Journal List > J Nutr Health > v.48(1) > 1081417

Jang, Suh, and Chung: Metabolic risk and nutritional state according to breakfast energy level of Korean adults: Using the 2007~2009 Korea National Health and Nutrition Examination Survey

Abstract

Purpose

The aim of this study was to determine an appropriate energy level of breakfast with less risk of chronic disease for Korean adults.

Methods

Using data from the 2007~2009 Korean National Health & Nutrition Examination Survey, from a total of 12,238 adults aged 19~64, the final 7,769 subjects were analyzed except subjects who were undergoing treatment for cancer or metabolic disorder. According to the percent of breakfast energy intake versus their estimated energy requirement (EER), the subjects were divided into four groups: < 10% (very low, VL), 10~20% (low, L), 20~30% (moderate, M), ≥ 30% (sufficient, S). All data were analyzed on the metabolic risk and nutritional state after application of weighted value and adjustment of sex, age, residential area, income, education, job or jobless, and energy intake using a general linear model or logistic regression.

Results

The subjects of group S were 16.9% of total subjects, group M 39.2%, group L 37.6%, and group VL 6.3%. The VL group included more male subjects, younger-aged (19 to 40 years), urban residents, higher income, higher education, and fewer breakfasts eaters together with family members. Among the 4 groups, the VL group showed the highest waist circumference, while the S group showed the lowest waist circumference, body mass index, and serum total cholesterol. The groups of VL and L with lower intake of breakfast energy showed high percent of energy from protein and fat, and low percent of energy from carbohydrate. With the increase of breakfast energy level, intake of energy, most nutrients and food groups increased, and the percentage of subjects consuming nutrients below EAR decreased. The VL group showed relatively higher intake of snacks, sugar, meat and eggs, oil, and seasonings, and the lowest intake of vegetable. Risk of obesity by waist circumference was highest in the VL group by 1.90 times of the S group and the same trend was shown in obesity by BMI. Risk of dyslipidemia by serum total cholesterol was 1.84 times higher in the VL group compared to the S group. Risk of diabetes by Glu-FBS (fasting blood sugar) was 1.57 times higher in the VL group compared to the S group.

Conclusion

The results indicate that higher breakfast energy level is positively related to lower metabolic risk and more desirable nutritional state in Korean adults. Therefore, breakfast energy intake more than 30% of their own EER would be highly recommended for Korean adults.

Figures and Tables

Fig. 1

Distribution of the subjects consuming the nutrient less than Estimated Average Requirement (EAR) from daily diet by breakfast energy level in the subjects1)

1) Adjusted for sex, age, residential area, income, education level, energy intake, and job 2) V: very low <10%, L: low, 0~20%, M: moderate 20~30%, S: sufficient = 30% of breakfast energy intake vs their own EER 3) Calculated by Complex Samples χ2-test
***: p < 0.001
jnh-48-46-g001
Table 1

General characteristics by breakfast energy level in the subjects

jnh-48-46-i001

1) V: very low <10%, L: low, 0~20%, M: moderate 20~30%, S: sufficient = 30% of breakfast energy intake vs their own EER 2) Calculated by Complex Samples χ2-test 3) N (%)

Table 2

Lifestyle characteristics by breakfast energy level in the subjects

jnh-48-46-i002

1) V: very low <10%, L: low, 0~20%, M: moderate 20~30%, S: sufficient = 30% of breakfast energy intake vs their own EER 2) Calculated by Complex Samples χ2-test 3) N (%) 4) Metabolic Equivalent of Task, the intensity of activities

Table 3

Anthropometric, blood pressure, and blood biochemical indices by breakfast energy level in the subjects1)

jnh-48-46-i003

1) Adjusted for sex, age, residential area, income, education level, and job 2) V: very low <10%, L: low, 0~20%, M: moderate 20~30%, S: sufficient = 30% of breakfast energy intake vs their own EER 3) Calculated by Complex Samples General Linear Model ANOVA 4) Mean ± SE

Table 4

Daily food group intake by breakfast energy level in the subjects1) (unit: g)

jnh-48-46-i004

1) Adjusted for sex, age, residential area, income, education level, and job 2) V: very low <10%, L: low, 0~20%, M: moderate 20~30%, S: sufficient = 30% of breakfast energy intake vs their own EER 3) Calculated by Complex Samples General Linear Model ANOVA 4) Mean ± SE

Table 5

Daily mean nutrients intake by breakfast energy level in the subjects1)

jnh-48-46-i005

1) Adjusted for sex, age, residential area, income, education level, energy intake, and job 2) V: very low <10%, L: low, 0~20%, M: moderate 20~30%, S: sufficient = 30% of breakfast energy intake vs their own EER 3) Calculated by Complex Samples General Linear Model ANOVA 4) Mean ± SE

†: Not adjusted for energy intake

Table 6

Nutrient adequacy ratio (NAR) and mean adequacy ratio (MAR) by breakfast energy level in the subjects1)

jnh-48-46-i006

1) Adjusted for sex, age, residential area, income, education level, and job 2) V: very low <10%, L: low, 0~20%, M: moderate 20~30%, S: sufficient = 30% of breakfast energy intake vs their own EER 3) Calculated by Complex Samples General Linear Model ANOVA 4) Mean ± SE

Table 7

Odds ratios for chronic disease by breakfast energy level in the subjects

jnh-48-46-i007

1) V: very low <10%, L: low, 0~20%, M: moderate 20~30%, S: sufficient = 30% of breakfast energy intake vs their own EER 2) OR1: Odds ratios calculated by Complex Samples Logistic Regression after adjusted for sex, age, residential area, income, education level, and job 3) OR2: Odds ratios adjusted for energy intake in addition to the above

†: Odds ratios (95% CI) based on the risk of S group

*: p < 0.05, **: p < 0.01, ***: p < 0.001

Notes

This work was supported by academic research fund of Chungnam National University.

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