Clinica Chimica Acta 439 (2015) 225–230
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Association between flavonoid intake and diabetes risk among the Koreans Jee-Young Yeon a, Yun Jung Bae b, Eun-Young Kim c, Eun-Ju Lee d,⁎ a
Nutrition Safety Policy Division, Food Nutrition and Dietary Safety Bureau, Ministry of Food and Drug Safety, Cheongju, 361-951, Republic of Korea Food and Nutrition Major, Division of Food Science and Culinary Arts, Shinhan University, Dongducheon 480-777, Republic of Korea Department of Food and Nutrition, Sookmyung Women's University, Seoul, Republic of Korea d Asan Institute for Life Sciences, Asan Medical Center, Seoul 138-736, Republic of Korea b c
a r t i c l e
i n f o
Article history: Received 8 April 2014 Received in revised form 27 October 2014 Accepted 29 October 2014 Available online 4 November 2014 Keywords: Type 2 diabetes mellitus Flavonoid Impaired fasting glucose Insulin KNHANES
a b s t r a c t Background: We investigated the association between flavonoid intake and type 2 diabetes mellitus (T2DM) risk factors including serum fasting glucose, insulin level, and insulin resistance. Methods: A total of 4186 participants who were involved in the 2007–2009 Korean National Health and Nutrition Examination Survey were examined. The participants were divided into 2 groups by fasting plasma glucose (FPG) as follows: normal fasting glucose (NFG; FPG b 100 mg/dl) and impaired fasting glucose (IFG) groups (FPG ≥100 mg/dl). Results: In the IFG group, body weight, body mass index, and waist circumference were increased. Fasting insulin level and homeostasis model assessment estimate of insulin resistance as markers of insulin resistance were higher in the IFG group. Intakes of energy and nutrients, including protein, fat, carbohydrate, crude fiber, vitamin C, calcium, phosphorus, and iron, did not differ between the 2 groups. For the male subjects, the energy-adjusted flavanone intake was lower in the IFG group than in the NFG group. Insulin and insulin resistance were inversely correlated with intakes of flavones and flavonols among the male subjects. Conclusion: These findings can provide valuable information for further development of appropriate strategies for diabetes prevention in Korea. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Impaired glucose homeostasis has been described to precede a diabetes mellitus (DM) diagnosis and is known as a prediabetes state comprising 2 subcategories, namely impaired fasting glucose (IFG) and impaired glucose tolerance, classified on the basis of glucose levels at fasting and after a glucose challenge (oral glucose tolerance test). Both conditions are associated with increased risk for DM. Consumption of fruits and vegetables is associated with lowered risk for major chronic diseases including diabetes, cardiovascular diseases and cancer [1]. These plant foods are the main sources of flavonoids. Flavonoids have 2 aromatic rings that are bound by an oxygenated heterocyclic ring. On the basis of their chemical structure, they are divided into several subclasses as follows: flavones, flavonols, flavanones, flavan-3-ols, and anthocyanins, among which flavones and flavonols are Abbreviations: IFG, impaired fasting glucose; FPG, fasting plasma glucose; HOMA-IR, Homeostasis model assessment estimate of insulin resistance; KNHANES, Korea National Health and Nutrition Examination Survey; NFG, normal fasting glucose; PPARγ, peroxisome proliferator-activated receptor γ; T2DM, type 2 diabetes mellitus; WC, waist circumference. ⁎ Corresponding author at: Asan Institute for Life Science, 88 Olympicro 43 gil, Songpa-gu, Seoul 138-736, Republic of Korea. Tel.: +82 2 3010 4677. E-mail address: [email protected] (E.-J. Lee).
http://dx.doi.org/10.1016/j.cca.2014.10.042 0009-8981/© 2014 Elsevier B.V. All rights reserved.
found in leafy vegetables and flavanones are mainly found in citrus fruits. Several studies reported that the total flavonoid intake in Western countries was estimated to be 1–200 mg/d [2,3]. Flavonoids has been established as possessing anti-inflammatory, antioxidative, and chemopreventive activities, which contribute to the health protective properties of plant foods. In vitro and in vivo studies observed that oxidative stress generation impaired pancreatic β-cell insulin secretion [4–6] and interfered with the insulin signaling pathway, thereby accelerating the progression to obvious type 2 DM (T2DM) from insulin resistance [7,8]. Intake of flavonoids, which are capable of scavenging free radicals and chelating deleterious oxidant-inducing metals such as iron and copper, has been associated with a reduced risk of cardiovascular disease and cancer [9–12]. Furthermore, accumulating evidence indicates that flavonoids influence glucose metabolism. In addition, results from mechanistic studies suggest that flavonoids may decrease glycemia and improve insulin secretion and sensitivity [13]. Nevertheless, the relevance of dietary flavonoids to insulin resistance or diabetic risk is less well studied and in epidemiological studies, very few of the individual polyphenolic compounds alone have been so far demonstrated to have a beneficial effect on T2DM. Few studies have evaluated dietary intakes of major flavonoid subclasses that are commonly consumed in the Korea diet in relation to
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the risk for T2DM. Therefore, we estimated the intake of individual flavonoids, including flavanones, flavonols, and flavones, in a cross-sectional study and the association between intakes of these flavonoids and T2DM risk factors, including serum fasting glucose level, insulin, and insulin resistance. 2. Subjects and methods 2.1. Study population We used data from the Fourth Korea National Health and Nutrition Examination Survey (KNHANES IV-3, 2007–2009), which was conducted by the Korea Centers for Disease Control and Prevention. KNHANES is a series of surveys designed to assess the health and nutritional status of the Korean population. The KNHANES began in 1998 and then was subsequently conducted in 2001 and 2005. Since 2007, the KNHANES has been conducted annually. The KNHANES consists of a health interview, health examination (physical examination, clinical measurements, and tests), and dietary interview. The subjects of the KNHANES were aged ≥ 1 y and selected from stratified multistage samples of the South Korean population from multiple geographic areas and ages of both sexes. A total of 8631 people participated in the 2010 KNHANES. Among them, 4186 persons aged 40–59 y were included as participants in this study. We chose subjects who had energy intakes ≥ 500 kcal b5000 kcal and had no missing data. The participants were divided into 2 groups according to fasting plasma glucose (FPG) as follows: normal fasting glucose (NFG; FPG level, b 100 mg/dl) and IFG; FPG level, 100–125 mg/dl). The 2011 clinical practice guidelines for T2DM in Korea recommend different screening methods according to IFG stage (stage 1, FPG level of 100–109 mg/dl, stage 2, FPG level of 110–125) [14]. Considering that the dataset did not include any personal information and participant consent was already taken obtained in the process of the KNHANES, this study was exempted from obtaining participant consent by the board. 2.2. Health examination survey and laboratory test Height and weight were measured to the nearest 0.1 cm and 0.1 kg, respectively. Body mass index (BMI) was calculated by dividing weight by height (kg/m2). FPG level was measured by the enzymatic method using the Hitachi automatic Analyzer 7600 (Hitachi, Japan) and fasting insulin level was determined by immunoradiometric assay using the 1470 Wizard Gamma Counter (PerkinElmer, Finland). Homeostasis model assessment estimate of insulin resistance (HOMAIR), a marker of insulin resistance, was calculated as follows: FPG level (in mg/dl) × fasting insulin level (in μU/dl)/22.5 [15]. 2.3. Dietary assessment and flavonoid intakes A single 24-h dietary recall was collected from each respondent through inperson interviews. We did not exclude any certain days such as holidays or weekends. To enhance recall, supplementary tools such as food models and two-dimensional food volumes and containers were used to assist the respondent's report of the volumes of the food items consumed. Recipes for all food items consumed were also collected. Based on the recipes collected from each household during the interview, the weight of each ingredient was estimated from the volume of food ingested. Nutrient intake from diet was estimated by combining the US Department of Agriculture Flavonoid databases (http://www.ars.usda.gov/Services/docs.htm?docid=6231) and 24-h dietary recall in the KNHANES IV-3 (2007–2009). In addition, we derived intakes of the 3 main flavonoid subclasses commonly consumed in the Korean diet, specifically flavanones (eriodictyol, hesperetin, and naringenin), flavonols (quercetin, kaempherol, and myricetin), and flavones (luteolin and apigenin).
2.4. Statistical analyses All statistical analyses were performed using the SAS software (version 9.2 SAS Institute Inc., Cary, NC, USA). Data were expressed as mean ± SE. SURVEYREG tests were used to evaluate the significance difference between the healthy and IFG groups. In addition, a multiple regression analysis was performed to determine the relationship between flavonoid intake and biochemical parameters by adjusting for various confounders including energy intake, age, BMI, WC, smoking, physical activity, and alcohol consumption. Five different models were used to examine the association between flavonoids intake and FPG level, insulin level, and HOMA-IR. A P b 0.05 was considered to be statistically significant. 3. Results 3.1. General characteristics and blood biochemistry The general characteristics of the subjects are presented in Table 1. Data for a total of 4186 participants (1611 men and 2575 women) were analyzed. The numbers of subjects with NFG and IFG levels was 3132 and 1054, respectively. Among the 1611 male subjects, 1088 had NFG levels and 523 had IFG levels. Among the women, 2044 had NFG levels and 531 had IFG levels. Men made up 32.5% of the total subjects, and women, 20.6%. The mean age, weight, BMI, and waist circumference (WC) in the IFG group were higher than those in the control group, both among the male and female subjects. Fasting insulin and HOMA-IR were also more elevated in the IFG group. 3.2. Intakes of nutrient and flavonoids Intakes of energy and nutrients, including protein, fat, carbohydrate, crude fiber, vitamin C, calcium, phosphorus, and iron, were not different between the 2 groups (Table 2). Intakes of flavonoid subclasses by sex according to FPG level are shown in Table 3. The intakes of flavanones, flavones, and flavonols were higher in the women than in the men. Energy-adjusted flavanone intake was lower among the male subjects in the NFG group. Intakes of eriodictyol and hesperetin, not naringenin, in the IFG group were statistically lower than in the NFG group. No significant association was found between intakes of flavones and flavonols, and the risk for IFG in the male subjects. 3.3. Multiple regression analysis of the relationship between flavonoid intake and biochemical parameters The associations between the intakes of flavonoid subclasses, and glucose, insulin, and HOMA-IR are presented according to sex in Table 4. We observed significant heterogeneity in the results by sex. Inverse associations with insulin and HOMA-IR were observed for flavones and flavonols in men (P-trend, 0.05 for all). In the female subjects, flavanones were inversely related to risk for IFG and after adjustment for other variables including BMI and WC using multiple regression analysis, flavanone intakes were independently associated with insulin and HOMA in women. Moreover, the inverse association between insulin and flavanone intakes became stronger with adjustment for BMI and WC. 4. Discussion IFG is a well-known risk factor for T2DM. Weight gain has been reported to decrease response to insulin and is associated with an increased risk of developing diabetes, suggesting that the association between obesity and diabetes is indisputable. A study based on the general Korean population reported that degree of BMI was increased with FPG levels b100 mg/dl, peaked with FPG levels of 100–109 mg/dl, and then plateaued with higher FPG levels [16]. The mean FPG levels in
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Table 1 Anthropometric measurements and blood biomarkers of subjects. Men
Age (y) Height (cm) Weight (kg) BMI (kg/m2) WC (cm) Insulin (μIU/ml) Glucose (mg/dl) HOMA-IR
Women
Total (n = 1611)
NFG (n = 1088)
IFG (n = 523)
p
Total (n = 2575)
NFG (n = 2044)
IFG (n = 531)
p
48.86 ± 0.15a 168.90 ± 0.18 69.07 ± 0.28 24.18 ± 0.08 84.90 ± 0.25 9.52 ± 0.17 95.80 ± 0.30 2.28 ± 0.04
48.63 ± 0.18 168.86 ± 0.24 68.07 ± 0.33 23.85 ± 0.10 83.91 ± 0.29 8.83 ± 0.16 90.38 ± 0.22 1.98 ± 0.04
49.37 ± 0.27 169.00 ± 0.30 71.28 ± 0.49 24.93 ± 0.15 87.08 ± 0.40 11.04 ± 0.36 107.89 ± 0.34 2.95 ± 0.10
0.025 NS b.0001 b.0001 b.0001 b.0001 b.0001 b.0001
49.01 ± 0.14 156.54 ± 0.15 58.28 ± 0.19 23.78 ± 0.08 79.45 ± 0.27 9.88 ± 0.18 92.61 ± 0.27 2.29 ± 0.05
48.65 ± 0.16 156.60 ± 0.15 57.54 ± 0.20 23.47 ± 0.08 78.56 ± 0.28 9.24 ± 0.17 89.12 ± 0.21 2.04 ± 0.04
50.43 ± 0.30 156.30 ± 0.32 61.18 ± 0.55 25.03 ± 0.21 82.94 ± 0.59 12.41 ± 0.61 106.43 ± 0.33 3.28 ± 0.17
b.0001 NS b.0001 b.0001 b.0001 b.0001 b.0001 b.0001
NFG: normal fasting glucose, IFG: impaired fasting glucose, and WC: waist circumference. All variables have been age-adjusted expect age. Significantly different between NFG group and IFG group at p b 0.05 by Surveyreg tests. a Mean ± SE.
the subjects in the IFG group were 107.89 mg/dl (men) and 106.43 mg/dl (women); in accordance with that study, the IFG group in our study showed higher body weight, BMI, and WC than the NFG group. Recently, WC has been recognized as a risk factor of diabetes incidence in IFG level. An interaction was observed between BMI category and the effect of WC increase on diabetes progression, with a larger impact in participants with BMIs b 25 kg/m2 than in those with BMIs ≥25 kg/m2 [17]. Our subjects had BMIs b25 kg/m2. Despite having lower BMIs, some Asian populations showed a similar or even higher prevalence of diabetes than Western populations. Research studies on diabetes in Korean populations reported similar results [18]. Glucose homeostasis is dependent on 3 factors, namely insulin secretion, insulin clearance, and insulin sensitivity. Insulin deficiency and insulin resistance have been known to be involved in the pathogenesis of T2DM. Insulin concentration and HOMA-IR were significantly higher in the IFG group than in the NFG group. HOMA-IR has been widely used as a reasonable surrogate measure of insulin resistance in an epidemiological study. There is evidence to suggest that high blood glucose level can elicit oxidative stress by increasing reactive oxygen species production and reducing intracellular antioxidant defense, which cause the deterioration of pancreatic β cells [7,19]. The measured anthropometric parameters showed a significant difference between normal individuals and those with the IFG, while nutrients intakes containing caloric intake did not differ between stratified participants according to FPG status. This may be reflected in conscious decision to smaller meals or dishes in IFG group due to overweight. Gajda et al. [20] also reported that diabetic subjects showed the lower caloric intakes from carbohydrate and even dietary fiber compared with non diabetic subjects. In addition, a report which was conducted in Korean people showed that mean intakes of energy, carbohydrate, fat, and protein were lower in obesity group more than the normal
group [21]. Another contributing factor could be that BMIs and WC are dependent on genetic and life style factors including a lack of physical activity, smoking, and alcohol consumption as well as excess caloric intakes. A study from Paek et al. [22] which study conducted in Korean men and women, reported that after controlling for BMI, multiple regression analysis of the dietary patterns showed that an alcohol consumption significantly affected the obesity and FPG level in male subjects. Antioxidants can have beneficial effects on pancreatic β cells by neutralizing the effects of oxidative stress. Flavonoids have high antioxidant activities as free radical scavengers and potent metal chelators [23,24]. Recently there has been a growing interest in hypoglycemic agents from natural products, especially those derived from plants. Several flavonoids, common components of human diets have been reported to improve hyperglycemia in DM by affecting glucose transport, insulinlike properties and insulin-receptor function [25–27]. The amount of intake for each subclass of flavonoids varied widely between the studies. The estimated flavanone intakes in this study were 47.61 and 44.45 mg for the male and female subjects, respectively. These values are higher than the recently reported ranges of flavanone intake based on food intake surveys in Ireland (29 mg/day), the UK (26 mg/day) [28], and Finland (27 mg/day). Flavanones, including hesperetin, eriodictyol and naringenin, are polyphenolic compounds highly and almost exclusively present in citrus fruits and juices. Of flavanones, hesperetin was the major contributor (85–94%), and orange and orange juice accounted for 93.8% of the dietary source of hesperetin, based on data on flavonoid intakes in US populations [29]. Flavones are widely distributed, albeit in small quantities, in foods of plant origin. Our results (0.78 mg/day) were within the mean amount of intake (range, 0.3–1.6 mg/day) in other adult populations studied [30–32]. However, the intakes of dietary flavonols in our
Table 2 Mean daily nutrient intake on the energy intake of the subjects. Men
Women
Total (n = 1611)
NFG (n = 1088
IFG (n = 523)
p
Total (n = 2575)
NFG (n = 2044
IFG (n = 531)
p
Energy (kcal)
2239.14 ± 22.42a
2252.26 ± 39.48
NS
1 633.35 ± 17.26
NS
36.60 ± 0.30 17.99 ± 0.23 159.83 ± 1.06 4.04 ± 0.06 52.04 ± 1.10 263.27 ± 4.22 614.57 ± 4.67 7.79 ± 0.12
36.75 ± 0.51 17.67 ± 0.37 157.62 ± 1.78 4.09 ± 0.11 54.19 ± 2.16 271.75 ± 8.37 618.41 ± 8.25 7.99 ± 0.23
NS NS NS NS NS NS NS NS
35.88 ± 0.26 17.37 ± 0.26 176.84 ± 0.83 4.74 ± 0.08 67.57 ± 1.59 284.88 ± 4.55 633.52 ± 4.02 8.43 ± 0.13
1639.77 ± 19.16 (/1000 kcal) 35.77 ± 0.29 17.20 ± 0.29 177.80 ± 0.91 4.71 ± 0.09 67.01 ± 1.55 282.27 ± 4.80 633.01 ± 4.34 8.54 ± 0.15
1604.15 ± 36.59
Protein (g) Fat (g) Carbohydrate (g) Crude fiber (g) Vitamin C (mg) Calcium (mg) Phosphorous (mg) Iron (mg)
2232.70 ± 25.60 (/1000 kcal) 36.52 ± 0.38 17.92 ± 0.28 161.47 ± 1.23 4.03 ± 0.08 51.09 ± 1.18 260.75 ± 4.75 614.59 ± 5.38 7.73 ± 0.15
36.11 ± 0.56 17.59 ± 0.49 174.61 ± 1.76 4.88 ± 0.19 70.13 ± 4.91 294.74 ± 9.65 635.93 ± 9.01 8.03 ± 0.22
NS NS NS NS NS NS NS NS
NFG: normal fasting glucose and IFG: impaired fasting glucose. All variables have been age-adjusted expect age. Significantly different between NFG group and IFG group at p b 0.05 by Surveyreg tests. a Mean ± SE.
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Table 3 Mean daily flavonoid content of intake foods on the energy intake of the subjects. Men
Flavanones (mg) Eriodictyol (mg) Hesperetin (mg) Naringenin (mg) Flavones (mg) Apigenin (mg) Luteolin (mg) Flavonols (mg) Kaempferol (mg) Myricetin (mg) Quercetin (mg)
Women
Total (n = 1611)
NFG (n = 1088
IFG (n = 523)
p
Total (n = 2575)
NFG (n = 2044)
IFG (n = 531)
p
21.26 ± 4.37a 0.17 ± 0.04 19.71 ± 4.33 1.38 ± 0.18 0.36 ± 0.02 0.07 ± 0.00 0.28 ± 0.01 15.72 ± 0.59 4.92 ± 0.13 0.30 ± 0.02 9.67 ± 0.51
26.41 ± 5.72 0.22 ± 0.05 24.90 ± 5.67 1.29 ± 0.18 0.36 ± 0.02 0.07 ± 0.00 0.29 ± 0.02 15.64 ± 0.68 4.75 ± 0.16 0.30 ± 0.02 9.76 ± 0.59
12.20 ± 5.02 0.08 ± 0.04 10.60 ± 4.96 1.52 ± 0.39 0.36 ± 0.03 0.08 ± 0.01 0.28 ± 0.02 16.29 ± 1.13 5.29 ± 0.23 0.30 ± 0.03 9.84 ± 0.96
0.034 0.016 0.031 NS NS NS NS NS NS NS NS
29.24 ± 4.17 0.20 ± 0.03 26.26 ± 4.11 2.77 ± 0.30 0.48 ± 0.04 0.12 ± 0.03 0.37 ± 0.02 17.06 ± 0.55 4.57 ± 0.10 0.45 ± 0.03 11.22 ± 0.48
31.47 ± 4.65 0.22 ± 0.04 28.57 ± 4.59 2.67 ± 0.30 0.50 ± 0.04 0.13 ± 0.04 0.38 ± 0.02 16.65 ± 0.62 4.49 ± 0.11 0.46 ± 0.04 10.92 ± 0.54
22.67 ± 7.28 0.14 ± 0.06 19.32 ± 7.07 3.21 ± 0.92 0.41 ± 0.03 0.08 ± 0.02 0.33 ± 0.03 18.70 ± 1.11 4.84 ± 0.21 0.42 ± 0.04 12.46 ± 0.98
NS NS NS NS NS NS NS NS NS NS NS
NFG: normal fasting glucose and IFG: impaired fasting glucose. All variables have been age-adjusted expect age Significantly different between NFG group and IFG group at p b 0.05 by Surveyreg tests. a Mean ± SE.
study (men, 34.38 mg/day; women, 27.15 mg/day) were higher than the mean values (range, 5–27 mg/day) of other studies [30,33], with the major sources being onions, tea, and apples. Such differences could be explained by the differences in dietary habits between various populations. Accumulated results demonstrated the anti-hyperglycemic activity of flavonoids and its mechanisms of flavonoids. Animal models of T2DM using db/db indicated that hesperidin, a glycoside form of hesperetin, play important roles in preventing the progression of hyperglycemia by increasing hepatic glycolysis and glycogen concentration and/or by lowering hepatic gluconeogenesis [34]. In addition, a recent study showed that eriodictyol, another flavanone, promoted insulinstimulated glucose uptake in HepG2 cells and differentiated 3T3-L1 adipocytes, through the inhibition of insulin-induced PI3K-dependent Akt phosphorylation. Our result demonstrated that the male subjects in the IFG group showed lower flavanones intake than the men in the NFG group. Nevertheless, we failed to identify a correlation between flavanone and T2DM risk factors in the male subjects. An inverse association between flavanone intake and insulin level was observed only in the female subjects after adjustment for energy intake and age. Bazzano et al. [1] reported that intake of juice, major source of flavanones, was associated with a higher risk of T2DM. Although fruit juices may have an antioxidant activity [35], they lack fiber, are less satiating, and tend to have high sugar content. In this study, we observed the inverse association between flavonol and flavones intakes and diabetes risk factor including insulin and insulin resistance. Knekt et al. [9] reported that intakes of flavonols, including quercetin and myricetin, were associated with a decreased risk of T2DM in 10,054 Finnish men and women. Results from primary human adipocytes indicated that quercetin prevented the tumor necrosis factor alpha-mediated serine phosphorylation of insulin receptor substrate-1 and protein tyrosine phosphatase-1B gene expression and the suppression of insulin-stimulated glucose uptake [36]. Consistent with these in vitro data, supplementation with quercetin showed the reduction of insulin resistance and hyperinsulinemia in rodent models of obesity [37,38]. Zhang and Liu [39] reported that kaempferol was confirmed as a naturally occurring anti-diabetic compound by protecting pancreatic beta-cell survival and function. The flavone luteolin has been reported as a ligand of peroxisome proliferator-activated receptor γ (PPARγ). PPARγ is a ligand-activated transcription factor belonging to the nuclear receptor superfamily that is crucial for the regulation of adipogenesis, lipid metabolism and glucose homeostasis [40] and can be a target molecule for treatment of T2DM. Luteolin was reported to influence insulin action and production of adipokines/cytokines in adipocytes by activating the PPARγ pathway [41]. The effects of flavonoids on diabetic risk factors showed the genderspecific differences. In male subjects, intakes of flavones and flavonols
were inversely related to the risk of diabetes and a significant inverse association was observed between flavanone intakes and risk of diabetes in women. We could not find a previous study that compared the effect of flavonoids on diabetes by gender. There was only one report which the effects of flavan-3-ols on risk factors of metabolic syndrome were different by gender and weight status [21]. In addition, the estimated means of daily flavanones intake for male and female were 21 mg/d and 29 mg/d, respectively. Intake of flavanones in male was lower than that of female by 30%. Lower amount of intake can induce low plasma concentration and the less effect. Another possibility could be the difference of flavonoid bioavailability according to gender. Unfortunately, up to now, there is not any report about this. Further studies on flavonoid bioavailability according to gender are necessary. This study had several limitations. One was its cross-sectional observational design, which probably led to reverse causation. Another limitation was that the data were not collected for the purpose of research; therefore, there might be more errors in the data collection process. In particular, the 24-h dietary recall data did not reflect the ordinary dietary pattern. Meanwhile, a strength of this study was the use of nationally representative data of the general population. A more important strength was that despite the cross-sectional design of this study, the correlation of flavonoid intake with biochemical parameters was fairly exact. In spite of these potential benefits of flavonoids on prevention of diabetes, risks of fructose consumption from fruit intakes should also be taken consideration. Although main sources of fructose are sugar and the honey, it is present frequently in the juices of fruits. It has been observed that obesity, DM, insulin resistance and hypertension are associated with chronic consumption of fructose. However, most of the fruits have low glycemic index due to the presence of fructose as the primary sugar and also due to the high fiber content in them. Moreover, fruit intakes of male and female in our study were 162.5 and 186.1 g, respectively (data not shown). Fructose contents in fruits are 2.5–12.5 g/100 g and orange juice contains 8–9 g/100 g. Stanhope et al [42] reported that when fructose at 30–60 g (~4–12% of energy) was added to the diet in the free-living state, there were no significant effects on lipid or glucose biomarkers. Like this, adverse metabolic effects of fructose are due to chronic high consumption (N 100 g/d) and there is lack of evidence of adverse effect on moderate consumption of fructose [43]. Moreover, Livesy [44] provided that the 50 g fructose/d cut point is 10% of metabolizable energy intake for a 2000 kcal/d diet and so generally corresponds to the level of fructose intake thought acceptable in people with diabetes. In conclusion, we observed that weight, BMI, WC, FPG level, insulin level, and HOMA-IR were increased in the IFG group, in both the male and female subjects. Among the dietary factors, lower intake of flavanone was observed in the male subjects of the IFG group. Furthermore,
Model 1; unadjusted model, Model 2; adjusted for energy intake and age, Model 3; adjusted for energy intake, age, and BMI, Model 4; adjusted for energy intake, age, BMI, and WC, and Model 5; adjusted for energy intake, age, BMI, WC, smoking, physical activity, and frequency of alcohol drinking.
NS NS NS NS 0.4647 −0.0002 −0.0002 −0.0007 −0.0008 −0.0008 NS NS NS NS NS −0.0195 −0.0196 −0.0166 −0.0152 −0.0151 NS NS 0.0089 0.0103 0.0119 −0.0001 −0.0001 −0.0002 −0.0002 −0.0002 0.0068 0.0115 0.0378 0.0391 0.0239 0.0430 0.0482 NS NS NS 0.0758 NS NS NS NS 0.0001 0.0001 0.0001 0.0001 0.0001
−0.0542 −0.0541 −0.0429 −0.0408 −0.0373
−0.0019 −0.0019 −0.0014 −0.0014 −0.0016
NS NS NS NS NS −0.0008 −0.0013 −0.0033 −0.0035 −0.0036 NS NS NS NS NS −0.0655 −0.0692 −0.0579 −0.0529 −0.0524 NS 0.0476 0.0044 0.0054 0.0063 −0.0005 −0.0005 −0.0008 −0.0008 −0.0008 0.0025 0.0049 0.0141 0.0161 0.0092 0.0323 0.0395 NS NS NS NS NS NS NS NS 0.0006 0.0006 0.0003 0.0003 0.0003
−0.2111 −0.2103 −0.1688 −0.1612 −0.1510
−0.0081 −0.0082 −0.0062 −0.0063 −0.0067
NS NS NS NS NS 0.0027 0.0067 0.0044 0.0042 0.0043 NS NS NS NS NS −0.2007 −0.1827 −0.1697 −0.1653 −0.1666 NS NS NS NS NS −0.0003 −0.0004 −0.0007 −0.0007 −0.0007 NS NS NS NS NS 0.0023 0.0007 0.0032 0.0030 0.0027 NS NS NS NS NS −0.2943 −0.3341 −0.2824 −0.2676 −0.2327 NS NS NS NS NS
p for trend β-coefficients p for trend p for trend
−0.0007 −0.0008 −0.0012 −0.0012 −0.0012
β-coefficients
Flavonols (mg) Table 4 Relationship between flavonoid content of intake foods and blood biomarkers.
Glucose Model 1 Model 2 Model 3 Model 4 Model 5 Insulin Model 1 Model 2 Model 3 Model 4 Model 5 HOMA Model 1 Model 2 Model 3 Model 4 Model 5
Flavonols (mg) Flavones (mg) Flavanones (mg)
β-coefficients
Flavanones (mg)
β-coefficients
Women (n = 2714)
Flavones (mg) Men (n = 1788)
p for trend
β-coefficients
p for trend
β-coefficients
p for trend
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Clinica Chimica Acta journal homepage: www.elsevier.com/locate/clinchim
Association between flavonoid intake and diabetes risk among the Koreans Jee-Young Yeon a, Yun Jung Bae b, Eun-Young Kim c, Eun-Ju Lee d,⁎ a
Nutrition Safety Policy Division, Food Nutrition and Dietary Safety Bureau, Ministry of Food and Drug Safety, Cheongju, 361-951, Republic of Korea Food and Nutrition Major, Division of Food Science and Culinary Arts, Shinhan University, Dongducheon 480-777, Republic of Korea Department of Food and Nutrition, Sookmyung Women's University, Seoul, Republic of Korea d Asan Institute for Life Sciences, Asan Medical Center, Seoul 138-736, Republic of Korea b c
a r t i c l e
i n f o
Article history: Received 8 April 2014 Received in revised form 27 October 2014 Accepted 29 October 2014 Available online 4 November 2014 Keywords: Type 2 diabetes mellitus Flavonoid Impaired fasting glucose Insulin KNHANES
a b s t r a c t Background: We investigated the association between flavonoid intake and type 2 diabetes mellitus (T2DM) risk factors including serum fasting glucose, insulin level, and insulin resistance. Methods: A total of 4186 participants who were involved in the 2007–2009 Korean National Health and Nutrition Examination Survey were examined. The participants were divided into 2 groups by fasting plasma glucose (FPG) as follows: normal fasting glucose (NFG; FPG b 100 mg/dl) and impaired fasting glucose (IFG) groups (FPG ≥100 mg/dl). Results: In the IFG group, body weight, body mass index, and waist circumference were increased. Fasting insulin level and homeostasis model assessment estimate of insulin resistance as markers of insulin resistance were higher in the IFG group. Intakes of energy and nutrients, including protein, fat, carbohydrate, crude fiber, vitamin C, calcium, phosphorus, and iron, did not differ between the 2 groups. For the male subjects, the energy-adjusted flavanone intake was lower in the IFG group than in the NFG group. Insulin and insulin resistance were inversely correlated with intakes of flavones and flavonols among the male subjects. Conclusion: These findings can provide valuable information for further development of appropriate strategies for diabetes prevention in Korea. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Impaired glucose homeostasis has been described to precede a diabetes mellitus (DM) diagnosis and is known as a prediabetes state comprising 2 subcategories, namely impaired fasting glucose (IFG) and impaired glucose tolerance, classified on the basis of glucose levels at fasting and after a glucose challenge (oral glucose tolerance test). Both conditions are associated with increased risk for DM. Consumption of fruits and vegetables is associated with lowered risk for major chronic diseases including diabetes, cardiovascular diseases and cancer [1]. These plant foods are the main sources of flavonoids. Flavonoids have 2 aromatic rings that are bound by an oxygenated heterocyclic ring. On the basis of their chemical structure, they are divided into several subclasses as follows: flavones, flavonols, flavanones, flavan-3-ols, and anthocyanins, among which flavones and flavonols are Abbreviations: IFG, impaired fasting glucose; FPG, fasting plasma glucose; HOMA-IR, Homeostasis model assessment estimate of insulin resistance; KNHANES, Korea National Health and Nutrition Examination Survey; NFG, normal fasting glucose; PPARγ, peroxisome proliferator-activated receptor γ; T2DM, type 2 diabetes mellitus; WC, waist circumference. ⁎ Corresponding author at: Asan Institute for Life Science, 88 Olympicro 43 gil, Songpa-gu, Seoul 138-736, Republic of Korea. Tel.: +82 2 3010 4677. E-mail address: [email protected] (E.-J. Lee).
http://dx.doi.org/10.1016/j.cca.2014.10.042 0009-8981/© 2014 Elsevier B.V. All rights reserved.
found in leafy vegetables and flavanones are mainly found in citrus fruits. Several studies reported that the total flavonoid intake in Western countries was estimated to be 1–200 mg/d [2,3]. Flavonoids has been established as possessing anti-inflammatory, antioxidative, and chemopreventive activities, which contribute to the health protective properties of plant foods. In vitro and in vivo studies observed that oxidative stress generation impaired pancreatic β-cell insulin secretion [4–6] and interfered with the insulin signaling pathway, thereby accelerating the progression to obvious type 2 DM (T2DM) from insulin resistance [7,8]. Intake of flavonoids, which are capable of scavenging free radicals and chelating deleterious oxidant-inducing metals such as iron and copper, has been associated with a reduced risk of cardiovascular disease and cancer [9–12]. Furthermore, accumulating evidence indicates that flavonoids influence glucose metabolism. In addition, results from mechanistic studies suggest that flavonoids may decrease glycemia and improve insulin secretion and sensitivity [13]. Nevertheless, the relevance of dietary flavonoids to insulin resistance or diabetic risk is less well studied and in epidemiological studies, very few of the individual polyphenolic compounds alone have been so far demonstrated to have a beneficial effect on T2DM. Few studies have evaluated dietary intakes of major flavonoid subclasses that are commonly consumed in the Korea diet in relation to
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the risk for T2DM. Therefore, we estimated the intake of individual flavonoids, including flavanones, flavonols, and flavones, in a cross-sectional study and the association between intakes of these flavonoids and T2DM risk factors, including serum fasting glucose level, insulin, and insulin resistance. 2. Subjects and methods 2.1. Study population We used data from the Fourth Korea National Health and Nutrition Examination Survey (KNHANES IV-3, 2007–2009), which was conducted by the Korea Centers for Disease Control and Prevention. KNHANES is a series of surveys designed to assess the health and nutritional status of the Korean population. The KNHANES began in 1998 and then was subsequently conducted in 2001 and 2005. Since 2007, the KNHANES has been conducted annually. The KNHANES consists of a health interview, health examination (physical examination, clinical measurements, and tests), and dietary interview. The subjects of the KNHANES were aged ≥ 1 y and selected from stratified multistage samples of the South Korean population from multiple geographic areas and ages of both sexes. A total of 8631 people participated in the 2010 KNHANES. Among them, 4186 persons aged 40–59 y were included as participants in this study. We chose subjects who had energy intakes ≥ 500 kcal b5000 kcal and had no missing data. The participants were divided into 2 groups according to fasting plasma glucose (FPG) as follows: normal fasting glucose (NFG; FPG level, b 100 mg/dl) and IFG; FPG level, 100–125 mg/dl). The 2011 clinical practice guidelines for T2DM in Korea recommend different screening methods according to IFG stage (stage 1, FPG level of 100–109 mg/dl, stage 2, FPG level of 110–125) [14]. Considering that the dataset did not include any personal information and participant consent was already taken obtained in the process of the KNHANES, this study was exempted from obtaining participant consent by the board. 2.2. Health examination survey and laboratory test Height and weight were measured to the nearest 0.1 cm and 0.1 kg, respectively. Body mass index (BMI) was calculated by dividing weight by height (kg/m2). FPG level was measured by the enzymatic method using the Hitachi automatic Analyzer 7600 (Hitachi, Japan) and fasting insulin level was determined by immunoradiometric assay using the 1470 Wizard Gamma Counter (PerkinElmer, Finland). Homeostasis model assessment estimate of insulin resistance (HOMAIR), a marker of insulin resistance, was calculated as follows: FPG level (in mg/dl) × fasting insulin level (in μU/dl)/22.5 [15]. 2.3. Dietary assessment and flavonoid intakes A single 24-h dietary recall was collected from each respondent through inperson interviews. We did not exclude any certain days such as holidays or weekends. To enhance recall, supplementary tools such as food models and two-dimensional food volumes and containers were used to assist the respondent's report of the volumes of the food items consumed. Recipes for all food items consumed were also collected. Based on the recipes collected from each household during the interview, the weight of each ingredient was estimated from the volume of food ingested. Nutrient intake from diet was estimated by combining the US Department of Agriculture Flavonoid databases (http://www.ars.usda.gov/Services/docs.htm?docid=6231) and 24-h dietary recall in the KNHANES IV-3 (2007–2009). In addition, we derived intakes of the 3 main flavonoid subclasses commonly consumed in the Korean diet, specifically flavanones (eriodictyol, hesperetin, and naringenin), flavonols (quercetin, kaempherol, and myricetin), and flavones (luteolin and apigenin).
2.4. Statistical analyses All statistical analyses were performed using the SAS software (version 9.2 SAS Institute Inc., Cary, NC, USA). Data were expressed as mean ± SE. SURVEYREG tests were used to evaluate the significance difference between the healthy and IFG groups. In addition, a multiple regression analysis was performed to determine the relationship between flavonoid intake and biochemical parameters by adjusting for various confounders including energy intake, age, BMI, WC, smoking, physical activity, and alcohol consumption. Five different models were used to examine the association between flavonoids intake and FPG level, insulin level, and HOMA-IR. A P b 0.05 was considered to be statistically significant. 3. Results 3.1. General characteristics and blood biochemistry The general characteristics of the subjects are presented in Table 1. Data for a total of 4186 participants (1611 men and 2575 women) were analyzed. The numbers of subjects with NFG and IFG levels was 3132 and 1054, respectively. Among the 1611 male subjects, 1088 had NFG levels and 523 had IFG levels. Among the women, 2044 had NFG levels and 531 had IFG levels. Men made up 32.5% of the total subjects, and women, 20.6%. The mean age, weight, BMI, and waist circumference (WC) in the IFG group were higher than those in the control group, both among the male and female subjects. Fasting insulin and HOMA-IR were also more elevated in the IFG group. 3.2. Intakes of nutrient and flavonoids Intakes of energy and nutrients, including protein, fat, carbohydrate, crude fiber, vitamin C, calcium, phosphorus, and iron, were not different between the 2 groups (Table 2). Intakes of flavonoid subclasses by sex according to FPG level are shown in Table 3. The intakes of flavanones, flavones, and flavonols were higher in the women than in the men. Energy-adjusted flavanone intake was lower among the male subjects in the NFG group. Intakes of eriodictyol and hesperetin, not naringenin, in the IFG group were statistically lower than in the NFG group. No significant association was found between intakes of flavones and flavonols, and the risk for IFG in the male subjects. 3.3. Multiple regression analysis of the relationship between flavonoid intake and biochemical parameters The associations between the intakes of flavonoid subclasses, and glucose, insulin, and HOMA-IR are presented according to sex in Table 4. We observed significant heterogeneity in the results by sex. Inverse associations with insulin and HOMA-IR were observed for flavones and flavonols in men (P-trend, 0.05 for all). In the female subjects, flavanones were inversely related to risk for IFG and after adjustment for other variables including BMI and WC using multiple regression analysis, flavanone intakes were independently associated with insulin and HOMA in women. Moreover, the inverse association between insulin and flavanone intakes became stronger with adjustment for BMI and WC. 4. Discussion IFG is a well-known risk factor for T2DM. Weight gain has been reported to decrease response to insulin and is associated with an increased risk of developing diabetes, suggesting that the association between obesity and diabetes is indisputable. A study based on the general Korean population reported that degree of BMI was increased with FPG levels b100 mg/dl, peaked with FPG levels of 100–109 mg/dl, and then plateaued with higher FPG levels [16]. The mean FPG levels in
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Table 1 Anthropometric measurements and blood biomarkers of subjects. Men
Age (y) Height (cm) Weight (kg) BMI (kg/m2) WC (cm) Insulin (μIU/ml) Glucose (mg/dl) HOMA-IR
Women
Total (n = 1611)
NFG (n = 1088)
IFG (n = 523)
p
Total (n = 2575)
NFG (n = 2044)
IFG (n = 531)
p
48.86 ± 0.15a 168.90 ± 0.18 69.07 ± 0.28 24.18 ± 0.08 84.90 ± 0.25 9.52 ± 0.17 95.80 ± 0.30 2.28 ± 0.04
48.63 ± 0.18 168.86 ± 0.24 68.07 ± 0.33 23.85 ± 0.10 83.91 ± 0.29 8.83 ± 0.16 90.38 ± 0.22 1.98 ± 0.04
49.37 ± 0.27 169.00 ± 0.30 71.28 ± 0.49 24.93 ± 0.15 87.08 ± 0.40 11.04 ± 0.36 107.89 ± 0.34 2.95 ± 0.10
0.025 NS b.0001 b.0001 b.0001 b.0001 b.0001 b.0001
49.01 ± 0.14 156.54 ± 0.15 58.28 ± 0.19 23.78 ± 0.08 79.45 ± 0.27 9.88 ± 0.18 92.61 ± 0.27 2.29 ± 0.05
48.65 ± 0.16 156.60 ± 0.15 57.54 ± 0.20 23.47 ± 0.08 78.56 ± 0.28 9.24 ± 0.17 89.12 ± 0.21 2.04 ± 0.04
50.43 ± 0.30 156.30 ± 0.32 61.18 ± 0.55 25.03 ± 0.21 82.94 ± 0.59 12.41 ± 0.61 106.43 ± 0.33 3.28 ± 0.17
b.0001 NS b.0001 b.0001 b.0001 b.0001 b.0001 b.0001
NFG: normal fasting glucose, IFG: impaired fasting glucose, and WC: waist circumference. All variables have been age-adjusted expect age. Significantly different between NFG group and IFG group at p b 0.05 by Surveyreg tests. a Mean ± SE.
the subjects in the IFG group were 107.89 mg/dl (men) and 106.43 mg/dl (women); in accordance with that study, the IFG group in our study showed higher body weight, BMI, and WC than the NFG group. Recently, WC has been recognized as a risk factor of diabetes incidence in IFG level. An interaction was observed between BMI category and the effect of WC increase on diabetes progression, with a larger impact in participants with BMIs b 25 kg/m2 than in those with BMIs ≥25 kg/m2 [17]. Our subjects had BMIs b25 kg/m2. Despite having lower BMIs, some Asian populations showed a similar or even higher prevalence of diabetes than Western populations. Research studies on diabetes in Korean populations reported similar results [18]. Glucose homeostasis is dependent on 3 factors, namely insulin secretion, insulin clearance, and insulin sensitivity. Insulin deficiency and insulin resistance have been known to be involved in the pathogenesis of T2DM. Insulin concentration and HOMA-IR were significantly higher in the IFG group than in the NFG group. HOMA-IR has been widely used as a reasonable surrogate measure of insulin resistance in an epidemiological study. There is evidence to suggest that high blood glucose level can elicit oxidative stress by increasing reactive oxygen species production and reducing intracellular antioxidant defense, which cause the deterioration of pancreatic β cells [7,19]. The measured anthropometric parameters showed a significant difference between normal individuals and those with the IFG, while nutrients intakes containing caloric intake did not differ between stratified participants according to FPG status. This may be reflected in conscious decision to smaller meals or dishes in IFG group due to overweight. Gajda et al. [20] also reported that diabetic subjects showed the lower caloric intakes from carbohydrate and even dietary fiber compared with non diabetic subjects. In addition, a report which was conducted in Korean people showed that mean intakes of energy, carbohydrate, fat, and protein were lower in obesity group more than the normal
group [21]. Another contributing factor could be that BMIs and WC are dependent on genetic and life style factors including a lack of physical activity, smoking, and alcohol consumption as well as excess caloric intakes. A study from Paek et al. [22] which study conducted in Korean men and women, reported that after controlling for BMI, multiple regression analysis of the dietary patterns showed that an alcohol consumption significantly affected the obesity and FPG level in male subjects. Antioxidants can have beneficial effects on pancreatic β cells by neutralizing the effects of oxidative stress. Flavonoids have high antioxidant activities as free radical scavengers and potent metal chelators [23,24]. Recently there has been a growing interest in hypoglycemic agents from natural products, especially those derived from plants. Several flavonoids, common components of human diets have been reported to improve hyperglycemia in DM by affecting glucose transport, insulinlike properties and insulin-receptor function [25–27]. The amount of intake for each subclass of flavonoids varied widely between the studies. The estimated flavanone intakes in this study were 47.61 and 44.45 mg for the male and female subjects, respectively. These values are higher than the recently reported ranges of flavanone intake based on food intake surveys in Ireland (29 mg/day), the UK (26 mg/day) [28], and Finland (27 mg/day). Flavanones, including hesperetin, eriodictyol and naringenin, are polyphenolic compounds highly and almost exclusively present in citrus fruits and juices. Of flavanones, hesperetin was the major contributor (85–94%), and orange and orange juice accounted for 93.8% of the dietary source of hesperetin, based on data on flavonoid intakes in US populations [29]. Flavones are widely distributed, albeit in small quantities, in foods of plant origin. Our results (0.78 mg/day) were within the mean amount of intake (range, 0.3–1.6 mg/day) in other adult populations studied [30–32]. However, the intakes of dietary flavonols in our
Table 2 Mean daily nutrient intake on the energy intake of the subjects. Men
Women
Total (n = 1611)
NFG (n = 1088
IFG (n = 523)
p
Total (n = 2575)
NFG (n = 2044
IFG (n = 531)
p
Energy (kcal)
2239.14 ± 22.42a
2252.26 ± 39.48
NS
1 633.35 ± 17.26
NS
36.60 ± 0.30 17.99 ± 0.23 159.83 ± 1.06 4.04 ± 0.06 52.04 ± 1.10 263.27 ± 4.22 614.57 ± 4.67 7.79 ± 0.12
36.75 ± 0.51 17.67 ± 0.37 157.62 ± 1.78 4.09 ± 0.11 54.19 ± 2.16 271.75 ± 8.37 618.41 ± 8.25 7.99 ± 0.23
NS NS NS NS NS NS NS NS
35.88 ± 0.26 17.37 ± 0.26 176.84 ± 0.83 4.74 ± 0.08 67.57 ± 1.59 284.88 ± 4.55 633.52 ± 4.02 8.43 ± 0.13
1639.77 ± 19.16 (/1000 kcal) 35.77 ± 0.29 17.20 ± 0.29 177.80 ± 0.91 4.71 ± 0.09 67.01 ± 1.55 282.27 ± 4.80 633.01 ± 4.34 8.54 ± 0.15
1604.15 ± 36.59
Protein (g) Fat (g) Carbohydrate (g) Crude fiber (g) Vitamin C (mg) Calcium (mg) Phosphorous (mg) Iron (mg)
2232.70 ± 25.60 (/1000 kcal) 36.52 ± 0.38 17.92 ± 0.28 161.47 ± 1.23 4.03 ± 0.08 51.09 ± 1.18 260.75 ± 4.75 614.59 ± 5.38 7.73 ± 0.15
36.11 ± 0.56 17.59 ± 0.49 174.61 ± 1.76 4.88 ± 0.19 70.13 ± 4.91 294.74 ± 9.65 635.93 ± 9.01 8.03 ± 0.22
NS NS NS NS NS NS NS NS
NFG: normal fasting glucose and IFG: impaired fasting glucose. All variables have been age-adjusted expect age. Significantly different between NFG group and IFG group at p b 0.05 by Surveyreg tests. a Mean ± SE.
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Table 3 Mean daily flavonoid content of intake foods on the energy intake of the subjects. Men
Flavanones (mg) Eriodictyol (mg) Hesperetin (mg) Naringenin (mg) Flavones (mg) Apigenin (mg) Luteolin (mg) Flavonols (mg) Kaempferol (mg) Myricetin (mg) Quercetin (mg)
Women
Total (n = 1611)
NFG (n = 1088
IFG (n = 523)
p
Total (n = 2575)
NFG (n = 2044)
IFG (n = 531)
p
21.26 ± 4.37a 0.17 ± 0.04 19.71 ± 4.33 1.38 ± 0.18 0.36 ± 0.02 0.07 ± 0.00 0.28 ± 0.01 15.72 ± 0.59 4.92 ± 0.13 0.30 ± 0.02 9.67 ± 0.51
26.41 ± 5.72 0.22 ± 0.05 24.90 ± 5.67 1.29 ± 0.18 0.36 ± 0.02 0.07 ± 0.00 0.29 ± 0.02 15.64 ± 0.68 4.75 ± 0.16 0.30 ± 0.02 9.76 ± 0.59
12.20 ± 5.02 0.08 ± 0.04 10.60 ± 4.96 1.52 ± 0.39 0.36 ± 0.03 0.08 ± 0.01 0.28 ± 0.02 16.29 ± 1.13 5.29 ± 0.23 0.30 ± 0.03 9.84 ± 0.96
0.034 0.016 0.031 NS NS NS NS NS NS NS NS
29.24 ± 4.17 0.20 ± 0.03 26.26 ± 4.11 2.77 ± 0.30 0.48 ± 0.04 0.12 ± 0.03 0.37 ± 0.02 17.06 ± 0.55 4.57 ± 0.10 0.45 ± 0.03 11.22 ± 0.48
31.47 ± 4.65 0.22 ± 0.04 28.57 ± 4.59 2.67 ± 0.30 0.50 ± 0.04 0.13 ± 0.04 0.38 ± 0.02 16.65 ± 0.62 4.49 ± 0.11 0.46 ± 0.04 10.92 ± 0.54
22.67 ± 7.28 0.14 ± 0.06 19.32 ± 7.07 3.21 ± 0.92 0.41 ± 0.03 0.08 ± 0.02 0.33 ± 0.03 18.70 ± 1.11 4.84 ± 0.21 0.42 ± 0.04 12.46 ± 0.98
NS NS NS NS NS NS NS NS NS NS NS
NFG: normal fasting glucose and IFG: impaired fasting glucose. All variables have been age-adjusted expect age Significantly different between NFG group and IFG group at p b 0.05 by Surveyreg tests. a Mean ± SE.
study (men, 34.38 mg/day; women, 27.15 mg/day) were higher than the mean values (range, 5–27 mg/day) of other studies [30,33], with the major sources being onions, tea, and apples. Such differences could be explained by the differences in dietary habits between various populations. Accumulated results demonstrated the anti-hyperglycemic activity of flavonoids and its mechanisms of flavonoids. Animal models of T2DM using db/db indicated that hesperidin, a glycoside form of hesperetin, play important roles in preventing the progression of hyperglycemia by increasing hepatic glycolysis and glycogen concentration and/or by lowering hepatic gluconeogenesis [34]. In addition, a recent study showed that eriodictyol, another flavanone, promoted insulinstimulated glucose uptake in HepG2 cells and differentiated 3T3-L1 adipocytes, through the inhibition of insulin-induced PI3K-dependent Akt phosphorylation. Our result demonstrated that the male subjects in the IFG group showed lower flavanones intake than the men in the NFG group. Nevertheless, we failed to identify a correlation between flavanone and T2DM risk factors in the male subjects. An inverse association between flavanone intake and insulin level was observed only in the female subjects after adjustment for energy intake and age. Bazzano et al. [1] reported that intake of juice, major source of flavanones, was associated with a higher risk of T2DM. Although fruit juices may have an antioxidant activity [35], they lack fiber, are less satiating, and tend to have high sugar content. In this study, we observed the inverse association between flavonol and flavones intakes and diabetes risk factor including insulin and insulin resistance. Knekt et al. [9] reported that intakes of flavonols, including quercetin and myricetin, were associated with a decreased risk of T2DM in 10,054 Finnish men and women. Results from primary human adipocytes indicated that quercetin prevented the tumor necrosis factor alpha-mediated serine phosphorylation of insulin receptor substrate-1 and protein tyrosine phosphatase-1B gene expression and the suppression of insulin-stimulated glucose uptake [36]. Consistent with these in vitro data, supplementation with quercetin showed the reduction of insulin resistance and hyperinsulinemia in rodent models of obesity [37,38]. Zhang and Liu [39] reported that kaempferol was confirmed as a naturally occurring anti-diabetic compound by protecting pancreatic beta-cell survival and function. The flavone luteolin has been reported as a ligand of peroxisome proliferator-activated receptor γ (PPARγ). PPARγ is a ligand-activated transcription factor belonging to the nuclear receptor superfamily that is crucial for the regulation of adipogenesis, lipid metabolism and glucose homeostasis [40] and can be a target molecule for treatment of T2DM. Luteolin was reported to influence insulin action and production of adipokines/cytokines in adipocytes by activating the PPARγ pathway [41]. The effects of flavonoids on diabetic risk factors showed the genderspecific differences. In male subjects, intakes of flavones and flavonols
were inversely related to the risk of diabetes and a significant inverse association was observed between flavanone intakes and risk of diabetes in women. We could not find a previous study that compared the effect of flavonoids on diabetes by gender. There was only one report which the effects of flavan-3-ols on risk factors of metabolic syndrome were different by gender and weight status [21]. In addition, the estimated means of daily flavanones intake for male and female were 21 mg/d and 29 mg/d, respectively. Intake of flavanones in male was lower than that of female by 30%. Lower amount of intake can induce low plasma concentration and the less effect. Another possibility could be the difference of flavonoid bioavailability according to gender. Unfortunately, up to now, there is not any report about this. Further studies on flavonoid bioavailability according to gender are necessary. This study had several limitations. One was its cross-sectional observational design, which probably led to reverse causation. Another limitation was that the data were not collected for the purpose of research; therefore, there might be more errors in the data collection process. In particular, the 24-h dietary recall data did not reflect the ordinary dietary pattern. Meanwhile, a strength of this study was the use of nationally representative data of the general population. A more important strength was that despite the cross-sectional design of this study, the correlation of flavonoid intake with biochemical parameters was fairly exact. In spite of these potential benefits of flavonoids on prevention of diabetes, risks of fructose consumption from fruit intakes should also be taken consideration. Although main sources of fructose are sugar and the honey, it is present frequently in the juices of fruits. It has been observed that obesity, DM, insulin resistance and hypertension are associated with chronic consumption of fructose. However, most of the fruits have low glycemic index due to the presence of fructose as the primary sugar and also due to the high fiber content in them. Moreover, fruit intakes of male and female in our study were 162.5 and 186.1 g, respectively (data not shown). Fructose contents in fruits are 2.5–12.5 g/100 g and orange juice contains 8–9 g/100 g. Stanhope et al [42] reported that when fructose at 30–60 g (~4–12% of energy) was added to the diet in the free-living state, there were no significant effects on lipid or glucose biomarkers. Like this, adverse metabolic effects of fructose are due to chronic high consumption (N 100 g/d) and there is lack of evidence of adverse effect on moderate consumption of fructose [43]. Moreover, Livesy [44] provided that the 50 g fructose/d cut point is 10% of metabolizable energy intake for a 2000 kcal/d diet and so generally corresponds to the level of fructose intake thought acceptable in people with diabetes. In conclusion, we observed that weight, BMI, WC, FPG level, insulin level, and HOMA-IR were increased in the IFG group, in both the male and female subjects. Among the dietary factors, lower intake of flavanone was observed in the male subjects of the IFG group. Furthermore,
Model 1; unadjusted model, Model 2; adjusted for energy intake and age, Model 3; adjusted for energy intake, age, and BMI, Model 4; adjusted for energy intake, age, BMI, and WC, and Model 5; adjusted for energy intake, age, BMI, WC, smoking, physical activity, and frequency of alcohol drinking.
NS NS NS NS 0.4647 −0.0002 −0.0002 −0.0007 −0.0008 −0.0008 NS NS NS NS NS −0.0195 −0.0196 −0.0166 −0.0152 −0.0151 NS NS 0.0089 0.0103 0.0119 −0.0001 −0.0001 −0.0002 −0.0002 −0.0002 0.0068 0.0115 0.0378 0.0391 0.0239 0.0430 0.0482 NS NS NS 0.0758 NS NS NS NS 0.0001 0.0001 0.0001 0.0001 0.0001
−0.0542 −0.0541 −0.0429 −0.0408 −0.0373
−0.0019 −0.0019 −0.0014 −0.0014 −0.0016
NS NS NS NS NS −0.0008 −0.0013 −0.0033 −0.0035 −0.0036 NS NS NS NS NS −0.0655 −0.0692 −0.0579 −0.0529 −0.0524 NS 0.0476 0.0044 0.0054 0.0063 −0.0005 −0.0005 −0.0008 −0.0008 −0.0008 0.0025 0.0049 0.0141 0.0161 0.0092 0.0323 0.0395 NS NS NS NS NS NS NS NS 0.0006 0.0006 0.0003 0.0003 0.0003
−0.2111 −0.2103 −0.1688 −0.1612 −0.1510
−0.0081 −0.0082 −0.0062 −0.0063 −0.0067
NS NS NS NS NS 0.0027 0.0067 0.0044 0.0042 0.0043 NS NS NS NS NS −0.2007 −0.1827 −0.1697 −0.1653 −0.1666 NS NS NS NS NS −0.0003 −0.0004 −0.0007 −0.0007 −0.0007 NS NS NS NS NS 0.0023 0.0007 0.0032 0.0030 0.0027 NS NS NS NS NS −0.2943 −0.3341 −0.2824 −0.2676 −0.2327 NS NS NS NS NS
p for trend β-coefficients p for trend p for trend
−0.0007 −0.0008 −0.0012 −0.0012 −0.0012
β-coefficients
Flavonols (mg) Table 4 Relationship between flavonoid content of intake foods and blood biomarkers.
Glucose Model 1 Model 2 Model 3 Model 4 Model 5 Insulin Model 1 Model 2 Model 3 Model 4 Model 5 HOMA Model 1 Model 2 Model 3 Model 4 Model 5
Flavonols (mg) Flavones (mg) Flavanones (mg)
β-coefficients
Flavanones (mg)
β-coefficients
Women (n = 2714)
Flavones (mg) Men (n = 1788)
p for trend
β-coefficients
p for trend
β-coefficients
p for trend
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