Supplemental Material can be found at:
http://jn.nutrition.org/content/suppl/2011/12/21/jn.111.14442
8.DC1.html
The Journal of Nutrition
Nutritional Epidemiology
Total and Specific Polyphenol Intakes in Midlife
Are Associated with Cognitive Function
Measured 13 Years Later1–3
Emmanuelle Kesse-Guyot,4* Léopold Fezeu,4 Valentina A. Andreeva,4 Mathilde Touvier,4
Augustin Scalbert,5 Serge Hercberg,4,6 and Pilar Galan4
4
Unité de Recherche en Epidémiologie Nutritionnelle, U557 Inserm; U1125 Inra; Cnam; Université Paris 13, CRNH IdF, Bobigny, France;
International Agency for Research on Cancer, Nutrition and Metabolism Section, Biomarkers Group, Lyon, France; and 6Département
de Santé Publique, Hôpital Avicenne, Bobigny, France
5
Abstract
Polyphenols, and in particular flavonoids, are omnipresent plant-food components displaying biochemical properties
polyphenol intake and cognitive performance. Polyphenol intake was estimated using the Phenol-Explorer database
applied to at least six 24-h dietary records collected in 1994–1996 as part of the SU.VI.MAX (Supplémentation en
Vitamines et Minéraux Antioxydants) study. The cognitive performance of 2574 middle-aged adults participating in the
cohort was assessed in 2007–2009 using the following four neuropsychological tests: phonemic and semantic fluency, the
RI-48 Cued Recall test, the Trail Making test, and Forward and Backward Digit Span. Inter-correlations among the test
scores were estimated with principal component analysis. Associations between polyphenol intake and cognition were
assessed by multivariate linear regression and ANCOVA. In multivariate models, high total polyphenol intake was
associated with better language and verbal memory (P = 0.01) but not with executive functioning (P = 0.09). More
specifically, intake of catechins (P = 0.001), theaflavins (P = 0.002), flavonols (P = 0.01), and hydroxybenzoic acids (P =
0.0004) was positively associated with language and verbal memory, especially with episodic memory assessed by the
RI-48 test. In contrast, negative associations between scores on executive functioning and intake of dihydrochalcones (P =
0.01), catechins (P = 0.01), proanthocyanidins (P = 0.01), and flavonols (P = 0.01) were detected. High intake of specific
polyphenols, including flavonoids and phenolic acids, may help to preserve verbal memory, which is a salient vulnerable
domain in pathological brain aging. Further investigations are needed to clarify the observed negative associations
regarding executive functioning. J. Nutr. 142: 76–83, 2012.
Introduction
As the elderly population is rapidly increasing, age-associated
neurodegenerative disorders, including dementia, represent a
major public health concern. The lack of curative treatment for
cognitive decline and dementia argues for improvement of the
prevention strategies via modifiable risk factors and behaviors,
1
Supported by the French National Research Agency (no. ANR-05-PNRA-010),
the French Ministry of Health, Médéric, Sodexo, Ipsen, MGEN, and Pierre Fabre.
Mederic and Mutuelle Générale de l’Education Nationale are French health
insurance organizations, which are complementary to the National Health
Insurance System. Ipsen and Pierre Fabre are private pharmaceutical companies.
Sodexo, a food catering company, supported the study by organizing meetings
between researchers and study participants. Sponsors were not involved in the
analysis or interpretation of findings.
2
Author disclosures: E. Kesse-Guyot, L. Fezeu, V. Andreeva, M. Touvier, A.
Scalbert, S. Hercberg, and P. Galan, no conflicts of interest.
3
Supplemental Tables 1–3 are available from the “Online Supporting Material”
link in the online posting of the article and from the same link in the online table of
contents at jn.nutrition.org.
* To whom correspondence should be addressed. E-mail: [email protected].
univ-paris13.fr.
76
such as dietary intake (1). Polyphenols represent a ubiquitous
group of microcomponents contained in various plant-derived
foods. Flavonoids and phenolic acids are the two most frequently
consumed classes of polyphenols (2). Over the past few years,
the potential of polyphenols to preserve brain health has become
the subject of substantial research interest. Experimental studies
suggest that these compounds, especially flavonoids, display
neuroprotective effects, including enhancement of the neuronal
function, stimulating brain flow, and inducing neurogenesis, and
might prevent age-related damage to the central nervous system
through their antioxidant properties and anti-inflammatory
activities (3–6).
However, such findings are based on specific phenolic compounds regardless of their bioavailability, level of consumption,
or ability to cross the blood-brain barrier (7). Such deficiencies
argue for the need for well-designed epidemiological studies
carried out in human populations.
Research on the relationship between the consumption of
polyphenol-rich foods (8–12) and various cognitive outcomes
has hypothesized a positive impact of these micronutrients on
ã 2012 American Society for Nutrition.
Manuscript received May 11, 2011. Initial review completed July 26, 2011. Revision accepted October 3, 2011.
First published online November 16, 2011; doi:10.3945/jn.111.144428.
Downloaded from jn.nutrition.org by guest on December 21, 2015
possibly beneficial to brain health. We sought to evaluate the long-term association between total and class-specific
Materials and Methods
Study population. The SU.VI.MAX study (1994–2002) was initially
designed as a randomized, double-blind, placebo-controlled, primary
prevention trial that included a total of 12,741 (7713 women aged 35–60
y, 5028 men aged 45–60 y) individuals for a planned follow-up of 8 y.
The aim of the study was to test the potential efficacy of daily
supplementation with antioxidant vitamins and minerals at nutritional
doses [ascorbic acid (120 mg), vitamin E (30 mg), b-carotene (6 mg),
selenium (100 mg), and zinc (20 mg)] regarding the incidence of cancer,
CVD, and all-cause mortality (18,19). From the initial SU.VI.MAX
cohort, a total of 6850 participants were included in the SU.VI.MAX 2
study (2007–2009) aimed at evaluating quality of aging (20). The SU.VI.
MAX and SU.VI.MAX 2 studies were conducted according to the
guidelines laid down in the Declaration of Helsinki and were approved
by the Ethics Committee for Studies with Human Subjects of ParisCochin Hospital (CCPPRB nos. 706 and 2364, respectively) and the
Comité National Informatique et Liberté (CNIL nos. 334641 and
907094, respectively). Written informed consent was obtained from each
participant.
Dietary data collection. During the course of the SU.VI.MAX study,
participants were invited to complete a 24-h dietary record every 2 mo
for a total of 6 records/y. These dietary records were randomly
distributed across 2 weekend days and 4 weekdays/y, so that each day
of the week and all seasons were covered, thus accounting for individual
variability in nutrient intake. Data were collected via computerized
questionnaires using the Minitel, a small terminal used in France as an
adjunct to the telephone. For the codification of foods, participants were
assisted by using an instruction manual that included validated photographs of .250 generic foods represented in three main portion sizes.
Participants could also choose from two intermediate or two extreme
portions for a total of seven different portion sizes (21). French recipes
validated by food and nutrition professionals were used to assess the
amounts of specific nutrients consumed from composite dishes. The
Phenol-Explorer database (17) and a published validated composition
7
Abbreviations used: AD, Alzheimer’s disease; BP, blood pressure; CVD,
cardiovascular disease; PCA, principal component analysis; SU.VI.MAX,
Supplémentation en Vitamines et Minéraux Antioxydant; TMT, Trail Making test.
table (22) were used to compute polyphenol and other nutrient intakes.
Only polyphenol classes or subclasses with a mean daily intake .5 mg/d
were considered in the present analysis (2).
Cognitive assessment. Self-reported memory troubles (yes/no) were
recorded at baseline (1994). In 2007–2009, all participants in SU.VI.
MAX 2 were invited to undergo a medical check-up that included a
clinical examination and a neuropsychological evaluation carried out by
trained neuropsychologists. Episodic memory was evaluated using the
RI-48, a delayed, cued recall test based on a list of 48 words belonging to
12 different categories. This test was designed to minimize “ceiling”
effects encountered in some list-learning instruments. The score was the
total number of words retrieved correctly (maximum score of 48) (23).
Lexical-semantic memory was assessed via two verbal fluency tasks: a
semantic fluency task, which consisted of naming as many animals as
possible, and a phonemic fluency task consisting of citing words
beginning with the letter P. The score was the total number of correct
words produced over a 2-min period for each task (24). Working
memory was assessed with the Forward and Backward Digit Span (25).
Participants were asked to repeat two sequences of digits, forward or
backward. The number of digits increased by one until the participant
failed two consecutive trials of the same digit span. One point was scored
for each correct sequence repeated, with a maximum score of 14 points
for digit span forward as well as backward (25). Mental flexibility was
assessed via the Delis-Kaplan TMT consisting of connecting numbers
and letters, alternating between the two series. The score was the time in
seconds needed to complete the task (26), implying that a lower value
indicated better performance. For our analyses, we used the inverse of
the TMT score; thus, a higher score corresponded to a better result.
Covariates. At baseline, information on gender, date of birth, smoking
status (never smoked, former or current smoker), physical activity
(irregular, equivalent to ,1 h walking/d, equivalent to at least 1 h
walking/d), and education (primary, secondary, or university level) was
collected. Anthropometric measurements were obtained at the first
clinical examination (1995–1996). Weight was measured using an
electronic scale, with participants wearing indoor clothing and no shoes.
Height was measured under the same conditions with a wall-mounted
stadiometer. BP was measured with a mercury sphygmomanometer usi
ng a standardized procedure. It was taken once from each arm in partici
pants who had been lying down for at least 10 min. The mean of these
two measurements was used in the analyses. Medication use was
self-reported at baseline and the end of the follow-up. Fasting blood
samples were obtained at baseline and the end of the follow-up and all bi
ochemical measurements were centralized. Fasting blood glucose was
measured using an enzymatic method (Advia 1650; Bayer Diagnostics).
In case of suspected CVD during the follow-up period, relevant medi
cal data (clinical, biochemical, histological, and radiological reports)
were requested from participants, physicians, and/or hospitals. All
reported CVD events were reviewed and validated by an independent
expert committee. In SU.VI.MAX 2, depressive symptoms were assessed
using the French version of the Center for Epidemiologic Studies
Depression Scale (27).
Statistical analyses. Among participants with available neuropsychological evaluation data aged between 45 and 60 y at enrollment, those
with at least three 24-h dietary records from May to October and at least
three records from November to April (thus accounting for seasonality
and intra-individual variability in nutrient intake) provided during the
first 2 y of follow-up were selected for inclusion in the present study.
Among the 6850 adults included in the SU.VI.MAX 2 study, all
cognitive tests were completed by a total of 4447 individuals aged 45–60
y at baseline. Among them, 2819 participants had complete dietary
intake data (i.e., at least six complete 24-h dietary records provided
during the first 2 y of follow-up). From that subsample, we selected a
total of 2574 participants without missing values on the covariables for
inclusion in the present analysis.
We modeled food and nutrient intakes as the respective mean values
across all available 24-h records. Energy adjustment was performed
using the residual method (28). Quartiles of energy-adjusted polyphenol
Polyphenols and cognition
77
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cognition. A Dutch study showed a decreased risk of AD7 among
current smokers with high concentrations of flavonoid intake
(13). Two other studies carried out in the same population
reported a lower risk of dementia and cognitive decline among
those with high flavonoid intake compared to their low-intake
counterparts (14,15).
The physiological properties, bioavailability, and thus potential effects on brain health may vary widely from one
polyphenol compound to another, yet currently there are to our
knowledge no specific research data regarding the different
subtypes of flavonoids.
Recently, the Phenol-Explorer database (16) has become
available to the scientific community, providing data on a total
of 502 different polyphenols (in aglycones, glycosides, and ester
forms) from 452 different foods (17). In addition to total
flavonoid composition, the database also includes detailed composition data for the various subtypes of flavonoids, i.e.,
flavonols, flavanols, flavones, flavonones, and catechines as
well as phenolic acids, lignans, and stilbenes. Recent developments of the Phenol-Explorer system offer the opportunity for
improved precision in estimating polyphenol intakes in the SU.
VI.MAX cohort (2).
The aim of the present study was to evaluate the hypothesized
positive associations between the midlife level of intake of different
types of polyphenols and cognitive function assessed 13 y later.
Results
Intake of polyphenols. Total crude polyphenol intakes were
1.28 6 0.51 and 1.12 6 0.48 g/d among men and women,
respectively (Table 1). Flavonoid and hydroxycinnamic acids
were the two main classes of polyphenols consumed, with
intakes of 0.57 6 0.28 and 0.62 6 0.41g/d, respectively, among
men and 0.50 6 0.26 and 0.55 6 0.41 g/d, respectively, among
women.
The main food and beverage sources of polyphenols were
coffee (36.8%), fruits (18.7%), wine (11.3%), and tea (9.4%)
(data not tabulated).
Participant characteristics. The mean age of the population at
the time of the cognitive evaluation was 66 y. The baseline
characteristics of the participants are shown across quartiles of
total polyphenol intake (Table 2). Compared to participants in
the bottom quartile, those in the highest quartile of polyphenol
intake were more often men and smokers. Increasing polyphenol
intake was significantly associated with a higher level of
education, physical activity, and total energy intake as well as
alcohol, protein, and micronutrient intakes and with a decreased
likelihood of self-reported memory troubles. The percentage of
men (P = 0.15) and women (P = 0.74) with memory troubles was
similar across polyphenol intake quartiles (data not tabulated).
Cognitive factors. Two main cognitive factors were extracted
with PCA, accounting for 61% of the total initial variance in
78
Kesse-Guyot et al.
TABLE 1
Baseline intakes of total and subtypes of polyphenols
by gender (SU.VI.MAX study, 1994–1996)1
Men (n = 1413)
Women (n = 1161)
P
mg/d
Total polyphenols
Flavonoids
Anthocyanins
Dihydrochalcones
Dihydroflavonols
Catechins
Theaflavins
Flavanones
Flavones
Flavonols
Proanthocyanidins
Stilbenes
Lignans
Hydroxybenzoic acids
Hydroxycinnamic acids
Sources of polyphenols
Polyphenols from coffee
Polyphenols from fruit
Polyphenols from wine
Polyphenols from chocolate
Polyphenols from tea
Polyphenols from vegetables
Polyphenols from bread
Polyphenols from potatoes
1280
571
71
4
10
89
8
28
38
54
269
7
0.5
41
621
6 512
6 278
6 52
64
6 10
6 98
6 17
6 33
6 19
6 26
6 176
66
6 0.2
6 34
6 413
1120
499
45
4
4
117
16
26
29
50
210
3
0.4
44
549
6 477
6 261
6 37
63
65
6 132
6 24
6 27
6 14
6 30
6 145
63
6 0.2
6 44
6 413
,0.0001
,0.0001
,0.0001
0.23
,0.0001
0.27
,0.0001
0.15
,0.0001
,0.0001
,0.0001
,0.0001
,0.0001
0.12
,0.0001
508
218
192
109
76
52
44
28
6 414
6 174
6 177
6 150
6 160
6 37
6 29
6 19
458
207
71
91
149
54
30
20
6 417
6 145
6 98
6 128
6 219
6 38
6 21
6 134
,0.0001
0.90
,0.0001
0.001
,0.0001
0.12
,0.0001
,0.0001
1
Data are mean 6 SD. SU.VI.MAX, Supplémentation en Vitamines et Minéraux
Antioxydant.
cognitive performance (Supplemental Table 2). The first factor
accounted for 42% of the variance and reflected language and
verbal memory abilities (e.g., memory for words and other
abstractions involving language) (24). The test scores with the
highest loadings on factor 1 pertained to the semantic (0.80) and
phonemic fluency (0.66) tests and the RI-48 cued recall task
(0.74).
The second factor accounted for 19% of variance and
reflected executive functioning. Test scores with the highest
loadings were the Forward (0.85) and Backward (0.84) Digit
Span tasks and, to a lesser extent, the TMT (0.50).
Association between polyphenol intake and language and
verbal memory (Factor 1). Results of the analyses of the
association between energy-adjusted total and class-specific
polyphenol intake and language and verbal memory are presented
in Table 3. In the initial, age- and gender-adjusted model, intakes
of total polyphenol, total flavonoids, anthocyanins, catechins,
theaflavins, flavanones, flavonols, lignans, and hydroxybenzoic
acids were positively associated with the language and verbal
memory score. In the final multivariate model, the associations
were somewhat attenuated but remained significant for total
polyphenols, total flavonoids, catechins, theaflavins, flavonols,
and hydroxybenzoic acids. Performance on the RI-48 test,
measuring episodic memory, largely accounted for the observed
relationships (Supplemental Table 3).
Association between polyphenols intake and executive
functioning (Factor 2). Results of the analyses of the association between energy-adjusted total and class-specific polyphenol intake and executive functioning are presented in Table 4. In
Downloaded from jn.nutrition.org by guest on December 21, 2015
intake were calculated. BMI was calculated as the ratio of weight:
squared height (kg/m2). Hypertension at baseline was defined as systolic
BP $140 mm Hg, diastolic BP $90 mm Hg, or self-reported antihypertensive drug use. Presence of diabetes was defined as blood glucose $7
mmol/L or self-reported antidiabetic drug use. To limit exclusion due to
missing values, we excluded only participants with missing data for
covariates with ,5% missing. Thus, in case of missing clinical measurements for BMI, self-reported data were used when available. A
missing category was used in case of missing values for hypertension
status at baseline.
The inverse of the TMT score was log-transformed to improve
normality. PCA was performed to compute the inter-correlations among
the various test scores, thereby maximizing the explained variance.
Factors were rotated via an orthogonal transformation. A Cattel’s scree
plot (a plot of the total variance related to each pattern) was used to
determine the number of patterns to be retained in the final model. For
purposes of facilitating interpretability, the cognitive scores were
converted into T scores (50 6 10, mean 6 SD). Thus, a 1-point
difference in the test score corresponded to one-tenth of a SD difference.
Mean polyphenol intakes are reported by gender. Descriptive
baseline characteristics are reported as mean 6 SD or percentage across
total polyphenol intake quartiles. The provided P values refer to the
nonparametric Wilcoxon’s rank test, the linear contrast test, or the trend
chi-square test, as appropriate.
ANCOVA were used for assessing the association between quartiles
of total polyphenol and polyphenol subtype intakes and the cognitive
scores. The initial model was adjusted for gender and age at the time of
the cognitive evaluation. The final multivariate model was further
adjusted for educational level, energy intake, number of 24-h dietary
records, Western and healthy dietary patterns extracted using PCA
(Supplemental Table 1), depressive symptoms concomitant with the
cognitive performance assessment, and diabetes and CVD status during
the follow-up as well as the following baseline covariates: memory
troubles, alcohol intake, physical activity, intervention group (active vs.
placebo), BMI, tobacco use, and hypertension.
All tests of significance were 2-sided and the type I error was set at
5%. Statistical analyses were performed using SAS software (version 9.1,
SAS Institute).
TABLE 2
Baseline characteristics of the population across total polyphenol intake quartiles (SU.VI.MAX Study; 1994–1996)1
Quartile 1 (#863 mg/d) Quartile 2 (.863 to #1145 mg/d) Quartile 3 (.1145 to #1487 mg/d) Quartile 4 (.1487 mg/d)
644
42.7
643
52.4
644
58.7
643
65.8
,0.0001
65.3 6 4.6
24.1 6 3.5
65.6 6 4.5
24.3 6 3.4
65.6 6 4.6
24.2 6 3.1
65.8 6 4.7
24.6 6 3.2
0.10
0.02
23.5
32.1
44.4
24.7
30.0
45.3
21.6
29.7
48.8
20.8
24.9
54.3
0.001
24.7
40.2
35.1
21.2
40.0
38.9
22.5
36.2
41.3
18.2
42.0
39.8
0.01
64.0
28.0
8.0
50.5
54.1
36.2
9.6
54.7
45.3
43.6
11.0
56.2
38.7
49.1
12.1
54.4
,0.0001
11.1 6
1810 6
12 6
41 6
18 6
42 6
17 6
278 6
83 6
3.8 6
2.3
477
13
4.9
2.7
5.7
6
85
37
2.2
11.1
2030
19
40.4
17.7
41.8
19
315
95
3.9
6 2.1
6 499
6 18
6 4.7
6 2.6
6 5.8
66
6 77
6 38
6 2.0
11.2
2160
24
40.2
17.6
42.1
21
341
105
4.2
6 2.1
6 508
6 20
6 4.9
6 2.5
6 6.0
66
6 88
6 44
6 2.1
11.2
2310
30
40.6
17.4
42.0
23
370
110
4.4
6 2.1
6 552
6 25
6 4.7
6 2.5
6 5.8
68
6 105
6 49
6 2.5
0.13
0.19
,0.0001
,0.0001
0.18
,0.0001
0.47
,0.0001
,0.0001
,0.0001
,0.0001
Values are mean 6 SD or percent as appropriate, n = 2574. SU.VI.MAX, Supplémentation en Vitamines et Minéraux Antioxydant.
P values based on linear contrast or chi-squared trend test.
3
Energy intake excluding energy from alcohol.
4
Values are percentage of total daily energy intake (without alcohol).
1
2
the initial, age- and gender-adjusted model, intakes of dihydrochalcones and flavanones were negatively associated with
executive functioning scores.
In the final multivariate model, the association with dihydrochalcones remained significant. In addition, increased intakes
of catechines, proanthocyanidins, and flavanols were related to
lower scores on the executive functioning factor.
There was no association with total polyphenol intake. In-depth
analyses indicated that intakes of dihydrochalcones, catechins, and
flavanols were negatively associated with Forward Digit Span
scores, whereas proanthocyanidin intake was negatively associated
with Backward Digit Span scores (Supplemental Table 3).
Discussion
In this large prospective study, a positive association was observed
between total polyphenol intake and cognitive factors reflecting
language and verbal memory assessed after a follow-up of 13 y,
even after accounting for various confounding factors, including
vascular parameters, alcohol intake, and overall dietary patterns.
More specifically, increasing intake of total flavonoids, catechins,
theaflavines, flavonols, and phenolic acids was positively associated with long-term language and verbal memory capacities.
In contrast, no beneficial association was detected between total
polyphenol intake and a cognitive score reflecting executive
functioning (e.g., working memory and mental flexibility).
Unexpectedly, an adverse effect was found for some specific
classes of polyphenols (catechins, proanthocyanidins, and flavonols). Overall, our findings suggest that the various polyphenol
compounds may be differentially involved in the preservation of
distinct cognitive domains. The clinical importance of our
estimates may be evaluated according to educational level, which
has consistently demonstrated an inverse association with cognitive function (1). In this study, the mean values on the verbal
memory and executive functioning factors were 7.42 and 6.82
among those with high and low levels of education, respectively.
Thus, a difference of 1 point on the language and verbal memory
factor between the top and bottom quartiles of total polyphenol
intake may be considered relatively low at the individual level,
but this difference is probably important at the population level.
Animal models support the positive effect of specific flavonoids on some aspects of cognition (6), in agreement with our
findings regarding language and verbal memory. Some epidemiological studies are also in favor of a beneficial effect of consumption of polyphenol-rich foods on various cognitive
outcomes (8–12). In a recent cross-sectional study carried out
in Norway (12), better cognitive performance was observed
among participants with increased consumption of chocolate,
wine, and tea. However, that study did not exclude the
possibility that other components of these foods, or the overall
dietary patterns conducive to such intakes, may be responsible
for the observed relationships. As underlined by these authors,
Polyphenols and cognition
79
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n
Male, %
General characteristics
Age at cognitive evaluation, y
BMI, kg/m2
Physical activity, %
Irregular
,1 h/d
$1 h/d
Education, %
Primary
Secondary
University
Smoking status, %
Never smoker
Former smoker
Current smoker
Intervention group, %
Dietary information
24-h records, n
Energy intake,3 kcal/d
Alcohol intake, g/d
Lipids,4 %
Proteins,4 %
Carbohydrates,4 %
Fiber, g/d
Folic acid, mg/d
Vitamin C, mg/d
b-Carotene, mg/d
P2
TABLE 3
Energy-adjusted associations between quartiles of
total and class-specific polyphenol intakes and
language and verbal memory (cognitive factor 1)
(SU.VI.MAX and SU.VI.MAX 2 studies, 1994–2007)1
Quartile
1
Quartile
3
Quartile
4
P
2
644
643
644
643
49.0 6 0.4 49.7 6 0.4 51.1 6 0.4 50.6 6 0.4 0.0004
48.5 6 0.7 48.9 6 0.7 50.2 6 0.7 49.6 6 0.7 0.01
644
643
644
643
48.5 6 0.4 50.2 6 0.4 50.4 6 0.4 51.4 6 0.4 0.0001
48.3 6 0.7 49.7 6 0.7 49.5 6 0.7 49.8 6 0.7 0.03
644
643
644
643
49.5 6 0.4 49.7 6 0.4 50.8 6 0.4 50.5 6 0.4
49.1 6 0.7 48.9 6 0.7 50.0 6 0.7 49.2 6 0.7
0.02
0.50
644
643
644
643
49.9 6 0.4 50.3 6 0.4 50.6 6 0.4 49.7 6 0.4
49.2 6 0.7 49.4 6 0.7 49.8 6 0.7 48.6 6 0.7
0.91
0.43
644
643
644
643
49.6 6 0.4 50.2 6 0.4 50.6 6 0.4 50.0 6 0.4
48.9 6 0.7 49.8 6 0.7 49.6 6 0.7 48.9 6 0.8
0.36
0.99
644
643
644
643
48.3 6 0.4 50.1 6 0.4 50.5 6 0.4 51.6 6 0.4 0.0001
48.1 6 0.7 49.3 6 0.7 49.4 6 0.7 50.1 6 0.7 0.001
644
643
644
643
48.5 6 0.4 49.8 6 0.4 50.5 6 0.4 51.6 6 0.4 0.0001
48.2 6 0.7 49.2 6 0.7 49.5 6 0.7 50.1 6 0.7 0.002
644
643
644
643
49.5 6 0.4 50.3 6 0.4 50.1 6 0.4 50.5 6 0.4
49.1 6 0.7 49.7 6 0.7 49.2 6 0.7 49.1 6 0.7
0.10
0.78
644
643
644
643
49.5 6 0.4 49.8 6 0.4 50.4 6 0.4 50.7 6 0.4
48.9 6 0.7 49.2 6 0.7 49.5 6 0.7 49.6 6 0.7
0.02
0.19
644
643
644
643
50.7 6 0.4 50.0 6 0.4 49.7 6 0.4 50.0 6 0.4
49.8 6 0.7 49.4 6 0.7 48.9 6 0.7 49.0 6 0.7
0.19
0.09
644
643
644
643
48.8 6 0.4 49.8 6 0.4 50.7 6 0.4 51.2 6 0.4 0.0001
48.4 6 0.7 49.2 6 0.7 49.6 6 0.7 49.9 6 0.7 0.01
644
643
644
643
49.5 6 0.4 50.2 6 0.4 50.8 6 0.4 50.0 6 0.4
48.8 6 0.7 49.7 6 0.7 49.8 6 0.7 48.9 6 0.8
0.25
0.87
644
643
644
643
49.5 6 0.4 49.5 6 0.4 51.0 6 0.4 50.5 6 0.4
48.9 6 0.7 49.0 6 0.7 50.3 6 0.7 49.2 6 0.7
0.01
0.33
644
643
644
643
48.3 6 0.4 50.1 6 0.4 50.4 6 0.4 51.7 6 0.4 0.0001
(Continued)
80
Kesse-Guyot et al.
Continued
Quartile
1
Quartile
2
Quartile
3
Quartile
4
P2
Model 24
48.0 6 0.7 49.1 6 0.7 49.7 6 0.7 50.1 6 0.7 0.0004
Hydroxycinnamic acids
n
644
643
644
643
Model 13
50.0 6 0.4 50.1 6 0.4 50.2 6 0.4 50.3 6 0.4 0.58
48.9 6 0.7 49.0 6 0.7 49.3 6 0.7 49.9 6 0.7 0.07
Model 24
Values are adjusted mean 6 SEM of the language and verbal memory factor across
quartiles of polyphenols intake. CVD, cardiovascular disease; PCA, principal component analysis; SU.VI.MAX, Supplémentation en Vitamines et Minéraux Antioxydant.
2
P-linear contrast across quartiles of polyphenols intake.
3
Model 1: adjusted for age (y) and gender.
4
Model 2: model 1 + energy intake (kcal), number of 24-h dietary records, education
(primary/secondary/university) and intervention group (active vs. placebo), BMI (kg/m2),
tobacco use status (former/never/current), physical activity (irregular, equivalent to ,1 h
walking/d, equivalent to $1 h walking/d), diabetes mellitus during follow-up (yes/no),
baseline hypertension status (yes/no), CVD during follow-up (yes/no), CES–D (Center
for Epidemiologic Studies–Depression Scale) score, self-reported memory troubles
(yes/no) at baseline, and Western and healthy dietary patterns extracted via PCA.
1
investigating foods rich in certain nutrients does not permit a full
understanding of the specific effects of these nutrients.
Three other studies have reported links between flavonoids
and risk of dementia (13,15), cognitive performance, and
cognitive decline (14). Two of these studies were carried out
in the same population and supported a protective effect of
flavonoid intake on cognitive outcomes (14,15). The third study
observed a decreased risk of AD among participants with high
intake of flavonoids, but these associations were significant only
in smokers (13). These findings support the hypothesis of a
potentially favorable effect of high intake of flavonoids on global
cognitive function and prevention of AD. However, no studies to
our knowledge have focused specifically on individual cognitive
functions; indeed, cognitive domains have been suggested to be
differentially affected during pathologic aging (29).
Moreover, it has been suggested that nutritional factors exert
site-specific effects within brain regions (30). For example, a
cross-sectional study reported a positive association between tea
consumption and cognitive functions other than attention (9).
That finding is in agreement with those in the present study
regarding the differential effects of nutritional factors according
to specific cognitive function domains.
Most existing mechanistic hypotheses concerning the link
between polyphenol intake and brain health pertain to specific
flavonoid properties. These compounds, especially when derived from fruit, may enhance memory and learning through
their effects on synaptic plasticity, neuronal communication,
and blood flow (31–33). For example, long-term memory and
synaptic plasticity are modulated by the activity of genes
regulated by the transcription factor CREB, which has been
shown to be activated by flavonoids. Such mechanisms could help
explain our findings regarding better language and verbal
memory performance with increasing flavonoid intake (31). In
addition, one in vitro study recently suggested that phenolic acids,
especially caffeic acid, may have similar or greater neuroprotective effects than flavonoids against neurotoxic molecules
involved in Parkinson’s disease progression (34), but further
investigations regarding hydroxybenzoic acids and memory are
needed. To our knowledge, no molecular mechanisms accounting
for the negative association between dihydrochalcones, catechins,
proanthocyanidins, and flavonols and executive function have
been advanced. However, it has been suggested that, under
Downloaded from jn.nutrition.org by guest on December 21, 2015
Total Polyphenols
n
Model 13
Model 24
Flavonoids
n
Model 13
Model 24
Anthocyanins
n
Model 13
Model 24
Dihydrochalcones
n
Model 13
Model 24
Dihydroflavonols
n
Model 13
Model 24
Catechins
n
Model 13
Model 24
Theaflavins
n
Model 13
Model 24
Proanthocyanidins
n
Model 13
Model 24
Flavonones
n
Model 13
Model 24
Flavones
n
Model 13
Model 24
Flavonols
n
Model 13
Model 24
Stilbenes
n
Model 13
Model 24
Lignans
n
Model 13
Model 24
Hydroxybenzoic acids
n
Model 13
Quartile
2
TABLE 3
TABLE 4
Energy-adjusted associations between quartiles of
total and class-specific polyphenol intakes and
executive functioning (cognitive factor 2) (SU.VI.
MAX and SU.VI.MAX 2 studies, 1994–2007)1
Quartile
1
Quartile
3
Quartile
4
P
2
644
49.9 6 0.4
50.9 6 0.7
643
50.1 6 0.4
50.8 6 0.7
644
49.8 6 0.4
50.4 6 0.7
643
49.8 6 0.4
50.0 6 0.7
0.80
0.09
644
49.9 6 0.4
51.1 6 0.7
643
50.0 6 0.4
50.8 6 0.7
644
49.5 6 0.4
50.0 6 0.7
643
50.2 6 0.4
50.2 6 0.7
0.80
0.07
644
49.7 6 0.4
50.7 6 0.7
643
49.8 6 0.4
50.5 6 0.7
644
50.0 6 0.4
50.5 6 0.7
643
50.1 6 0.4
50.3 6 0.7
0.38
0.59
644
50.6 6 0.4
51.3 6 0.7
643
50.0 6 0.4
50.6 6 0.7
644
49.6 6 0.4
50.2 6 0.7
643
49.4 6 0.4
49.9 6 0.7
0.02
0.01
644
49.8 6 0.4
50.8 6 0.7
643
49.6 6 0.4
50.5 6 0.7
644
50.2 6 0.4
50.5 6 0.7
643
50.0 6 0.4
50.3 6 0.8
0.46
0.62
644
49.9 6 0.4
51.3 6 0.7
643
50.3 6 0.4
51.0 6 0.7
644
49.8 6 0.4
50.1 6 0.7
643
49.7 6 0.4
49.9 6 0.7
0.57
0.01
644
50.1 6 0.4
51.3 6 0.7
643
49.6 6 0.4
50.4 6 0.7
644
50.0 6 0.4
50.4 6 0.7
643
49.9 6 0.4
50.2 6 0.7
0.91
0.06
644
50.3 6 0.4
51.2 6 0.7
643
49.8 6 0.4
50.5 6 0.7
644
50.1 6 0.4
50.6 6 0.7
643
49.5 6 0.4
49.8 6 0.7
0.24
0.01
644
49.0 6 0.4
49.7 6 0.7
643
50.0 6 0.4
50.8 6 0.7
644
50.4 6 0.4
51.0 6 0.7
643
50.2 6 0.4
50.7 6 0.7
0.02
0.07
644
49.7 6 0.4
50.3 6 0.7
643
50.2 6 0.4
50.9 6 0.7
644
49.5 6 0.4
50.1 6 0.7
643
50.2 6 0.4
50.7 6 0.7
0.61
0.76
644
50.2 6 0.4
51.5 6 0.7
643
50.0 6 0.4
50.8 6 0.7
644
49.4 6 0.4
49.8 6 0.7
643
50.0 6 0.4
50.1 6 0.7
0.49
0.01
644
49.9 6 0.4
51.0 6 0.7
643
49.4 6 0.4
50.3 6 0.7
644
50.3 6 0.4
50.6 6 0.7
643
50.0 6 0.4
50.2 6 0.8
0.49
0.45
644
49.6 6 0.4
50.7 6 0.7
643
50.1 6 0.4
50.8 6 0.7
644
49.9 6 0.4
50.6 6 0.7
643
50.0 6 0.4
50.0 6 0.7
0.60
0.32
644
49.4 6 0.4
643
50.4 6 0.4
644
49.4 6 0.4
643
50.4 6 0.4
0.25
(Continued)
Continued
Model 24
Hydroxycinnamic acids
n
Model 13
Model 24
Quartile
1
Quartile
2
Quartile
3
Quartile
4
P2
50.8 6 0.7
50.9 6 0.7
50.0 6 0.7
50.5 6 0.7
0.36
644
49.8 6 0.4
50.6 6 0.7
643
49.4 6 0.4
50.0 6 0.7
644
50.8 6 0.4
51.5 6 0.7
643
49.5 6 0.4
50.1 6 0.7
0.87
0.93
1
Values are adjusted mean 6 SEM of executive functioning score across quartiles of
polyphenol intake. CVD, cardiovascular disease; PCA, principal component analysis;
SU.VI.MAX, Supplémentation en Vitamines et Minéraux Antioxydant.
2
P-linear contrast across quartiles of polyphenols intake.
3
Model 1: adjusted for age (y) and gender.
4
Model 2: model 1 + energy intake (kcal), number of 24-h dietary records, education
(primary/secondary/university) and intervention group (active vs. placebo), BMI (kg/m2),
tobacco use status (former/never/current), physical activity (irregular, equivalent to ,1
h walking/d, equivalent to $1 h walking/d), diabetes mellitus during follow-up (yes/no),
baseline hypertension status (yes/no), CVD during follow-up (yes/no), CES–D (Center
for Epidemiologic Studies–Depression Scale) score, self-reported memory troubles
(yes/no) at baseline, and Western and healthy dietary patterns extracted via PCA.
certain conditions, some catechins (derived from tea, fruits, wine,
and to a lesser extent cocoa) may have dual effects on the brain
through prooxidant action (35).
Finally, experimental (30) and epidemiological (36) studies
have reported that different foods or nutrients from various
sources might exert region-specific actions within brain structures. Overall, further investigations aimed at elucidating the
mechanisms of action of these components regarding different
cognitive domains are warranted.
Most published studies in this area have focused on total
flavonoid intake, estimated with respect to the main flavonoid
compounds rather than on class-specific flavonoids. For example,
in the PAQUID study, flavonoid intakes were estimated via
quercetin, kaempferol, myricetin, luteolin, and apigenin intake,
thus possibly biasing the estimates, because other flavonoids were
not taken into consideration. The Phenol-Explorer database is the
first database of its kind that provides detailed and accurate
information about a wide variety of polyphenols. Previously
developed databases mainly focused on specific flavonoids, preventing a direct comparison of polyphenol intakes across studies.
However, levels of such intakes have been shown to dramatically
differ from one population to another. For example, flavonoid
intake was 14 6 6 mg/d in the PAQUID study (14), 29 6 12 mg/d
in the Rotterdam study (13), and 571 6 278 mg/d among women
and 621 6 413 mg/d among men in our study. Such variability
may stem from differences in the dietary patterns, under- or
overestimation of food consumption, or methodological discrepancies regarding the assessment of nutrient composition with
different food composition tables (2). Making food composition
tables consistent with one another is crucial for accurately
comparing intake levels among studies (2).
Some limitations of our study should be mentioned. Because
cognitive evaluation data at baseline were not available, we were
unable to control for baseline levels of cognitive performance
according to level of polyphenol intake. However, considering
the baseline age range and general health status of the participants, it is unlikely that cognitive impairment was present at
baseline. Moreover, self-reported memory troubles did not differ
across level of polyphenol intake. Another limitation pertains to
the measurement of dietary practices only at baseline without
accounting for dietary changes over the years. If indeed dietary
change had occurred, such participants’ nutrient intake might
Polyphenols and cognition
81
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Total polyphenols
n
Model 13
Model 24
Flavonoids
n
Model 13
Model 24
Anthocyanins
n
Model 13
Model 24
Dihydrochalcones
n
Model 13
Model 24
Dihydroflavonols
n
Model 13
Model 24
Catechins
n
Model 13
Model 24
Theaflavins
n
Model 13
Model 24
Proanthocyanidins
n
Model 13
Model 24
Flavanones
n
Model 13
Model 24
Flavones
n
Model 13
Model 24
Flavonols
n
Model 13
Model 24
Stilbenes
n
Model 13
Model 24
Lignans
n
Model 13
Model 24
Hydroxybenzoic acids
n
Model 13
Quartile
2
TABLE 4
Acknowledgments
The authors especially thank Stéphane Raffard, neuropsychologist, who was responsible for standardization of the cognitive
evaluation; Nathalie Arnault (statistician), who coordinated
82
Kesse-Guyot et al.
data management; Frédérique Ferrat, who coordinated the
logistic aspects of the neuropsychological evaluation; and
Gwenaël Monot (computer scientist), who coordinated the computing aspects. E.K.G. carried out data checking and analyses and
was responsible for drafting the manuscript; V.A.A., L.F., A.S.,
S.H., M.T., and P.G. were involved in interpreting results and
editing the manuscript; and E.K.G., P.G., and S.H. were responsible for developing the design and protocol of the study. All
authors read and approved the final manuscript.
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