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Dietary Total Antioxidant Capacity Is Associated with Diet and Plasma Antioxidant Status in Healthy Young Adults
RESEARCH Research and Professional Briefs
Dietary Total Antioxidant Capacity Is Associated with Diet and Plasma Antioxidant Status in Healthy Young Adults Ying Wang; Meng Yang, PhD; Sang-Gil Lee, MS; Catherine G. Davis, MS, RD; Sung I. Koo, PhD; Ock K. Chun, PhD, MPH
ARTICLE INFORMATION
ABSTRACT
Article history:
Dietary total antioxidant capacity (TAC), based on the cumulative antioxidant activities of all the antioxidants present in food, has been shown to be inversely associated with risks of chronic diseases. However, dietary TAC has not been validated for its relevance in a healthy young population or for reliability and predictability for antioxidant status. Our study aimed to validate TAC as a tool in assessing antioxidant intake and to investigate whether dietary TAC predicts plasma antioxidant status in a healthy young population. Sixty healthy, nonsmoking college students at the University of Connecticut ages 18 to 25 years were recruited. Thirty-day food records and two 12-hour fasting blood samples were collected for dietary and plasma antioxidant assessments. After adjustment for total energy intake, TAC from diet and supplement was positively correlated with intakes of carotenoids (P⬍0.01), beta carotene (P⬍0.05), -cryptoxanthin (P⬍0.05), flavonoids (P⬍0.0001), isoflavones (P⬍0.01), flavan-3-ols (P⬍0.01), flavones (P⬍0.05), and flavonols (P⬍0.0001). Dietary TAC was an independent predictor of plasma TAC determined by vitamin C equivalent antioxidant capacity (P⬍0.01) and by ferric-reducing ability of plasma (P⬍0.0001), plasma glutathione peroxidase (P⬍0.01), red blood cell glutathione peroxidase (P⬍0.05), ␣-tocopherol (P⬍0.05), and lutein (P⬍0.05). Results were similar for TAC from diet sources only. The findings suggest that dietary TAC is a good predictor of dietary and plasma antioxidant status in this sample of young adult men and women.
Accepted 17 May 2012
Keywords: Total antioxidant capacity (TAC) Plasma antioxidant status Antioxidant enzyme Diet Young adults Copyright © 2012 by the Academy of Nutrition and Dietetics. 2212-2672/$36.00 doi: 10.1016/j.jand.2012.06.007
J Acad Nutr Diet. 2012;112:1626-1635.
F
RUIT AND VEGETABLE CONSUMPTION HAS LONG been reported to be associated with lower incidence and mortality rates of several chronic diseases such as cardiovascular disease,1-4 cancer,1,2 and Alzheimer’s disease.3,4 One hypothesis of the protective effects is that all types of antioxidant compounds, including vitamin C, vitamin E, carotenoids, and phytochemicals such as flavonoids and proanthocyanidins could protect cells from free radical–induced oxidative damage. To consider the cumulative antioxidant capacity of all the antioxidants present in foods or body fluids, the concept of total antioxidant capacity (TAC) was introduced.5 It remains inconclusive which dietary antioxidants are responsible for the aforementioned associations with disease reduction, and no single antioxidant reflects overall quality of the diet. Moreover, several randomized controlled studies examining the protective mechanisms of some vitamin supplements or food extracts failed to present any beneficial results.6-8 Furthermore, high-dose and long-term use of vitamin supplements are drawing health concern due to their potential adverse effects.6-9 In contrast, intervention studies that investigate whole foods’ metabolic functions in human beings have reported positive results.6,7 For example, in a recent randomized controlled study, a diet high in antioxidants was shown 1626
JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS
to improve endothelial function measured by flow-mediated dilatation,6 indicating that combined multiple antioxidants in the diet might exert more beneficial effects on oxidative stress than a single antioxidant. If the antioxidant effect assumption is valid, dietary TAC, which is an integrated parameter that considers the overall antioxidant capacity of most of the known antioxidants, will be a useful tool when investigating the association between food consumption and disease risk. Dietary TAC has been shown to be a good indicator of diet antioxidant status in a group of postmenopausal women.8 In a young population, dietary TAC has been shown to be an indicator of diet quality because it had high association with the other two indicators of diet quality—Mediterranean energy density hypothesis– oriented dietary scores and non-Mediterranean hypothesis– oriented dietary scores;9 however, few studies assessed dietary TAC’s ability to predict dietary antioxidant status and plasma antioxidant status in a young population.10,11 Estimating dietary TAC is the first step in the validation process. But previous studies varied in the methodology of dietary TAC estimation.10-14 The variation comes from two components: dietary assessment methods (eg, food frequency questionnaire [FFQ], 24-hour dietary recall, and food record [FR]) and dietary TAC databases that were used. Most © 2012 by the Academy of Nutrition and Dietetics.
RESEARCH of the previous studies estimated dietary TAC by collecting dietary data from an FFQ.10-14 One of the limitations of an FFQ is inaccuracy of assessing usual diet intake, especially total energy by an FFQ.12 Dietary TAC was calculated by multiplying amount of a food item by its corresponding TAC value of unit weight from a food TAC database. Such a dietary TAC database includes a number of food items that were directly analyzed for TAC by analytical methods such as oxygen radical absorbance capacity, ferric reducing ability of plasma (FRAP), or Trolox equivalent antioxidant capacity (TEAC). A food TAC database is limited in number of food items and is not comparable to another database that uses different TAC assays. We collected dietary data by 30-day FR and used a nutrient TAC database where 45 forms of antioxidants from families of vitamin E, carotenoids, flavonoids, and procyanidines, as well as vitamin C and selenium, were analyzed by vitamin-C equivalent antioxidant capacity (VCEAC) method to calculate cumulative dietary TAC.13 Food records are regarded as the gold standard compared with other dietary assessment methodologies, due to the quantitatively accurate information on food consumed during the recording period. Compared with food TAC database, using nutrient TAC database to calculate theoretical TAC is not limited by the number of food items. Although there is no perfect assay that could capture all antioxidants, VCEAC modified from TEAC enables expression of plasma TAC in weight units, which are familiar to the public and easy to link with dietary TAC intake status. The aim of this study was to test the hypothesis that dietary TAC, estimated in a more precise way, is a good predictor of antioxidant intake and plasma antioxidant status in a healthy young population. In this study, if not otherwise stated, dietary TAC refers to TAC from diet and supplements.
METHODS Study Population and Design A cross-sectional study was conducted in 60 (20 men and 40 women) healthy young college students. Participants 18 to 25 years of age who were apparently healthy, with a normal body mass index range for height and weight, were recruited through flyers and e-mails from the University of Connecticut in Storrs. Participants were excluded if they were taking any prescribed medication or had a history of certain chronic conditions or diseases, including cardiovascular disease, certain cancers, and chronic obstructive pulmonary disease. This project and its procedures were reviewed and approved by the Human Investigation Review Committee of the University of Connecticut. Written informed consent was obtained from each study participant. All participants were compensated for participating in the study. At the initial visit, participants completed a brief physical examination, including measured weight, height, and blood pressures, and a fasting blood finger stick blood sample, followed by a survey (College Student Health and Nutrition Survey) regarding their medical, dietary, and tobacco and alcohol consumption histories. Weight and height were measure by an electronic scale (Detecto); blood pressure was measured twice using an automatic blood pressure monitor (Omron HEM-780) while the participant was seated. The fasting finger stick blood sample was used to measure lipid profile (Cholestech LDX). Final inclusion in the study was determined based on the health examination results and self-reported October 2012 Volume 112 Number 10
health and nutrition history. The study was a 30-day observational study, without any specific treatment or intervention. Eligible participants completed the first blood draw at the initial visit. Participants also were instructed to follow their usual dietary habits, and they were educated on how to record food and supplement intake by an experienced research staff member. Participants were asked to send their FRs to the research staff through a daily e-mail message during the 30 days. The rationale of collecting 30-day food records was that our recent study found the number of days required to obtain stable intake information on most antioxidants was ⬎7 days but ⬍30 days (C. G. Davis, MS, and colleagues, unpublished data, May 2011). The final visit occurred 30 days after the initial visit. Participants completed a second blood draw, survey, and body measurement, as well as the final FR. In total, 77 eligible participants were recruited, with 22% attrition over the 30 days.
Dietary Assessment Each participant’s 30-day FR was entered into Nutrition Data System for Research software (version 2010, Nutrition Coordinating Center, University of Minnesota) for food composition analyses. Because the Nutrition Data System for Research does not provide flavonoid and proanthocyanidin intake data, intakes of these food components were estimated by matching food consumption data with nutrients in flavonoids and proanthocyanidins as described previously.14 Each participant’s individual antioxidant intake was estimated by multiplying the content of 43 individual antioxidants (29 flavonoids, three proanthocyanidins, seven carotenoids, two vitamins E, vitamin C, and selenium) by the daily consumption of each selected food item and supplement. Individual antioxidant capacity was then determined by multiplying the individual amount of each antioxidant compound by their respective antioxidant capacities expressed as VCEAC from a nutrient TAC database.13 Dietary TAC was determined by summating the individual antioxidant capacities. In this study, the TAC values of participants’ diets were expressed as mg vitamin C equivalents (VCE) per day.
Blood Collection and Plasma Antioxidant Analyses Twelve-hour fasting blood samples were collected in evacuated containers with ethylenediaminetetraacetic acid or heparin at the first and last visits, respectively. All plasma biomarkers were calculated as the average of first and last values to represent usual in vivo status during the 30-day period. Samples were centrifuged immediately in a dark room at 500g for 15 minutes at 4⬚C. Plasma samples were then separated in small aliquots and stored at ⫺80⬚C until analysis. After removing plasma and white buffy layer (leukocytes), erythrocytes were lysed in 4 vol ice-cold high-performance liquid chromatography (HPLC)-grade water and centrifuged at 10,000g for 15 minutes at 4⬚C. Erythrocyte lysate was then separated in small aliquots and stored at ⫺80⬚C until analysis. The outcome measures included plasma TAC; glucose; lipid profiles (total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol); plasma antioxidant nutrients; and enzymes. Glucose and lipids were analyzed as potential covariates that may affect plasma antioxidant status. Plasma TAC was determined by VCEAC and FRAP assays, respectively. VCEAC assay, which was developed JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS
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RESEARCH by Miller and colleagues15 and modified by Kim and colleagues,16 measures the 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) radical chromogen at 734 nm, using 2,2’-Azobis(2-amidinopropane) dihydrochloride as a thermolabile water-soluble radical initiator. The reduction of 2,2’azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) radical chromogen is proportional to the TAC in plasma. The results were expressed as mg VCE per liter plasma. The FRAP assay determines the ability of the sample to reduce ferric iron to ferrous iron in a low-pH environment. A colored ferroustripyridyltriazine complex is formed during this process and has a maximum absorbance at 593 nm.17 The results are expressed as mol Trolox per liter plasma. Plasma total phenolics were analyzed using the Folin-Ciocalteu method described by another study.18 Briefly, 200 L diluted plasma were mixed with 200 L Folin-Ciocalteu reagent (Sigma) and allowed to stand for 6 minutes. Two milliliters of 7% sodium carbonate (Sigma) solution was added to each sample and allowed to stand at room temperature for 90 minutes. Absorbance was read at 750 nm vs prepared blank. Plasma vitamin C and uric acid were determined as described19 using HPLC (Agilent Technology 1200) with a UV detector, separated with an Eclipse XDB-C18 column (5 m; 250 mm⫻4.6 mm) (Agilent Technology) and Zorbax C18 guard column (5 m; 12 mm⫻4.6 mm) (Agilent Technology). Vitamin E (as ␣- and ␥-tocopherol) and carotenoids were measured simultaneously by the HPLC system (Agilent 1100, Hewlett Packard) with a photodiode array detector and a C18 RP Symmetry analytical column (5 m, 250 mm⫻4.6 mm) (Agilent Technology), as described previously.20,21 Superoxide dismutase, catalase (CAT), and glutathione peroxidase (GPx) activities in plasma and red blood cells (RBC) were determined using commercially available kits (Cayman Chemical Company). Enzyme activities in RBCs were expressed as units per gram hemoglobin. Hemoglobin concentrations were determined using a commercially available kit (QuantiChrom hemoglobin assay, BioAssay Systems).
Statistical Analysis All statistical analyses were conducted using Statistical Analysis Software (version 9.2, 2009, SAS Institute Inc). To test the assumptions of general linear model, residual and goodness of fit were analyzed. All dietary and plasma antioxidant variables were log transformed to meet the underlying assumption. To evaluate associations between dietary or plasma antioxidants and dietary TAC, subjects were equally divided into three groups according to dietary TAC intake. P values were tested across the median values of dietary TAC in each group by analysis of covariance using the General Linear Model procedure. To examine relationships between dietary TAC and dietary antioxidants, data were adjusted by age, sex, and total energy intake. To examine associations between dietary TAC and plasma levels, data were analyzed by two models. The simple model was adjusted for age, ethnicity, and plasma cholesterol (except ascorbic acid and uric acid). To test the sensitivity of dietary TAC as a predicting tool, the simple model was further adjusted for fruit and fruit juices, vegetable and vegetable juices, and supplement use, which are the major contributors to dietary TAC. Data were reported as geometric least square means and 95% CIs if strongly skewed. The level of statistical significance was set at P⬍0.05. 1628
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RESULTS AND DISCUSSION Dietary TAC Intake According to Demographic, Clinical, and Dietary Characteristics In this study population, the mean intake of TAC from diet was 456 mg VCE/day, and the mean TAC from both diet and supplement was 496 mg VCE/day. Although 68% of participants used supplements, the quantity and frequency of supplement use was not significant. Consequently the results were similar when either diet alone or diet and supplement as an indicator of plasma antioxidant status was tested. As shown in Table 1, dietary TAC was higher in older participants, vegetarians, and participants who had higher intakes of energy, tea, fruits and fruit juices, and vegetables and vegetable juices (P⬍0.05) when participants were divided into three groups by their dietary TAC values. Vegetarian status was self-reported by the participants in the College Student Health and Nutrition Survey form. Being a vegetarian or vegan has been identified as a strong predictor of fruit and vegetable consumption.22 Expectedly, highest dietary TAC intake had the largest number of self-reported vegetarians; however, the P value was not significant, possibly due to the small sample size. A previous study has shown the main sources of dietary TAC in a group of healthy postmenopausal women in the United States as fruits and fruit juices, vegetables and vegetable juices, tea, wine, and supplements.8 Similarly, in this younger group of men and women, higher dietary TAC consumers reported greater intakes of fruits and fruit juices, vegetables and vegetable juices, and tea.
Association between TAC from Both Diet and Supplements and Individual Dietary Antioxidants After adjustment for total energy intake, TAC from diet and supplements was positively associated with total carotenoids (P⬍0.01) and its subgroups such as beta carotene (P⬍0.05) and -cryptoxanthin (P⬍0.05), as well as flavonoids (P⬍0.0001) and its subgroups isoflavones (P⬍0.01), flavan-3-ols (P⬍0.01), flavones (P⬍0.05), and flavonols (P⬍0.0001) (Table 2). But TAC from diet and supplements was negatively associated with ␥-tocopherol (P⬍0.0001). Similar results were found for TAC from diet only (data not shown). Evidence indicates that antioxidant intake is, more consistently than fruit and vegetable intake, associated with a reduction in the risk of chronic diseases such as type 2 diabetes.23 In our study, data suggest that dietary TAC is an effective dietary predictor of antioxidant intake. Several observational studies already found a favorable role of dietary TAC in endothelial and lung function6,24 and negative associations with risks of ischemic stroke, rectal cancer,25,26 metabolic syndrome,27 and biomarkers of cardiovascular disease.28
Association between TAC from Both Diet and Supplements and Individual Plasma Antioxidants and Enzymes After adjustment for basic factors that include age, sex, ethnicity, total energy intake, and plasma cholesterol (as well as uric acid for FRAP and VCEAC) in the simple model, TAC from diet and supplement was positively correlated with plasma TAC measured by FRAP (P⬍0.0001) and VCEAC (P⬍0.01), whereas the third group had significantly higher VCEAC than the first two groups (Table 3). Meanwhile, TAC from diet and October 2012 Volume 112 Number 10
October 2012 Volume 112 Number 10
Table 1. Demographic, clinical, and dietary characteristics according to the dietary total antioxidant capacity (TAC) levels of healthy young adultsa TAC from Diet and Supplements
TAC from Diet Characteristic
T1 (nⴝ20)
T2 (nⴝ20)
T3 (nⴝ20)
30.6-246
254-427
448-2,345
b
P value
T1 (nⴝ20)
T2 (nⴝ20)
T3 (nⴝ20)
117-284
293-448
453-2,428
P value
TAC level Range (mg vitamin C equivalents/d) Median (mg V vitamin C equivalents/d)
194
334
577
207
356
647
Mean (mg vitamin C equivalents/d)
184
337
848
207
369
913
4™™™™™ mean⫾standard deviation ™™™™™3
4™™™™™ mean⫾standard deviation ™™™™™3
Participant characteristic Age (y)
18.8⫾1.0
20.1⫾.1.7
20.5⫾2.0
⬍0.01
18.9⫾1.0
20.1⫾1.8
20.4⫾2.0
⬍0.05
Body mass index
23.3⫾2.3
23.3⫾2.1
22.7⫾3.6
NSc
23.4⫾2.2
23.1⫾2.4
22.8⫾3.4
NS
Fasting glucose (mg/dL)
83.8⫾6.3
82.6⫾10.9
84.6⫾5.0
NS
83.1⫾5.2
82.4⫾10.8
85.3⫾6.0
NS
Triglycerides (mg/dL)e
87.8⫾31.4
79.4⫾30.3
75.7⫾32.4
NS
91.3⫾29.1
81.9⫾36.2
70.2⫾25.5
NS
d
f
163⫾28.9
165⫾37.1
149⫾25.2
NS
166⫾29.2
163⫾36.3
148⫾25.6
NS
High-density lipoprotein cholesterol (mg/dL)f
62.1⫾11.8
63.6⫾14.3
58.9⫾14.7
NS
62.7⫾11.5
63.1⫾14.7
58.7⫾14.6
NS
Supplement use (%)
70
65
70
NS
65
65
75
NS
5
5
20
NS
5
5
20
NS
Vegetarian (%) Food intake Energy intake (kcal/d)
1,798⫾660
2,154⫾675
2,281⫾598
⬍0.05
1,803⫾634
2,174⫾674
2,257⫾634
⬍0.05
Tea (serving/d)
0.16⫾0.10
0.14⫾0.11
0.83⫾0.95
⬍0.0001
0.16⫾0.10
0.17⫾0.15
0.85⫾0.97
⬍0.001
Wine (serving/d)
0.12⫾0.15
0.13⫾0.16
0.12⫾0.21
NS
0.12⫾0.15
0.12⫾0.16
0.12⫾0.22
NS
Beer (serving/d)
0.20⫾0.20
0.36⫾0.48
0.73⫾0.58
NS
0.17⫾0.19
0.40⫾0.49
0.73⫾0.58
⬍0.05
Fruits and fruit juices (serving/d)
1.44⫾0.98
1.94⫾0.93
2.34⫾1.83
⬍0.05
1.53⫾0.94
1.89⫾0.95
2.30⫾1.88
⬍0.05
Vegetables and vegetable juices (serving/d)
2.76⫾1.01
3.57⫾1.66
3.97⫾1.27
⬍0.05
2.63⫾0.98
3.73⫾1.55
3.93⫾1.35
⬍0.01
a
Participants were ranked according to dietary TAC levels and divided evenly into three groups: T1, T2, and T3. Continuous variables were examined using general linear model. Categorical variables were examined with 2 analysis. c NS⫽not significant. d To convert mg/dL glucose to mmol/L, multiply mg/dL by 0.0555. To convert mmol/L glucose to mg/dL, multiply mmol/L by 18.0. Glucose of 108 mg/dL⫽6.0 mmol/L. e To convert mg/dL triglyceride to mmol/L, multiply mg/dL by 0.0113. To convert mmol/L triglyceride to mg/dL, multiply mmol/L by 88.6. Triglyceride of 159 mg/dL⫽1.80 mmol/L. f To convert mg/dL cholesterol to mmol/L, multiply mg/dL by 0.026. To convert mmol/L cholesterol to mg/dL, multiply mmol/L by 38.6. Cholesterol of 193 mg/dL⫽5.00 mmol/L. b
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JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS
Cholesterol, total (mg/dL)
JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS
Variable
Model
T1 (nⴝ20)
T2 (nⴝ20)
T3 (nⴝ20)
P valueb
TAC from diet and supplements Range (mg vitamin C equivalents/d)
117-284
293-448
453-2,428
Median (mg vitamin C equivalents/d)
207
356
647
Mean (mg vitamin C equivalents/d)
207
369
913
Individual antioxidants
Geometric mean
Tocopherol intakec (mg/d)
␣-Tocopherol (mg/d) ␥-Tocopherol (mg/d) Ascorbic acid (mg/d) Carotenoid intake (mg/d)
␣-Carotene (mg/d) October 2012 Volume 112 Number 10
-Cryptoxanthin (mg/d) Lutein⫹zeaxanthin (mg/d) Lycopene (mg/d)
Geometric mean
95% CI
Geometric mean
95% CI
Basic
33.4
(20.6, 54.1)
52.1
(32.2, 84.4)
84.5
(52.2, 137)
⬍0.05
Adjustedd
38.1
(22.5, 64.4)
49.5
(30.3, 81.0)
78.1
(47.1, 129)
NSe
Basic
15.1
(8.0, 28.3)
28.5
(15.2, 53.5)
55.3
(29.5, 104)
⬍0.05
Adjusted
17.0
(8.5, 33.9)
27.2
(14.2, 52.0)
51.6
(26.5, 100)
NS
Basic
11.1
(9.3, 13.3)
12.6
(10.5, 15.0)
10.4
(8.7, 12.5)
NS
Adjusted
13.2
(11.6, 15.1)
11.8
(10.4, 13.3)
9.4
(8.3, 10.7)
⬍0.0001
Basic
209
(112, 389)
350
(188, 651)
655
(352, 1,218)
⬍0.05
Adjusted
199
(102, 387)
357
(191, 667)
675
(356, 1,282)
NS
Basic Adjusted
-Carotene (mg/d)
95% CI
8.9
(7.0, 11.2)
12.4
(9.9, 15.7)
15.2
(12.1, 19.2)
⬍0.01
10.1
(8.0, 12.7)
11.7
(9.4, 14.6)
14.2
(11.4, 17.8)
⬍0.01
Basic
2.2
(1.6, 3.1)
3.4
(2.5, 4.7)
4.4
(3.2, 6.1)
⬍0.05
Adjusted
2.4
(1.7, 3.3)
3.3
(2.4, 4.6)
4.3
(3.1, 6.0)
⬍0.05
Basic
0.31
(0.19, 0.50)
0.39
(0.24, 0.63)
0.67
(0.41, 1.10)
NS
Adjusted
0.31
(0.18, 0.53)
0.37
(0.23, 0.62)
0.69
(0.41, 1.20)
NS
Basic
0.08
(0.05, 0.12)
0.16
(0.10, 0.25)
0.14
(0.09, 0.22)
⬍0.05
Adjusted
0.09
(0.06, 0.14)
0.15
(0.10, 0.22)
0.13
(0.08, 0.20)
⬍0.05
Basic
1.5
(1.1, 2.1)
2.6
(1.9, 3.5)
2.4
(1.8, 3.3)
⬍0.05
Adjusted
1.7
(1.2, 2.3)
2.5
(1.8, 3.4)
2.3
(1.7, 3.2)
NS
Basic
4.1
(3.0, 5.6)
4.4
(3.3, 6.1)
5.5
(4.1, 7.5)
NS
Adjusted
5.1
(3.8, 7.0)
4.1
(3.1, 5.5)
4.8
(3.6, 6.5)
⬍0.05
(continued on next page)
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Table 2. Comparison of dietary intakes of individual antioxidants according to the levels of total antioxidant capacity (TAC) from diet and supplements in healthy young adultsa
October 2012 Volume 112 Number 10
Table 2. Comparison of dietary intakes of individual antioxidants according to the levels of total antioxidant capacity (TAC) from diet and supplements in healthy young adultsa (continued) Variable Flavonoid intake (mg/d) Isoflavones (mg/d) Anthocyanidins (mg/d) Flavan-3-ols (mg/d)
T1 (nⴝ20)
Basic
37.3
(26.7, 52.1)
72.8
(52.1, 102)
181
(129, 253)
⬍0.0001
Adjusted
41.3
(28.7, 59.5)
69.9
(49.7, 98.3)
170
(120, 241)
⬍0.0001
Basic
1.0
(0.6, 1.8)
2.5
(1.4, 4.4)
2.8
(1.6, 5.0)
⬍0.05
1.3
(0.7, 2.3)
2.3
(1.3, 4.0)
2.4
(1.4, 4.3)
⬍0.01
Basic
6.6
(3.3, 12.9)
11.0
(5.6, 21.6)
7.8
(4.0, 15.4)
NS
Adjusted
7.8
(3.8, 15.8)
9.9
(5.1, 19.2)
7.4
(3.7,14.6)
NS
Basic
Flavonols (mg/d) Proanthocyanidins (mg/d)
9.1
(4.4, 18.8)
21.3
(10.3, 44.2)
84.8
(40.9, 176)
⬍0.001
10.7
(4.9, 23.6)
19.3
(9.2, 40.4)
79.0
(37, 168)
⬍0.01
Basic
4.8
(2.8, 8.3)
6.0
(3.5, 10.3)
6.6
(3.8, 11.2)
NS
Adjusted
5.4
(3.0, 9.6)
5.6
(3.3, 9.6)
6.3
(3.6, 11.0)
NS
Basic
0.9
(0.6, 1.3)
1.0
(0.7, 1.5)
1.5
(1.0, 2.2)
NS
Adjusted
1.1
(0.7, 1.6)
0.9
(0.6, 1.3)
1.4
(0.9, 2.0)
⬍0.05
Basic
7.0
(5.8, 8.4)
11.9
(9.8, 14.3)
18.8
(15.6, 22.7)
⬍0.0001
Adjusted
7.7
(6.3, 9.4)
11.5
(9.6, 13.9)
17.6
(14.5, 21.2)
⬍0.0001
Basic
43.4
(25.2, 74.8)
75.0
(43.5, 129)
80.7
(46.8, 139)
NS
Adjusted
54.0
(30.6, 95.3)
67.1
(39.5, 114)
72.5
(42.1, 125)
NS
a
Participants were ranked according to TAC from diet and supplements and divided evenly into three groups: T1, T2, and T3. Antioxidant intake data were log transformed for test. P value was calculated across the median value of intake of TAC from diet in each tertile using general linear model. Tocopherols include ␣-, -, ␥-, and ␦-tocopherols. d Model was adjusted for age, sex, and total energy intake. e NS⫽not significant. b c
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Flavones (mg/d)
T3 (nⴝ20)
Adjusted
Adjusted Flavanones (mg/d)
T2 (nⴝ20)
P valueb
Model
JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS
Intake
Model
T1 (nⴝ20)
T2 (nⴝ20)
T3 (nⴝ20)
117-284
293-448
453-2,428
P valueb
TAC from diet and supplements Range (mg vitamin C equivalents/d) Median (mg vitamin C equivalents/d)
207
356
647
Mean (mg vitamin C equivalents/d)
207
369
913
Geometric mean
95% CI
Geometric mean
95% CI
Geometric mean
95% CI
Antioxidant enzymes Plasma superoxide dismutase (U/mL) Red blood cell superoxide dismutase (U/g hemoglobin) Plasma catalase (U/mL)
Model 1c
8.1
(7.2, 9.2)
9.0
(8.0, 10.1)
8.7
(7.7, 9.7)
NSd
Model 2e
8.1
(7.2, 9.2)
9.0
(8.0, 10.1)
8.6
(7.7, 9.7)
NS NS
Model 1
831
(756, 913)
801
Model 2
841
(764, 926)
806
Model 1
Plasma glutathione peroxidase (U/mL) Red blood cell glutathione peroxidase (U/g hemoglobin)
(18.4, 30.4)
24.6
(18.3, 30.9)
784
(714, 862)
(736, 882)
770
35.2
(29.4, 40.9)
35.1
(29.2, 40.9)
(699, 847)
NS
24.5
(18.7, 30.3)
⬍0.05
24.3
(18.4, 30.3)
⬍0.05
Model 1
21,943
(18,165, 26,505)
18,694
(15,604, 22,396)
18,526
(15,337, 22,378)
NS
Model 2
22,314
(18,259, 27,268)
18,665
(15,474, 22,514)
18,245
(14,941, 22,279)
NS
Model 1
155
(143, 168)
179
(168, 191)
192
(180, 204)
⬍0.01
Model 2
155
(142, 168)
179
(167, 191)
192
(180, 204)
⬍0.01
Model 1
1,921
(1,606, 2,298)
1,972
(1,662, 2,341)
1,986
(1,660, 2,375)
⬍0.05
Model 2
1,923
(1,600, 2,311)
2,008
(1,691, 2,385)
1,950
(1,623, 2,342)
NS
Model 2 Red blood cell catalase (U/g hemoglobin)
24.4
(732, 876)
Antioxidant nutrients October 2012 Volume 112 Number 10
Ascorbic acid (mol/L) Total phenolics (mg gallic acid equivalent/L)
␣-Tocopherol (mol/L)
Model 3f
71.7
(66.4, 76.9)
67.0
(62.2, 71.8)
71.9
(66.9, 76.9)
NS
Model 4g
72.4
(67.2, 77.7)
67.0
(62.2, 71.8)
71.2
(66.1, 76.2)
NS
Model 1
2,530
(2,460, 2,600)
2,525
(2,458, 2,591)
2,596
(2,529, 2,663)
NS
Model 2
2,537
(2,464, 2,609)
2,520
(2,453, 2,588)
2,594
(2,525, 2,663)
NS
Model 1
21
(18.4, 23.9)
23.4
(20.7, 26.5)
24.7
(21.6, 28.1)
⬍0.05
Model 2
21.3
(18.7, 24.4)
23.1
(20.4, 26.2)
24.6
(21.5, 28.1)
⬍0.05
(continued on next page)
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Table 3. Plasma antioxidant profiles according to levels of total antioxidant capacity (TAC) from diet and supplements in healthy young adultsa
October 2012 Volume 112 Number 10
Table 3. Plasma antioxidant profiles according to levels of total antioxidant capacity (TAC) from diet and supplements in healthy young adultsa (continued) Intake
Model
␥-Tocopherol (mol/L)
Model 1
9.5
(7.4, 12.1)
10.7
(8.5, 13.5)
9.9
Model 2
8.6
(7.0, 10.7)
11.1
(9.1, 13.6)
10.5
Model 1
0.58
(0.43, 0.77)
0.78
(0.59, 1.02)
Model 2
0.63
(0.48, 0.83)
0.74
(0.58, 0.95)
Model 1
0.18
(0.12, 0.26)
0.27
Model 2
0.20
(0.14, 0.29)
0.25
Model 1
0.11
(0.08, 0.15)
Model 2
0.12
(0.08, 0.16)
Model 1
0.18
Model 2
0.19
Model 1 Model 2
Total carotenoids
-Carotene (mol/L) ␣-Carotene (mol/L) -Cryptoxanthin (mol/L) Lutein (mol/L) Zeaxanthin (mol/L)
Uric acid (mol/L) TAC by vitamin C equivalent antioxidant capacity (mg vitamin C equivalents/L) TAC by ferric reducing ability of plasma (molTrolox/L)
T2 (nⴝ20)
P valueb
T3 (nⴝ20) (7.7, 12.7)
NS
(8.5, 13)
⬍0.01
0.83
(0.62, 1.11)
NS
0.8
(0.61, 1.05)
NS
(0.19, 0.39)
0.26
(0.17, 0.38)
NS
(0.18, 0.36)
0.24
(0.17, 0.35)
NS
0.13
(0.09, 0.18)
0.24
(0.17, 0.33)
NS
0.12
(0.09, 0.17)
0.23
(0.17, 0.32)
NS
(0.13, 0.25)
0.21
(0.16, 0.29)
0.22
(0.16, 0.31)
NS
(0.14, 0.26)
0.20
(0.15, 0.27)
0.22
(0.16, 0.30)
NS
0.016
(0.012, 0.023)
0.024
(0.017, 0.032)
0.021
(0.015, 0.029)
NS
0.017
(0.012, 0.024)
0.022
(0.017, 0.03)
0.021
(0.015, 0.029)
⬍0.05
Model 1
0.039
(0.033, 0.046)
0.041
(0.035, 0.048)
0.037
(0.031, 0.043)
NS
Model 2
0.040
(0.034, 0.047)
0.040
(0.034, 0.046)
0.037
(0.031, 0.043)
NS
Model 1
0.036
(0.029, 0.045)
0.033
(0.027, 0.04)
0.028
(0.022, 0.035)
NS
Model 2
0.037
(0.029, 0.047)
0.032
(0.026, 0.04)
0.027
(0.021, 0.035)
NS
Model 3
287
(258, 316)
308
(282, 334)
320
(292, 347)
⬍0.05
Model 4
288
(258, 318)
308
(281, 335)
319
(290, 348)
NS
Model 5h
294
(284, 304)
290
(281, 299)
302
(293, 311)
⬍0.01
Model 6i
294
(284, 305)
289
(280, 299)
302
(292, 311)
⬍0.05
Model 5
501
(473, 528)
519
(494, 545)
524
(498, 550)
⬍0.0001
Model 6
502
(473, 531)
518
(491, 544)
524
(497, 551)
⬍0.001
a
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Participants were ranked according to TAC from diet and supplements and divided evenly into three groups: T1, T2, and T3. Plasma antioxidant variables were log transformed for test. P value was calculated across the median value of intake of TAC from diet in each tertile using general linear model. c Model was adjusted for age, sex, ethnicity, total energy intake, and plasma cholesterol. d NS⫽not significant. e Model was adjusted for age, sex, ethnicity, total energy intake, plasma cholesterol, fruit and fruit juice intake, vegetable and vegetable juice intake, and supplement use. f Model was adjusted for age, sex, ethnicity, and total energy intake. g Model was adjusted for age, sex, ethnicity, total energy intake, fruit and fruit juice intake, vegetable and vegetable juice intake, and supplement use. h Model was adjusted for age, sex, ethnicity, total energy intake, plasma cholesterol, and uric acid. i Model was adjusted for age, sex, ethnicity, total energy intake, plasma cholesterol, uric acid, fruit and fruit juice intake, vegetable and vegetable juice intake, and supplement use. b
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JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS
Lycopene (mol/L)
T1 (nⴝ20)
RESEARCH supplement paralleled plasma ␣-tocopherol (P⬍0.05) and uric acid (P⬍0.05) in the simple model. For the antioxidant enzymes, plasma and RBC GPx (P⬍0.01 and P⬍0.05, respectively) levels increased with TAC across the three groups; plasma CAT level was significantly higher in the second groups than the other two groups (P⬍0.05). After further adjustment for fruit and vegetable intakes as well as supplement use, the trend for uric acid and RBC GPx disappeared. Diets of participants in the highest TAC intake group were higher in ␣-tocopherol, vitamin C, carotenoids, especially beta carotene and -cryptoxanthin, as well as flavonoids compared with low and medium TAC consumers. However, highest TAC consumers did not have the highest corresponding plasma antioxidants except ␣-tocopherol. One plausible reason is that the bioavailability was low for those nutrients or affected by the food matrix consumed together.29 The other possible reason is that plasma was saturated with these antioxidants attributed to the supplement use. For example, plasma vitamin C concentration plateau is maximized at around 200 mg/day in healthy people,30 whereas the average amount of vitamin C consumed was at least 200 mg/day in each TAC group, suggesting that excessive vitamin C intake did not contribute to any further increase in plasma vitamin C level. A previous study showed that dietary TAC was the only independent predictor of plasma beta carotene levels in healthy individuals.31 Similarly, Marchand and colleagues32 conducted a fruit and vegetable intervention study and found that plasma carotenoids and ascorbic acids were markers of compliance to a high fruit and vegetable diet. In our study, a significantly higher plasma lutein level with higher dietary TAC was found, suggesting that dietary TAC is an independent marker for plasma lutein level in this population. A positive and significant correlation between dietary TAC and plasma TAC was observed in this healthy young population, which is consistent with results from a number of studies examining the ability of a diet high in fruits and vegetables to modulate plasma TAC.32-38 Despite several observational studies showing a positive correlation between a diet high in TAC and plasma TAC,35,37 intervention studies reported different outcomes.33-36,38-41 Acute studies that monitored dynamic change of plasma TAC after consumption of tea, coffee, red wine, nuts, fruits, and vegetables found a significant increase of plasma TAC that reached its peak 1 hour or 2 hours after consumption.33,34,36,38,42 However, chronic intervention studies on the long-term effect of consuming TAC-rich foods on fasting plasma TAC levels reported inconclusive results.37,39,41,43 Because few previous studies examined whether dietary TAC modulates plasma TAC, our study provides evidence that dietary TAC is an important modulator of antioxidant status in vivo in healthy young human subjects. Antioxidant enzymes also play an important role in the antioxidant defenses of the body. Antioxidant enzymes mainly exert protection at the cellular level, but they are active at the plasma level. At the cellular level, an increased level of RBC GPx was found across the tertiles of TAC from both diet and supplement, with no change in superoxide dismutase or CAT activities. Relationships between dietary TAC and antioxidant enzymes are not well established. Previously, increased GPx activity was observed with apple-blackcurrant juice intake for 1 week44 but not with grape-skin extract.45 1634
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Our study has limitations. The cross-sectional study design prevents any causal inferences from being drawn. Although potential covariates have been adjusted, other unknown but related cofactors might not have been included in analyses. Nevertheless, this study supported the hypothesis that dietary TAC is a good indicator of diet quality with respect to reflecting the antioxidant capacity of a diet, as well as a predictor of plasma antioxidant status.
CONCLUSIONS Dietary TAC was validated as a useful tool in predicting dietary and plasma status of antioxidants. Further studies that assess dietary TAC in predicting oxidative stress biomarkers and inflammatory biomarkers are warranted.
References 1.
Doll R. An overview of the epidemiological evidence linking diet and cancer. Proc Nutr Soc. 1990;49(2):119-131.
2.
Hertog MGL, Kromhout D, Aravanis C, et al. Flavonoid intake and long-term risk of coronary heart disease and cancer in the seven countries study. Arch Intern Med. 1995;155(4):381-386.
3.
Dai Q, Borenstein AR, Wu Y, et al. Fruit and vegetable juices and Alzheimer’s disease: The Kame Project. Am J Med. 2006;119(9):751-759.
4.
Kang JH, Ascherio A, Grodstein F. Fruit and vegetable consumption and cognitive decline in aging women. Ann Neurol. 2005;57(5):713720.
5.
Serafini M, Del Rio D. Understanding the association between dietary antioxidants, redox status and disease: Is the Total Antioxidant Capacity the right tool? Redox Rep. 2004;9:145-152.
6.
Franzini L, ArdigÓ D, ValtueÒa S, et al. Food selection based on high total antioxidant capacity improves endothelial function in a low cardiovascular risk population. Nutr Metab Cardiovasc Dis. 2012;22(1): 50-57.
7.
ValtueÒa S, Pellegrini N, Franzini L, et al. Food selection based on total antioxidant capacity can modify antioxidant intake, systemic inflammation, and liver function without altering markers of oxidative stress. Am J Clin Nutr. 2008;87(5):1290-1297.
8.
Wang Y, Yang M, Lee S-G, et al. Total antioxidant capacity: A useful tool in assessing antioxidant intake status. Natural Compounds and Apoptosis. New York, NY: Springer 2012 (in press).
9.
Puchau B, Zulet MA, de EchÂvarri AG, et al. Dietary total antioxidant capacity: A novel indicator of diet quality in healthy young adults. J Am Coll Nutr. 2009;28(6):648-656.
10.
Rautiainen S, Serafini M, Morgenstern R, et al. The validity and reproducibility of food-frequency questionnaire-based total antioxidant capacity estimates in Swedish women. Am J Clin Nutr. 2008;87:12471253.
11.
Pellegrini N, Salvatore S, Valtuena S, et al. Development and validation of a food frequency questionnaire for the assessment of dietary total antioxidant capacity. J Nutr. 2007;137(1):93-98.
12.
Subar AF, Kipnis V, Troiano RP, et al. Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: the OPEN study. Am J Epidemiol. 2003;158(1):1-13.
13.
Floegel A, Kim D-O, Chung S-J, et al. Development and validation of an algorithm to establish a total antioxidant capacity database of the US diet. Int J Food Sci Nutr. 2010;61(6):600-623.
14.
Chun OK, Chung S, Song W. Estimated dietary flavonoid intakes and major food sources of U.S. adults. J Nutr. 2007;137(5):1244-1252.
15.
Miller NJ, Rice-Evans C, Davies MJ, et al. A novel method for measuring antioxidant capacity and its application to monitoring the antioxidant status in premature neonates. Clin Sci. 1993;84(4):407-412.
16.
Kim DO, Lee KW, Lee HJ, et al. Vitamin C equivalent antioxidant capacity (VCEAC) of phenolic phytochemicals. J Agric Food Chem. 2002; 50(13):3713-3717.
17.
Benzie, Iris FF, Strain JJ. The ferric reducing ability of plasma (FRAP) as a measure of “antioxidant power”: The FRAP assay. Anal Biochem. 1996;239(1):70-76.
18.
Singleton VL, Rossi JA Jr. Colorimetry of total phenolics with phospho-
October 2012 Volume 112 Number 10
RESEARCH molybdic-phosphotungstic acid reagents. Am J Enol Vitic. 1965; 16(3):144-158.
32.
Le Marchand L, Hankin JH, Carter FS, et al. A pilot study on the use of plasma carotenoids and ascorbic acid as markers of compliance to a high fruit and vegetable dietary intervention. Cancer Epidemiol Biomarkers Prev. 1994;3(3):245-251.
19.
Ross MA. Determination of ascorbic acid and uric acid in plasma by high-performance liquid chromatography. J Chromatogr B Analyt Technol Biomed Life Sci. 1994;657(1):197-200.
33.
20.
Bruno RS, Dugan CE, Smyth JA, et al. Green tea extract protects leptindeficient, spontaneously obese mice from hepatic steatosis and injury. J Nutr. 2008;138(2):323-331.
Cao G, Russell RM, Lischner N, et al. Serum antioxidant capacity is increased by consumption of strawberries, spinach, red wine or vitamin C in elderly women. J Nutr. 1998;128:2383-2390.
34.
21.
Karppia J, Nurmia T, Olmedilla-Alonsob B, et al. Simultaneous measurement of retinol, ␣-tocopherol and six carotenoids in human plasma by using an isocratic reversed-phase HPLC method. J Chromatogr B Analyt Technol Biomed Life Sci. 2008;867(2):226-232.
Day A, Stansbie D. Cardioprotective effect of red wine may be mediated by urate. Clin Chem. 1995;41:1319-1320.
35.
22.
Pollard J, Greenwood D, Kirk S, et al. Lifestyle factors affecting fruit and vegetable consumption in the UK Women’s Cohort Study. Appetite. 2001;37(1):71-79.
Khalil A, Gaudreau P, Cherki M, et al. Antioxidant-rich food intakes and their association with blood total antioxidant status and vitamin C and E levels in community-dwelling seniors from the Quebec longitudinal study NuAge. Exp Gerontol. 2011;46(6):475-481.
36.
23.
Hamer M, Chida Y. Intake of fruit, vegetables, and antioxidants and risk of type 2 diabetes: Systematic review and meta-analysis. J Hypertens. 2007;25(12):2361-2369.
Natella F, Nardini M, Giannetti I, et al. Coffee drinking influences plasma antioxidant capacity in humans. J Agric Food Chem. 2002; 50(21):6211-6216.
37.
24.
di Giuseppe R, Arcari A, Serafini M, et al. Total dietary antioxidant capacity and lung function in an Italian population: A favorable role in premenopausal/never smoker women. Eur J Clin Nutr. 2012; 66(1):61-68.
Pitsavos C, Panagiotakos DB, Tzima N, et al. Adherence to the Mediterranean diet is associated with total antioxidant capacity in healthy adults: The ATTICA study. Am J Clin Nutr. 2005;82(3):694699.
38.
Torabian S, Haddad E, Rajaram S, et al. Acute effect of nut consumption on plasma total polyphenols, antioxidant capacity and lipid peroxidation. J Hum Nutr Diet. 2009;22(1):64-71.
39.
Record IR, Dreosti IE, McInerney JK. Changes in plasma antioxidant status following consumption of diets high or low in fruit and vegetables or following dietary supplementation with an antioxidant mixture. Br J Nutr. 2001;85(4):459-464.
25.
Mekary RA, Wu K, Giovannucci E, et al. Total antioxidant capacity intake and colorectal cancer risk in the Health Professionals Follow-up Study. Cancer Causes Control. 2010;21(8):1315-1321.
26.
Del Rio D, Agnoli C, Pellegrini N, et al. Total antioxidant capacity of the diet is associated with lower risk of ischemic stroke in a large Italian cohort. J Nutr. 2011;141(1):118-123.
40.
Puchau B, Zulet MA, de EchÂvarri AG, Hermsdorff HH, MartÎnez JA. Dietary total antioxidant capacity is negatively associated with some metabolic syndrome features in healthy young adults. Nutrition. 2010;26(5):534-541.
Leenen R, Roodenburg AJ, Tijburg LB, et al. A single dose of tea with or without milk increases plasma antioxidant activity in humans. Eur J Clin Nutr. 2005;54(1):87-92.
41.
McKay DL, Chen CY, Yeum KJ, et al. Chronic and acute effects of walnuts on antioxidant capacity and nutritional status in humans: A randomized, cross-over pilot study. Nutr J. 2010;9:21.
42.
Leenen R, Roodenburg AJ, Tijburg LB, et al. A single dose of tea with or without milk increases plasma antioxidant activity in humans. Eur J Clin Nutr. 2000;54(1):87-92.
43.
Dragsted LO, Pedersen A, Hermetter A, et al. The 6-a-day study: Effects of fruit and vegetables on markers of oxidative stress and antioxidative defence in healthy nonsmokers. Am J Clin Nutr. 2004;79(6): 1060-1072.
27.
28.
Neyestani T, Shariatzade N, Kalayi A, et al. Regular daily intake of black tea improves oxidative stress biomarkers and decreases serum C-reactive protein levels in type 2 diabetic patients. Ann Nutr Metab. 2010;57(1):40-49.
29.
van Het Hof K, West CE, Weststrate JA, et al. Dietary factors that affect the bioavailability of carotenoids. J Nutr. 2000;130(3):503-506.
30.
Levine M, Conry-Cantilena C, Wang Y, et al. Vitamin C pharmacokinetics in healthy volunteers: Evidence for a recommended dietary allowance. Proc Natl Acad Sci. 1996;93:3704-3709.
44.
ValtueÒa S, Del Rio D, Pellegrini N, et al. The total antioxidant capacity of the diet is an independent predictor of plasma beta-carotene. Eur J Clin Nutr. 2007;61(1):69-76.
Young JF, Nielsen SE, HaraldsdÔttir J, et al. Effect of fruit juice intake on urinary quercetin excretion and biomarkers of antioxidative status. Am J Clin Nutr. 1999;69(1):87-94.
45.
Young JF, Dragsted LO, Daneshvar B, et al. The effect of grape-skin extract on oxidative status. Br J Nutr. 2000;84(4):505-513.
31.
AUTHOR INFORMATION Y. Wang is a PhD student, S.-G. Lee is a PhD student, S. I. Koo is a professor and department head, and O. K. Chun is an assistant professor, all with the Department of Nutritional Sciences, University of Connecticut, Storrs. M. Yang is an MPH student, Harvard School of Public Health, Boston, MA; at the time of the study, she was a PhD student, Department of Nutritional Sciences, University of Connecticut, Storrs. C. G. Davis is a registered dietitian; at the time of the study, she was an MS student, Department of Nutritional Sciences, University of Connecticut, Storrs. Address correspondence to: Ock K. Chun, PhD, MPH, Department of Nutritional Sciences, University of Connecticut, 3624 Horsebarn Rd Extension Unit 4017, Storrs, CT 06269-4017. E-mail: [email protected]
STATEMENT OF POTENTIAL CONFLICT OF INTEREST No potential conflict of interest was reported by the authors.
FUNDING/SUPPORT The study was supported by a grant from the University of Connecticut USDA Hatch (no. CONS00846).
October 2012 Volume 112 Number 10
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1635
Dietary Total Antioxidant Capacity Is Associated with Diet and Plasma Antioxidant Status in Healthy Young Adults Ying Wang; Meng Yang, PhD; Sang-Gil Lee, MS; Catherine G. Davis, MS, RD; Sung I. Koo, PhD; Ock K. Chun, PhD, MPH
ARTICLE INFORMATION
ABSTRACT
Article history:
Dietary total antioxidant capacity (TAC), based on the cumulative antioxidant activities of all the antioxidants present in food, has been shown to be inversely associated with risks of chronic diseases. However, dietary TAC has not been validated for its relevance in a healthy young population or for reliability and predictability for antioxidant status. Our study aimed to validate TAC as a tool in assessing antioxidant intake and to investigate whether dietary TAC predicts plasma antioxidant status in a healthy young population. Sixty healthy, nonsmoking college students at the University of Connecticut ages 18 to 25 years were recruited. Thirty-day food records and two 12-hour fasting blood samples were collected for dietary and plasma antioxidant assessments. After adjustment for total energy intake, TAC from diet and supplement was positively correlated with intakes of carotenoids (P⬍0.01), beta carotene (P⬍0.05), -cryptoxanthin (P⬍0.05), flavonoids (P⬍0.0001), isoflavones (P⬍0.01), flavan-3-ols (P⬍0.01), flavones (P⬍0.05), and flavonols (P⬍0.0001). Dietary TAC was an independent predictor of plasma TAC determined by vitamin C equivalent antioxidant capacity (P⬍0.01) and by ferric-reducing ability of plasma (P⬍0.0001), plasma glutathione peroxidase (P⬍0.01), red blood cell glutathione peroxidase (P⬍0.05), ␣-tocopherol (P⬍0.05), and lutein (P⬍0.05). Results were similar for TAC from diet sources only. The findings suggest that dietary TAC is a good predictor of dietary and plasma antioxidant status in this sample of young adult men and women.
Accepted 17 May 2012
Keywords: Total antioxidant capacity (TAC) Plasma antioxidant status Antioxidant enzyme Diet Young adults Copyright © 2012 by the Academy of Nutrition and Dietetics. 2212-2672/$36.00 doi: 10.1016/j.jand.2012.06.007
J Acad Nutr Diet. 2012;112:1626-1635.
F
RUIT AND VEGETABLE CONSUMPTION HAS LONG been reported to be associated with lower incidence and mortality rates of several chronic diseases such as cardiovascular disease,1-4 cancer,1,2 and Alzheimer’s disease.3,4 One hypothesis of the protective effects is that all types of antioxidant compounds, including vitamin C, vitamin E, carotenoids, and phytochemicals such as flavonoids and proanthocyanidins could protect cells from free radical–induced oxidative damage. To consider the cumulative antioxidant capacity of all the antioxidants present in foods or body fluids, the concept of total antioxidant capacity (TAC) was introduced.5 It remains inconclusive which dietary antioxidants are responsible for the aforementioned associations with disease reduction, and no single antioxidant reflects overall quality of the diet. Moreover, several randomized controlled studies examining the protective mechanisms of some vitamin supplements or food extracts failed to present any beneficial results.6-8 Furthermore, high-dose and long-term use of vitamin supplements are drawing health concern due to their potential adverse effects.6-9 In contrast, intervention studies that investigate whole foods’ metabolic functions in human beings have reported positive results.6,7 For example, in a recent randomized controlled study, a diet high in antioxidants was shown 1626
JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS
to improve endothelial function measured by flow-mediated dilatation,6 indicating that combined multiple antioxidants in the diet might exert more beneficial effects on oxidative stress than a single antioxidant. If the antioxidant effect assumption is valid, dietary TAC, which is an integrated parameter that considers the overall antioxidant capacity of most of the known antioxidants, will be a useful tool when investigating the association between food consumption and disease risk. Dietary TAC has been shown to be a good indicator of diet antioxidant status in a group of postmenopausal women.8 In a young population, dietary TAC has been shown to be an indicator of diet quality because it had high association with the other two indicators of diet quality—Mediterranean energy density hypothesis– oriented dietary scores and non-Mediterranean hypothesis– oriented dietary scores;9 however, few studies assessed dietary TAC’s ability to predict dietary antioxidant status and plasma antioxidant status in a young population.10,11 Estimating dietary TAC is the first step in the validation process. But previous studies varied in the methodology of dietary TAC estimation.10-14 The variation comes from two components: dietary assessment methods (eg, food frequency questionnaire [FFQ], 24-hour dietary recall, and food record [FR]) and dietary TAC databases that were used. Most © 2012 by the Academy of Nutrition and Dietetics.
RESEARCH of the previous studies estimated dietary TAC by collecting dietary data from an FFQ.10-14 One of the limitations of an FFQ is inaccuracy of assessing usual diet intake, especially total energy by an FFQ.12 Dietary TAC was calculated by multiplying amount of a food item by its corresponding TAC value of unit weight from a food TAC database. Such a dietary TAC database includes a number of food items that were directly analyzed for TAC by analytical methods such as oxygen radical absorbance capacity, ferric reducing ability of plasma (FRAP), or Trolox equivalent antioxidant capacity (TEAC). A food TAC database is limited in number of food items and is not comparable to another database that uses different TAC assays. We collected dietary data by 30-day FR and used a nutrient TAC database where 45 forms of antioxidants from families of vitamin E, carotenoids, flavonoids, and procyanidines, as well as vitamin C and selenium, were analyzed by vitamin-C equivalent antioxidant capacity (VCEAC) method to calculate cumulative dietary TAC.13 Food records are regarded as the gold standard compared with other dietary assessment methodologies, due to the quantitatively accurate information on food consumed during the recording period. Compared with food TAC database, using nutrient TAC database to calculate theoretical TAC is not limited by the number of food items. Although there is no perfect assay that could capture all antioxidants, VCEAC modified from TEAC enables expression of plasma TAC in weight units, which are familiar to the public and easy to link with dietary TAC intake status. The aim of this study was to test the hypothesis that dietary TAC, estimated in a more precise way, is a good predictor of antioxidant intake and plasma antioxidant status in a healthy young population. In this study, if not otherwise stated, dietary TAC refers to TAC from diet and supplements.
METHODS Study Population and Design A cross-sectional study was conducted in 60 (20 men and 40 women) healthy young college students. Participants 18 to 25 years of age who were apparently healthy, with a normal body mass index range for height and weight, were recruited through flyers and e-mails from the University of Connecticut in Storrs. Participants were excluded if they were taking any prescribed medication or had a history of certain chronic conditions or diseases, including cardiovascular disease, certain cancers, and chronic obstructive pulmonary disease. This project and its procedures were reviewed and approved by the Human Investigation Review Committee of the University of Connecticut. Written informed consent was obtained from each study participant. All participants were compensated for participating in the study. At the initial visit, participants completed a brief physical examination, including measured weight, height, and blood pressures, and a fasting blood finger stick blood sample, followed by a survey (College Student Health and Nutrition Survey) regarding their medical, dietary, and tobacco and alcohol consumption histories. Weight and height were measure by an electronic scale (Detecto); blood pressure was measured twice using an automatic blood pressure monitor (Omron HEM-780) while the participant was seated. The fasting finger stick blood sample was used to measure lipid profile (Cholestech LDX). Final inclusion in the study was determined based on the health examination results and self-reported October 2012 Volume 112 Number 10
health and nutrition history. The study was a 30-day observational study, without any specific treatment or intervention. Eligible participants completed the first blood draw at the initial visit. Participants also were instructed to follow their usual dietary habits, and they were educated on how to record food and supplement intake by an experienced research staff member. Participants were asked to send their FRs to the research staff through a daily e-mail message during the 30 days. The rationale of collecting 30-day food records was that our recent study found the number of days required to obtain stable intake information on most antioxidants was ⬎7 days but ⬍30 days (C. G. Davis, MS, and colleagues, unpublished data, May 2011). The final visit occurred 30 days after the initial visit. Participants completed a second blood draw, survey, and body measurement, as well as the final FR. In total, 77 eligible participants were recruited, with 22% attrition over the 30 days.
Dietary Assessment Each participant’s 30-day FR was entered into Nutrition Data System for Research software (version 2010, Nutrition Coordinating Center, University of Minnesota) for food composition analyses. Because the Nutrition Data System for Research does not provide flavonoid and proanthocyanidin intake data, intakes of these food components were estimated by matching food consumption data with nutrients in flavonoids and proanthocyanidins as described previously.14 Each participant’s individual antioxidant intake was estimated by multiplying the content of 43 individual antioxidants (29 flavonoids, three proanthocyanidins, seven carotenoids, two vitamins E, vitamin C, and selenium) by the daily consumption of each selected food item and supplement. Individual antioxidant capacity was then determined by multiplying the individual amount of each antioxidant compound by their respective antioxidant capacities expressed as VCEAC from a nutrient TAC database.13 Dietary TAC was determined by summating the individual antioxidant capacities. In this study, the TAC values of participants’ diets were expressed as mg vitamin C equivalents (VCE) per day.
Blood Collection and Plasma Antioxidant Analyses Twelve-hour fasting blood samples were collected in evacuated containers with ethylenediaminetetraacetic acid or heparin at the first and last visits, respectively. All plasma biomarkers were calculated as the average of first and last values to represent usual in vivo status during the 30-day period. Samples were centrifuged immediately in a dark room at 500g for 15 minutes at 4⬚C. Plasma samples were then separated in small aliquots and stored at ⫺80⬚C until analysis. After removing plasma and white buffy layer (leukocytes), erythrocytes were lysed in 4 vol ice-cold high-performance liquid chromatography (HPLC)-grade water and centrifuged at 10,000g for 15 minutes at 4⬚C. Erythrocyte lysate was then separated in small aliquots and stored at ⫺80⬚C until analysis. The outcome measures included plasma TAC; glucose; lipid profiles (total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol); plasma antioxidant nutrients; and enzymes. Glucose and lipids were analyzed as potential covariates that may affect plasma antioxidant status. Plasma TAC was determined by VCEAC and FRAP assays, respectively. VCEAC assay, which was developed JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS
1627
RESEARCH by Miller and colleagues15 and modified by Kim and colleagues,16 measures the 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) radical chromogen at 734 nm, using 2,2’-Azobis(2-amidinopropane) dihydrochloride as a thermolabile water-soluble radical initiator. The reduction of 2,2’azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) radical chromogen is proportional to the TAC in plasma. The results were expressed as mg VCE per liter plasma. The FRAP assay determines the ability of the sample to reduce ferric iron to ferrous iron in a low-pH environment. A colored ferroustripyridyltriazine complex is formed during this process and has a maximum absorbance at 593 nm.17 The results are expressed as mol Trolox per liter plasma. Plasma total phenolics were analyzed using the Folin-Ciocalteu method described by another study.18 Briefly, 200 L diluted plasma were mixed with 200 L Folin-Ciocalteu reagent (Sigma) and allowed to stand for 6 minutes. Two milliliters of 7% sodium carbonate (Sigma) solution was added to each sample and allowed to stand at room temperature for 90 minutes. Absorbance was read at 750 nm vs prepared blank. Plasma vitamin C and uric acid were determined as described19 using HPLC (Agilent Technology 1200) with a UV detector, separated with an Eclipse XDB-C18 column (5 m; 250 mm⫻4.6 mm) (Agilent Technology) and Zorbax C18 guard column (5 m; 12 mm⫻4.6 mm) (Agilent Technology). Vitamin E (as ␣- and ␥-tocopherol) and carotenoids were measured simultaneously by the HPLC system (Agilent 1100, Hewlett Packard) with a photodiode array detector and a C18 RP Symmetry analytical column (5 m, 250 mm⫻4.6 mm) (Agilent Technology), as described previously.20,21 Superoxide dismutase, catalase (CAT), and glutathione peroxidase (GPx) activities in plasma and red blood cells (RBC) were determined using commercially available kits (Cayman Chemical Company). Enzyme activities in RBCs were expressed as units per gram hemoglobin. Hemoglobin concentrations were determined using a commercially available kit (QuantiChrom hemoglobin assay, BioAssay Systems).
Statistical Analysis All statistical analyses were conducted using Statistical Analysis Software (version 9.2, 2009, SAS Institute Inc). To test the assumptions of general linear model, residual and goodness of fit were analyzed. All dietary and plasma antioxidant variables were log transformed to meet the underlying assumption. To evaluate associations between dietary or plasma antioxidants and dietary TAC, subjects were equally divided into three groups according to dietary TAC intake. P values were tested across the median values of dietary TAC in each group by analysis of covariance using the General Linear Model procedure. To examine relationships between dietary TAC and dietary antioxidants, data were adjusted by age, sex, and total energy intake. To examine associations between dietary TAC and plasma levels, data were analyzed by two models. The simple model was adjusted for age, ethnicity, and plasma cholesterol (except ascorbic acid and uric acid). To test the sensitivity of dietary TAC as a predicting tool, the simple model was further adjusted for fruit and fruit juices, vegetable and vegetable juices, and supplement use, which are the major contributors to dietary TAC. Data were reported as geometric least square means and 95% CIs if strongly skewed. The level of statistical significance was set at P⬍0.05. 1628
JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS
RESULTS AND DISCUSSION Dietary TAC Intake According to Demographic, Clinical, and Dietary Characteristics In this study population, the mean intake of TAC from diet was 456 mg VCE/day, and the mean TAC from both diet and supplement was 496 mg VCE/day. Although 68% of participants used supplements, the quantity and frequency of supplement use was not significant. Consequently the results were similar when either diet alone or diet and supplement as an indicator of plasma antioxidant status was tested. As shown in Table 1, dietary TAC was higher in older participants, vegetarians, and participants who had higher intakes of energy, tea, fruits and fruit juices, and vegetables and vegetable juices (P⬍0.05) when participants were divided into three groups by their dietary TAC values. Vegetarian status was self-reported by the participants in the College Student Health and Nutrition Survey form. Being a vegetarian or vegan has been identified as a strong predictor of fruit and vegetable consumption.22 Expectedly, highest dietary TAC intake had the largest number of self-reported vegetarians; however, the P value was not significant, possibly due to the small sample size. A previous study has shown the main sources of dietary TAC in a group of healthy postmenopausal women in the United States as fruits and fruit juices, vegetables and vegetable juices, tea, wine, and supplements.8 Similarly, in this younger group of men and women, higher dietary TAC consumers reported greater intakes of fruits and fruit juices, vegetables and vegetable juices, and tea.
Association between TAC from Both Diet and Supplements and Individual Dietary Antioxidants After adjustment for total energy intake, TAC from diet and supplements was positively associated with total carotenoids (P⬍0.01) and its subgroups such as beta carotene (P⬍0.05) and -cryptoxanthin (P⬍0.05), as well as flavonoids (P⬍0.0001) and its subgroups isoflavones (P⬍0.01), flavan-3-ols (P⬍0.01), flavones (P⬍0.05), and flavonols (P⬍0.0001) (Table 2). But TAC from diet and supplements was negatively associated with ␥-tocopherol (P⬍0.0001). Similar results were found for TAC from diet only (data not shown). Evidence indicates that antioxidant intake is, more consistently than fruit and vegetable intake, associated with a reduction in the risk of chronic diseases such as type 2 diabetes.23 In our study, data suggest that dietary TAC is an effective dietary predictor of antioxidant intake. Several observational studies already found a favorable role of dietary TAC in endothelial and lung function6,24 and negative associations with risks of ischemic stroke, rectal cancer,25,26 metabolic syndrome,27 and biomarkers of cardiovascular disease.28
Association between TAC from Both Diet and Supplements and Individual Plasma Antioxidants and Enzymes After adjustment for basic factors that include age, sex, ethnicity, total energy intake, and plasma cholesterol (as well as uric acid for FRAP and VCEAC) in the simple model, TAC from diet and supplement was positively correlated with plasma TAC measured by FRAP (P⬍0.0001) and VCEAC (P⬍0.01), whereas the third group had significantly higher VCEAC than the first two groups (Table 3). Meanwhile, TAC from diet and October 2012 Volume 112 Number 10
October 2012 Volume 112 Number 10
Table 1. Demographic, clinical, and dietary characteristics according to the dietary total antioxidant capacity (TAC) levels of healthy young adultsa TAC from Diet and Supplements
TAC from Diet Characteristic
T1 (nⴝ20)
T2 (nⴝ20)
T3 (nⴝ20)
30.6-246
254-427
448-2,345
b
P value
T1 (nⴝ20)
T2 (nⴝ20)
T3 (nⴝ20)
117-284
293-448
453-2,428
P value
TAC level Range (mg vitamin C equivalents/d) Median (mg V vitamin C equivalents/d)
194
334
577
207
356
647
Mean (mg vitamin C equivalents/d)
184
337
848
207
369
913
4™™™™™ mean⫾standard deviation ™™™™™3
4™™™™™ mean⫾standard deviation ™™™™™3
Participant characteristic Age (y)
18.8⫾1.0
20.1⫾.1.7
20.5⫾2.0
⬍0.01
18.9⫾1.0
20.1⫾1.8
20.4⫾2.0
⬍0.05
Body mass index
23.3⫾2.3
23.3⫾2.1
22.7⫾3.6
NSc
23.4⫾2.2
23.1⫾2.4
22.8⫾3.4
NS
Fasting glucose (mg/dL)
83.8⫾6.3
82.6⫾10.9
84.6⫾5.0
NS
83.1⫾5.2
82.4⫾10.8
85.3⫾6.0
NS
Triglycerides (mg/dL)e
87.8⫾31.4
79.4⫾30.3
75.7⫾32.4
NS
91.3⫾29.1
81.9⫾36.2
70.2⫾25.5
NS
d
f
163⫾28.9
165⫾37.1
149⫾25.2
NS
166⫾29.2
163⫾36.3
148⫾25.6
NS
High-density lipoprotein cholesterol (mg/dL)f
62.1⫾11.8
63.6⫾14.3
58.9⫾14.7
NS
62.7⫾11.5
63.1⫾14.7
58.7⫾14.6
NS
Supplement use (%)
70
65
70
NS
65
65
75
NS
5
5
20
NS
5
5
20
NS
Vegetarian (%) Food intake Energy intake (kcal/d)
1,798⫾660
2,154⫾675
2,281⫾598
⬍0.05
1,803⫾634
2,174⫾674
2,257⫾634
⬍0.05
Tea (serving/d)
0.16⫾0.10
0.14⫾0.11
0.83⫾0.95
⬍0.0001
0.16⫾0.10
0.17⫾0.15
0.85⫾0.97
⬍0.001
Wine (serving/d)
0.12⫾0.15
0.13⫾0.16
0.12⫾0.21
NS
0.12⫾0.15
0.12⫾0.16
0.12⫾0.22
NS
Beer (serving/d)
0.20⫾0.20
0.36⫾0.48
0.73⫾0.58
NS
0.17⫾0.19
0.40⫾0.49
0.73⫾0.58
⬍0.05
Fruits and fruit juices (serving/d)
1.44⫾0.98
1.94⫾0.93
2.34⫾1.83
⬍0.05
1.53⫾0.94
1.89⫾0.95
2.30⫾1.88
⬍0.05
Vegetables and vegetable juices (serving/d)
2.76⫾1.01
3.57⫾1.66
3.97⫾1.27
⬍0.05
2.63⫾0.98
3.73⫾1.55
3.93⫾1.35
⬍0.01
a
Participants were ranked according to dietary TAC levels and divided evenly into three groups: T1, T2, and T3. Continuous variables were examined using general linear model. Categorical variables were examined with 2 analysis. c NS⫽not significant. d To convert mg/dL glucose to mmol/L, multiply mg/dL by 0.0555. To convert mmol/L glucose to mg/dL, multiply mmol/L by 18.0. Glucose of 108 mg/dL⫽6.0 mmol/L. e To convert mg/dL triglyceride to mmol/L, multiply mg/dL by 0.0113. To convert mmol/L triglyceride to mg/dL, multiply mmol/L by 88.6. Triglyceride of 159 mg/dL⫽1.80 mmol/L. f To convert mg/dL cholesterol to mmol/L, multiply mg/dL by 0.026. To convert mmol/L cholesterol to mg/dL, multiply mmol/L by 38.6. Cholesterol of 193 mg/dL⫽5.00 mmol/L. b
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Cholesterol, total (mg/dL)
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Variable
Model
T1 (nⴝ20)
T2 (nⴝ20)
T3 (nⴝ20)
P valueb
TAC from diet and supplements Range (mg vitamin C equivalents/d)
117-284
293-448
453-2,428
Median (mg vitamin C equivalents/d)
207
356
647
Mean (mg vitamin C equivalents/d)
207
369
913
Individual antioxidants
Geometric mean
Tocopherol intakec (mg/d)
␣-Tocopherol (mg/d) ␥-Tocopherol (mg/d) Ascorbic acid (mg/d) Carotenoid intake (mg/d)
␣-Carotene (mg/d) October 2012 Volume 112 Number 10
-Cryptoxanthin (mg/d) Lutein⫹zeaxanthin (mg/d) Lycopene (mg/d)
Geometric mean
95% CI
Geometric mean
95% CI
Basic
33.4
(20.6, 54.1)
52.1
(32.2, 84.4)
84.5
(52.2, 137)
⬍0.05
Adjustedd
38.1
(22.5, 64.4)
49.5
(30.3, 81.0)
78.1
(47.1, 129)
NSe
Basic
15.1
(8.0, 28.3)
28.5
(15.2, 53.5)
55.3
(29.5, 104)
⬍0.05
Adjusted
17.0
(8.5, 33.9)
27.2
(14.2, 52.0)
51.6
(26.5, 100)
NS
Basic
11.1
(9.3, 13.3)
12.6
(10.5, 15.0)
10.4
(8.7, 12.5)
NS
Adjusted
13.2
(11.6, 15.1)
11.8
(10.4, 13.3)
9.4
(8.3, 10.7)
⬍0.0001
Basic
209
(112, 389)
350
(188, 651)
655
(352, 1,218)
⬍0.05
Adjusted
199
(102, 387)
357
(191, 667)
675
(356, 1,282)
NS
Basic Adjusted
-Carotene (mg/d)
95% CI
8.9
(7.0, 11.2)
12.4
(9.9, 15.7)
15.2
(12.1, 19.2)
⬍0.01
10.1
(8.0, 12.7)
11.7
(9.4, 14.6)
14.2
(11.4, 17.8)
⬍0.01
Basic
2.2
(1.6, 3.1)
3.4
(2.5, 4.7)
4.4
(3.2, 6.1)
⬍0.05
Adjusted
2.4
(1.7, 3.3)
3.3
(2.4, 4.6)
4.3
(3.1, 6.0)
⬍0.05
Basic
0.31
(0.19, 0.50)
0.39
(0.24, 0.63)
0.67
(0.41, 1.10)
NS
Adjusted
0.31
(0.18, 0.53)
0.37
(0.23, 0.62)
0.69
(0.41, 1.20)
NS
Basic
0.08
(0.05, 0.12)
0.16
(0.10, 0.25)
0.14
(0.09, 0.22)
⬍0.05
Adjusted
0.09
(0.06, 0.14)
0.15
(0.10, 0.22)
0.13
(0.08, 0.20)
⬍0.05
Basic
1.5
(1.1, 2.1)
2.6
(1.9, 3.5)
2.4
(1.8, 3.3)
⬍0.05
Adjusted
1.7
(1.2, 2.3)
2.5
(1.8, 3.4)
2.3
(1.7, 3.2)
NS
Basic
4.1
(3.0, 5.6)
4.4
(3.3, 6.1)
5.5
(4.1, 7.5)
NS
Adjusted
5.1
(3.8, 7.0)
4.1
(3.1, 5.5)
4.8
(3.6, 6.5)
⬍0.05
(continued on next page)
RESEARCH
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Table 2. Comparison of dietary intakes of individual antioxidants according to the levels of total antioxidant capacity (TAC) from diet and supplements in healthy young adultsa
October 2012 Volume 112 Number 10
Table 2. Comparison of dietary intakes of individual antioxidants according to the levels of total antioxidant capacity (TAC) from diet and supplements in healthy young adultsa (continued) Variable Flavonoid intake (mg/d) Isoflavones (mg/d) Anthocyanidins (mg/d) Flavan-3-ols (mg/d)
T1 (nⴝ20)
Basic
37.3
(26.7, 52.1)
72.8
(52.1, 102)
181
(129, 253)
⬍0.0001
Adjusted
41.3
(28.7, 59.5)
69.9
(49.7, 98.3)
170
(120, 241)
⬍0.0001
Basic
1.0
(0.6, 1.8)
2.5
(1.4, 4.4)
2.8
(1.6, 5.0)
⬍0.05
1.3
(0.7, 2.3)
2.3
(1.3, 4.0)
2.4
(1.4, 4.3)
⬍0.01
Basic
6.6
(3.3, 12.9)
11.0
(5.6, 21.6)
7.8
(4.0, 15.4)
NS
Adjusted
7.8
(3.8, 15.8)
9.9
(5.1, 19.2)
7.4
(3.7,14.6)
NS
Basic
Flavonols (mg/d) Proanthocyanidins (mg/d)
9.1
(4.4, 18.8)
21.3
(10.3, 44.2)
84.8
(40.9, 176)
⬍0.001
10.7
(4.9, 23.6)
19.3
(9.2, 40.4)
79.0
(37, 168)
⬍0.01
Basic
4.8
(2.8, 8.3)
6.0
(3.5, 10.3)
6.6
(3.8, 11.2)
NS
Adjusted
5.4
(3.0, 9.6)
5.6
(3.3, 9.6)
6.3
(3.6, 11.0)
NS
Basic
0.9
(0.6, 1.3)
1.0
(0.7, 1.5)
1.5
(1.0, 2.2)
NS
Adjusted
1.1
(0.7, 1.6)
0.9
(0.6, 1.3)
1.4
(0.9, 2.0)
⬍0.05
Basic
7.0
(5.8, 8.4)
11.9
(9.8, 14.3)
18.8
(15.6, 22.7)
⬍0.0001
Adjusted
7.7
(6.3, 9.4)
11.5
(9.6, 13.9)
17.6
(14.5, 21.2)
⬍0.0001
Basic
43.4
(25.2, 74.8)
75.0
(43.5, 129)
80.7
(46.8, 139)
NS
Adjusted
54.0
(30.6, 95.3)
67.1
(39.5, 114)
72.5
(42.1, 125)
NS
a
Participants were ranked according to TAC from diet and supplements and divided evenly into three groups: T1, T2, and T3. Antioxidant intake data were log transformed for test. P value was calculated across the median value of intake of TAC from diet in each tertile using general linear model. Tocopherols include ␣-, -, ␥-, and ␦-tocopherols. d Model was adjusted for age, sex, and total energy intake. e NS⫽not significant. b c
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Flavones (mg/d)
T3 (nⴝ20)
Adjusted
Adjusted Flavanones (mg/d)
T2 (nⴝ20)
P valueb
Model
JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS
Intake
Model
T1 (nⴝ20)
T2 (nⴝ20)
T3 (nⴝ20)
117-284
293-448
453-2,428
P valueb
TAC from diet and supplements Range (mg vitamin C equivalents/d) Median (mg vitamin C equivalents/d)
207
356
647
Mean (mg vitamin C equivalents/d)
207
369
913
Geometric mean
95% CI
Geometric mean
95% CI
Geometric mean
95% CI
Antioxidant enzymes Plasma superoxide dismutase (U/mL) Red blood cell superoxide dismutase (U/g hemoglobin) Plasma catalase (U/mL)
Model 1c
8.1
(7.2, 9.2)
9.0
(8.0, 10.1)
8.7
(7.7, 9.7)
NSd
Model 2e
8.1
(7.2, 9.2)
9.0
(8.0, 10.1)
8.6
(7.7, 9.7)
NS NS
Model 1
831
(756, 913)
801
Model 2
841
(764, 926)
806
Model 1
Plasma glutathione peroxidase (U/mL) Red blood cell glutathione peroxidase (U/g hemoglobin)
(18.4, 30.4)
24.6
(18.3, 30.9)
784
(714, 862)
(736, 882)
770
35.2
(29.4, 40.9)
35.1
(29.2, 40.9)
(699, 847)
NS
24.5
(18.7, 30.3)
⬍0.05
24.3
(18.4, 30.3)
⬍0.05
Model 1
21,943
(18,165, 26,505)
18,694
(15,604, 22,396)
18,526
(15,337, 22,378)
NS
Model 2
22,314
(18,259, 27,268)
18,665
(15,474, 22,514)
18,245
(14,941, 22,279)
NS
Model 1
155
(143, 168)
179
(168, 191)
192
(180, 204)
⬍0.01
Model 2
155
(142, 168)
179
(167, 191)
192
(180, 204)
⬍0.01
Model 1
1,921
(1,606, 2,298)
1,972
(1,662, 2,341)
1,986
(1,660, 2,375)
⬍0.05
Model 2
1,923
(1,600, 2,311)
2,008
(1,691, 2,385)
1,950
(1,623, 2,342)
NS
Model 2 Red blood cell catalase (U/g hemoglobin)
24.4
(732, 876)
Antioxidant nutrients October 2012 Volume 112 Number 10
Ascorbic acid (mol/L) Total phenolics (mg gallic acid equivalent/L)
␣-Tocopherol (mol/L)
Model 3f
71.7
(66.4, 76.9)
67.0
(62.2, 71.8)
71.9
(66.9, 76.9)
NS
Model 4g
72.4
(67.2, 77.7)
67.0
(62.2, 71.8)
71.2
(66.1, 76.2)
NS
Model 1
2,530
(2,460, 2,600)
2,525
(2,458, 2,591)
2,596
(2,529, 2,663)
NS
Model 2
2,537
(2,464, 2,609)
2,520
(2,453, 2,588)
2,594
(2,525, 2,663)
NS
Model 1
21
(18.4, 23.9)
23.4
(20.7, 26.5)
24.7
(21.6, 28.1)
⬍0.05
Model 2
21.3
(18.7, 24.4)
23.1
(20.4, 26.2)
24.6
(21.5, 28.1)
⬍0.05
(continued on next page)
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Table 3. Plasma antioxidant profiles according to levels of total antioxidant capacity (TAC) from diet and supplements in healthy young adultsa
October 2012 Volume 112 Number 10
Table 3. Plasma antioxidant profiles according to levels of total antioxidant capacity (TAC) from diet and supplements in healthy young adultsa (continued) Intake
Model
␥-Tocopherol (mol/L)
Model 1
9.5
(7.4, 12.1)
10.7
(8.5, 13.5)
9.9
Model 2
8.6
(7.0, 10.7)
11.1
(9.1, 13.6)
10.5
Model 1
0.58
(0.43, 0.77)
0.78
(0.59, 1.02)
Model 2
0.63
(0.48, 0.83)
0.74
(0.58, 0.95)
Model 1
0.18
(0.12, 0.26)
0.27
Model 2
0.20
(0.14, 0.29)
0.25
Model 1
0.11
(0.08, 0.15)
Model 2
0.12
(0.08, 0.16)
Model 1
0.18
Model 2
0.19
Model 1 Model 2
Total carotenoids
-Carotene (mol/L) ␣-Carotene (mol/L) -Cryptoxanthin (mol/L) Lutein (mol/L) Zeaxanthin (mol/L)
Uric acid (mol/L) TAC by vitamin C equivalent antioxidant capacity (mg vitamin C equivalents/L) TAC by ferric reducing ability of plasma (molTrolox/L)
T2 (nⴝ20)
P valueb
T3 (nⴝ20) (7.7, 12.7)
NS
(8.5, 13)
⬍0.01
0.83
(0.62, 1.11)
NS
0.8
(0.61, 1.05)
NS
(0.19, 0.39)
0.26
(0.17, 0.38)
NS
(0.18, 0.36)
0.24
(0.17, 0.35)
NS
0.13
(0.09, 0.18)
0.24
(0.17, 0.33)
NS
0.12
(0.09, 0.17)
0.23
(0.17, 0.32)
NS
(0.13, 0.25)
0.21
(0.16, 0.29)
0.22
(0.16, 0.31)
NS
(0.14, 0.26)
0.20
(0.15, 0.27)
0.22
(0.16, 0.30)
NS
0.016
(0.012, 0.023)
0.024
(0.017, 0.032)
0.021
(0.015, 0.029)
NS
0.017
(0.012, 0.024)
0.022
(0.017, 0.03)
0.021
(0.015, 0.029)
⬍0.05
Model 1
0.039
(0.033, 0.046)
0.041
(0.035, 0.048)
0.037
(0.031, 0.043)
NS
Model 2
0.040
(0.034, 0.047)
0.040
(0.034, 0.046)
0.037
(0.031, 0.043)
NS
Model 1
0.036
(0.029, 0.045)
0.033
(0.027, 0.04)
0.028
(0.022, 0.035)
NS
Model 2
0.037
(0.029, 0.047)
0.032
(0.026, 0.04)
0.027
(0.021, 0.035)
NS
Model 3
287
(258, 316)
308
(282, 334)
320
(292, 347)
⬍0.05
Model 4
288
(258, 318)
308
(281, 335)
319
(290, 348)
NS
Model 5h
294
(284, 304)
290
(281, 299)
302
(293, 311)
⬍0.01
Model 6i
294
(284, 305)
289
(280, 299)
302
(292, 311)
⬍0.05
Model 5
501
(473, 528)
519
(494, 545)
524
(498, 550)
⬍0.0001
Model 6
502
(473, 531)
518
(491, 544)
524
(497, 551)
⬍0.001
a
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Participants were ranked according to TAC from diet and supplements and divided evenly into three groups: T1, T2, and T3. Plasma antioxidant variables were log transformed for test. P value was calculated across the median value of intake of TAC from diet in each tertile using general linear model. c Model was adjusted for age, sex, ethnicity, total energy intake, and plasma cholesterol. d NS⫽not significant. e Model was adjusted for age, sex, ethnicity, total energy intake, plasma cholesterol, fruit and fruit juice intake, vegetable and vegetable juice intake, and supplement use. f Model was adjusted for age, sex, ethnicity, and total energy intake. g Model was adjusted for age, sex, ethnicity, total energy intake, fruit and fruit juice intake, vegetable and vegetable juice intake, and supplement use. h Model was adjusted for age, sex, ethnicity, total energy intake, plasma cholesterol, and uric acid. i Model was adjusted for age, sex, ethnicity, total energy intake, plasma cholesterol, uric acid, fruit and fruit juice intake, vegetable and vegetable juice intake, and supplement use. b
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JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS
Lycopene (mol/L)
T1 (nⴝ20)
RESEARCH supplement paralleled plasma ␣-tocopherol (P⬍0.05) and uric acid (P⬍0.05) in the simple model. For the antioxidant enzymes, plasma and RBC GPx (P⬍0.01 and P⬍0.05, respectively) levels increased with TAC across the three groups; plasma CAT level was significantly higher in the second groups than the other two groups (P⬍0.05). After further adjustment for fruit and vegetable intakes as well as supplement use, the trend for uric acid and RBC GPx disappeared. Diets of participants in the highest TAC intake group were higher in ␣-tocopherol, vitamin C, carotenoids, especially beta carotene and -cryptoxanthin, as well as flavonoids compared with low and medium TAC consumers. However, highest TAC consumers did not have the highest corresponding plasma antioxidants except ␣-tocopherol. One plausible reason is that the bioavailability was low for those nutrients or affected by the food matrix consumed together.29 The other possible reason is that plasma was saturated with these antioxidants attributed to the supplement use. For example, plasma vitamin C concentration plateau is maximized at around 200 mg/day in healthy people,30 whereas the average amount of vitamin C consumed was at least 200 mg/day in each TAC group, suggesting that excessive vitamin C intake did not contribute to any further increase in plasma vitamin C level. A previous study showed that dietary TAC was the only independent predictor of plasma beta carotene levels in healthy individuals.31 Similarly, Marchand and colleagues32 conducted a fruit and vegetable intervention study and found that plasma carotenoids and ascorbic acids were markers of compliance to a high fruit and vegetable diet. In our study, a significantly higher plasma lutein level with higher dietary TAC was found, suggesting that dietary TAC is an independent marker for plasma lutein level in this population. A positive and significant correlation between dietary TAC and plasma TAC was observed in this healthy young population, which is consistent with results from a number of studies examining the ability of a diet high in fruits and vegetables to modulate plasma TAC.32-38 Despite several observational studies showing a positive correlation between a diet high in TAC and plasma TAC,35,37 intervention studies reported different outcomes.33-36,38-41 Acute studies that monitored dynamic change of plasma TAC after consumption of tea, coffee, red wine, nuts, fruits, and vegetables found a significant increase of plasma TAC that reached its peak 1 hour or 2 hours after consumption.33,34,36,38,42 However, chronic intervention studies on the long-term effect of consuming TAC-rich foods on fasting plasma TAC levels reported inconclusive results.37,39,41,43 Because few previous studies examined whether dietary TAC modulates plasma TAC, our study provides evidence that dietary TAC is an important modulator of antioxidant status in vivo in healthy young human subjects. Antioxidant enzymes also play an important role in the antioxidant defenses of the body. Antioxidant enzymes mainly exert protection at the cellular level, but they are active at the plasma level. At the cellular level, an increased level of RBC GPx was found across the tertiles of TAC from both diet and supplement, with no change in superoxide dismutase or CAT activities. Relationships between dietary TAC and antioxidant enzymes are not well established. Previously, increased GPx activity was observed with apple-blackcurrant juice intake for 1 week44 but not with grape-skin extract.45 1634
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Our study has limitations. The cross-sectional study design prevents any causal inferences from being drawn. Although potential covariates have been adjusted, other unknown but related cofactors might not have been included in analyses. Nevertheless, this study supported the hypothesis that dietary TAC is a good indicator of diet quality with respect to reflecting the antioxidant capacity of a diet, as well as a predictor of plasma antioxidant status.
CONCLUSIONS Dietary TAC was validated as a useful tool in predicting dietary and plasma status of antioxidants. Further studies that assess dietary TAC in predicting oxidative stress biomarkers and inflammatory biomarkers are warranted.
References 1.
Doll R. An overview of the epidemiological evidence linking diet and cancer. Proc Nutr Soc. 1990;49(2):119-131.
2.
Hertog MGL, Kromhout D, Aravanis C, et al. Flavonoid intake and long-term risk of coronary heart disease and cancer in the seven countries study. Arch Intern Med. 1995;155(4):381-386.
3.
Dai Q, Borenstein AR, Wu Y, et al. Fruit and vegetable juices and Alzheimer’s disease: The Kame Project. Am J Med. 2006;119(9):751-759.
4.
Kang JH, Ascherio A, Grodstein F. Fruit and vegetable consumption and cognitive decline in aging women. Ann Neurol. 2005;57(5):713720.
5.
Serafini M, Del Rio D. Understanding the association between dietary antioxidants, redox status and disease: Is the Total Antioxidant Capacity the right tool? Redox Rep. 2004;9:145-152.
6.
Franzini L, ArdigÓ D, ValtueÒa S, et al. Food selection based on high total antioxidant capacity improves endothelial function in a low cardiovascular risk population. Nutr Metab Cardiovasc Dis. 2012;22(1): 50-57.
7.
ValtueÒa S, Pellegrini N, Franzini L, et al. Food selection based on total antioxidant capacity can modify antioxidant intake, systemic inflammation, and liver function without altering markers of oxidative stress. Am J Clin Nutr. 2008;87(5):1290-1297.
8.
Wang Y, Yang M, Lee S-G, et al. Total antioxidant capacity: A useful tool in assessing antioxidant intake status. Natural Compounds and Apoptosis. New York, NY: Springer 2012 (in press).
9.
Puchau B, Zulet MA, de EchÂvarri AG, et al. Dietary total antioxidant capacity: A novel indicator of diet quality in healthy young adults. J Am Coll Nutr. 2009;28(6):648-656.
10.
Rautiainen S, Serafini M, Morgenstern R, et al. The validity and reproducibility of food-frequency questionnaire-based total antioxidant capacity estimates in Swedish women. Am J Clin Nutr. 2008;87:12471253.
11.
Pellegrini N, Salvatore S, Valtuena S, et al. Development and validation of a food frequency questionnaire for the assessment of dietary total antioxidant capacity. J Nutr. 2007;137(1):93-98.
12.
Subar AF, Kipnis V, Troiano RP, et al. Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: the OPEN study. Am J Epidemiol. 2003;158(1):1-13.
13.
Floegel A, Kim D-O, Chung S-J, et al. Development and validation of an algorithm to establish a total antioxidant capacity database of the US diet. Int J Food Sci Nutr. 2010;61(6):600-623.
14.
Chun OK, Chung S, Song W. Estimated dietary flavonoid intakes and major food sources of U.S. adults. J Nutr. 2007;137(5):1244-1252.
15.
Miller NJ, Rice-Evans C, Davies MJ, et al. A novel method for measuring antioxidant capacity and its application to monitoring the antioxidant status in premature neonates. Clin Sci. 1993;84(4):407-412.
16.
Kim DO, Lee KW, Lee HJ, et al. Vitamin C equivalent antioxidant capacity (VCEAC) of phenolic phytochemicals. J Agric Food Chem. 2002; 50(13):3713-3717.
17.
Benzie, Iris FF, Strain JJ. The ferric reducing ability of plasma (FRAP) as a measure of “antioxidant power”: The FRAP assay. Anal Biochem. 1996;239(1):70-76.
18.
Singleton VL, Rossi JA Jr. Colorimetry of total phenolics with phospho-
October 2012 Volume 112 Number 10
RESEARCH molybdic-phosphotungstic acid reagents. Am J Enol Vitic. 1965; 16(3):144-158.
32.
Le Marchand L, Hankin JH, Carter FS, et al. A pilot study on the use of plasma carotenoids and ascorbic acid as markers of compliance to a high fruit and vegetable dietary intervention. Cancer Epidemiol Biomarkers Prev. 1994;3(3):245-251.
19.
Ross MA. Determination of ascorbic acid and uric acid in plasma by high-performance liquid chromatography. J Chromatogr B Analyt Technol Biomed Life Sci. 1994;657(1):197-200.
33.
20.
Bruno RS, Dugan CE, Smyth JA, et al. Green tea extract protects leptindeficient, spontaneously obese mice from hepatic steatosis and injury. J Nutr. 2008;138(2):323-331.
Cao G, Russell RM, Lischner N, et al. Serum antioxidant capacity is increased by consumption of strawberries, spinach, red wine or vitamin C in elderly women. J Nutr. 1998;128:2383-2390.
34.
21.
Karppia J, Nurmia T, Olmedilla-Alonsob B, et al. Simultaneous measurement of retinol, ␣-tocopherol and six carotenoids in human plasma by using an isocratic reversed-phase HPLC method. J Chromatogr B Analyt Technol Biomed Life Sci. 2008;867(2):226-232.
Day A, Stansbie D. Cardioprotective effect of red wine may be mediated by urate. Clin Chem. 1995;41:1319-1320.
35.
22.
Pollard J, Greenwood D, Kirk S, et al. Lifestyle factors affecting fruit and vegetable consumption in the UK Women’s Cohort Study. Appetite. 2001;37(1):71-79.
Khalil A, Gaudreau P, Cherki M, et al. Antioxidant-rich food intakes and their association with blood total antioxidant status and vitamin C and E levels in community-dwelling seniors from the Quebec longitudinal study NuAge. Exp Gerontol. 2011;46(6):475-481.
36.
23.
Hamer M, Chida Y. Intake of fruit, vegetables, and antioxidants and risk of type 2 diabetes: Systematic review and meta-analysis. J Hypertens. 2007;25(12):2361-2369.
Natella F, Nardini M, Giannetti I, et al. Coffee drinking influences plasma antioxidant capacity in humans. J Agric Food Chem. 2002; 50(21):6211-6216.
37.
24.
di Giuseppe R, Arcari A, Serafini M, et al. Total dietary antioxidant capacity and lung function in an Italian population: A favorable role in premenopausal/never smoker women. Eur J Clin Nutr. 2012; 66(1):61-68.
Pitsavos C, Panagiotakos DB, Tzima N, et al. Adherence to the Mediterranean diet is associated with total antioxidant capacity in healthy adults: The ATTICA study. Am J Clin Nutr. 2005;82(3):694699.
38.
Torabian S, Haddad E, Rajaram S, et al. Acute effect of nut consumption on plasma total polyphenols, antioxidant capacity and lipid peroxidation. J Hum Nutr Diet. 2009;22(1):64-71.
39.
Record IR, Dreosti IE, McInerney JK. Changes in plasma antioxidant status following consumption of diets high or low in fruit and vegetables or following dietary supplementation with an antioxidant mixture. Br J Nutr. 2001;85(4):459-464.
25.
Mekary RA, Wu K, Giovannucci E, et al. Total antioxidant capacity intake and colorectal cancer risk in the Health Professionals Follow-up Study. Cancer Causes Control. 2010;21(8):1315-1321.
26.
Del Rio D, Agnoli C, Pellegrini N, et al. Total antioxidant capacity of the diet is associated with lower risk of ischemic stroke in a large Italian cohort. J Nutr. 2011;141(1):118-123.
40.
Puchau B, Zulet MA, de EchÂvarri AG, Hermsdorff HH, MartÎnez JA. Dietary total antioxidant capacity is negatively associated with some metabolic syndrome features in healthy young adults. Nutrition. 2010;26(5):534-541.
Leenen R, Roodenburg AJ, Tijburg LB, et al. A single dose of tea with or without milk increases plasma antioxidant activity in humans. Eur J Clin Nutr. 2005;54(1):87-92.
41.
McKay DL, Chen CY, Yeum KJ, et al. Chronic and acute effects of walnuts on antioxidant capacity and nutritional status in humans: A randomized, cross-over pilot study. Nutr J. 2010;9:21.
42.
Leenen R, Roodenburg AJ, Tijburg LB, et al. A single dose of tea with or without milk increases plasma antioxidant activity in humans. Eur J Clin Nutr. 2000;54(1):87-92.
43.
Dragsted LO, Pedersen A, Hermetter A, et al. The 6-a-day study: Effects of fruit and vegetables on markers of oxidative stress and antioxidative defence in healthy nonsmokers. Am J Clin Nutr. 2004;79(6): 1060-1072.
27.
28.
Neyestani T, Shariatzade N, Kalayi A, et al. Regular daily intake of black tea improves oxidative stress biomarkers and decreases serum C-reactive protein levels in type 2 diabetic patients. Ann Nutr Metab. 2010;57(1):40-49.
29.
van Het Hof K, West CE, Weststrate JA, et al. Dietary factors that affect the bioavailability of carotenoids. J Nutr. 2000;130(3):503-506.
30.
Levine M, Conry-Cantilena C, Wang Y, et al. Vitamin C pharmacokinetics in healthy volunteers: Evidence for a recommended dietary allowance. Proc Natl Acad Sci. 1996;93:3704-3709.
44.
ValtueÒa S, Del Rio D, Pellegrini N, et al. The total antioxidant capacity of the diet is an independent predictor of plasma beta-carotene. Eur J Clin Nutr. 2007;61(1):69-76.
Young JF, Nielsen SE, HaraldsdÔttir J, et al. Effect of fruit juice intake on urinary quercetin excretion and biomarkers of antioxidative status. Am J Clin Nutr. 1999;69(1):87-94.
45.
Young JF, Dragsted LO, Daneshvar B, et al. The effect of grape-skin extract on oxidative status. Br J Nutr. 2000;84(4):505-513.
31.
AUTHOR INFORMATION Y. Wang is a PhD student, S.-G. Lee is a PhD student, S. I. Koo is a professor and department head, and O. K. Chun is an assistant professor, all with the Department of Nutritional Sciences, University of Connecticut, Storrs. M. Yang is an MPH student, Harvard School of Public Health, Boston, MA; at the time of the study, she was a PhD student, Department of Nutritional Sciences, University of Connecticut, Storrs. C. G. Davis is a registered dietitian; at the time of the study, she was an MS student, Department of Nutritional Sciences, University of Connecticut, Storrs. Address correspondence to: Ock K. Chun, PhD, MPH, Department of Nutritional Sciences, University of Connecticut, 3624 Horsebarn Rd Extension Unit 4017, Storrs, CT 06269-4017. E-mail: [email protected]
STATEMENT OF POTENTIAL CONFLICT OF INTEREST No potential conflict of interest was reported by the authors.
FUNDING/SUPPORT The study was supported by a grant from the University of Connecticut USDA Hatch (no. CONS00846).
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