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Higher dietary flavone, flavonol, and catechin intakes are associated with less of an increase in BMI over time in women: a longitudinal analysis from the Netherlands Cohort Study^1,2,3

¹ From the Department of Epidemiology, School for Oncology and Developmental Biology (GROW) (PAvdB, MPW, and LAEH) and the Nutrition and Toxicology Research Institute, Maastricht University, Maastricht, Netherlands (NUTRIM) (ICWA and PCD); the Department of Methodology and Statistics, Maastricht University, Maastricht, Netherlands (TA); and the Department of Food and Chemical Risk Analysis (HAMB) and the Department of Prevention and Health (RAG), TNO Quality of Life, Zeist, Netherlands

² Supported by the Dutch Cancer Society and by a VENI Innovational Research Grant from the Netherlands Organization for Scientific Research—Earth and Life Sciences.

³ Address reprint requests and correspondence LAE Hughes, Maastricht University, Faculty of Health, Medicine and Life Sciences, Department of Epidemiology, PO Box 616, 6200 MD Maastricht, Netherlands. E-mail: laura.hughes{at}epid.unimaas.nl.s

	ABSTRACT

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Background: Dietary flavonoids are suggested to have antiobesity effects. Prospective evidence of an association between flavonoids and body mass index (BMI) is lacking in general populations.

Objective: We assessed this association between 3 flavonoid subgroups and BMI over a 14-y period in 4280 men and women aged 55–69 y at baseline from the Netherlands Cohort Study.

Design: Dietary intake was estimated at baseline (1986) by a validated food-frequency questionnaire. BMI was ascertained through self-reported height (in 1986) and weight (in 1986, 1992, and 2000). Analyses were based on sex-specific quintiles for the total intake of 6 catechins and of 3 flavonols/flavones. Linear mixed effect modeling was used to assess longitudinal associations in 3 adjusted models: age only, lifestyle (age, energy intake, physical activity, smoking status, alcohol intake, type 2 diabetes, and coffee consumption), and lifestyle and diet (vegetables, fruit, fiber, grains, sugar, dessert, and dieting habits).

Results: After adjustment for age and confounders, the BMI (kg/m²) of women with the lowest intake of total flavonols/flavones and total catechins increased by 0.95 and 0.77, respectively, after 14 y. Women with the highest intake of total flavonols/flavones and total catechins experienced a significantly lower increase in BMI of 0.40 and 0.31, respectively (between group difference: P < 0.05). This difference remained after additional adjustment for dietary determinants and after stratification of median baseline BMI. In men, no significant differences in BMI change were observed over the quintiles of flavonoid intake after 14 y.

Conclusion: Our results suggest that flavonoid intake may contribute to maintaining body weight in the general female population.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
It is well accepted that overweight and obesity are major contributors to the global burden of chronic disease and disability. According to the World Health Organization, an individual is considered overweight if his or her body mass index (BMI; in kg/m²) is >25 and obese if his or her BMI exceeds 30 (1). It is of great importance to determine effective and safe mechanisms for maintaining a healthy body weight as the prevalence of overweight, and obesity continues to rise at an alarming rate.

The role of dietary intake and modification for weight maintenance has traditionally been described in terms of macronutrients and micronutrients; however, emerging evidence suggests that the flavonoids, a group of nonnutritive phytochemicals with diverse beneficial biochemical and antioxidant effects (2–9), may be a dietary factor that can also modulate body weight (9–24). Present in foods of plant origin such as fruit, vegetables, tea, wine, seeds, herbs, spices, and whole grains, >6000 naturally occurring flavonoids have been identified and classified into 6 major subgroups: catechins, flavonols, flavones, flavanones, anthocyanins, and isoflavones (25).

Short-term studies using green tea as a source of catechins have shown a reduction in body weight and body fat compared with baseline measurements in overweight individuals (15, 17–20, 23, 24). The major catechins found in the diet are (+)-catechin, (–)-epicatechin, (–)-epigallocatechin (EGC), (+)-gallocatechin (GC), (–)-epicatechin gallate (ECG), and (–)-epigallocatechin gallate (EGCG) (26). Animal studies have shown that catechins increase energy expenditure, increase glucose uptake in skeletal muscle, decrease glucose uptake in adipose tissue, and prevent obesity in a dose-response fashion (22, 27). Additionally, animal studies have shown an antiobesity effect of the major dietary flavonols (quercetin, myricetin, and kaempferol) and the major dietary flavones (luteolin and apigenin) through mechanisms such as influences on glucose uptake and fatty acid catabolism (16, 21). Recent molecular data suggests that other subclasses of flavonoids may have an effect on adipokine secretion and up-regulation of gene expression (9–11, 13).

Applying the findings of human studies to the general population is difficult because of the short duration of the interventions and because they included primarily overweight and obese subjects (15, 17–20, 23, 24). The Netherlands Cohort Study on diet and cancer (NLCS) provided a unique opportunity to assess the association between flavonoid intake and BMI change over time in the general population. Because the majority of evidence suggesting an association between flavonoid intake and body weight currently exists for the catechin, flavonol, and flavone groups, we focused on only these 3 subclasses in the present study.

	SUBJECTS AND METHODS

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Subjects and study design
The NLCS is a prospective cohort study that was initiated in 1986 with the enrollment of 120 852 individuals in the Netherlands and with the purpose of investigating the association between diet and the development of cancer. The cohort included 58 279 men and 62 573 women between the ages of 55 and 69 y at baseline who completed a self-administered questionnaire on dietary habits, lifestyle, health, and demographic information. Municipal registries from throughout the Netherlands were used to constitute an efficient sampling frame reflective of the general population. Further details of the design of the NLCS were described in previous publications (28–30).

The NLCS is a case-cohort design with a subcohort of 5000 individuals randomly selected from the larger cohort on recruitment into the study. These individuals have been followed-up biennially from baseline in 1986 for migration and vital status to estimate person time at risk. Follow-up of the subcohort has also allowed for the additional accumulation of prospective data regarding a number of factors related to body weight and weight change. This subcohort was the study population used for the present study.

In our analysis, individuals who returned incomplete baseline dietary questionnaires, individuals with missing values for height or weight at baseline, and all prevalent cancer cases other than skin cancer at baseline were excluded. This resulted in an initial study population of 4280 individuals. Follow-up measurements specifically regarding BMI were recorded in the years 1992 and 2000, and data were available for 3787 and 2091 individuals, respectively, at these time points. The study protocol of the NLCS was approved by the Medical Ethics Committees of the University Hospital Maastricht and TNO Nutrition in February 1985 and July 1986, respectively.

Dietary assessment
The measurement instrument used to assess dietary flavonoid intake at baseline was a self-administered food-frequency questionnaire (FFQ) consisting of 150 food items (28–30). This dietary assessment was part of a larger questionnaire that also included questions regarding a number of lifestyle factors. The FFQ was aimed at habitual intake; therefore, dietary intake with a reference period of 1 y was assessed to account for seasonal variations in some foods, such as vegetables and fruit (28). For each item on the questionnaire, the frequency of consumption was asked on a scale consisting of 7 categories. The number of servings per consumption frequency was reported in natural units (eg, slice of bread) or household units (eg, spoonful) or the individual serving size in grams was asked. For some foods, the frequency categories were replaced by the number of serving units taken daily, weekly, or monthly. An open-ended question was included to account for any foods eaten regularly but not included in the questionnaire (30). Questionnaire data were key-entered twice and processed in a manner blinded with respect to case/subcohort status to minimize observer bias in the coding and interpretation of data. The questionnaire was shown to be valid and reliable and is described in greater detail elsewhere (28–30).

The major sources of dietary catechins and flavonol/flavone intake in our population are similar to other studies in the Dutch population. These include tea, apples, pears, chocolate, and broad beans for catechin intake (31, 32) and tea, onions, leek, apples, pears, and sweet peppers for flavonol/flavone intakes (33). Information regarding the flavonoid content in different foods and beverages on the questionnaire was required to enable the epidemiologic evaluation of these substances (32, 34–36). This was done individually for catechins, flavones, and flavonols for every item on the FFQ. To determine catechin concentrations, tables from Arts et al (31, 32) were used. These tables contain the catechin content of 24 different fruit and fruit varieties, 27 different types of vegetables and legumes, staple foods, processed foods, chocolate, 8 types of black tea, 18 types of red and white wine, apple juice, grape juice, iced tea, beer, chocolate milk, and coffee commonly consumed in the Netherlands. Furthermore, these products were sampled multiple times in different seasons and from different retail outlets (31, 32). Data by Hertog et al (34, 35), derived in a similar fashion, were used to determine the concentration of flavonols and flavones. Concentrations of each specific flavonoid are reported for each item on the FFQ in mg/100 g of fresh weight of edible portion of food and in mg/100 mL of beverage. The flavonoid content of each participant's diet was calculated by multiplying the reported consumption frequency and consumed quantity on the FFQ by the assigned flavonoid content of each food.

Ascertainment of BMI
Subjects were followed up biennially since the time of the baseline questionnaire. At these time points, additional self-administered questionnaires were mailed to all individuals given they were still alive and reachable at the same address. If necessary, new addresses were obtained and individuals were contacted there. Height (cm) was self-measured and reported on the baseline dietary questionnaire. Body weight (kg) was reported on questionnaires on 3 different occasions: at baseline in the autumn of 1986 and in the autumn of 1992 and 2000. In 1986 and 1992, the question was open-ended and phrased as "how much do you weigh now (kg)?" In 2000, subjects were asked "have you weighed yourself recently (yes/no)?" If the subjects answered "yes," they were directed to an open-ended question, "how much do you weigh (kg)?" At all 3 time points, the weight measurement was self-reported. BMI (in kg/m²) was calculated for each time point by using the recorded weight at each time point divided by height squared at baseline.

Statistical analysis
Data were analyzed by using Stata (version 9.2; Statacorp, College Station, TX). All analyses were conducted separately for catechin and flavonol/flavone intakes and were stratified by sex, because sex was shown to act as an effect modifier (data not shown). Flavonol and flavone intakes were considered together because flavones contributed minimally to total flavonoid intake. Sex-specific quintiles of total catechins, total flavonols/flavones, and specific catechin and flavonol compounds were assessed. Mean total flavonol/flavone intake and total catechin intake as well as other population characteristics were analyzed by using data from the baseline questionnaire. Pearson's correlation and one-factor analysis of variance was applied to determine the correlation between continuous variables and total flavonoid intake, and a chi-square test was used to assess the association between total flavonoid intake and categorical variables.

Linear mixed effect (LME) modeling was applied to assess the change in BMI over time and the longitudinal relation between flavonoid intake at baseline and BMI at baseline (1986), in 1992, and in 2000. The mixed model consists of 2 parts: fixed effects and random effects. Fixed effects describe population slopes for a set of considered covariates, which include exposures and confounders. Random effects describe individual variability in outcome and in changes over time. By considering individual random slopes, this model allowed us to examine the influence of covariates on the change in BMI over time (37). This model also accounts for the correlation between repeated measurements on the same subject and accounts for missing values at various time points (38).

For the LME model, a categorical time variable was created by using the values 0, 6, and 14; reflecting the time points (in y) of the BMI measurements from baseline. Two dummy variables indicating the 3 time points and 4 flavonoid intake dummy variables were entered into the model. Furthermore, interactions of the time dummies with the 4 flavonoid intake dummies (8 interaction terms) were included. A random slope for time at the individual level was obtained by using time as a continuous variable. Longitudinal information was derived by considering the regression coefficients of the time dummies and the regression coefficients of the flavonoid-time interaction terms. The coefficients of the time dummies reflect the change in BMI over time (6 and 14 y, respectively) in the lowest quintile. The coefficient of an interaction term gives the difference between the change in BMI in a quintile after 6 and 14 y and the change in BMI in the lowest quintile of flavonoid intake as the reference category.

In addition to an unadjusted and age adjusted model, we created an LME model adjusted for age plus confounding variables. These variables were identified as being associated with both BMI and flavonoid intake from the previous literature or were variables that, when entered in our model, resulted in a >10% change in the regression coefficients. These included age (y), total energy intake (kcal/d), coffee drinking (cups/d), physical activity (min/d), smoking status (current smoker, ex-smoker, and never smoker), alcohol intake (g/d), and the presence of type 2 diabetes (yes or no). Intervention research has shown a potential synergistic relation between caffeine and flavonoids (20); therefore, we performed an additional stratified analysis testing coffee drinking as a possible effect modifier.

We hypothesized that individuals with a high intake of dietary flavonoids would also have a healthier lifestyle and, as a result, less of an increase in BMI over time. Therefore, we created a fourth model additionally adjusted for fiber, fruit, vegetable, grain, desert, and sugar intakes (g/d) and dieting habits in the 5 y leading up to the baseline questionnaire (yes or no). Furthermore, we investigated whether an association was present over a range of BMI values or whether it would be present only in individuals who had the most weight to lose. Using median BMI at baseline (women: 24.64; men: 24.80) to classify individuals as having a low or high BMI, we conducted a stratified analysis adjusting for initial confounders and the extra dietary and lifestyle factors. Finally, although LME models should be robust to missing values, we conducted the initial analysis excluding individuals with missing BMI measurements at 1 or 2 time points (n = 1992 remaining) and excluding individuals who developed cancer between 1986 and 2000 (n = 3496 remaining). All models were tested for evidence of a linear trend by using the time-by-quintile interaction. Two-tailed P values <0.05 were considered statistically significant in all analyses.

	RESULTS

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Baseline population characteristics are presented in Table 1. Flavonoid intake was higher in women than in men for all investigated catechins and flavonols/flavones. Compared with women, men consumed more calories, drank more alcohol, and had a higher proportion of current and ex-smokers. For both men and women, higher flavonoid intake was associated with higher total energy intake, a smaller proportion of current smokers, and a higher level of physical activity. In men, higher intake was also associated with older age. The presence of type 2 diabetes did not differ across quintiles of intake in both sexes (data not shown). In both men and women, BMI increased slightly from baseline over time, although this increase was only significant in women (Table 2).

Figure 1

Figure 2

View larger version (15K): [in this window] [in a new window]   FIGURE 1.. Change in BMI (kg/m2) over 14 y for men in each quintile of total dietary flavonol/flavone intake (A; P for trend 0.06) and total dietary catechin intake (B; P for trend = 0.95). Graphs derived from linear mixed models adjusted for total energy intake, physical activity, smoking status, alcohol consumption, type 2 diabetes, coffee drinking, and age.

View larger version (17K): [in this window] [in a new window]   FIGURE 2.. Change in BMI (kg/m2) over 14 y for women in each quintile of total dietary flavonol/flavone intake (A; P for trend = 0.52) and total dietary catechin intake (B; P for trend = 0.08). Graphs derived from linear mixed models adjusted for total energy intake, physical activity, smoking status, alcohol consumption, type 2 diabetes, coffee drinking, and age. *Significantly lower BMI increase than in the lowest quintile, P < 0.05.

Table 3

Table 4

Table 5

Table 6

	DISCUSSION

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

Our finding of a protective association between catechin intake and BMI in women is supported by human intervention studies using tea or tea extracts as a treatment for overweight and obesity. Tsuchida et al (15) reported that, compared with controls, subjects consuming high levels of catechins experienced a significant decrease in BMI (0.49) after a 12-wk randomized controlled trial. Treatment consisted of 588 mg catechins/d; similar doses were used in other successful intervention studies (18, 20). In our study, the mean total catechin intake in women in the highest quintile was 125 mg/d. Because this is a much lower concentration than what was used in intervention studies, it is interesting that we still observed significant inverse associations with BMI, even after adjusting for all confounders. Because diet assessed through the FFQ in our study reflects the diet of individuals for an entire year preceding baseline, and has been observed to be stable for 5 y (29), a much longer exposure time to these substances is expected compared with the controlled intervention studies described above.

The observation that there was a protective association between myricetin and BMI in women is intriguing. Myricetin contributes minimally to the percentage of total flavonols in the daily diet (52, 53). In our population, tea, onions, and leeks contributed most to myricetin intake (33). Despite limited evidence in the literature suggesting a direct association between myricetin and obesity, evidence indicates that myricetin can improve the metabolic profile (54, 55). Although a chance finding cannot be ruled out, further research regarding the relation between myricetin and body weight would be of interest.

It is well accepted that major modifiers of BMI change are energy restriction and physical activity. Although we adjusted our models for these variables, we also recognized that, because flavonoids are derived from healthy foods, individuals with the highest flavonoid intake likely had an overall healthier lifestyle than did those with the lowest intake, and this phenomenon may result in less of a BMI increase over time. When we attempted to control for further potential confounding in our model by accounting for intake of vegetables, fruit, grains, fiber, sugar, deserts, and dieting habits, our observations did not change. Although residual confounding cannot be ruled out entirely, our results suggest that there is an independent association between dietary flavonoid intake and BMI change in women.

There was a clear association between flavonoid intake and BMI change in women, but this was not the case in men. Descriptive analyses at baseline showed that over each quintile of intake, mean consumption of both total flavonols/flavones and catechins was higher in women than in men. This observation is supported by a previous study examining catechin intake in the general Dutch population, which estimated the average intake of the 6 major catechins as 50 mg/d, with a significantly higher intake in women than in men (60 compared with 40 mg/d, respectively) (36). It is possible that flavonoid consumption in men may not have been high enough for an association to be observed. Additionally, our analysis showed that, in general, BMI increased much less over time in men than in women.

Our study had many strengths. Although only baseline data on flavonoid intake and other dietary information were available, the FFQ used in the NLCS was shown to be reproducible over a period of 5 y (29). It is well established that flavonoid concentrations can vary according to growing season, transportation, and food processing, and these limitations can result in inaccurate reporting of flavonoid concentrations in composition databases. We attempted to control for this by using sources of high quality to calculate the flavonoid concentrations of food on the FFQ (31, 32, 34, 35). However, it should be noted that the concentrations we calculated may still have been influenced by these limitations. Human intervention studies have generally administered tea, or specific catechins isolated from tea, as a treatment for weight loss. It has been proposed that the results from several of these studies were attributable to caffeine or to a synergistic effect between caffeine and catechins rather than to catechins alone (20). We considered coffee drinking a proxy for caffeine in our adjustment and also observed no effect modification in an additional analysis stratified for low and high coffee drinkers. However, it should be acknowledged that we could not account for all sources of dietary caffeine, such as from tea and cocoa. We considered flavonoid intake from the whole diet, which accounts for a wide variety of food sources and allowed for a more complete estimate of total flavonoid intake. Finally, we accounted for a number of lifestyle and dietary factors suggested to be important when studying the health effects of flavonoids using epidemiologic data (25, 36).

Our results are questionable because of the use of self-reported weight and height to ascertain BMI in our population. Although the measurement of self-reported weight was not independently validated in the NLCS, many examples in the literature suggest that this method is a valid and reliable tool for assessing body weight and height in cohort studies. Analysis of large cohorts conducted in the Japanese, British, Swedish, and American working population have all concluded that self-reported weight and height are generally valid and reliable (56–59); however, there is a general tendency for women, especially overweight women, to underreport weight and for men to overreport height. An underestimation of weight and an overestimation of height will underestimate BMI and, as a result, will underestimate the prevalence of overweight and obesity (56–58). Although misclassification could not be ruled out, the associations we observed between dietary flavonoid intake and BMI may actually have been stronger than we reported if the overweight women in our study had underestimated their weight

The age group of our population was also a limitation. The subjects were 55 y of age at baseline and thus became elderly over the course of the 14 y of the study. For many subcohort members, only 1 or 2 weight measurements were available for analysis. To check for survivorship bias, we conducted an additional analysis using only those subjects who reported all 3 BMI measurements, and our results did not change. Because of the design of the NLCS, we were also able to reconduct the analysis after eliminating individuals who developed cancer at some time point between 1986 and 2000. We observed that the BMI change in women in the highest quintile remained significantly lower over the 14 y period than did BMI change in the women with the lowest intake.

The FFQ used in the NLCS only measured flavonoid intake as derived from food in the daily diet. In response to the growing public interest in dietary supplements, especially with respect to weight loss and weight maintenance, epidemiologic studies should consider the effect of individual flavonoid extracts and supplements on BMI in addition to dietary food sources, and intervention studies should study the safety of consuming high concentrations of supplements on a regular basis (60, 61). Finally, although the bioavailability of flavonoid subclasses such as the anthocyanidins are quite low (62, 63), future studies may consider investigating the association between these flavonoids and BMI change, because emerging evidence suggests that they may also possess mechanisms to modulate body weight.

In conclusion, our finding of a significant inverse association between dietary flavonoid intake and BMI increase in women suggests that, over time, flavonoid intake may be useful for weight maintenance, even in persons who are not obese. On a population level, it is relatively easy to increase one's flavonoid intake through the daily diet.

	ACKNOWLEDGMENTS

 
We are indebted to the participants of this study and thank the cancer registries (IKA, IKL, IKMN, IKN, IKO, IKR, IKST, IKW, IKZ, and VIKC) and the Netherlands Nationwide Registry Pathology (PALGA). We also thank S van de Crommert and J Nelissen for their assistance with data entry and data management; A Volovics and A Kester for statistical advice; L van Amelsvoort for sharing his expertise on longitudinal data analysis; L Schouten, C de Zwart, M Moll, W van Dijk, M Jansen, and A Pisters for assistance; and H van Montfort, T van Moergastel, L van den Bosch, and R Schmeitz for programming assistance.

The authors' responsibilities were as follows—LAEH: carried out the statistical analysis, interpreted the data, and helped draft the manuscript; MPW, ICWA, and TA: assisted with the statistical analysis and data interpretation; MPW and ICWA: helped draft the manuscript, conceived the idea for the current research question, and critically revised the manuscript; PAvdB and RAG: conceived the study, participated in the design and coordination of the study, and critically revised the manuscript for important intellectual content; HAMB: developed the database of flavonoid composition of foods in the FFQ and critically revised the manuscript; and PCD: critically revised the manuscript. All authors approved the final version of the manuscript, and none of the authors had a conflict of interest.

	REFERENCES

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 

1. World Health Organization. The challenge of obesity in the WHO European Region. Copenhagen, Denmark: World Health Organization, 2005. (Factsheet EURO/13/05.)
2. Soobrattee MA, Neergheen VS, Luximon-Ramma A, et al. Phenolics as potential antioxidant therapeutic agents: mechanism and actions. Mutat Res 2005;579:200–13.[Medline]
3. Peterson J, Dwyer J. Flavonoids: dietary occurrence and biochemical activity. Nutr Res 1998;18:1995–2018.
4. Holt RR, Actis-Goretta L, Momma TY, Keen CL. Dietary flavanols and platelet reactivity. J Cardiovasc Pharmacol 2006;47(suppl 2):S187–96, discussion S206–189.[Medline]
5. Hollman PC, Katan MB. Dietary flavonoids: intake, health effects and bioavailability. Food Chem Toxicol 1999;37:937–42.[Medline]
6. Higdon JV, Frei B. Tea catechins and polyphenols: health effects, metabolism, and antioxidant functions. Crit Rev Food Sci Nutr 2003;43:89–143.[Medline]
7. Henning SM, Niu Y, Lee NH, et al. Bioavailability and antioxidant activity of tea flavanols after consumption of green tea, black tea, or a green tea extract supplement. Am J Clin Nutr 2004;80:1558–64.[Abstract/Free Full Text]
8. Aron PM, Kennedy JA. Flavan-3-ols: nature, occurrence and biological activity. Mol Nutr Food Res 2008;52:79–104.[Medline]
9. Prior RL, Wu X. Anthocyanins: structural characteristics that result in unique metabolic patterns and biological activities. Free Radic Res 2006;40:1014–28.[Medline]
10. Tsuda T, Horio F, Uchida K, et al. Dietary cyanidin 3-O-beta-D-glucoside-rich purple corn color prevents obesity and ameliorates hyperglycemia in mice. J Nutr 2003;133:2125–30.[Abstract/Free Full Text]
11. Tsuda T. Regulation of adipocyte function by anthocyanins; possibility of preventing the metabolic syndrome. J Agric Food Chem 2008;56:642–6.[Medline]
12. Prior RL, Wu X, Gu L, et al. Whole berries versus berry anthocyanins: interactions with dietary fat levels in the C57BL/6J mouse model of obesity. J Agric Food Chem 2008;56:647–53.[Medline]
13. Kwon SH, Ahn IS, Kim SO, et al. Anti-obesity and hypolipidemic effects of black soybean anthocyanins. J Med Food 2007;10:552–6.[Medline]
14. Wolfram S, Wang Y, Thielecke F. Anti-obesity effects of green tea: from bedside to bench. Mol Nutr Food Res 2006;50:176–87.[Medline]
15. Tsuchida T, Itakura H, Nakamura H. Reduction of body fat in humans by long term ingestion of catechins. Prog Med 2002;22:2189–203.
16. Strobel P, Allard C, Perez-Acle T, et al. Myricetin, quercetin and catechin-gallate inhibit glucose uptake in isolated rat adipocytes. Biochem J 2005;386:471–8.[Medline]
17. Rumpler W, Seale J, Clevidence B, et al. Oolong tea increases metabolic rate and fat oxidation in men. J Nutr 2001;131:2848–52.[Abstract/Free Full Text]
18. Ikeda I, Hamamoto R, Uzu K, et al. Dietary gallate esters of tea catechins reduce deposition of visceral fat, hepatic triacylglycerol, and activities of hepatic enzymes related to fatty acid synthesis in rats. Biosci Biotechnol Biochem 2005;69:1049–53.[Medline]
19. Dulloo AG, Duret C, Rohrer D, et al. Efficacy of a green tea extract rich in catechin polyphenols and caffeine in increasing 24-h energy expenditure and fat oxidation in humans. Am J Clin Nutr 1999;70:1040–5.[Abstract/Free Full Text]
20. Diepvens K, Kovacs EM, Vogels N, Westerterp-Plantenga MS. Metabolic effects of green tea and of phases of weight loss. Physiol Behav 2006;87:185–91.[Medline]
21. de Boer VC, van Schothorst EM, Dihal AA, et al. Chronic quercetin exposure affects fatty acid catabolism in rat lung. Cell Mol Life Sci 2006;63:2847–58.[Medline]
22. Choo JJ. Green tea reduces body fat accretion caused by high-fat diet in rats through beta-adrenoceptor activation of thermogenesis in brown adipose tissue. J Nutr Biochem 2003;14:671–6.[Medline]
23. Chantre P, Lairon D. Recent findings of green tea extract AR25 (Exolise) and its activity for the treatment of obesity. Phytomedicine 2002;9:3–8.[Medline]
24. Boschmann M, Thielecke F. The effects of epigallocatechin-3-gallate on thermogenesis and fat oxidation in obese men: a pilot study. J Am Coll Nutr 2007;26(suppl):389S–95S.[Abstract/Free Full Text]
25. Arts ICW, Hollman P. Polyphenols and disease risk in epidemiologic studies. Am J Clin Nutr 2005;81(suppl):317S–25S.[Abstract/Free Full Text]
26. Palermo CM, Hernando JI, Dertinger SD, et al. Identification of potential aryl hydrocarbon receptor antagonists in green tea. Chem Res Toxicol 2003;16:865–72.[Medline]
27. Wolfram S, Raederstorff D, Wang Y, et al. TEAVIGO (epigallocatechin gallate) supplementation prevents obesity in rodents by reducing adipose tissue mass. Ann Nutr Metab 2005;49:54–63.[Medline]
28. van den Brandt PA, Goldbohm RA, van 't Veer P, et al. A large-scale prospective cohort study on diet and cancer in The Netherlands. J Clin Epidemiol 1990;43:285–95.[Medline]
29. Goldbohm RA, van 't Veer P, van den Brandt PA, et al. Reproducibility of a food frequency questionnaire and stability of dietary habits determined from five annually repeated measurements. Eur J Clin Nutr 1995;49:420–9.[Medline]
30. Goldbohm R, van den Brandt P, Brants H, et al. Validation of a dietary questionnaire used in a large-scale prospective cohort study on diet and cancer. Eur J Clin Nutr 1994;48:253–65.[Medline]
31. Arts ICW, van De Putte B, Hollman P. Catechin contents of foods commonly consumed in The Netherlands. 2. Tea, wine, fruit juices, and chocolate milk. J Agric Food Chem 2000;48:1752–7.[Medline]
32. Arts ICW, van de Putte B, Hollman P. Catechin contents of foods commonly consumed in The Netherlands. 1. Fruits, vegetables, staple foods, and processed foods. J Agric Food Chem 2000;48:1746–51.[Medline]
33. Goldbohm RA, Hertog MGL, Brants HAM, et al. Intake of flavonoids and cancer risk: a prospective cohort study. In: Armado RAH, Bardocz S, Serra F, eds. Polyphenols in food. Aberdeen, United Kingdom: European Commission Publications, 1997:159–66.
34. Hertog MGL, Hollman PCH, van de Pute B. Content of potentially anticarcinogenic flavonoids of tea infusions, wines, and fruit juices. J Agric Food Chem 1993;41:1242–6.
35. Hertog MGL, Hollman PCH, MB K. Content of potentially anticarcinogenic flavonoids of 28 vegetables and 9 fruits commonly consumed in the Netherlands. J Agric Food Chem 1994;40:2379–83.
36. Arts ICW, Hollman PC, Feskens EJ, et al. Catechin intake and associated dietary and lifestyle factors in a representative sample of Dutch men and women. Eur J Clin Nutr 2001;55:76–81.[Medline]
37. Phillips SM, Bandini LG, Cyr H, et al. Dairy food consumption and body weight and fatness studied longitudinally over the adolescent period. Int J Obes Relat Metab Disord 2003;27:1106–13.[Medline]
38. Finucane MM, Samet JH, Horton NJ. Translational methods in biostatistics: linear mixed effect regression models of alcohol consumption and HIV disease progression over time. Epidemiol Perspect Innov 2007;4:8.[Medline]
39. Wu CH, Yang YC, Yao WJ, et al. Epidemiological evidence of increased bone mineral density in habitual tea drinkers. Arch Intern Med 2002;162:1001–6.[Abstract/Free Full Text]
40. Wu CH, Lu FH, Chang CS, et al. Relationship among habitual tea consumption, percent body fat, and body fat distribution. Obes Res 2003;11:1088–95.[Medline]
41. Tokunaga S, White IR, Frost C, et al. Green tea consumption and serum lipids and lipoproteins in a population of healthy workers in Japan. Ann Epidemiol 2002;12:157–65.[Medline]
42. Kono S, Shinchi K, Wakabayashi K, et al. Relation of green tea consumption to serum lipids and lipoproteins in Japanese men. J Epidemiol 1996;6:128–33.[Medline]
43. Imai K, Nakachi K. Cross sectional study of effects of drinking green tea on cardiovascular and liver diseases. BMJ 1995;310:693–6.[Abstract/Free Full Text]
44. Renehan AG, Tyson M, Egger M, et al. Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet 2008;371:569–78.[Medline]
45. World Cancer Research Fund. Food, nutrition, physical activity, and the prevention of cancer. Available from: http://www.dietandcancerreport.org (cited 3 September 2008).
46. Pischon T, Lahmann PH, Boeing H, et al. Body size and risk of colon and rectal cancer in the European Prospective Investigation Into Cancer and Nutrition (EPIC). J Natl Cancer Inst 2006;98:920–31.[Abstract/Free Full Text]
47. Holbrook TL, Barrett-Connor E, Wingard DL. The association of lifetime weight and weight control patterns with diabetes among men and women in an adult community. Int J Obes 1989;13:723–9.[Medline]
48. Czernichow S, Mennen L, Bertrais S, et al. Relationships between changes in weight and changes in cardiovascular risk factors in middle-aged French subjects: effect of dieting. Int J Obes Relat Metab Disord 2002;26:1138–43.[Medline]
49. Adams KF, Schatzkin A, Harris TB, et al. Overweight, obesity, and mortality in a large prospective cohort of persons 50 to 71 years old. N Engl J Med 2006;355:763–78.[Abstract/Free Full Text]
50. Huang Z, Willett WC, Manson JE, et al. Body weight, weight change, and risk for hypertension in women. Ann Intern Med 1998;128:81–8.[Abstract/Free Full Text]
51. Panico S, Palmieri L, Donfrancesco C, et al. Preventive potential of body mass reduction to lower cardiovascular risk: the Italian Progetto CUORE study. Prev Med 2008;47:53–60.[Medline]
52. Sampson L, Rimm E, Hollman PC, et al. Flavonol and flavone intakes in US health professionals. J Am Diet Assoc 2002;102:1414–20.[Medline]
53. Hertog M, Hollman P, Katan M, Kromhout D. Intake of potentially anticarcinogenic flavonoids and their determinants in adults in The Netherlands. Nutr Cancer 1993;20:21–9.[Medline]
54. Ong KC, Khoo HE. Effects of myricetin on glycemia and glycogen metabolism in diabetic rats. Life Sci 2000;67:1695–705.[Medline]
55. Abidov M, Ramazanov A, Jimenez Del Rio M, Chkhikvishvili I. Effect of Blueberin on fasting glucose, C-reactive protein and plasma aminotransferases, in female volunteers with diabetes type 2: double-blind, placebo controlled clinical study. Georgian Med News 2006;141:66–72.[Medline]
56. Wada K, Tamakoshi K, Tsunekawa T, et al. Validity of self-reported height and weight in a Japanese workplace population. Int J Obes (Lond) 2005;29:1093–9.[Medline]
57. Spencer EA, Appleby PN, Davey GK, Key TJ. Validity of self-reported height and weight in 4808 EPIC-Oxford participants. Public Health Nutr 2002;5:561–65.[Medline]
58. Nyholm M, Gullberg B, Merlo J, et al. The validity of obesity based on self-reported weight and height: implications for population studies. Obesity (Silver Spring) 2007;15:197–208.[Medline]
59. Bolton-Smith C, Woodward M, Tunstall-Pedoe H, Morrison C. Accuracy of the estimated prevalence of obesity from self reported height and weight in an adult Scottish population. J Epidemiol Community Health 2000;54:143–8.[Abstract/Free Full Text]
60. Schmidt M, Schmitz HJ, Baumgart A, et al. Toxicity of green tea extracts and their constituents in rat hepatocytes in primary culture. Food Chem Toxicol 2005;43:307–14.[Medline]
61. Galati G, Lin A, Sultan AM, O'Brien PJ. Cellular and in vivo hepatotoxicity caused by green tea phenolic acids and catechins. Free Radic Biol Med 2006;40:570–80.[Medline]
62. Mazza G. Anthocyanins and cardiovascular health. World of Food Science [serial online] 2007. Available from: http://www.worldfoodscience.org/pdf/WoFS_Anthocy_and_Cardiovascular_Health_April%2011_2007-Mazza.pdf (cited 11 April 2008).
63. Frank T, Netzel M, Strass G, et al. Bioavailability of anthocyanidin-3-glucosides following consumption of red wine and red grape juice. Can J Physiol Pharmacol 2003;81:423–35.[Medline]

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