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Distribution and Exposure Prevalence of Carbohydrate-based Food Intake among Obese Korean Adults Based on the Health Examinees (HEXA) Study
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Research Article
Distribution and Exposure Prevalence of Carbohydrate-based Food Intake among Obese Korean Adults Based on the Health Examinees (HEXA) Study
Yuri Han, Sung-Ok Kwon, Sang-Ah Leeorcid
Korean Journal of Community Nutrition 2017;22(2):159-170.
DOI: https://doi.org/10.5720/kjcn.2017.22.2.159
Published online: April 30, 2017

Department of Preventive Medicine, Kangwon National University School of Medicine, Gangwon-do, Korea.

Corresponding author: Sang-Ah Lee. Department of Preventive Medicine, Kangwon National University School of Medicine, 1, Gangwondaehak-gil, Gangwon-do, 24341, Korea. Tel: (033) 250-8871, sangahlee@kangwon.ac.kr
• Received: April 19, 2017   • Revised: April 24, 2017   • Accepted: April 24, 2017

Copyright © 2017 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.

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  • Objectives
    The purpose of this study was to estimate the distribution and exposure prevalence of total carbohydrate intake and the carbohydrate-based foods such as rice, noodles, sweet potatoes, sweet drinks, milk and fruits and to characterize intake patterns among obese Korean adults.
  • Methods
    Subjects included 137,363 adults aged 40 years or older who participated in a Health Examinees (HEXA) Study. Multiple regression analysis of data from Semi-Quantitative Food Frequency Questionnaire (SQFFQ) identified food sources of carbohydrates. Weight, height and waist circumstance (WC) were measured, and the body mass index (BMI) was calculated. Obesity was defined as BMI ≥ 25 kg/m2 and abdominal obesity as WC ≥ 90 cm and ≥ 85 cm for males and females, respectively.
  • Results
    Obese adults appeared to have a higher total carbohydrate intake in the univariate analysis but had eaten less after adjustment for general and lifestyle factors, compared to normal weight adults (OR 0.78, 95% CI 0.73-0.82 for general obesity; OR 0.79, 95% CI 0.74-0.85, for abdominal obesity; P trend < 0.0001, respectively). Based on advance analysis for the food sources of carbohydrates, obese subjects had lower intake of rice (OR 0.86, 95% CI 0.68 -1.09 for general obesity; OR 0.87, 95% CI 0.67-1.13, for abdominal obesity; P trend < 0.0001, respectively) and higher intake of noodles (OR 1.21, 95% CI 1.16-1.27 for general obesity; OR 1.25, 95% CI 1.19-1.32, for abdominal obesity; P trend < 0.0001 respectively). With regard to other food sources of carbohydrates such as milk and fruits, intake was lower among obese compared to normal weight subjects.
  • Conclusions
    In the Korean middle-aged and older obesity groups, the intake of carbohydrates and the related foods was lower than in normal weight subjects, except for noodles. We conclude that a higher intake of noodles may enhance weight-gain. Therefore, this study suggested that the guidelines should consider the types of carbohydrate sources and the amount consumed from foods in order to provide proper guidance with regard to control and prevent obesity among Korean adults.
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Appendix 1

Contribution of specific foods for carbohydrate intake

kjcn-22-159-a001
R2 : Cumulative R2 by stepwise multiple regression
Table 1

Characteristics of the study subjects according to the quintile categories of total carbohydrate intake

kjcn-22-159-i001.jpg

P values were calculated by chi-square test

Table 2

Odds ratios and 95% confidence interval for obesity according to the distribution of total carbohydrate intake and major carbohydrate source foods

kjcn-22-159-i002.jpg

1) Obesity: BMI ≥ 25 kg/m2, Abdominal obesity: Waist Circumference M ≥ 90/F ≥ 85

2) Model 1: Crude

3) Model 2: Adjusted for age, sex, education, job, married, income

4) Model 3: Adjusted for Model 2 + drinking status, smoking status, exercise, total energy intake

Table 3

Distribution of carbohydrate source foods intake according to the noodle intake

kjcn-22-159-i003.jpg

1) Model 1: Adjusted for age, sex

2) Model 2: Adjusted for age, sex, education, job, married, income, total energy intake

Table 4

Odds ratios and 95% confidence interval of obesity according to the noodle intake in Korean adults

kjcn-22-159-i004.jpg

1) Obesity: BMI ≥ 25 kg/m2, Abdominal obesity: Waist Circumference M ≥ 90/F ≥ 85

2) The tertile for g/day for each noodle

3) Model 1: Crude

4) Model 2: Adjusted for age, sex, education, job, married, income

5) Model 3: Adjusted for Model 2 + drinking status, smoking status, exercise, total energy intake

Table 5

Odds ratios and 95% confidence interval of obesity according to the noodle intake by gender

kjcn-22-159-i005.jpg

1) Obesity: BMI ≥ 25 kg/m2, Abdominal obesity: Waist Circumference M ≥ 90/F ≥ 85

2) Model 1: Crude

3) Model 2: Adjusted for age, sex, education, job, married, income

4) Model 3: Adjusted for Model 2 + drinking status, smoking status, exercise, total energy intake

Figure & Data

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    Distribution and Exposure Prevalence of Carbohydrate-based Food Intake among Obese Korean Adults Based on the Health Examinees (HEXA) Study
    Distribution and Exposure Prevalence of Carbohydrate-based Food Intake among Obese Korean Adults Based on the Health Examinees (HEXA) Study

    Characteristics of the study subjects according to the quintile categories of total carbohydrate intake

    P values were calculated by chi-square test

    Odds ratios and 95% confidence interval for obesity according to the distribution of total carbohydrate intake and major carbohydrate source foods

    1) Obesity: BMI ≥ 25 kg/m2, Abdominal obesity: Waist Circumference M ≥ 90/F ≥ 85

    2) Model 1: Crude

    3) Model 2: Adjusted for age, sex, education, job, married, income

    4) Model 3: Adjusted for Model 2 + drinking status, smoking status, exercise, total energy intake

    Distribution of carbohydrate source foods intake according to the noodle intake

    1) Model 1: Adjusted for age, sex

    2) Model 2: Adjusted for age, sex, education, job, married, income, total energy intake

    Odds ratios and 95% confidence interval of obesity according to the noodle intake in Korean adults

    1) Obesity: BMI ≥ 25 kg/m2, Abdominal obesity: Waist Circumference M ≥ 90/F ≥ 85

    2) The tertile for g/day for each noodle

    3) Model 1: Crude

    4) Model 2: Adjusted for age, sex, education, job, married, income

    5) Model 3: Adjusted for Model 2 + drinking status, smoking status, exercise, total energy intake

    Odds ratios and 95% confidence interval of obesity according to the noodle intake by gender

    1) Obesity: BMI ≥ 25 kg/m2, Abdominal obesity: Waist Circumference M ≥ 90/F ≥ 85

    2) Model 1: Crude

    3) Model 2: Adjusted for age, sex, education, job, married, income

    4) Model 3: Adjusted for Model 2 + drinking status, smoking status, exercise, total energy intake

    Table 1 Characteristics of the study subjects according to the quintile categories of total carbohydrate intake

    P values were calculated by chi-square test

    Table 2 Odds ratios and 95% confidence interval for obesity according to the distribution of total carbohydrate intake and major carbohydrate source foods

    1) Obesity: BMI ≥ 25 kg/m2, Abdominal obesity: Waist Circumference M ≥ 90/F ≥ 85

    2) Model 1: Crude

    3) Model 2: Adjusted for age, sex, education, job, married, income

    4) Model 3: Adjusted for Model 2 + drinking status, smoking status, exercise, total energy intake

    Table 3 Distribution of carbohydrate source foods intake according to the noodle intake

    1) Model 1: Adjusted for age, sex

    2) Model 2: Adjusted for age, sex, education, job, married, income, total energy intake

    Table 4 Odds ratios and 95% confidence interval of obesity according to the noodle intake in Korean adults

    1) Obesity: BMI ≥ 25 kg/m2, Abdominal obesity: Waist Circumference M ≥ 90/F ≥ 85

    2) The tertile for g/day for each noodle

    3) Model 1: Crude

    4) Model 2: Adjusted for age, sex, education, job, married, income

    5) Model 3: Adjusted for Model 2 + drinking status, smoking status, exercise, total energy intake

    Table 5 Odds ratios and 95% confidence interval of obesity according to the noodle intake by gender

    1) Obesity: BMI ≥ 25 kg/m2, Abdominal obesity: Waist Circumference M ≥ 90/F ≥ 85

    2) Model 1: Crude

    3) Model 2: Adjusted for age, sex, education, job, married, income

    4) Model 3: Adjusted for Model 2 + drinking status, smoking status, exercise, total energy intake


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