Journal List > Korean J Nutr > v.46(1) > 1043984

Song, Paik, and Song: The relationship between intake of nutrients and food groups and insulin resistance in Korean adults: Using the Fourth Korea National Health and Nutrition Examination Survey (KNHANES IV, 2007-2009)

Abstract

The aim of this study was to examine the relationship between dietary variables and the prevalence of insulin resistance (IR) in middle-aged Korean adults using data from the 2007-2009 Korea National Health and Nutrition Examination Survey. Because IR is closely linked with metabolic syndrome, subjects were divided into three groups according to symptoms of metabolic syndrome: the 'Normal group' without any symptoms, the 'Risk group' with one or two symptoms, and the 'Metabolic syndrome (MetS) group' with three or more symptoms. Subjects between the ages of 30 and 65 years with no prior diagnosis or treatment for diabetes, hypertension, or dyslipidemia were selected. The number of subjects per group was as follows: 2,085 adults in the Normal group, 3,699 adults in the Risk group, and 1,160 adults in the MetS group. Metabolic syndrome was defined according to Adult Treatment Panel III criteria with modified waist circumference cutoff values (men ≥ 90 cm, women ≥ 85 cm). Subjects with HOMA-IR > 2.0 were classified as IR. Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) was calculated using the following formula: (fasting plasma glucose × fasting plasma insulin)/22.5. Nutrients and food groups intake were obtained from a single 24-hour recall. Subjects with IR in the Normal group were more obese and less physically active than non-IR subjects. In the MetS group, subjects with IR were more obese and had a lower prevalence of smoking and drinking, compared with non-IR subjects. Men with IR in the Normal group had a tendency to consume more oils and sugars than non-IR men, while women with IR in the same group had higher intake of carbohydrate, dietary glycemic index, and dietary glycemic load than non-IR women. Women with IR in the Risk group had lower energy intake but higher intake of oils and sugars than non-IR women. In the MetS group, consumption of fruits was higher in subjects with IR than in non-IR subjects. In conclusion, findings of this study suggest that dietary carbohydrate intake, including glycemic index, may be associated with IR in healthy women. Further research in prospective cohort studies in order to examine the effects of dietary carbohydrate on IR incidence will be necessary.

Figures and Tables

Fig. 1
Flow chart of subjects selection.
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Fig. 2
Prevalence of insulin resistance (IR) by symptoms of metabolic syndrome. 1) Insulin resistance (IR) was defined as HOMA-IR > 2.0. Homeostasis model assessment of insulin resistance (HOMA-IR), a surrogate measure of IR, was calculated by the following formula; [fasting plasma glucose (mmol/L) × fasting plasma insulin (µIU/mL)]/22.5. 2) Subjects without any symptoms of metabolic syndrome were defined as the normal group. 3) Subjects with 1 or 2 symptoms of metabolic syndrome were defined as the risk group. 4) Subjects with 3 or more symptoms of metabolic syndrome were defined as the MetS group.
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Table 1
Comparison of general characteristics between Non-IR and IR1) subjects in the normal, risk, and MetS group
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1) Insulin resistance (IR) was defined as HOMA-IR > 2.0. Homeostasis model assessment of insulin resistance (HOMAIR), a surrogate measure of IR, was calculated by the following formula; [fasting plasma glucose (mmol/L) × fasting plasma insulin (µIU/mL)]/22.5 2) Subjects without any symptoms of metabolic syndrome were defined as the normal group 3) Subjects with 1 or 2 symptoms of metabolic syndrome were defined as the risk group 4) Subjects with 3 or more symptoms of metabolic syndrome were defined as the metabolic syndrome (MetS) group 5) p-values were obtained from chi-square tests for categorical variables and from general linear model (GLM) for continuous variables after adjustment for sex (men or women), age (continuous), and BMI (continuous) 6) Current alcohol use was assigned "yes" if a subject drank a glass of alcohol or more per month over the previous year 7) Physical activity was assigned "yes" if a subject engaged in physical activity at high intensity more than 20 minutes at least 3 days or more per week over the previous week 8) Mean ± Standard error (all such values) were obtained from general linear model (GLM) after adjustment for sex (men or women), age (continuous), and BMI (continuous)

Table 2
Comparison of adjusted1) mean intake of nutrient and food groups between Non-IR and IR subjects in the normal group2) (n = 2,085)
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1) All values were adjusted for age (continuous), BMI (continuous), and energy intake (continuous) 2) Subjects without any symptoms of metabolic syndrome were defined as the normal group 3) IR was defined as HOMA-IR > 2.0. Homeostasis model assessment of insulin resistance (HOMAIR), a surrogate measure of IR, was calculated by the following formula; [fasting plasma glucose (mmol/L) × fasting plasma insulin (µIU/mL)]/22.5 4) p-values were obtained from general linear model (GLM) after adjustment for age (continuous), BMI (continuous), and energy intake (continuous) 5) Dietary glycemic index and dietary glycemic load were calculated using glucose as the reference food

Table 3
Comparison of adjusted1) mean intake of nutrient and food groups between Non-IR and IR subjects in the risk group2) (n = 3,699)
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1) All values were adjusted for age (continuous), BMI (continuous), and energy intake (continuous) 2) Subjects with 1 or 2 symptoms of metabolic syndrome were defined as the risk group 3) Insulin resistance (IR) was defined as HOMA-IR > 2.0. Homeostasis model assessment of insulin resistance (HOMAIR), a surrogate measure of IR, was calculated by the following formula; [fasting plasma glucose (mmol/L) × fasting plasma insulin (µIU/mL)]/22.5 4) p-values were obtained from general linear model (GLM) after adjustment for age (continuous), BMI (continuous), and energy intake (continuous) 5) Dietary glycemic index and dietary glycemic load were calculated using glucose as the reference food

Table 4
Comparison of adjusted1) mean intake of nutrient and food groups between Non-IR and IR subjects in the MetS group2) (n = 1,160)
kjn-46-61-i004

1) All values were adjusted for age (continuous), BMI (continuous), and energy intake (continuous) 2) Subjects with 3 or more symptoms of metabolic syndrome were defined as the MetS group 3) Insulin resistance (IR) was defined as HOMA-IR > 2.0. Homeostasis model assessment of insulin resistance (HOMAIR), a surrogate measure of IR, was calculated by the following formula; [fasting plasma glucose (mmol/L) × fasting plasma insulin (µIU/mL)]/22.5 4) p-values were obtained from general linear model (GLM) after adjustment for age (continuous), BMI (continuous), and energy intake (continuous) 5) Dietary glycemic index and dietary glycemic load were calculated using glucose as the reference food

Notes

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology (2010-0004536).

References

1. Lim S, Shin H, Song JH, Kwak SH, Kang SM, Yoon JW, Choi SH, Cho SI, Park KS, Lee HK, Jang HC, Koh KK. Increasing prevalence of metabolic syndrome in Korea: the Korean National Health and Nutrition Examination Survey for 1998-2007. Diabetes Care. 2011; 34(6):1323–1328.
2. Grundy SM. Metabolic syndrome pandemic. Arterioscler Thromb Vasc Biol. 2008; 28(4):629–636.
crossref
3. Alberti KG, Zimmet P, Shaw J. Metabolic syndrome-a new world-wide definition. A Consensus Statement from the International Diabetes Federation. Diabet Med. 2006; 23(5):469–480.
crossref
4. Reaven GM. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes. 1988; 37(12):1595–1607.
crossref
5. Grundy SM. Hypertriglyceridemia, insulin resistance, and the metabolic syndrome. Am J Cardiol. 1999; 83(9B):25F–29F.
crossref
6. Mikhail N. The metabolic syndrome: insulin resistance. Curr Hypertens Rep. 2009; 11(2):156–158.
crossref
7. Bonora E, Targher G, Alberiche M, Bonadonna RC, Saggiani F, Zenere MB, Monauni T, Muggeo M. Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care. 2000; 23(1):57–63.
crossref
8. McKeown NM, Meigs JB, Liu S, Saltzman E, Wilson PW, Jacques PF. Carbohydrate nutrition, insulin resistance, and the prevalence of the metabolic syndrome in the Framingham Offspring Cohort. Diabetes Care. 2004; 27(2):538–546.
crossref
9. Lee S, Kang ES, Lee KE, Jin H, Choi SH, Kim DJ, Ahn CW, Cha BS, Lim SK, Lee HC, Huh KB. Insulin resistance can predict the risk of metabolic syndrome. Korean J Med. 2002; 63(1):54–60.
10. Lau C, Faerch K, Glümer C, Tetens I, Pedersen O, Carstensen B, Jørgensen T, Borch-Johnsen K. Inter99 study. Dietary glycemic index, glycemic load, fiber, simple sugars, and insulin resistance: the Inter99 study. Diabetes Care. 2005; 28(6):1397–1403.
crossref
11. O'Sullivan TA, Bremner AP, O'Neill S, Lyons-Wall P. Glycaemic load is associated with insulin resistance in older Australian women. Eur J Clin Nutr. 2010; 64(1):80–87.
12. Simmons RK, Alberti KG, Gale EA, Colagiuri S, Tuomilehto J, Qiao Q, Ramachandran A, Tajima N, Brajkovich Mirchov I, Ben-Nakhi A, Reaven G, Hama Sambo B, Mendis S, Roglic G. The metabolic syndrome: useful concept or clinical tool? Report of a WHO Expert Consultation. Diabetologia. 2010; 53(4):600–605.
crossref
13. Song S, Choi H, Lee S, Park JM, Kim BR, Paik HY, Song Y. Establishing a table of glycemic index values for common Korean foods and an evaluation of the dietary glycemic index among the Korean adult population. Korean J Nutr. 2012; 45(1):80–93.
crossref
14. Du H, van der A DL, van Bakel MM, van der Kallen CJ, Blaak EE, van Greevenbroek MM, Jansen EH, Nijpels G, Stehouwer CD, Dekker JM, Feskens EJ. Glycemic index and glycemic load in relation to food and nutrient intake and metabolic risk factors in a Dutch population. Am J Clin Nutr. 2008; 87(3):655–661.
crossref
15. Murakami K, Sasaki S, Takahashi Y, Okubo H, Hirota N, Notsu A, Fukui M, Date C. Reproducibility and relative validity of dietary glycaemic index and load assessed with a self-administered diet-history questionnaire in Japanese adults. Br J Nutr. 2008; 99(3):639–648.
crossref
16. The Korean Nutrition Society. Dietary reference intakes for Koreans. 2010. 1st revision. Seoul: The Korean Nutrition Society.
17. The Rural Development Administration. Food nutrient data by portions commonly used. 2009. 1st revision. Suwon: The Rural Development Administration.
18. The Korean Dietetic Association. Samsung Medical Center. Food photo of the eye-to-weight. 1999. Seoul: The Korean Dietetic Association.
19. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985; 28(7):412–419.
crossref
20. Schwimmer JB, Deutsch R, Rauch JB, Behling C, Newbury R, Lavine JE. Obesity, insulin resistance, and other clinicopathological correlates of pediatric nonalcoholic fatty liver disease. J Pediatr. 2003; 143(4):500–505.
crossref
21. Eslam M, Aparcero R, Kawaguchi T, Del Campo JA, Sata M, Khattab MA, Romero-Gomez M. Meta-analysis: insulin resistance and sustained virological response in hepatitis C. Aliment Pharmacol Ther. 2011; 34(3):297–305.
crossref
22. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC Jr, Spertus JA, Costa F. American Heart Association. National Heart, Lung, and Blood Institute. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005; 112(17):2735–2752.
23. Lee SY, Park HS, Kim DJ, Han JH, Kim SM, Cho GJ, Kim DY, Kwon HS, Kim SR, Lee CB, Oh SJ, Park CY, Yoo HJ. Appropriate waist circumference cutoff points for central obesity in Korean adults. Diabetes Res Clin Pract. 2007; 75(1):72–80.
crossref
24. McAuley KA, Williams SM, Mann JI, Goulding A, Chisholm A, Wilson N, Story G, McLay RT, Harper MJ, Jones IE. Intensive lifestyle changes are necessary to improve insulin sensitivity: a randomized controlled trial. Diabetes Care. 2002; 25(3):445–452.
crossref
25. Meigs JB, D'Agostino RB Sr, Wilson PW, Cupples LA, Nathan DM, Singer DE. Risk variable clustering in the insulin resistance syndrome. The Framingham Offspring Study. Diabetes. 1997; 46(10):1594–1600.
crossref
26. Miyatake N, Nishikawa H, Morishita A, Kunitomi M, Wada J, Suzuki H, Takahashi K, Makino H, Kira S, Fujii M. Daily walking reduces visceral adipose tissue areas and improves insulin resistance in Japanese obese subjects. Diabetes Res Clin Pract. 2002; 58(2):101–107.
crossref
27. Park HS, Oh SW, Cho SI, Choi WH, Kim YS. The metabolic syndrome and associated lifestyle factors among South Korean adults. Int J Epidemiol. 2004; 33(2):328–336.
crossref
28. Reaven GM. Diet and syndrome X. Curr Atheroscler Rep. 2000; 2(6):503–507.
crossref
29. Murakami K, Sasaki S, Takahashi Y, Okubo H, Hosoi Y, Horiguchi H, Oguma E, Kayama F. Dietary glycemic index and load in relation to metabolic risk factors in Japanese female farmers with traditional dietary habits. Am J Clin Nutr. 2006; 83(5):1161–1169.
crossref
30. Kim K, Yun SH, Choi BY, Kim MK. Cross-sectional relationship between dietary carbohydrate, glycaemic index, glycaemic load and risk of the metabolic syndrome in a Korean population. Br J Nutr. 2008; 100(3):576–584.
crossref
31. Levitan EB, Cook NR, Stampfer MJ, Ridker PM, Rexrode KM, Buring JE, Manson JE, Liu S. Dietary glycemic index, dietary glycemic load, blood lipids, and C-reactive protein. Metabolism. 2008; 57(3):437–443.
crossref
32. Finley CE, Barlow CE, Halton TL, Haskell WL. Glycemic index, glycemic load, and prevalence of the metabolic syndrome in the Cooper Center Longitudinal Study. J Am Diet Assoc. 2010; 110(12):1820–1829.
crossref
33. Choi H, Song S, Kim J, Chung J, Yoon J, Paik HY, Song Y. High carbohydrate intake was inversely associated with high-density lipoprotein cholesterol among Korean adults. Nutr Res. 2012; 32(2):100–106.
crossref
34. Park SH, Lee KS, Park HY. Dietary carbohydrate intake is associated with cardiovascular disease risk in Korean: analysis of the third Korea National Health and Nutrition Examination Survey (KNHANES III). Int J Cardiol. 2010; 139(3):234–240.
crossref
35. Yoo S, Nicklas T, Baranowski T, Zakeri IF, Yang SJ, Srinivasan SR, Berenson GS. Comparison of dietary intakes associated with metabolic syndrome risk factors in young adults: the Bogalusa Heart Study. Am J Clin Nutr. 2004; 80(4):841–848.
crossref
36. Lutsey PL, Steffen LM, Stevens J. Dietary intake and the development of the metabolic syndrome: the Atherosclerosis Risk in Communities study. Circulation. 2008; 117(6):754–761.
crossref
37. Shin A, Lim SY, Sung J, Shin HR, Kim J. Dietary intake, eating habits, and metabolic syndrome in Korean men. J Am Diet Assoc. 2009; 109(4):633–640.
crossref
38. Jung HJ, Han SN, Song S, Paik HY, Baik HW, Joung H. Association between adherence to the Korean Food Guidance System and the risk of metabolic abnormalities in Koreans. Nutr Res Pract. 2011; 5(6):560–568.
crossref
39. Cheung BM. The cardiovascular continuum in Asia-a new paradigm for the metabolic syndrome. J Cardiovasc Pharmacol. 2005; 46(2):125–129.
crossref
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