Mind Diet Adherence and Cognitive Performance in the Framingham Heart Study

Abstract

Background:

Adherence to the Mediterranean-DASH for Neurodegenerative Delay (MIND) diet has previously been associated with cognitive decline and dementia. To our knowledge, no prior study has investigated the association between the MIND diet and measures of brain volume, silent brain infarcts (SBIs), or brain atrophy.

Objective:

We evaluated whether adherence to the MIND diet associated with superior cognitive function, larger brain volumes, fewer SBIs, and less cognitive decline in the community-based Framingham Heart Study.

Methods:

2,092 participants (mean±SD, age 61±9) completed Food Frequency Questionnaires, averaged across a maximum of 3-time points (examination cycles 5, 6, and 7), cognitive testing at examination cycle 7 (present study baseline: 1998–2001) and after a mean±SD of 6.6±1.1 years from baseline (n = 1,584). A subset of participants also completed brain magnetic resonance imaging (MRI) at examination cycle 7 (n = 1,904). In addition, participants with dementia, stroke, and other relevant neurological diseases such as significant head trauma, subdural hematoma, or multiple sclerosis were excluded from the analyses.

Results:

Higher MIND diet scores were associated with better global cognitive function (β±SE,+0.03SD±0.01; p = 0.004), verbal memory, visual memory, processing speed, verbal comprehension/reasoning, and with larger total brain volume (TBV) following adjustments for clinical, lifestyle and demographic covariates, but not with other brain MRI measures (i.e., hippocampal volume, lateral ventricular volume, white matter hyperintensity volume, and SBIs) or cognitive decline.

Conclusion:

Higher MIND diet scores associated with better cognitive performance and larger TBV at baseline, but not with cognitive decline. Clinical trials are needed to ascertain whether adopting the MIND diet affects trajectories of cognitive decline.

Keywords

Apolipoprotein ɛ4 brain volume cognition dietary pattern framingham heart study MIND diet silent brain infarcts

INTRODUCTION

The population is aging worldwide, leading to an increasing global burden of dementia. Modifying diet might be one way to reduce risk of dementia as diet may play a pivotal role in reducing oxidative stress and inflammation, two pathways contributing to dementia risk factors [1 –3]. Studies have examined associations between dietary patterns, including the Mediterranean diet and the Dietary Approach to Stop Hypertension (DASH) diet, and neurodegeneration [4 –6]. Results showed that higher adherence to a Mediterranean or DASH diet is associated with less cognitive decline [4] and brain atrophy [5]. A combination of both these dietary patterns was proposed as a dietary strategy to combat the increasing burden of dementia in the form of the Mediterranean-DASH for Neurodegenerative Delay (MIND) dietary pattern [7]. Studies have observed that higher MIND diet scores associated with better cognition and slower cognitive decline (4.5–6 years of follow-up) [7 –11]. These prior studies predominantly included individuals aged 70 years and older, except two studies [8, 10] that included individuals aged 60 years and older and were performed over a relatively short follow-up period. In addition, previous literature has shown inconsistent results regarding the associations between adherence to the MIND diet and cognitive decline [7 , 10]. As the biological changes of Alzheimer’s disease start decades before dementia onset, longitudinal studies are needed to investigate the relationship between MIND diet adherence and preclinical endophenotypes of dementia.

We examined the relationship between adherence to the MIND diet and cross-sectional cognitive function, brain volume, and silent brain infarcts on magnetic resonance imaging (MRI) in the Framingham Heart Study. In addition, we investigated the relationship between adherence to the MIND diet and the progression of cognitive decline over a mean±SD time of 6.6±1.1 years.

MATERIAL AND METHODS

Study sample

The Framingham Heart Study (FHS) involves a series of ongoing, prospective, population-based cohorts from the town of Framingham, MA, USA. The Original cohort was established in 1948 with the aim to identify factors that contribute to the development of cardiovascular disease [12]. In 1971, the Offspring cohort was established, including children of the Original cohort and their spouses [13]. The Offspring cohort enrolled 5,124 participants who have been studied over nine examination cycles, approximately once every 4 years. All participants provided written informed consent. The study protocol was approved by the institutional review board and Boston University Medical Center.

For the present study, we assessed self-reported dietary intake from participants of the Offspring cohort using a food frequency questionnaire (FFQ) administered at examination cycles 5 (1991–1995), 6 (1995–1998), and 7 (1998–2001). A flow chart is shown in Fig. 1. To be included in the present investigation, participants were required to have completed the FFQ at examination cycle 7 (as study baseline) and at least one other time point (examination cycles 5 or 6). Examination cycle 7 was defined as baseline for this study since data on both confounders and outcome were obtained at this time point. Participants were excluded if they had an abnormal estimated total energy intake (<600 –>3999 kcal for females or > 4199 kcal for males) and > 13 missing items (n = 643) [14]. We excluded participants who did not complete the cognitive test battery at examination cycle 7, and participants with prevalent dementia, stroke, or other significant neurological disease, such as significant head trauma, subdural hematoma, or multiple sclerosis. We included data from n = 2,092 participants who completed neuropsychological testing and a large subset of whom also had completed brain MRI scans (n = 1,904). Participants underwent neuropsychological assessment and a brain MRI scan on an average of 0.8±0.8 years after examination cycle 7; 95%of participants completed their cognitive assessment and brain MRI on the same day. In addition, we created a sample to investigate the association between the MIND diet score and the progression of cognitive decline longitudinally (n = 1,584). Between examination cycles 7 and 8 (2005–2008), changes in the neuropsychological outcomes were examined over an average of approximately 6.6±1.1 years.

Fig. 1

Flow chart of the participants included in the study. n, number; FFQ, food frequency questionnaire; NP, neuropsychological assessment; MRI, magnetic resonance imaging. ^*other relevant neurological disease known to impact cognition includes illness or injury such as traumatic brain injury, primary brain tumor, or multiple sclerosis.

MIND diet scores

MIND diet scores were examined using the validated 126-item Harvard semi-quantitative FFQ [15, 16]. The FFQ is designed to assess dietary intake over the past year. Participants were asked how often they consumed food items (i.e., from never or < 1 per month to > 6 per day), the type of food item and whether food items were homemade or ready-made. For each food item, a commonly used portion size was given. In addition, the FFQ included questions on mostly used breakfast cereal, types of fats and oils, and frequency of consumption of fried foods. Intakes of food components (i.e., nutrients, food items, or food groups) were computed by multiplying the frequency of consumption of each food item by the nutrient content of the specified portions.

The MIND diet score comprises 15 food groups, including 10 favorable (i.e., green leafy vegetables, other vegetables, berries, nuts, whole grains, fish, beans, poultry, wine and olive oil) and 5 non-favorable food groups (i.e., butter and margarine, cheese, red meat and products, fast fried foods, and pastries and sweets) (Supplementary Table 2). Olive oil consumption was scored 1 if used as the primary oil and 0 otherwise. We scored all other food groups with a score of 0, 0.5, or 1 according to the frequency of consumption of each food item portion and/or when the intake of the food group adhered to the MIND diet score (range from 0–15, higher scores indicating higher adherence to the MIND diet) [7]. Our scoring of the MIND diet was consistent with that of Morris et al. [7] with some refinement owing to the greater number of items in our FFQ, allowing for comprehensive MIND diet scoring. For example, we were able to capture intake of potato chips, which have not been measured in previous MIND diet studies [7 –9].

We averaged the MIND diet scores across examination cycle 7 (1998–2001) and at least one of the prior examination cycles: 5 (1991–1995) and 6 (1995–1998), 86%of participants completed all three FFQs from our largest cognitive (n = 2,092) and brain volume (n = 1,904) outcome samples (Fig. 1). Thus, adherence to the MIND diet score was assessed over a maximum of 10 years (correlations between the three examination-specific MIND diet scores ranged between 0.586–0.665).

Assessment of cognitive function and cognitive decline

Cognitive function (i.e., cross-sectional) and cognitive decline (assessed as annualized change) were measured using a battery of validated neuropsychological tests. Our battery included Visual Reproductions Delayed Recall (visual memory) and Logical Memory Delayed Recall (meaningful/verbal memory) from the Wechsler Memory Scale, Similarities (verbal comprehension/reasoning) from the Wechsler Adult Intelligence Scale, Trail Making Test A (processing speed) and Trail Making Test B minus A (processing speed and executive function), and the Hooper Visual Organization Test (closure/visual integration and mental rotation) [17]. We also used principal component analysis (i.e., forcing a single component solution). Task scores were standardized (i.e., z-scores) and summed according to their weighting to the overall cognitive factor [18]) to investigate a composite measure of cognitive function reflecting general cognitive ability. The composite score combines weighted loadings for Trail-Making Test Part B, Hooper Visual Organization Test, Logical Memory, Visual Reproductions, Paired Associate Learning, and Similarities. Higher scores across all cognitive endpoints indicate superior performance, except Trail-Making Test, whereby higher scores indicate slower task completion. Performance on the Trail Making Test and the Hooper Visual Organization Test were natural logarithmically transformed to normalize skewed distributions. For the Trail Making Test scores directionality was reversed such that higher scores on all tests reflected better performance (cross-sectional) or less decline in performance (prospectively).

Assessment of brain volume and white matter injury

MRI examinations were conducted using a Siemens 1.5-T scanner (Siemens Medical Solutions) using T1-weighted coronal spoiled gradient-recalled echo acquisition and fluid-attenuated inversion recovery sequences with standard MRI parameters. Further information about the imaging methodology has been reported elsewhere [19]. We examined brain volume (total brain volume (TBV), lateral ventricular volume (LVV), hippocampal volume (HPV)), silent brain infarcts (SBIs), and white matter injury (white matter hyperintensity volume (WMHV)) on MRI cross-sectionally. WMHV was natural logarithmically transformed to normalize skewed distributions. Furthermore, brain volumes were expressed as a percentage of total cranial volume, thus adjusting for difference in head size. TBV was calculated as the total brain parenchymal volume. LVV was calculated by analyzing central cerebrospinal fluid spaces, excluding the temporal horn. SBIs were identified according to STandards for ReportIng Vascular changes on nEuroimaging (STRIVE) criteria [20]. Analysis of MRI images was completed by a neurologist who was blind to participants’ MIND diet scores.

Covariates

At examination 7, a physician-administered medical history and examination were performed [21]. Apolipoprotein E ɛ4 allele (APOE ɛ4) genotyping has been described previously [22, 23]. Total energy intake was estimated from the FFQ, and education was categorized into three groups (up to completion of 12 years of education leading to high school degree but no college; some college; college degree). Body mass index (BMI) was defined as weight (in kilograms) divided by the square of height (in meters). Physical activity was self-reported using the physical activity index [24]. Smoking was categorized into two groups (current smokers and not current smokers), as were prevalent diabetes mellitus (i.e., based on clinical assessment: blood glucose ≥200 mg/dL or fasting blood glucose ≥126 mg/dL or on anti-diabetic medication) and cardiovascular disease (CVD) (i.e., prevalence; participants are continuously surveilled for CVD and are considered to have developed CVD if upon review by a panel of three investigators from the Framingham Endpoint Review Committee there is agreement that there was a definite manifestation of coronary heart disease, intermittent claudication, congestive heart failure, stroke, or transient ischemic attack) (diseased and not diseased). Depressive symptoms were examined using the Center for Epidemiologic Studies Depression Scale (CESD) scores (≥16). Anti-hypertensive medication usage was categorized into users and non-users and systolic blood pressure was measured according to a standardized procedure. Fasting blood samples at examination cycle 7 were drawn from participants after an overnight fast. Total cholesterol and high-density lipoprotein (HDL) cholesterol concentrations were measured directly using standardized assays. Furthermore, the time interval between completion of the FFQ and the measurement of the imaging/neuropsychological outcomes was calculated.

Statistical analysis

SAS Software 9.4 (SAS Institute, Cary, NC, USA) was used to perform separate multivariable linear (for continuous outcomes) and logistic (for binary outcomes) regressions to examine the associations between the MIND diet score and outcomes.

The main results are presented as adjusted beta coefficients accompanied by standard errors. The beta estimates represent the change in standard deviation units of each respective outcome per one unit increase in the MIND diet score. Standardization was done by subtracting a location measure and dividing by a scale measure such that resulting data has a mean of 0 and a standard deviation of 1. In addition, odds ratios and 95%confidence intervals (CI) are presented for SBI. A p-value < 0.05 and < 0.10 was considered statistically significant for our primary analysis and for our tests of interactions, respectively. Missing data were excluded from analysis (Neuropsychology assessment cross-sectional sample: APOE ɛ4 (n = 44), BMI (n = 5), physical activity (n = 48), smoking status (n = 1), prevalent diabetes (n = 8), anti-hypertensive medication (n = 1), systolic blood pressure (n = 1), total to HDL cholesterol ratio (n = 12), and high level of depressive symptoms (n = 20); MRI cross-sectional sample: APOE ɛ4 (n = 41), body mass index (n = 5), physical activity (n = 40), smoking status (n = 1), prevalent diabetes (n = 7), anti-hypertensive medication (n = 1), systolic blood pressure (n = 1), total to HDL cholesterol ratio (n = 10), and high level of depressive symptoms (n = 17); Neuropsychology assessment longitudinal sample: APOE ɛ4 (n = 30), body mass index (n = 3), physical activity (n = 29), prevalent diabetes (n = 3), total to HDL cholesterol ratio (n = 7), and high level of depressive symptoms (n = 17)). Confounders were selected based on the published literature. Model 1 was adjusted for age, age squared (non-linear relationships have been found between age and cognition and brain MRI outcomes in our FHS sample and in the FHS cohort in general [25]), sex, APOE ɛ4 status, total energy intake, education (for cognitive outcomes), and the time interval between completion of the FFQ and the measurement of the neuropsychological and MRI outcomes. Model 2 was additionally adjusted for lifestyle factors (BMI, physical activity, and smoking status), cardiometabolic factors (prevalent diabetes, prevalent cardiovascular disease, anti-hypertensive medication, systolic blood pressure, and total to HDL cholesterol ratio), and high level of depressive symptoms (score≥16 on the Centre for Epidemiologic Studies Depression Scale). For our secondary analyses, we tested for interactions between the MIND diet score and APOE ɛ4 status and sex separately using model 1 of the cross-sectional analyses (p_interaction < 0.10). Stratified analyses were run where significant interactions were observed, adjusting for model 1 covariates.

Results

Cohort demographics

Table 1 and Supplementary Table 1 detail the sample characteristics. Participants were on average 61±9 years old, males were slightly less represented (45.7%) than females and the APOE ɛ4 allele was present in 22.0 %of the participants. Further, a comparison of participants in our study sample and those who filled out the FFQ at exam 7 versus those who did not fill out the food frequency questionnaire, showed that participants who did not fill out the FFQ were slightly less educated, were more likely to use anti-hypertensive medication, to smoke and to be diagnosed with diabetes and/or CVD (Supplementary Table 3). The distribution of the MIND diet components stratified by sex can be found in Supplementary Table 4.

Table 1

Baseline characteristics of participants included in the study

Characteristic		MIND diet score
	Overall (n = 2,092)¹	Tertile 1	Tertile 2	Tertile 3
Age, y	61±9	60±10	61±9	61±9
Time from Exam 7 to	0.8±0.8	0.7±0.7	0.8±0.8	0.8±0.8
NP Evaluation, y
Time between Exam 7 and Exam 8 NP Evaluations, y	6.6±1.1	6.6±1.0	6.6±1.2	6.6±1.2

Men, n (%)	956 (45.7)	399 (57.6)	334 (46.6)	223 (32.7)
Education, n (%)
Up to high school degree	656 (31.4)	277 (40.0)	215 (30.0)	164 (24.0)
Some years of college	616 (29.5)	192 (27.7)	221 (30.8)	203 (29.8)
College degree	820 (39.2)	224 (32.3)	281 (39.2)	315 (46.2)
BMI, kg/m², Median [Q1, Q3]	27 [24, 31]	28 [25, 32]	27 [24, 31]	26 [24, 29]
Total Cholesterol, mg/dL	201±37	199±37	203±37	202±36
HDL Cholesterol, mg/dL	54±17	50±16	53±15	58±17
Total to HDL Cholesterol ratio	4.1±1.3	4.3±1.4	4.1±1.3	3.8±1.2
Systolic blood pressure, mmHg	126±18	126±19	127±19	125±18
Anti-hypertensive medication, n (%)	647 (31)	219 (32)	220 (31)	208 (31)
Diabetes, n (%)	236 (11)	95 (14)	76 (11)	65 (10)
Prevalent CVD, n (%)	217 (10)	77 (11)	80 (11)	60 (9)
Current smoker, n (%)	234 (11)	117 (17)	72 (10)	45 (7)
High depressive symptoms², n (%)	155 (7)	65 (9)	51 (7)	39 (6)
Apolipoprotein ɛ4 allele, n (%)	459 (22)	148 (21)	149 (21)	162 (24)
Total energy intake, kcal	1,848±595	1,983±651	1,827±583	1,732±518
Average daily PAI score, Median [Q1, Q3]	37 [33, 41]	36 [33, 41]	37 [34, 41]	37 [34, 41]
MIND diet score	6.8±1.7	4.9±0.8	6.7±0.5	8.7±0.9
MIND diet score, Median [Q1, Q3]	6.7 [5.5, 8.0]	5.0 [4.3, 5.5]	6.8 [6.3, 7.2]	8.5 [8.0, 9.3]
MIND diet score range	1.5 –11.7	1.5 –5.8	6.0 –7.5	7.7–11.7
Neuropsychology Measures (n = 2092)
Logical Memory Delayed, n Correct	10.6±3.6	10.2±3.5	10.7±3.6	10.9±3.6
Visual Reproductions Delayed, n Correct	8.2±3.4	7.9±3.4	8.2±3.4	8.4±3.2
Trail Making A, minutes, Median [Q1, Q3]	0.5 [0.4, 0.6]	0.5 [0.4, 0.6]	0.5 [0.4, 0.6]	0.5 [0.4, 0.6]
Trail Making B-A, minutes, Median [Q1, Q3]	0.7 [0.5, 1.0]	0.7 [0.5, 1.1]	0.7 [0.5, 1.0]	0.6 [0.4, 0.9]
Hooper Visual Organization Test, total Correct, Median [Q1, Q3]	25.5 [24.0 –27.0]	25.5 [23.5, 27.0]	25.5 [23.5, 27.0]	25.5 [24.0, 27.0]
Similarities, n Correct	16.8±3.5	16.5±3.7	16.8±3.5	17.2±3.3
Global Cognition, weighted score units	0.01±0.97	–0.09±0.98	0.00±0.98	0.1±0.9
MRI Measures (n = 1904)
Total brain volume, %of ICV	77.3±2.6	77.4±2.7	77.0±2.6	77.6±2.5
Lateral ventricular volume, %of ICV	1.9±1.1	1.9±1.1	2.0±1.0	1.8±1.1
Hippocampal volume, %of ICV	0.5±0.1	0.5±0.1	0.5±0.1	0.6±0.1
Any silent brain infarct, n (%)	210 (11.0)	69 (10.8)	73 (11.2)	68 (11.1)
White matter hyperintensity volume, %of ICV, Median [Q1, Q3]	0.07 [0.03, 0.15]	0.04 [0.02, 0.08]	0.04 [0.02, 0.08]	0.04 [0.2, 0.07]

Mean±SD reported, unless specified otherwise. ¹Baseline demographic and clinical characteristics were defined at examination 7. ²High depressive symptoms are defined using the Center for Epidemiologic Studies Depression Scale (CESD) scores (≥16). Abbreviations = CVD, cardiovascular disease; dL, deciliter; HDL, high-density lipoprotein; ICV, intracranial volume; kcal, kilocalories; kg, kilogram; m, meter; mg, milligram; mmHg, millimeters of mercury; MIND, Mediterranean-DASH for Neurodegenerative Delay; MRI, magnetic resonance imaging; NP, neuropsychology; n, number; PAI, physical activity index; Q, quartile.

Adherence to the MIND diet and cognitive function

Higher adherence to the MIND diet was significantly associated with better performance on the global cognitive measure and on tests of Visual Reproductions Delayed Recall, Trail Making Test A, and Similarities in Model 1 (Table 2). No associations were observed between adherence to the MIND diet and performance on Logical Memory Delayed Recall, Trail Making Test B-A, or the Hooper Visual Organization Test. After additional adjustments for Model 2 covariates, the associations remained significant for our global cognitive measure and tests of Visual Reproductions Delayed Recall, Trail Making Test A, and Similarities. Additionally, the relationship between higher adherence to the MIND diet and better performance on the Logical Memory Delayed Recall test was statistically significant in Model 2. We further investigated the relationship between the individual MIND diet components and our global cognition measure. We observed relationships between higher intakes of other vegetables, nuts, olive oil, whole grains, beans, poultry, and wine and better performance on the global cognition measure (Supplementary Table 5). In addition, we observed a relationship between higher cheese intake and worse performance on the global cognitive measure (Supplementary Table 5).

Table 2

MIND diet score and neuropsychological test performance at baseline exam 7 (n = 2,092)

Neuropsychology Measures	Model 1		Model 2
Per one unit increase in the MIND diet score	β±SE¹	p ²	β±SE¹	p ²
Logical Memory Delayed, n Correct	0.02±0.01	0.06	0.03 ± 0.01	0.02
Visual Reproductions Delayed Recall, n Correct	0.04 ± 0.01	0.001	0.03 ± 0.01	0.01
Trail Making A, min^3,4	0.04 ± 0.01	0.001	0.03 ± 0.01	0.01
Trail Making B-A, min^3,4	0.01±0.01	0.15	0.01±0.01	0.30
Hooper Visual Organization Test, n Correct³	0.01±0.01	0.27	0.01±0.01	0.28
Similarities, n Correct	0.03 ± 0.01	0.01	0.03 ± 0.01	0.02
Global Cognition, weighted score units	0.03 ± 0.01	0.002	0.03 ± 0.01	0.004

Model 1: Is adjusted for age at neuropsychological evaluation (NP) Exam 7, age squared at NP Exam 7, sex, apolipoprotein ɛ4 status, average daily calorie intake, education, and time from Exam 7 to outcome assessment. Model 2: Model 1 + additionally adjusted for BMI, physical activity index, smoking status, diabetes status, prevalent cardiovascular disease, depressive symptoms, anti-hypertensive medication usage, systolic blood pressure, and total to HDL cholesterol ratio. ¹The beta estimates give the standard deviation unit difference in each respective outcome per one unit increase in the MIND diet score. ²A p-value < 0.05 was considered statistically significant. ³Performance on the tests were natural log-transformed. ⁴For the Trail Making Test scores directionality was reversed such that higher scores reflect superior performance. Abbreviations = MIND, Mediterranean-DASH for Neurodegenerative Delay; min, minutes; n, number; SE, standard error.

To help with the interpretation of our results, we regressed age on global cognition (PC1 scores) and found that a one-year increase in age corresponded to a 0.04 standard deviation unit decrease in PC1 among participants aged < 60 years old and a 0.08 standard deviation unit decrease in PC1 among participants aged > 60 years old. Thus, a one-point increase in the MIND diet score was equivalent to a 0.75 year decrease in cognitive aging among participants aged < 60 years old and a 0.38 year decrease cognitive aging among participants aged > 60 years old (i.e., persons with a one-point higher MIND diet score appeared 0.75 years [< 60 y] or 0.38 years [> 60 y] younger in terms of their global cognitive performance).

Adherence to the MIND diet and cognitive decline

Higher adherence to the MIND diet was significantly associated with less decline in performance on the test of Similarities in Model 1, but the association just failed to reach significance in Model 2 (Table 3). Higher MIND diet scores were not associated with annualized change in any other cognitive outcome (Table 3).

Table 3

MIND diet score and annualized change in neuropsychological test performance from baseline (exam 7) to exam 8 (n = 1,584)

Neuropsychology Measures	Model 1		Model 2
Per one unit increase in the MIND diet score	β±SE¹	p ²	β±SE¹	p ²
Change in Logical Memory Delayed, n Correct	–0.01±0.02	0.51	–0.02±0.02	0.32
Change in Visual Reproductions Delayed, n Correct	–0.01±0.02	0.68	–0.01±0.02	0.58
Change in Trail Making A (min)	–0.004±0.02	0.79	–0.004±0.02	0.79
Change in Trail Making B-A (min)	–0.02±0.02	0.33	–0.02±0.02	0.28
Change in Hooper Visual Organization Test, n Correct	–0.02±0.02	0.30	-0.02±0.02	0.31
Change in Similarities, n Correct	0.03 ± 0.02	0.04	0.03±0.02	0.05
Change in Global Cognition, weighted score units	-0.005±0.02	0.76	-0.002±0.02	0.87

Model 1: is adjusted for age at neuropsychological evaluation (NP), age squared at NP, sex, apolipoprotein ɛ4 status, average daily calorie intake, education and time from Exam 7 to outcome assessment. Model 2: Model 1 + additionally adjusted for BMI, physical activity index, smoking status, diabetes status, prevalent cardiovascular disease, depressive symptoms, anti-hypertensive medication usage, systolic blood pressure, and total to HDL cholesterol ratio. ¹The beta estimates give the standard deviation unit difference in each respective outcome per one unit increase in the MIND diet score. Higher betas indicate less annualized decline. ²A p-value < 0.05 was considered statistically significant. Abbreviations = MIND, Mediterranean-DASH for Neurodegenerative Delay; min, minutes; n, number; SE, standard error.

In addition, exclusion of participants in the lowest ten percentiles of the cognitive scores at baseline or participants who were diagnosed with other neurological diseases known to impact cognition or had a stroke between examination cycles 7 and 8 did not change the results (data not shown).

Adherence to the MIND diet, brain volume and SBIs

We observed a significant cross-sectional association between higher adherence to the MIND diet and higher TBV in both statistical models (Table 4). Higher MIND diet scores were not associated with any other MRI outcomes.

Table 4

MIND diet score and MRI markers at baseline exam 7 (n = 1,904)

Brain MRI measures	Model 1		Model 2
Per one unit increase in the MIND diet score	β±SE¹	p ²	β±SE¹	p ²
Total Brain Volume, %ICV	0.03 ± 0.01	0.002	0.02 ± 0.01	0.02
Lateral Ventricular Volume, %ICV	–0.01±0.01	0.27	–0.007±0.01	0.59
Hippocampal Volume, %ICV	0.02±0.01	0.15	0.02±0.01	0.20
White-Matter Hyperintensity Volume³, %ICV	–0.01±0.01	0.20	–0.02±0.01	0.15
Silent brain infarcts (OR [95%CI])	0.99 [0.91 –1.09]	0.87	0.99 [0.91 –1.09]	0.89

Model 1: is adjusted for age at MRI, age squared at MRI, sex, apolipoprotein ɛ4 status, average daily calorie intake, and time from Exam 7 to MRI imaging. Model 2: Model 1 + additionally adjusted for BMI, physical activity index, smoking status, diabetes status, prevalent cardiovascular disease, depression status, anti-hypertensive medication usage, systolic blood pressure and total to HDL cholesterol ratio. ¹The beta estimates give the standard deviation unit difference in each respective outcome per one unit increase in the MIND diet score. ²A p-value < 0.05 was considered statistically significant. ³ natural log-transformed. Abbreviations = CI, Confidence interval; ICV, intracranial volume; MIND, Mediterranean-DASH for Neurodegenerative Delay; MRI, magnetic resonance imaging; OR, odds ratio; SE, standard error.

Secondary analyses: Interactions in the association between adherence to the MIND diet and cognitive function

We observed significant interactions between higher MIND diet scores and the presence of an APOE ɛ4 allele in their associations with each of the global cognitive measure, Logical Memory Delayed Recall, Trail Making Test A and Trail Making Test B-A (Supplementary Table 6). Additionally, we observed significant interactions between adherence to the MIND diet score and sex in their association with Similarities test performance.

Following stratification of results, higher adherence to the MIND diet was significantly associated with better global cognitive function and better performance on the Logical Memory Delayed Recall test and the Trail Making Test A in APOE ɛ4 carriers only (Supplementary Table 7). Furthermore, higher adherence to the MIND diet was significantly associated with better performance on the Similarities test in males (but not females) (Supplementary Table 8).

Secondary analyses: Interactions in the association between adherence to the MIND diet and brain volume and SBI

We observed significant interactions between adherence to the MIND diet and the presence of an APOE ɛ4 allele when investigating HPV (Supplementary Table 9). Higher adherence to the MIND diet was significantly associated with larger HPV in participants without an APOE ɛ4 allele. No other interactions were observed (Supplementary Table 10).

Discussion

In our community-based sample, higher adherence to the MIND diet was associated cross-sectionally with better global cognitive function, visual memory, processing speed, verbal memory and verbal comprehension/reasoning. Thus, our data suggests that the above cognitive domains are best correlated with MIND diet adherence. Also, higher MIND diet scores were associated with larger TBV, but not with regional brain volumes or SBIs across the whole sample. However, adherence to the MIND diet was not associated with cognitive decline in our fully adjusted models.

Adherence to the MIND diet and cognitive function and cognitive decline

Our finding that higher adherence to the MIND diet was associated with better cognitive performance is to some extent consistent with previous observational studies [8, 26]. Similar to our findings, the Health and Retirement Study reported that higher MIND diet scores associated with better global cognition [8]. In addition, the DZNE-Longitudinal Cognitive Impairment and Dementia Study reported that higher MIND diet scores associated with better memory [26]. We observed no relationship between adherence to the MIND diet and cognitive decline. In accordance with our findings, The Nurses’ Health Study (NHS) did not find relationships between MIND diet adherence and averaged global cognition, decline over six years in global cognition, verbal memory, and Telephone Interview for Cognitive Status in females [9]. However, the study did report a relationship between higher adherence to the MIND diet and higher averaged verbal memory performance [9]. The Rush Memory and Aging Project study (MAP) reported that higher adherence to the MIND diet was associated with slower global and domain specific cognitive decline over 4.7 years of follow-up [7]. Consistent with the MAP study, the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K), also reported an association between higher MIND diet scores and slower cognitive decline [10]. In addition, the Personality and Total Health (PATH) Through Life cohort which investigated the association of adherence to the MIND diet with cognitive impairment, reported that higher adherence to the MIND diet was associated with lower odds of 12-year cognitive impairment [27]. Numerous factors may explain these discrepant findings. First, as compared to our cohort and the NHS sample, participants included in the MAP and SNAC-K were 10 to 20 years older, putting them at greater risk of cognitive impairment and perhaps better able to detect changes in cognitive function. Second, the discrepancy between our cross-sectional and longitudinal findings might be due to a lack of power, as we lost approximately 500 participants who lacked neuropsychology assessment data in our longitudinal analysis.

Comparison between adherence to the MIND diet score and the Mediterranean diet for brain structure and brain injury

To our knowledge, no prior study has reported on the association between the MIND diet score and brain structure and brain injury. Previous studies have investigated the Mediterranean diet in relation to brain volume [5 , 28–30]. Consistent with our findings, the Washington Heights/Inwood Columbia Aging Project reported that higher adherence to the Mediterranean diet was associated with larger TBV [5]. Furthermore, similar to our result, the Mayo Clinic Study reported that higher adherence to the Mediterranean diet was not associated with HPV [28]. In contrast to our study, the Prospective Investigation of the Vasculature in Uppsala Seniors cohort, reported that higher adherence to the Mediterranean diet was not associated with TBV or TWMV [30]. The Lothian Birth Cohort 1936 also observed no cross-sectional association between the Mediterranean type diet and TBV. Albeit the authors reported that greater adherence to a Mediterranean type diet was associated with less reduction in TBV over three years of follow-up [29]. Our study observed an association between MIND diet adherence and TBV, but not with specific brain regions. it might be that TBV was a more sensitive marker of brain health in this middle-aged to older healthy population as compared to specific brain region volumes, which may decline with the onset of vascular and neurodegenerative diseases, which are more common in later life. Sabuncu et al. suggested that significant volume loss in the hippocampus is unlikely to occur during the preclinical phase of a neurodegenerative disease, as volume loss may be associated with clinical symptoms [31]. Since current imaging research has focused on the Mediterranean type diet, further research is needed to ascertain the relationship between MIND diet adherence and brain atrophy on MRI. Future studies could also leverage other imaging modalities (e.g., Aβ and tau PET imaging) to ascertain whether the MIND diet associates with dementia pathologies in vivo.

Effect modifications

In our secondary analyses, we speculated that the relationship between the MIND diet and the brain outcomes may have differed by APOE ɛ4 status and sex. We observed that the relationships between higher adherence to the MIND diet and better cognitive test performance was stronger among APOE ɛ4 carriers. The APOE gene plays a role in the transportation of cholesterol and fatty acids in the bloodstream [32, 33], and interacts with Aβ as an Aβ-binding protein [34]. With regards to its role in fat metabolism, the APOE ɛ4 allele tends to catabolize more omega-3 fatty acids (i.e., anti-inflammatory compounds) in APOE ɛ4 carriers as compared to the catabolism process among non-carriers [35]. We observed that higher adherence to the MIND diet was associated with larger HPV in APOE ɛ4 non-carriers. In contrast, our analyses of cognitive domains suggested stronger associations between MIND diet adherence and neuropsychological performance in APOE ɛ4 carriers. Further research is needed to better characterize effect modification by APOE ɛ4 status in the context of dietary intake and dementia. We also observed a stronger association between MIND diet adherence and verbal reasoning in males as compared to females. These differential effects of the MIND diet across the sexes may be explained by the fact that females tended to have a healthier lifestyle (e.g., a BMI < 25 kg/m², physically active, and non-smokers) in comparison to males and thus had less to gain by adhering to the MIND diet.

The role of green leafy vegetables and berries in brain health

Unlike the Mediterranean and DASH diet, the MIND diet was specifically designed with the aim of promoting healthy brain aging. Instead of advocating for high intake of all fruits and all vegetables (as with the Mediterranean diet), the MIND diet score emphasizes the consumption of berries and green leafy vegetables [7]. Among fruits, berries are of particular importance because of their high polyphenol content. In animal studies, polyphenols have been shown to improve cognition or prevent cognitive decline by promoting or protecting neurogenesis and synaptic plasticity in the hippocampus [36]. In addition, an observational study in humans showed a relationship between higher intake of berries and less cognitive decline over 4 years [37] and another study found an association between higher strawberry intake and a decreased risk for dementia over a mean follow-up of 7 years [38].

Green leafy vegetables, rich in vitamin E, carotenoids and folate, have recently been suggested to protect against cognitive decline among participants included in the MAP [39]. The beneficial effect of green leafy vegetables can partly be ascribed to vitamin E, which acts as a cellular membrane protector and counteracts oxidative stress, consequently functioning as a neuroprotector and counteractor of Aβ-associated free radicals [40, 41].

Strengths and limitations

Strengths of this study include our large population-based sample, the ability to comprehensively investigate cognition by using a wide range of cognitive tests, and the investigation of brain volume and vascular brain injury with MRI. We also averaged dietary intake over a number of time points to estimate dietary intake over a maximum of 10 years. In addition, we were able to adjust for many important confounders, including lifestyle and risk factors for dementia. However, some limitations need to be taken into account. First, we used an FFQ to assess dietary intake, which is subject to measurement error and recall bias. Therefore, we excluded participants with dementia, stroke and/or other neurological diseases from the analyses to avoid respondent/recall bias. To account for potential systematic measurement error, we adjusted our analyses for total energy intake [42]. However, we acknowledge the possible presence of non-differential misclassification, which may have led to bias towards the null [43]. In addition, we encourage other studies to replicate our analyses, since those who completed the FFQ were slightly healthier than those who did not. Second, our FFQ limited us to include only blueberries and strawberries in the berry group of the MIND diet score. But MAP was limited to strawberries [7]. Third, our study was observational, which precludes conclusions about the causality of the observed associations due to residual confounding and potential reverse causality. With regard to reverse causality, the fact that we constructed a MIND diet score over three consecutive visits over a maximum of 10 years of follow up makes such a reverse causation bias less likely. Fourth, we did not adjust for multiple comparisons, since many of our analyses were exploratory, and thus some of the observed associations may be due to chance. Subgroup analyses might have lacked power and increased the likelihood of a type 1 error. Fifth, we had a long follow-up time for the longitudinal analysis, but as compared to multiple follow-up assessment in MAP and NHS, we had one follow-up assessment available [7, 9]. Lastly, participants included in our study were mainly white individuals of European ancestry, limiting the generalizability of our findings to other races/ethnicity.

In conclusion, greater adherence to the MIND diet score was associated cross-sectionally with better scores across a range of cognitive tests and with larger TBV on MRI in our community cohort. However, we found little evidence for a relationship between higher MIND diet scores and cognitive decline longitudinally. Future longitudinal research is needed across diverse populations with different dietary habits and eating patterns. Furthermore, based on our findings, we encourage future studies to investigate the impact of the MIND diet on different subgroups at-risk for dementia, including persons who are carriers/non-carriers of the APOE ɛ4 gene. Ultimately, randomized controlled trials, such as the MIND Diet Intervention to Prevent Alzheimer’s Disease trial (https://grantome.com/grant/NIH/R01-AG052583-03S1), will be needed to determine whether adopting the MIND diet score can improve cognitive trajectories with aging.

Footnotes

ACKNOWLEDGMENTS

We thank the FHS participants for donating their time to our research. The Framingham Heart Study was supported by the National Heart, Lung, and Blood Institute (contract no. N01- HC-25195, HHSN268201500001I and no. 75N92019D00031); and the National Institute on Aging (R01 AG054076, R01 AG049607, R01 AG033193, U01 AG049505, U01 AG052409, U01 AG058589, RF1 AG059421)); and by grants from the National Institute of Neurological Disorders and Stroke (NS017950 and UH2 NS100605). MPP’s salary is supported by a National Heart Foundation of Australia Future Leader Fellowship (GTN102052).

Authors’ disclosures available online ().

The supplementary material is available in the electronic version of this article: .

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