu.ac.kr

Received 26 August 2016       Revised 2 September 2016       Accepted 19 September 2016

© 2016 The Korean Nutrition Society

(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

Purpose

The purpose of this study was to estimate intakes of macronutrients and antioxidant vitamins according to the Hansik consumption rate among Korean adults.

Methods

Using data from the 2007~2012 Korea National Health and Nutrition Examination Survey, a total of 33,069 subjects aged over 19 years old were included in this study. We estimated individual daily Hansik consumption rates and intakes of macronutrients and antioxidant vitamins, including vitamin A and its subgroup such as retinol, α-carotene, β-carotene, and β-cryptoxanthin, vitamin C, and vitamin E, by linking food consumption data with the nutrient and antioxidant vitamin database of commonly consumed foods.

Results

Around 75% of subjects consumed Hansik in over 75% of their daily total consumed food. The most frequently consumed Hansik was cabbage kimchi (1.57 times/day), followed by multigrain rice (0.86 times/day) and white rice (0.80 times/day). The household income level and education level was inversely associated with the Hansik consumption rate. There was a positive relationship between Hansik consumption rate and vitamin A, β-carotene, β-cryptoxanthin, and vitamin C intakes. On the other hand, Hansik consumption rate was inversely associated with energy and fat intake.

Conclusion

The results of this study suggest that Hansik consumption could provide more antioxidant vitamins and less energy and fat. Thus, further research will be needed to analyze the association between Hansik and health effects.

Keywords: Hansik, nutrients intake, antioxidant vitamins, KNHANES

Figures and Tables

Table 1

Most frequently consumed Hansik foods and non-Hansik foods of the study population

jnh-49-323-i001

1) Intake rate was the proportion of subjects who consumed the food more than once a day.

*All analysis accounted for the complex sampling design and appropriate sampling weights of the national survey.

Table 2

General characteristics of the study population according to the Hansik consumption rate

jnh-49-323-i002

1) Number of missing values was 670, 2,613, and 2,113 for household income, education level, and BMI. 2) Household income level was divided equally among household income quartile groups based on the average monthly equalized household income (monthly household income/N of the household memberjnh-49-323-i008) according to the sex and age group. 3) P-values were from chi-square test for categorical variables and proc surveyreg for continuous variables. 4) 'Underweight' meant BMI (body mass index) < 18.5 kg/m2, 'Normal' meant 18.5 kg/m2 ≤ BMI < 23 kg/m2, 'Overweight' meant 23 kg/m2 ≤ BMI < 25 kg/m2, and 'Obese' meant BMI ≥ 25 kg/m2.22

*All analysis accounted for the complex sampling design and appropriate sampling weights of the national survey.

Table 3

Nutrients intake according to the Hansik consumption rate

jnh-49-323-i003

1) Values are mean ± SE. 2) P-values were adjusted for sex, age and household income. 3) P-values were from generalized linear model analysis.

*All nutrients were adjusted for total energy intakes except for carbohydrate, protein, and fat.

*All analysis accounted for the complex sampling design and appropriate sampling weights of the national survey.

Table 4

Nutrients intake of Q1 versus Q4 of Hansik consumption rate by sex

jnh-49-323-i004

1) Values are mean ± SE. 2) P-values were adjusted for age and household income. 3) P-values were from t-test.

*All analysis accounted for the complex sampling design and appropriate sampling weights of the national survey.

Table 5

Nutrients intake of Q1 versus Q4 of Hansik consumption rate by age group

jnh-49-323-i005

1) Values are mean ± SE. 2) P-values were adjusted for sex and household income. 3) P-values were from t-test.

*All analysis accounted for the complex sampling design and appropriate sampling weights of the national survey.

Table 6

Nutrients intake of Q1 versus Q4 of Hansik consumption rate by household income level

jnh-49-323-i006

1) Values are mean ± SE. 2) Household income level was divided equally among household income quartile groups based on the average monthly equalized household income (monthly household income/N of the household memberjnh-49-323-i008) according to the sex and age group. 3) P-values were adjusted for sex and age. 4) P-values were from t-test.

*All analysis accounted for the complex sampling design and appropriate sampling weights of the national survey.

Table 7

Food group intake according to the Hansik consumption rate

jnh-49-323-i007

1) Values are mean ± SE. 2) P-values were adjusted for sex, age, and household income. 3) P-values were from generalized linear model analysis.

*All analysis accounted for the complex sampling design and appropriate sampling weights of the national survey.

Notes

This work was carried out with the support of 'Research Program for Agricultural Science and Technology Development', National Academy of Agricultural Science, Rural Development Administration (Project No. PJ011637022016).

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