1.Carbohydrate Composition Associated with the 2-Year Incidence of Metabolic Syndrome in Korean Adults.
Nam H CHO ; Ara K CHO ; Hyun Kyu KIM ; Jong Bae KIM ; Kyung Eun LEE ; Sung Soo KIM ; Yeon Jung KIM ; Hak C JANG ; Inkyung BAIK
Clinical Nutrition Research 2017;6(2):122-129
The aim of this study was to investigate the association between macronutrient composition and metabolic syndrome (MetS) incidence in Korean adults. Data were obtained from a cohort of 10,030 members aged 40 to 69 years who were enrolled from the 2 cities (Ansung and Ansan) between 2001 and 2002 to participate in the Korean Genome Epidemiology Study. Of these members, 5,565 participants, who were free of MetS and reported no diagnosis of cardiovascular disease at baseline, were included in this study. MetS was defined using the criteria of the National Cholesterol Education Program-Adult Treatment Panel III and Asia-Pacific criteria for waist circumference. MetS incidence rate were identified during a 2-year follow-up period. Baseline dietary information was obtained using a semi-quantitative food frequency questionnaire. Multivariate logistic regression analysis was used to evaluate the association between the quartiles of percentages of total calorie from macronutrients consumed and MetS incidence. In analyses, baseline information, including age, sex, body mass index, income status, educational status, smoking status, alcohol drinking status, and physical activity level was considered as confounding variables. Participants with the second quartile of the percentages of carbohydrate calorie (67%–70%) had a 23% reduced odds ratio (95% confidence interval, 0.61–0.97) for MetS incidence compared with those with the fourth quartile after adjusting for confounding variables. The findings suggest that middle aged or elderly Korean adults who consume approximately 67%–70% of calorie from carbohydrate have a reduced risk of MetS.
Adult*
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Aged
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Alcohol Drinking
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Body Mass Index
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Cardiovascular Diseases
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Cholesterol
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Cohort Studies
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Confounding Factors (Epidemiology)
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Diagnosis
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Education
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Educational Status
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Epidemiology
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Follow-Up Studies
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Genome
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Humans
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Incidence*
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Logistic Models
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Middle Aged
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Motor Activity
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Odds Ratio
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Smoke
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Smoking
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Waist Circumference