• Korean Journal of Community Nutrition
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• v.18 no.1
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• pp.77-87
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• 2013

This study was conducted to investigate the nutrient intakes of subjects by quartile of percent energy intake from cooked rice, consumption of cooked rice mixed with multi-grains and to evaluate rice consumption in relation to the risk of metabolic syndrome. The subjects were 5,830 males and females aged between 20~64 years based on 2007-2008 KNHNES data. Levels of percent energy intake from cooked rice were classified into 4 groups (Q1, Q2, Q3, Q4 groups: 25% of each) using data of 24-hour recall method from KNHNES. Using medical examination and questionnaire, subjects were classified according to diagnostic criteria of metabolic syndrome. The subjects with higher age, being married, lower education, lower economic level were more likely to take higher percent energy intake from cooked rice. Quartile Q3 of percent energy intake from cooked rice tended to show higher Index of Nutritional Quality (INQ) for fiber, calcium, iron, potassium and vitamin A. INQ of protein, dietary fiber, calcium, thiamin, phosphorus, potassium, riboflavin, niacin and vitamin C by consumption of cooked rice mixed with multi-grains was higher than that by consumption of cooked white rice when adjusted for age. No association with a risk for metabolic syndrome was found for quartile of percent energy intake from cooked rice or cooked rice mixed with multi-grains compared to cooked white rice after adjusting for energy, gender, age, BMI, alcohol, smoking, income and physical activity. In conclusion, consumption of over 54% energy intake from cooked rice or only cooked white rice showed relatively low INQs, but was not associated with a higher risk for metabolic syndrome.

• Korean Journal of Community Nutrition
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• v.27 no.3
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• pp.245-253
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• 2022

Objectives: This study was conducted to find out if the dietary iron intake of Koreans estimated by 2 different methods (iron content sources) using the food intake data from the Korea National Health and Nutrition Examination Survey (KNHANES) are comparable. One method was based on the KNHANES's Food & Nutrient Database (FND) derived mainly from the Korean Food Composition Table and the other used the iron content (IC) of food samples processed in the Korean Total Diet Study (KTDS). Methods: Dietary intake data from the 2013-2016 KNHANES was used to select representative foods (RFs) in KTDS for iron analysis. Selection of the RFs and cooking methods for each RF (RF × cooking method pair) was performed according to the 'Guidebook for Korean Total Diet Studies' and resulted in a total of 132 RFs and 224 'RF × cooking method' pairs. RFs were collected in 9 metropolitan cities nationwide once or twice (for those with seasonality) in 2018 and made into 6 composites each, based on the origin and season prior to cooking. Then, the RF composites prepared to a 'table ready' state for KTDS were analyzed by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Dietary iron intake of the Korean population was estimated using only RFs' intake data based on the 2 sources of iron content, namely FND-KNHANES and IC-KTDS. Results: RFs in KTDS covered 92.0% of total food intake of Koreans in the 2016-2018 KNHANES. Mean iron intake of Koreans was 7.77 mg/person/day by IC-KTDS vs 9.73 mg/person/day by FND-KNHANES. The major food groups contributing to iron intake were meats (21.7%), vegetables (20.5%), and grains & cereals (13.4%) as per IC-KTDS. On the other hand, the latter source (FND-KNHANES) resulted in a very different profile: grains & cereals (31.1%), vegetables (16.8%), and meats (15.3%). While the top iron source was beef, accounting for 8.6% in the former, it was polished rice (19.2%) in the latter. There was a 10-fold difference in the iron content of polished rice between 2 sources that iron intakes excluding the contribution by polished rice resulted in very similar values: 7.58 mg/person/day by IC-KTDS and 7.86 mg/person/day by FND-KNHANES. Conclusions: This study revealed that the dietary iron intake estimated by 2 different methods were quite comparable, excluding one RF, namely polished rice. KTDS was thus proven to be a useful tool in estimating a 'closer-to-real' dietary intake of nutrients for Koreans and further research on various nutrients is warranted.

• Journal of Nutrition and Health
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• v.50 no.1
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• pp.74-84
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• 2017

Purpose: In this study, factors of metabolic syndrome and nutritional status were examined according to gender and occupations using the 2013 Korea National Health and Nutrition Examination Survey (KNHANES). Methods: This study was conducted on 1,750 workers (male : 892, female : 858) aged between 30 and 64, who participated in a health survey, health examination, and nutrition survey using the 6th 2013 KNHANES. Occupations were classified into white collar and blue collar workers, and nutrient intake was analyzed using a food frequency questionnaire. Analysis of complex sample design data through SPSS 19.0 was used for analysis. Results: The prevalence rate of metabolic syndrome among blue collar (35.1%) was higher than that among white collar workers (26.8%) in male subjects (p < 0.05) as well as in blue collar (24.8%) compared to white collar workers (8.9%) in female subjects (p < 0.001). Intake frequency per week, considering one portion by food category, showed significant differences in cooked rice (p < 0.05) and bakeries and confectioneries (p < 0.05) in make workers as well as stew and casserole (p < 0.01) and fruits (p < 0.05) in female workers. With regard to nutrient intake by occupation and gender, white collar workers consumed a greater amount of nutrients (not including total energy intake) compared to blue collar workers in both male and female workers. With regard to nutrient adequacy ratio (NAR) and mean adequacy ratio (MAR) according to gender and occupation, white collar workers showed higher numbers than blue collar workers in both male and female subjects. Conclusions: This study examined the prevalence rates of metabolic syndrome and nutrient intake according to gender and occupation. In both male and female subjects, blue collar workers showed higher prevalence rates compared to white collar workers, and their diet quality was worse than white collar workers' diet quality. Considering this result, customized nutrition education according to gender and occupation should be provided to workers to prevent diseases.