Abstract
INTRODUCTION:
The objective was to analyze associations between dietary intake of multiple nutrients and altered cognitive function and/or decline.
METHODS:
Observational analyses of participants (n=6,334) in two randomized trials of nutritional supplements for age-related macular degeneration: Age-Related Eye Disease Study (AREDS) and AREDS2.
RESULTS:
In AREDS, for 4 of 38 nutrients examined, higher intake quintiles were significantly associated with decreased risk of cognitive impairment on the Modified Mini-Mental State test (<80): β-carotene, copper, docosahexaenoic acid, and insoluble fiber. In AREDS2, for 13 of 44 nutrients, higher intake quintiles were associated with decreased risk on the Telephone Interview Cognitive Status-Modified (<30). Rate of cognitive decline over up to 10 years was not significantly different with higher intake of any nutrient.
DISCUSSION:
Higher dietary intake of multiple nutrients, including specific vitamins, minerals, carotenoids, fatty acids, and fiber, was associated with lower risk of cognitive impairment but not slower decline in cognitive function.
Keywords: Diet, nutrient, cognitive function, cognitive impairment, Alzheimer’s disease, dementia, vitamins, minerals, carotenoids, fatty acids, fiber
1. Introduction
Dementia is a syndrome in which gradual cognitive impairment interferes with everyday tasks. It is characterized by a progressive decrease in cognitive abilities including learning, memory, attention, language, intelligence, and perception. Alzheimer’s disease (AD) is the most common form. No pharmacological treatments are available to modify the course of dementia.(1,2) This means that preventative approaches have an important role. Indeed, one third of AD cases worldwide have been attributed to potentially modifiable risk factors.(3)
In older individuals with accelerated cognitive decline, who may have higher risk of dementia (4,5), preventative interventions aimed at slowing cognitive decline may be productive, i.e., decreasing progression to mild cognitive impairment (MCI) and/or from MCI to dementia. In this context, diet may be highly relevant. Indeed, diet can exert profound effects on biological aging (6–10), and has been associated with age-related conditions linked to dementia, such as diabetes and cardiovascular disease.(11,12) Some observational studies have observed that higher intakes of particular dietary nutrients are associated with decreased or increased risk of cognitive impairment and/or cognitive decline.(13–16)
The Age-Related Eye Disease Study (AREDS) and AREDS2 were multicenter phase III randomized clinical trials (RCT) designed to assess the effects of nutritional supplementation on AMD progression.(17,18) In both, the primary outcome was progression to late AMD. Recent AREDS/AREDS2 analyses demonstrated that closer adherence to a Mediterranean dietary pattern was associated with lower risk of cognitive impairment and that higher fish intake was associated with lower risk of cognitive impairment and slower decline in cognitive function.(19) Additional analysis of the biologically active nutrients may provide more insights into the molecular basis of disease, with implications for potential preventative strategies.
The aim of this report was to examine potential associations between the dietary intake of multiple nutrients and both cross-sectional status and longitudinal changes in cognitive function.
2. Methods
The study designs for AREDS and AREDS2 have been described previously.(17,20,21) In AREDS, 4,757 participants (55-80 years) were recruited (1992-1998) at 11 US retinal specialty clinics and enrolled into AMD categories (no AMD to unilateral late AMD). In AREDS2, 4,203 participants (50-85 years) with bilateral large drusen or unilateral late AMD were recruited (2006-2008) at 82 US retinal specialty clinics.
2.1. Consent statement
Institutional review board approval was obtained at each site and all participants provided written informed consent. The research was conducted under the Declaration of Helsinki and, for AREDS2, complied with the Health Insurance Portability and Accountability Act.
2.2. Study procedures
AREDS participants were randomly assigned to placebo, antioxidants, zinc, or the combination.(17) AREDS2 participants were randomly assigned to receive the supplements that lowered risk of AMD progression in AREDS, either (i) alone, or with additional (ii) lutein/zeaxanthin, (iii) docosahexaenoic acid (DHA) plus eicosapentaenoic acid (EPA), or (iv) the combination.(18) Eligible participants had to provide informed consent and be free of conditions that would make follow-up or medication compliance difficult. Hence, participants with dementia at baseline were effectively excluded.
2.3. AREDS and AREDS2: ancillary studies of cognitive function
An AREDS ancillary study examining cognitive function was added to the protocol in June 2000, as described previously.(20) Between July 2000 and March 2004, the tests were administered (25-30 minutes) in person by certified interviewers. Of the 4,360 AREDS participants alive at ancillary study implementation, 3,074 (70.5%) consented and underwent testing.(20)
An AREDS2 ancillary study examining cognitive function was pre-specified in the protocol, as described previously.(21) The tests were administered (30 minutes) over the telephone by certified interviewers. Justification for telephone testing had previously been demonstrated in AREDS data.(22) The first testing administration was within three months of randomization. Repeat administrations took place every two years, until close-out of the main study at five years. Of the 4,203 AREDS2 participants, 3,470 (82.6%) consented and underwent testing at baseline.(21) Following close-out at five years, of these, 1,291 (37.2%) participants underwent repeat testing at 10 years (AREDS2 10-year follow-on study).
The batteries of cognitive function tests used have been described previously.(20,21) The individual tests are listed in Table 1 and described in the Supplement. These included the Modified Mini-Mental State Examination (3MS), for AREDS, and the Telephone Interview Cognitive Status-Modified (TICS-M, a version of the 3MS), for AREDS2. In addition, a composite score (representing an overall score for the whole battery) was calculated as the sum of the z-scores for each test within the battery.(21,22)
Table 1.
Cognitive function tests used, ranges in their scores (possible and observed within the study), and cut-off points used to define cognitive impairment
| Cognitive function test | Range possible | Range in study | Cut-off point | ||
|---|---|---|---|---|---|
| Min | Max | Min | Max | ||
| Age-Related Eye Disease Study | |||||
| 3MS* | 0 | 100 | 47 | 100 | ≤79 |
| Buschke immediate recall | 0 | 100 | 0 | 83.3 | ≤8.3 |
| Buschke overall word list | 0 | 12 | 0 | 11.2 | ≤3.3 |
| Logical memory part I | 0 | 75 | 0 | 69 | ≤22 |
| Logical memory part II | 0 | 50 | 0 | 45 | ≤9 |
| Animal category | 0 | - | 0 | 44 | ≤11 |
| Letter fluency | 0 | - | 1 | 91 | ≤21 |
| Logical memory part I | 0 | 75 | 0 | 69 | ≤22 |
| Logical memory part II | 0 | 50 | 0 | 45 | ≤9 |
| Digits backwards† | 0 | 12 | 0 | 12 | ≤3 |
| Composite score‡ | - | - | -23.5 | 17.9 | ≤−7.0 |
| Age-Related Eye Disease Study 2 | |||||
| TICS-M* | 0 | 41 | 12 | 41 | ≤29 |
| TICS-M recall | 0 | 10 | 0 | 10 | =0 |
| Animal category | 0 | - | 0 | 43 | ≤10 |
| Letter fluency | 0 | - | 0 | 118 | ≤19 |
| Alternating fluency | 0 | - | 0 | 14 | ≤1 |
| Logical memory part I | 0 | 75 | 0 | 69 | ≤22 |
| Logical memory part II | 0 | 50 | 0 | 46 | ≤9 |
| Digits backwards† | 0 | 100 | 0 | 100 | ≤23 |
| Composite score‡ | - | - | -21.1 | 17.6 | ≤−7.0 |
TICS-M = Telephone Interview Cognitive Status-Modified; 3MS = Modified Mini-Mental State Examination
The 3MS has a pre-defined cut-off point for cognitive impairment of 80 and the TICS-M has one of 30. For the other tests, cognitive impairment is defined as being in the lowest decile, except for the TICS-M recall, for which it is defined as being in the lowest quintile. In both study cohorts, the cut-off points were determined using only the participants included in the analyses; in AREDS2, the cut-off points were determined using all time-points (though the same cut-off point is used for all study visits)
Different versions of the digits backwards test were used in AREDS and AREDS2, hence the difference in the score ranges
Composite score is the sum of Z-scores from each test within the battery.
2.4. Outcome measurements
The primary outcome was cognitive impairment, defined as (i) 3MS <80 (AREDS) or TICS-M <30 (AREDS2), and (ii) composite score in the lowest decile (Table 1). The secondary outcomes were absolute scores of the (i) 3MS (AREDS) or TICS-M (AREDS2), and (ii) composite.
2.5. Assessment of the intake of dietary nutrients
In both studies, food frequency questionnaires (FFQs) were administered to all participants at randomization. The AREDS FFQ, a 90-item, semi-quantitative modified Block FFQ, has been described previously.(23) The AREDS2 FFQ, a 131-item, semi-quantitative Harvard FFQ, has been described previously.(24,25) In both FFQs, participants were asked how often, on average, they had consumed each food/beverage item during the preceding year. The FFQs were processed at the University of Minnesota Nutrition Coordinating Center to estimate the daily dietary intake of 38 nutrients (AREDS) or 44 nutrients (AREDS2). These excluded any additional intake from oral supplements (i.e., the randomized assignments). Each nutrient was divided by total calorie intake to represent nutrient intake density and intake quintiles were calculated (separately for each cohort and for men and women), with quintile 5 representing highest intake.
2.6. Genotype analysis
As part of AREDS/AREDS2, 2,889 (AREDS) and 1,826 (AREDS2) participants consented to genotype analysis. SNPs were analyzed using a custom Illumina HumanCoreExome array.(26) APOE haplotypes were defined by rs429358 and rs7412(27); they were considered as a 3-level variable (Table 2).
Table 2.
Baseline demographic, clinical, and genetic characteristics of the study populations.
| AREDS | AREDS2 | |
|---|---|---|
| Participants: n | 3029 | 3305 |
| Age (years): mean (SD) | 68.7 (4.9) | 72.9 (7.7) |
| Female: n (%) | 1721 (56.8) | 1908 (57.7) |
| Race: n (%) | ||
| White | 2912 (96.1) | 3211 (97.2) |
| Non-white | 117 (3.9) | 94 (2.8) |
| Education level: n (%) | ||
| High school or less | 935 (30.9) | 962 (29.1) |
| At least some college | 932 (30.8) | 1576 (47.7) |
| Postgraduate | 1160 (38.3) | 709 (21.5) |
| Unknown | 2 (0.1) | 58 (1.8) |
| Smoking status: n (%) | ||
| Never | 1435 (47.4) | 1409 (42.6) |
| Former | 1399 (46.2) | 1666 (50.4) |
| Current | 195 (6.4) | 230 (7.0) |
| History diabetes: n (%) | 231 (7.6) | 2895 (87.6) |
| History hypertension: n (%) | 1046 (34.5) | 1924 (58.2) |
| 3MS score (AREDS) or TICS-M score (AREDS2): mean (SD) | 92.9 (6.3)* | 32.9 (3.5)* |
| Participants with cognitive impairment: n (%) (3MS <80 in AREDS; TICS-M <30 in AREDS2) |
119 (3.9)* | 492 (14.9)* |
| Depression score CES-D > 16: n (%) | 374 (12.3) | 1397 (42.3) |
| Follow-up | ||
| Follow-up time from baseline cognitive test to last cognitive test (years): mean (SD) | - | 6.5 (3.8) |
| Cognitive function testing at 2 years: n (%) | - | 2919 (88.3%) |
| Cognitive function testing at 4 years: n (%) | - | 2589 (78.3%) |
| Cognitive function testing at 10 years: n (%) | - | 1291 (39.1%) |
| Participants with genetic data: n | 2360 | 1517 |
| APOE haplotype: n (%) | ||
| 0 (ε2/ε2 or ε2/ε3) | 382 (16.2) | 281 (18.5) |
| 1 (ε3/ε3, ε2/ε4, or ε1/ε3) | 1541 (65.3) | 954 (62.9) |
| 2 (ε3/ε4 or ε4/ε4) | 436 (18.5) | 282 (18.6) |
AREDS = Age-Related Eye Disease Study; SD = standard deviation; CES-D = Center for Epidemiologic Studies Depression Scale; TICS-M = Telephone Interview Cognitive Status-Modified; 3MS = Modified Mini-Mental State Examination
Cognitive function data are shown at baseline for AREDS2; for AREDS, they are shown at the single time-point of assessment (during follow-up)
2.7. Statistical analyses
In AREDS and AREDS2, considered separately, analyses of cognitive impairment were performed for each nutrient by logistic regression; for cognitive test scores, general linear models were used in AREDS and mixed-model regression in AREDS2. For AREDS2, the regression took into account the repeated measures, number of tests, and unequal time spacing by using a spatial power correlation; an autoregressive correlation structure was used for the repeated measures logistic regression. Significance was set by Bonferroni correction at 0.0007 (AREDS) and 0.0006 (AREDS2), though higher P-values were not disregarded.
The regression analyses were repeated with adjustment for treatment assignment (i.e., the oral supplements or placebo to which participants were randomized), including an interaction term between nutrient intake (treated continuously) and treatment assignment. In AREDS, this included antioxidants as main effect and zinc as main effect; in AREDS2, this included DHA/EPA as main effect and lutein/zeaxanthin as main effect. The regression analyses were also repeated with adjustment for Centrum multivitamin use (in AREDS only, since Centrum use was almost universal in AREDS2).
The analyses were repeated with inclusion of an interaction term between APOE haplotype and nutrient intake (for each nutrient with significant associations at P<0.01 in the primary analyses).
For AREDS2, to compare rates of cognitive decline according to nutrient intake quintiles, data from participants with multiple testing were analyzed using a model that included an interaction term of time-point and intake quintile. Significance was set at 0.0006 (Bonferroni). The analyses of cognitive test scores were repeated, including an interaction term of nutrient intake quintile and APOE haplotype.
All models were adjusted for baseline age, sex, race, smoking, diabetes, hypertension, baseline depression score (CES-D ≥16 or not), total calorie intake, and (AREDS2 only) years from baseline. Total calorie intake was included to decrease confounding and reduce extraneous variation from factors like physical activity and metabolic efficiency.(28,29) Participants were excluded from an analysis if they had missing covariates or data for the relevant test. Analyses were conducted using SAS version 9.4 (SAS Institute Inc).
3. Results
3.1. Participant cohorts: baseline characteristics
The AREDS enrolled 4,757 participants. Of the 4,360 participants alive at ancillary cognitive study implementation, 3,074 (70.5%) undertook one or more cognitive tests. Of these, 3,029 (98.5%) had no missing data (in either the cognitive function tests or covariates) and comprised the study population. Similarly, the AREDS2 enrolled 4,203 participants. Of these, 3,470 (82.6%) undertook one or more cognitive tests at baseline. Of these, 3,305 (95.2%) had cognitive function and covariate data available for the TICS-M analyses, while 2,887 (83.2%, a subset of the 3,305) had cognitive function and covariate data available for the composite score analyses. The characteristics of the participants are shown in Table 2, and their dietary intake in Supplementary Tables 1–3. In AREDS, the proportion of participants with cognitive impairment (3MS <80) at the single time-point of assessment was 3.9%. In AREDS2, the proportion with cognitive impairment (TICS-M <30) at study baseline was 14.8%. APOE risk haplotypes were significantly associated with increased risk of cognitive impairment, based on the composite score, in both AREDS and AREDS2 (Supplementary Table 4).
3.2. Analysis of cognitive function according to the intake of individual dietary nutrients
Age-Related Eye Disease Study
The results of cross-sectional analyses, according to the dietary intake of individual nutrients, are shown in Figure 1 and Table 3. In AREDS, for 4 of the 38 nutrients examined, intake quintiles 4 and/or 5 (with quintile 1 as reference) were significantly associated with decreased risk of cognitive impairment on the 3MS test at the Bonferroni level of P=0.0007: β-carotene, copper, DHA, and insoluble dietary fiber. For an additional 12 nutrients, association was present at the nominal level: vitamin A, niacin, vitamin B6, folate, β-carotene equivalents, α-carotene, lycopene, zinc, EPA, EPA+DHA, galactose, and soluble dietary fiber. No nutrient had intake quintiles 4 and/or 5 associated with increased risk at the Bonferroni level. For 4 nutrients, association with increased risk was present at the nominal level: vitamin D, saturated fat, monounsaturated fat (MUFA), and oleic acid. Regarding the absolute scores, the regression estimates are shown in Supplementary Figure 1.
Figure 1.
Butterfly plots showing odds ratios for cognitive impairment in the Age-Related Eye Disease Study (AREDS) cohort. For each nutrient, the odds ratio of dietary intake quintile 5 (with quintile 1 as reference) is shown on the x axis, with protective associations in blue and harmful associations in red; smaller P values are denoted by darker colors. The results are adjusted for baseline age, sex, race, smoking, diabetes, hypertension, baseline depression score (Center for Epidemiologic Studies Depression Scale [CES-D] ≥16 or not), and total calorie intake. A. Cognitive impairment defined as Modified Mini-Mental State test score < 80. B. Cognitive impairment defined as composite score in the lowest decile.
Table 3.
Results of the logistic regression modeling of cognitive impairment according to quintiles of nutrient intake in the Age-Related Eye Disease Study cohort: odds ratios and P values (n=3029 participants). Results are shown in comparison to quintile 1 (reference).
| Modified mini-mental* | Composite* | |||
|---|---|---|---|---|
| Nutrient | Q4 vs Q1 | Q5 vs Q1 | Q4 vs Q1 | Q5 vs Q1 |
| Vitamin A IU | 0.46 (0.25,0.84) | 0.40 (0.22,0.74) | 0.66 (0.44,0.98) | 0.64 (0.43,0.96) |
| 0.0112 | 0.0038 | 0.0418 | 0.0314 | |
| Retinol | 1.08 (0.59,1.99) | 1.00 (0.54,1.85) | 0.87 (0.59,1.28) | 0.85 (0.58,1.27) |
| 0.8025 | 0.9921 | 0.4732 | 0.4330 | |
| Vitamin D | 2.17 (1.14,4.10) | 1.46 (0.75,2.84) | 1.39 (0.93,2.09) | 1.18 (0.78,1.78) |
| 0.0177 | 0.2676 | 0.1106 | 0.4253 | |
| Vitamin E | 1.01 (0.58,1.75) | 0.70 (0.39,1.26) | 0.82 (0.56,1.20) | 0.91 (0.63,1.33) |
| 0.9727 | 0.2353 | 0.3081 | 0.6383 | |
| Vitamin C | 0.73 (0.41,1.27) | 0.56 (0.31,1.02) | 0.57 (0.39,0.83) | 0.49 (0.33,0.73) |
| 0.2633 | 0.0578 | 0.0038 | 0.0005 | |
| Thiamine | 1.04 (0.56,1.94) | 0.89 (0.47,1.71) | 1.04 (0.70,1.54) | 0.80 (0.53,1.21) |
| 0.9018 | 0.7369 | 0.8374 | 0.2849 | |
| Riboflavin | 0.63 (0.35,1.12) | 0.75 (0.42,1.33) | 0.82 (0.56,1.20) | 0.91 (0.62,1.34) |
| 0.1172 | 0.3223 | 0.3108 | 0.6247 | |
| Niacin | 0.75 (0.43,1.30) | 0.49 (0.27,0.91) | 0.92 (0.62,1.37) | 0.87 (0.58,1.30) |
| 0.3106 | 0.0231 | 0.6755 | 0.4913 | |
| Vitamin B6 | 0.67 (0.36,1.25) | 0.52 (0.27,1.00) | 0.94 (0.62,1.44) | 0.89 (0.58,1.36) |
| 0.2090 | 0.0493 | 0.7817 | 0.5969 | |
| Folate | 0.77 (0.43,1.37) | 0.48 (0.25,0.91) | 0.77 (0.52,1.14) | 0.70 (0.46,1.05) |
| 0.3765 | 0.0239 | 0.1957 | 0.0816 | |
| Vitamin B12 | 0.71 (0.41,1.24) | 0.58 (0.32,1.05) | 0.87 (0.59,1.28) | 0.86 (0.58,1.27) |
| 0.2261 | 0.0730 | 0.4862 | 0.4546 | |
| Beta-Carotene | 0.55 (0.32,0.96) | 0.30 (0.16,0.57) | 0.51 (0.34,0.76) | 0.52 (0.35,0.78) |
| 0.0350 | 0.0002 | 0.0010 | 0.0013 | |
| Beta-Carotene Equivalents | 0.53 (0.30,0.92) | 0.37 (0.21,0.68) | 0.52 (0.35,0.78) | 0.56 (0.37,0.83) |
| 0.0235 | 0.0012 | 0.0015 | 0.0037 | |
| Alpha-Carotene | 0.72 (0.41,1.27) | 0.50 (0.27,0.92) | 0.88 (0.59,1.30) | 0.74 (0.49,1.11) |
| 0.2573 | 0.0250 | 0.5110 | 0.1442 | |
| Beta-Cryptoxanthin | 0.94 (0.52,1.71) | 0.95 (0.52,1.73) | 0.71 (0.48,1.05) | 0.70 (0.47,1.04) |
| 0.8436 | 0.8635 | 0.0867 | 0.0768 | |
| Lutein and Zeaxanthin | 0.59 (0.32,1.10) | 0.59 (0.32,1.08) | 0.48 (0.31,0.73) | 0.68 (0.46,1.00) |
| 0.0989 | 0.0891 | 0.0006 | 0.0520 | |
| Lycopene | 0.76 (0.44,1.32) | 0.40 (0.21,0.75) | 0.80 (0.55,1.16) | 0.53 (0.35,0.79) |
| 0.3314 | 0.0041 | 0.2412 | 0.0018 | |
| Calcium | 1.22 (0.68,2.19) | 0.77 (0.42,1.44) | 0.99 (0.67,1.45) | 0.66 (0.44,0.98) |
| 0.4966 | 0.4168 | 0.9582 | 0.0417 | |
| Magnesium | 0.65 (0.36,1.17) | 0.62 (0.34,1.12) | 0.50 (0.33,0.76) | 0.55 (0.36,0.82) |
| 0.1510 | 0.1105 | 0.0012 | 0.0037 | |
| Iron | 0.75 (0.40,1.41) | 0.70 (0.37,1.33) | 1.01 (0.67,1.51) | 0.94 (0.63,1.42) |
| 0.3783 | 0.2729 | 0.9668 | 0.7812 | |
| Zinc | 0.71 (0.40,1.24) | 0.54 (0.29,0.98) | 0.81 (0.55,1.18) | 0.69 (0.46,1.02) |
| 0.2269 | 0.0443 | 0.2721 | 0.0653 | |
| Copper | 0.47 (0.27,0.83) | 0.28 (0.14,0.53) | 0.50 (0.33,0.76) | 0.51 (0.33,0.77) |
| 0.0088 | 0.0001 | 0.0012 | 0.0016 | |
| Selenium | 0.90 (0.50,1.62) | 0.74 (0.40,1.37) | 0.95 (0.64,1.41) | 0.90 (0.60,1.35) |
| 0.7209 | 0.3417 | 0.7834 | 0.6200 | |
| Cholesterol | 0.63 (0.35,1.13) | 0.81 (0.46,1.43) | 0.77 (0.52,1.16) | 1.18 (0.80,1.73) |
| 0.1197 | 0.4757 | 0.2105 | 0.3994 | |
| Saturated Fat | 2.03 (1.10,3.76) | 1.86 (0.98,3.54) | 1.56 (1.04,2.33) | 1.46 (0.96,2.23) |
| 0.0239 | 0.0586 | 0.0312 | 0.0759 | |
| Monounsaturated Fat | 2.02 (1.07,3.83) | 2.05 (1.06,3.96) | 1.62 (1.07,2.46) | 2.28 (1.51,3.44) |
| 0.0309 | 0.0333 | 0.0215 | <.0001 | |
| Oleic | 1.74 (0.92,3.30) | 2.13 (1.12,4.05) | 1.59 (1.06,2.39) | 2.09 (1.39,3.14) |
| 0.0880 | 0.0206 | 0.0263 | 0.0004 | |
| Linoleic | 0.92 (0.51,1.65) | 0.92 (0.52,1.63) | 1.03 (0.68,1.56) | 1.26 (0.85,1.88) |
| 0.7776 | 0.7689 | 0.8800 | 0.2454 | |
| Alpha-Linolenic | 0.60 (0.33,1.11) | 0.55 (0.30,1.01) | 0.65 (0.43,0.98) | 0.67 (0.44,1.00) |
| 0.1017 | 0.0552 | 0.0410 | 0.0480 | |
| Arachidonic | 0.63 (0.34,1.18) | 0.80 (0.44,1.45) | 1.10 (0.74,1.63) | 1.10 (0.74,1.64) |
| 0.1504 | 0.4691 | 0.6335 | 0.6291 | |
| EPA | 0.52 (0.29,0.91) | 0.40 (0.22,0.73) | 0.46 (0.31,0.69) | 0.41 (0.28,0.61) |
| 0.0220 | 0.0028 | 0.0001 | <.0001 | |
| DHA | 0.36 (0.20,0.66) | 0.35 (0.19,0.62) | 0.60 (0.41,0.88) | 0.47 (0.32,0.70) |
| 0.0009 | 0.0003 | 0.0085 | 0.0002 | |
| EPA+DHA | 0.49 (0.27,0.89) | 0.41 (0.22,0.74) | 0.67 (0.46,0.97) | 0.41 (0.27,0.62) |
| 0.0182 | 0.0034 | 0.0346 | <.0001 | |
| Galactose | 0.69 (0.41,1.17) | 0.40 (0.22,0.73) | 0.54 (0.37,0.80) | 0.44 (0.30,0.66) |
| 0.1643 | 0.0029 | 0.0018 | <.0001 | |
| Lactose | 1.15 (0.66,2.02) | 0.80 (0.44,1.44) | 1.08 (0.73,1.59) | 0.75 (0.50,1.13) |
| 0.6195 | 0.4553 | 0.6916 | 0.1690 | |
| Alcohol | 0.77 (0.39,1.54) | 0.67 (0.32,1.38) | 0.82 (0.53,1.25) | 0.47 (0.29,0.76) |
| 0.4610 | 0.2752 | 0.3526 | 0.0022 | |
| Soluble Dietary Fiber | 0.71 (0.40,1.29) | 0.46 (0.24,0.88) | 0.80 (0.54,1.20) | 0.55 (0.36,0.85) |
| 0.2619 | 0.0194 | 0.2804 | 0.0073 | |
| Insoluble Dietary Fiber | 0.70 (0.40,1.22) | 0.30 (0.15,0.60) | 0.60 (0.40,0.89) | 0.51 (0.34,0.78) |
| 0.2055 | 0.0006 | 0.0123 | 0.0017 | |
Results adjusted for baseline age, sex, race, smoking, diabetes, hypertension, baseline depression score (CES-D ≥16 or not), and total calorie intake.
The equivalent results for cognitive impairment according to the composite score are shown in Figure 1. For 6 nutrients, intake quintiles 4 and/or 5 were significantly associated with decreased risk at the Bonferroni level: vitamin C, lutein and zeaxanthin, EPA, DHA, EPA+DHA, and galactose. For an additional 11 nutrients, association was present at the nominal level. Conversely, for 2 nutrients, intake quintiles 4 and/or 5 were associated with increased risk at the Bonferroni level: MUFA and oleic acid. For 1 additional nutrient (saturated fat), association was present at the nominal level.
Age-Related Eye Disease Study 2
In similar analyses of AREDS2 (Figure 2 and Table 4), for 13 of the 44 nutrients examined, intake quintiles 4 and/or 5 were associated with decreased risk of cognitive impairment on the TICS-M test at the Bonferroni level of P=0.0006: vitamin E, folate, natural food folate, β-carotene, lutein/zeaxanthin, lycopene, magnesium, selenium, EPA, DHA, EPA+DHA, EPA+DPA+DHA (where DPA is docosapentaenoic acid), and alcohol. For an additional 10 nutrients, association with decreased risk was present at the nominal level. For 2 nutrients/characteristics, quintiles 4 and/or 5 were associated with increased risk at the Bonferroni level: retinol and glycemic load. For 1 additional nutrient/characteristic (glycemic index), association was present at the nominal level. Regarding the absolute scores, the regression estimates are shown in Supplementary Figure 2.
Figure 2.
Butterfly plots showing odds ratios for cognitive impairment in the Age-Related Eye Disease Study 2 (AREDS2) cohort. For each nutrient, the odds ratio of dietary intake quintile 5 (with quintile 1 as reference) is shown on the x axis, with protective associations in blue and harmful associations in red; smaller P values are denoted by darker colors. The results are adjusted for baseline age, sex, race, smoking, diabetes, hypertension, baseline depression score (Center for Epidemiologic Studies Depression Scale [CES-D] ≥16 or not), total calorie intake, and years from baseline. A. Cognitive impairment defined as Telephone Interview Cognitive Status-Modified test score < 30. B. Cognitive impairment defined as composite score in the lowest decile.
Table 4.
Results of the logistic regression modeling of cognitive impairment according to quintiles of nutrient intake in the Age-Related Eye Disease Study 2 cohort: odds ratios and P values. Results are shown in comparison to quintile 1 (reference).
| TICS (n=3305 participants)* |
Composite (n=2887 participants)* |
|||
|---|---|---|---|---|
| Nutrient | Q4 vs Q1 | Q5 vs Q1 | Q4 vs Q1 | Q5 vs Q1 |
| Vitamin A IU | 0.80 (0.63,1.01) | 0.76 (0.60,0.95) | 0.57 (0.41,0.80) | 0.55 (0.39,0.77) |
| 0.0561 | 0.0171 | 0.0012 | 0.0006 | |
| Vitamin A RAE | 0.96 (0.76,1.21) | 0.99 (0.79,1.24) | 0.71 (0.52,0.99) | 0.74 (0.53,1.04) |
| 0.7131 | 0.9138 | 0.0425 | 0.0799 | |
| Retinol | 1.23 (0.97,1.56) | 1.65 (1.31,2.09) | 0.93 (0.65,1.31) | 1.41 (1.01,1.98) |
| 0.0842 | <.0001 | 0.6664 | 0.0467 | |
| Vitamin D | 0.84 (0.67,1.04) | 0.72 (0.58,0.90) | 0.63 (0.46,0.87) | 0.55 (0.39,0.76) |
| 0.1138 | 0.0045 | 0.0041 | 0.0004 | |
| Vitamin E | 0.56 (0.45,0.70) | 0.46 (0.37,0.58) | 0.49 (0.36,0.68) | 0.33 (0.23,0.47) |
| <.0001 | <.0001 | <.0001 | <.0001 | |
| Vitamin C | 0.73 (0.58,0.91) | 0.83 (0.66,1.04) | 0.56 (0.40,0.79) | 0.68 (0.49,0.94) |
| 0.0052 | 0.1139 | 0.0008 | 0.0211 | |
| Thiamine | 0.83 (0.67,1.04) | 0.96 (0.77,1.21) | 1.06 (0.76,1.47) | 1.05 (0.75,1.46) |
| 0.1148 | 0.7512 | 0.7403 | 0.7945 | |
| Riboflavin | 0.92 (0.74,1.16) | 1.13 (0.90,1.42) | 0.88 (0.64,1.22) | 1.02 (0.72,1.44) |
| 0.4825 | 0.3002 | 0.4459 | 0.9290 | |
| Niacin | 0.84 (0.67,1.05) | 0.84 (0.67,1.06) | 1.01 (0.74,1.38) | 0.77 (0.54,1.08) |
| 0.1336 | 0.1524 | 0.9634 | 0.1257 | |
| Vitamin B6 | 0.76 (0.61,0.94) | 0.93 (0.75,1.17) | 0.66 (0.48,0.91) | 0.80 (0.58,1.11) |
| 0.0131 | 0.5407 | 0.0115 | 0.1840 | |
| Folate | 0.65 (0.52,0.81) | 0.84 (0.67,1.05) | 0.68 (0.49,0.94) | 0.78 (0.56,1.10) |
| 0.0002 | 0.1328 | 0.0210 | 0.1627 | |
| Natural Food Folate | 0.66 (0.53,0.82) | 0.60 (0.48,0.76) | 0.69 (0.51,0.94) | 0.40 (0.28,0.56) |
| 0.0002 | <.0001 | 0.0186 | <.0001 | |
| Folic Acid | 0.72 (0.58,0.91) | 0.87 (0.70,1.10) | 0.59 (0.42,0.83) | 0.79 (0.57,1.10) |
| 0.0061 | 0.2421 | 0.0027 | 0.1684 | |
| Vitamin B12 | 0.93 (0.74,1.16) | 1.21 (0.96,1.53) | 0.65 (0.47,0.91) | 0.93 (0.67,1.29) |
| 0.5063 | 0.1059 | 0.0110 | 0.6611 | |
| Beta-Carotene | 0.64 (0.51,0.81) | 0.65 (0.52,0.82) | 0.50 (0.36,0.70) | 0.47 (0.33,0.65) |
| 0.0002 | 0.0002 | <.0001 | <.0001 | |
| Alpha-Carotene | 0.84 (0.67,1.06) | 0.90 (0.72,1.13) | 0.53 (0.38,0.75) | 0.69 (0.51,0.95) |
| 0.1444 | 0.3748 | 0.0003 | 0.0228 | |
| Beta-Cryptoxanthin | 0.97 (0.76,1.22) | 1.17 (0.93,1.47) | 0.89 (0.64,1.26) | 1.06 (0.76,1.48) |
| 0.7696 | 0.1778 | 0.5188 | 0.7448 | |
| Lutein+Zeaxanthin | 0.67 (0.54,0.85) | 0.57 (0.45,0.72) | 0.72 (0.53,0.99) | 0.31 (0.22,0.45) |
| 0.0007 | <.0001 | 0.0440 | <.0001 | |
| Lycopene | 0.74 (0.59,0.92) | 0.64 (0.51,0.80) | 0.58 (0.42,0.81) | 0.61 (0.44,0.84) |
| 0.0059 | <.0001 | 0.0010 | 0.0025 | |
| Calcium | 0.82 (0.66,1.03) | 0.97 (0.77,1.22) | 0.63 (0.45,0.88) | 0.70 (0.51,0.98) |
| 0.0887 | 0.8119 | 0.0059 | 0.0362 | |
| Magnesium | 0.57 (0.45,0.71) | 0.59 (0.47,0.75) | 0.62 (0.45,0.85) | 0.47 (0.33,0.65) |
| <.0001 | <.0001 | 0.0036 | <.0001 | |
| Iron | 0.95 (0.76,1.18) | 0.90 (0.72,1.12) | 1.02 (0.73,1.41) | 1.07 (0.77,1.49) |
| 0.6271 | 0.3428 | 0.9211 | 0.6926 | |
| Zinc | 0.87 (0.69,1.08) | 0.87 (0.69,1.09) | 0.81 (0.59,1.11) | 0.69 (0.49,0.96) |
| 0.2087 | 0.2200 | 0.1915 | 0.0270 | |
| Copper | 0.88 (0.70,1.10) | 0.91 (0.73,1.15) | 0.77 (0.55,1.07) | 0.80 (0.57,1.12) |
| 0.2502 | 0.4362 | 0.1168 | 0.1900 | |
| Selenium | 0.91 (0.68,1.22) | 0.70 (0.59,0.81) | 0.85 (0.54,1.33) | 0.72 (0.58,0.91) |
| 0.5165 | <.0001 | 0.4679 | 0.0047 | |
| Cholesterol | 1.05 (0.84,1.32) | 1.03 (0.81,1.30) | 1.26 (0.91,1.74) | 0.89 (0.62,1.27) |
| 0.6671 | 0.8277 | 0.1680 | 0.5173 | |
| Saturated Fat | 1.19 (0.95,1.49) | 1.22 (0.97,1.53) | 1.15 (0.83,1.60) | 1.26 (0.91,1.75) |
| 0.1344 | 0.0858 | 0.4027 | 0.1667 | |
| Monounsaturated Fat | 0.83 (0.67,1.04) | 0.75 (0.60,0.94) | 0.96 (0.69,1.32) | 0.81 (0.57,1.15) |
| 0.1095 | 0.0135 | 0.7942 | 0.2383 | |
| Oleic Acid | 0.87 (0.70,1.08) | 0.77 (0.61,0.97) | 1.00 (0.73,1.38) | 0.80 (0.56,1.13) |
| 0.2056 | 0.0243 | 0.9816 | 0.2035 | |
| Linoleic Acid | 0.94 (0.75,1.19) | 0.92 (0.73,1.15) | 1.13 (0.80,1.60) | 0.94 (0.67,1.32) |
| 0.6249 | 0.4616 | 0.4817 | 0.7252 | |
| Alpha-Linolenic Acid | 1.01 (0.81,1.26) | 0.91 (0.73,1.14) | 1.01 (0.72,1.40) | 0.81 (0.58,1.13) |
| 0.9184 | 0.4071 | 0.9636 | 0.2166 | |
| Arachidonic Acid | 0.91 (0.72,1.14) | 1.08 (0.85,1.36) | 0.88 (0.62,1.23) | 1.07 (0.77,1.50) |
| 0.3896 | 0.5274 | 0.4438 | 0.6779 | |
| EPA | 0.49 (0.39,0.61) | 0.54 (0.43,0.68) | 0.46 (0.33,0.63) | 0.40 (0.29,0.55) |
| <.0001 | <.0001 | <.0001 | <.0001 | |
| DPA | 0.77 (0.61,0.97) | 0.67 (0.54,0.84) | 0.70 (0.50,0.97) | 0.58 (0.42,0.82) |
| 0.0286 | 0.0006 | 0.0315 | 0.0016 | |
| DHA | 0.54 (0.43,0.68) | 0.56 (0.45,0.69) | 0.49 (0.36,0.67) | 0.44 (0.32,0.61) |
| <.0001 | <.0001 | <.0001 | <.0001 | |
| EPA+DHA | 0.52 (0.41,0.65) | 0.54 (0.43,0.67) | 0.44 (0.32,0.60) | 0.41 (0.30,0.57) |
| <.0001 | <.0001 | <.0001 | <.0001 | |
| EPA+DPA+DHA | 0.56 (0.45,0.70) | 0.48 (0.38,0.60) | 0.43 (0.31,0.60) | 0.42 (0.31,0.59) |
| <.0001 | <.0001 | <.0001 | <.0001 | |
| Lactose | 1.16 (0.92,1.47) | 1.20 (0.95,1.50) | 0.96 (0.69,1.33) | 1.00 (0.72,1.40) |
| 0.1988 | 0.1192 | 0.7951 | 0.9802 | |
| Alcohol | 0.47 (0.38,0.59) | 0.46 (0.37,0.57) | 0.44 (0.32,0.60) | 0.31 (0.23,0.43) |
| <.0001 | <.0001 | <.0001 | <.0001 | |
| Fiber | 0.72 (0.57,0.90) | 0.79 (0.63,0.99) | 0.81 (0.58,1.14) | 0.82 (0.58,1.16) |
| 0.0045 | 0.0392 | 0.2270 | 0.2593 | |
| Total Choline | 0.85 (0.68,1.07) | 0.91 (0.72,1.14) | 0.74 (0.54,1.03) | 0.75 (0.53,1.05) |
| 0.1704 | 0.4174 | 0.0725 | 0.0899 | |
| Free Choline | 0.73 (0.58,0.91) | 0.69 (0.55,0.88) | 0.48 (0.34,0.66) | 0.46 (0.33,0.64) |
| 0.0058 | 0.0026 | <.0001 | <.0001 | |
| Glycemic Index | 1.36 (0.92,1.99) | 2.11 (1.33,3.35) | 1.72 (0.97,3.05) | 3.46 (1.77,6.77) |
| 0.1205 | 0.0015 | 0.0639 | 0.0003 | |
| Glycemic Load | 1.60 (1.27,2.02) | 1.68 (1.33,2.13) | 2.30 (1.60,3.30) | 2.48 (1.74,3.56) |
| <.0001 | <.0001 | <.0001 | <.0001 | |
Results adjusted for baseline age, sex, race, smoking, diabetes, hypertension, baseline depression score (CES-D ≥16 or not), total calorie intake, and years from baseline.
The equivalent results for cognitive impairment according to the composite score are shown in Figure 2. For 13 nutrients, intake quintiles 4 and/or 5 were associated with decreased risk at the Bonferroni level. For an additional 12 nutrients, association was present at the nominal level. For 2 nutrients/characteristics, intake quintiles 4 and/or 5 were associated with increased risk at the Bonferroni level: glycemic index and glycemic load. For 1 additional nutrient (retinol), association was present at the nominal level.
The results of additional analyses, where the analyses were repeated with adjustment for treatment assignment or Centrum multivitamin use, are provided in the Supplement (including Supplementary Tables 5–7). In analyses of interactions between nutrient intake and APOE haplotype (for each nutrient with significant associations at P<0.01 in the primary analyses), no significant interactions were observed in either AREDS or AREDS2 for the outcome of cognitive impairment (even at the nominal level).
3.3. Longitudinal analysis of cognitive function, according to the intake of individual dietary nutrients, in AREDS2
Analyses of cognitive decline over time were possible in AREDS2, owing to the repeated nature of the cognitive assessments (at baseline, two, four, and 10 years), but not in AREDS. In AREDS2, for each nutrient, the proportions of participants with cognitive impairment changed over time in a similar way, irrespective of nutrient intake quintiles. Similarly, the rate of change over time in cognitive function scores was not significantly different according to intake quintiles. The p-interaction values between quintile and study year were greater than 0.01 in all cases (for both TICS-M and the composite score).
APOE risk haplotypes were significantly associated with faster decline in cognitive function scores, for the composite score (p=0.02 for level 2 vs 0; Supplementary Table 8). However, no significant interaction (at p=0.01) was observed between APOE haplotype and intake, for any nutrient, in terms of rate of decline.
Discussion
Main findings and interpretation
This study comprised a comprehensive analysis of a wide variety of dietary nutrients in two US study populations of older individuals without frank dementia at baseline, examined in clinical trial settings that included detailed testing of cognitive function. Higher dietary intake of some nutrients was associated with lower risk of cognitive impairment and higher cognitive function scores. These dietary nutrients with protective associations comprised ones from multiple classes, including vitamins, minerals, carotenoids, lipids, and others. Those with the strongest and most consistent associations included vitamins A-C (i.e., including several different B vitamins) and E, the minerals copper, magnesium, selenium, and zinc, the carotenoids lutein, zeaxanthin, beta-carotene, and lycopene, the lipids DHA and EPA, and others such as fiber. In contrast, higher intake of other nutrients was associated with higher risk of cognitive impairment and lower cognitive function scores. Those with the strongest and most consistent harmful associations included the lipids MUFA, oleic acid, and saturated fatty acids, and diets with high glycemic index or load.
Overall, many of these associations support the idea that a Mediterranean-like diet pattern is associated with decreased risk of cognitive impairment. Indeed, the results are consistent with a recent report (based on the same AREDS/AREDS2 cohorts) showing that higher adherence to a Mediterranean-like diet pattern was associated with decreased risk of cognitive impairment.(19) For example, the Mediterranean diet pattern comprises frequent consumption of plant-based foods containing high levels of the vitamins, carotenoids, and minerals observed to have protective associations in this study.(30,31) Similarly, the Mediterranean diet is characterized by infrequent consumption of foods containing saturated/monounsaturated fats or with high glycemic indices (e.g., red meat and refined sugars, respectively) that had harmful associations in the current study.
Longitudinal analyses of cognitive function in the AREDS2 demonstrated that, for each nutrient, the likelihood of cognitive impairment changed over time in a similar way, irrespective of nutrient intake quintiles; similarly, the rate of change in cognitive function scores did not differ. Hence, cognitive decline did not appear to be significantly faster or slower with higher intake of any one of the nutrients analyzed. Overall, therefore, differences in dietary intake for many nutrients were associated with strong cross-sectional but absent longitudinal differences in cognitive function.
Several potential explanations may exist for differing associations with cognitive impairment versus cognitive decline. First, cognitive decline may actually be slower with higher intake of some nutrients, but with strength of association too small to be captured here; a larger sample size and longer follow-up might be required. Second, cognitive decline may truly not differ according to higher intake of these nutrients. Differences in cognitive function according to nutrient intake might be explained by differences in peak cognitive function earlier in life, caused by dietary intake, but followed by relatively equal rates of decline irrespective of nutrient intake. However, higher peak cognitive function earlier in life from dietary influences might represent superior resilience to neurodegeneration, i.e., greater cognitive reserve.(32) Third, the associations might relate to confounding by unmeasured health or socioeconomic factors.
In general, the results were consistent between the two datasets for most nutrients examined, despite several differences between the two studies, including decade of study, dietary habits, FFQ used, and cognitive testing approach. For example, protective associations were consistent for the lipids DHA and EPA, multiple carotenoids, several vitamins, and fiber. For lutein, zeaxanthin, DHA, and EPA, the consistency occurred despite one quarter of AREDS2 participants being randomly assigned to lutein/zeaxanthin supplementation, one quarter to DHA/EPA, and one quarter to both. Indeed, in AREDS2, oral supplementation with DHA/EPA or lutein/zeaxanthin had no statistically significant effect on yearly change in cognitive function.(21)
However, some potential inconsistencies were observed. For MUFA (and oleic acid, a common MUFA), weak but harmful associations were observed in AREDS, and weak but protective associations in AREDS2. These differences may relate to whether MUFA and oleic acid sources were predominantly from animal or plant foods and from high or low nutrient-dense foods. In the United States and northern European countries, the primary sources of MUFA are meat, dairy, and sugary foods, which are high in saturated fats and low in nutrient density.(33,34) However, in Mediterranean countries, the primary sources are plant foods, including olive oil. Similarly, for vitamin D, a weak but harmful association was observed in AREDS, and a weak but protective association in AREDS2. Again, this might reflect whether the sources were predominantly meat or other sources, including fish, eggs, or fortified dairy foods and cereals. For zinc and copper, protective associations were observed in AREDS, but no significant associations in AREDS2. However, this may be explained partially by the different randomized assignments: all AREDS2 participants were assigned zinc and copper supplements, where only half of AREDS participants were assigned these.
Regarding alcohol, although the odds ratio estimates for risk of cognitive impairment were below 1 in both AREDS and AREDS2, they were particularly low and highly significant in AREDS2. Potential reasons may include differences in FFQ used, type of alcohol (e.g., red wine vs liquor), and frequency (e.g., excess quantities rarely vs small quantities daily), together with the possibility of non-linear associations.
Comparison with literature
Relatively few previous studies have analyzed the dietary intake of a broad spectrum of nutrients simultaneously in this way, using prospectively obtained data, though other studies have examined individual nutrients or small numbers of nutrients, both from RCTs and observational data. This literature has been reviewed in detail.(13–16) In general, in RCTs, supplementation of individual nutrients has typically failed to improve cognition in healthy older adults, but has tended to improve cognition in populations at risk.(13) For example, the DO-HEALTH study in Europe randomized 2157 healthy older adults to vitamin D3 supplementation and/or omega-3 fatty acids and/or exercise, versus placebo, and observed no effect on cognitive function over 3 years.(35) By contrast, Yang et al in China randomized 183 older adults with MCI to vitamin D3 supplementation versus placebo, and observed improved cognitive function over 12 months.(36) Similarly, the FACIT study in the Netherlands randomized 791 older adults with elevated homocysteine concentrations to folic acid supplementation, versus placebo, and observed improved cognitive function only in those with low baseline plasma omega-3 fatty acid levels.(37) Very few RCTs have considered multiple nutrients in combination. However, the LipiDiDiet study in Europe randomized 311 older adults with MCI to a multi-nutrient drink versus placebo, and observed slower cognitive decline and decreased brain atrophy over 3 years.(38)
Strengths and limitations
The strengths of the study include the use of two separate datasets, each with large size, and the availability in AREDS2 of longitudinal data on cognitive function with long follow-up time. Importantly, both dietary and cognitive function data were prospectively obtained in a standardized, protocol-driven manner in a clinical trial setting, such that analyses for many dietary nutrients could be performed systematically.
Potential limitations have been described previously.(19,39) These include post hoc hypothesis generation, likely exclusion of individuals with substantial cognitive impairment, and the possibility of residual or unmeasured confounding (e.g., physical activity). Diet assessment by FFQ is known to contain non-differential measurement error, though energy adjustment may partially address this error.(40,41) Because of inherent differences in the FFQs used in AREDS and AREDS2, the assignment of food items to the nutrients analyzed had some differences between AREDS and AREDS2. Some participants may have had a degree of cognitive impairment at the time of FFQ assessment, which might lead to decreased accuracy of responses, though this possibility seems unlikely by itself to explain most findings. In AREDS2, given the possibility of preferential loss to follow-up of participants with worse cognitive function, the results may underestimate rates of progression to cognitive impairment. The study may have limited generalizability to populations where diets and other characteristics differ.
Conclusions
In these two North American study populations, for multiple nutrients in different classes, higher dietary intake was associated with lower risk of cognitive impairment and with higher cognitive function. However, no evidence was observed of slower cognitive decline according to higher dietary intake of any individual nutrient. These findings may help inform evidence-based dietary recommendations and add strength to evidence that particular dietary nutrients may maximize cognitive reserve against impairment and dementia.
Supplementary Material
Research in context.
1. Systematic Review
Publications on the relationship between nutrition and cognitive health or dementia were evaluated. Relatively few studies have performed both cross-sectional and longitudinal analyses of cognitive function according to the dietary intake of a wide range of nutrients in different classes.
2. Interpretation
Data from two large prospective clinical trials of nutritional supplements for age-related eye diseases were analyzed for differences in cognitive function or impairment by dietary nutrient intake. For multiple nutrients in different classes, higher dietary intake was associated with lower risk of cognitive impairment and with higher cognitive function. However, no evidence was observed of slower cognitive decline according to higher dietary intake of any individual nutrient.
3. Future Directions
These findings support the idea that particular dietary nutrients may maximize cognitive reserve against impairment and dementia. They provide insights into which nutrients may be most appropriate for testing in randomized trials.
Funding
This study was funded by the Intramural Research Program of the National Eye Institute, National Institutes of Health, including contract NOI-EY-0-2127 for the AREDS and contract HHS-N-260-2005-00007-C and ADB contract N01-EY-5-0007 for the AREDS2. Funds were generously contributed to these contracts by the following NIH institutes: Office of Dietary Supplements; National Center for Complementary and Alternative Medicine; National Institute on Aging; National Heart, Lung, and Blood Institute; and National Institute of Neurological Disorders and Stroke. The funding source was involved in the study design, in the collection, analysis, and interpretation of data, in the writing of the report, and in the decision to submit the article for publication.
Footnotes
Appendices of the AREDS and AREDS2 Research Groups appear in supplementary material
Conflicts of interest
No conflicts of interest for any author.
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