Abstract
Various dairy nutrients have been associated with cognitive performance. Several observational studies have explored associations between the intake of total dairy or some dairy subgroups and cognitive performance. However, studies on the potential impact of a broad variety of dairy subclasses are scarce. We examined cross-sectional associations between a wide assortment of dairy products and cognitive performance. A total of 619 Dutch community-dwelling adults aged ≥65 years completed a semi-quantitative Food Frequency Questionnaire. Cognitive performance was assessed with an extensive neuropsychological test battery; the tests were clustered into cognitive domains using z-scores. Linear and logistic regression analyses, adjusted for age, sex, BMI, education, smoking, alcohol consumption, habitual physical activity, total energy intake, and dietary factors, were performed to quantify the associations. The Benjamini–Hochberg method was used to correct for multiple testing. After full adjustment, higher skimmed dairy (β ± SD: 0.05 ± 0.02, p = 0.06), fermented dairy (0.04 ± 0.02, p = 0.09), and buttermilk (0.08 ± 0.03, p = 0.19) consumption were associated with better executive functioning. Logistic regression analyses indicated that a 30 g increase in Dutch cheese intake was associated with a 33% lower probability of poor information processing speed (PR = 0.67, 95% CI 0.47–0.97). No associations were observed between dairy consumption and attention and working memory or episodic memory.
Keywords: dairy consumption, cognition, elderly, observational
1. Introduction
In the Netherlands, nearly 270,000 people have dementia, which is estimated to increase up to more than a half million by 2040 [1]. As there is, as yet, no effective treatment to cure dementia, strategies to prevent or slow down the development of cognitive decline are warranted [2,3].
Nutrition has been identified as one of the determinants of age-related cognitive decline [4,5,6], where beneficial associations have been shown for various dairy nutrients such as bioactive peptides, vitamin B12, calcium, and whey protein (reviewed in [7]). Associations between dairy consumption and cognitive decline may also be explained through the potential effects on cardiometabolic pathways [8,9]. Conversely, through adverse associations with cardiometabolic health7, specific fatty acids, sodium, and sugar—as part of e.g., full-fat dairy products, cheese, and sugar-sweetened dairy products—have been adversely associated with cognition [10]. Thus, certain dairy nutrients may reinforce, but also counteract each other’s effects. To facilitate the formulation of concrete recommendations, studies exploring the associations of specific dairy groups (e.g., skimmed, semi-skimmed, full-fat, fermented, non-fermented) or products (e.g., milk, yogurt, cheese) with cognitive performance are needed.
To date, only a limited number of observational studies and one meta-analysis have explored the association between dairy consumption and cognition [11,12,13,14,15]. Crichton et al. conducted a systematic review with meta-analyses involving three cross-sectional and five prospective studies [11]. Whereas the results of cross-sectional studies were inconsistent, four out of five prospective studies observed an inverse association between higher full-fat dairy consumption and poorer cognitive performance. Most studies assessed overall cognitive performance or decline with the Mini Mental State examination (MMSE); a tool that may not be sensitive enough to detect cognitive differences in relatively cognitively healthy populations. In addition, most studies only explored the potential impact of the consumption of total dairy or some dairy subgroups.
Therefore, the aim of this study was to investigate associations between a broad variety of dairy subclasses and dairy products with domain-specific cognitive performance in Dutch adults aged ≥65 years.
2. Materials and Methods
2.1. Participants
This cross-sectional study was performed using baseline data of the B-PROOF study [16], a randomized, double-blind, placebo-controlled trial designed to assess the effect of daily oral supplementation of vitamin B12 (500 µg) and folic acid (400 µg) on fractures in 2919 mildly hyperhomocysteinemic adults ≥65 years. Participants were recruited at three study centres (i.e., Wageningen University, VU University, and Erasmus Medical Centre Rotterdam) from August 2008 to March 2011. Participants with homocysteine concentrations <12 µmol/L or >50 µmol/L, and creatinine concentrations >150 µmol/L were excluded. Only participants recruited in the surroundings of Wageningen (n = 856) underwent cognitive testing (n = 856) and completed a Food Frequency Questionnaire (FFQ) (n = 665). Of the 665 participants, 619 were available for analyses. Participants with potentially unreliable or incomplete FFQ data [i.e., men with energy intakes <800 kcal or >4200 kcal, women <500 kcal or >3500 kcal (n = 46)] were excluded [17]. The excluded and included baselines did not differ, except for age, which was slightly older in the excluded group (75 compared to 72 years old). Further details on the design and methods of the B-PROOF study can be obtained from the design article [16]. This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human participants were approved by the Medical Ethics Committee of Wageningen UR (ABR 20783.081.07). Written informed consent was obtained from all participants. The B-PROOF study was registered with the Netherlands Trial Register (trialregister.nl) as NTR1333 and at clinicaltrials.gov as NCT00696414.
2.2. Dietary Assessment
A 190-item Food Frequency Questionnaire (FFQ) was administered to assess habitual dietary intake where the previous month served as the reference period. The questionnaire was filled in at the participant’s home. The FFQ was designed to cover 96% of the absolute level of food intake and 95% of the between-person variability of each nutrient under study, as assessed in the Dutch National Food Consumption Survey of 1998 [18]. Participants answered questions relating to frequency by selecting answers ranging from ‘never’ to ‘6–7 days per week’. Portion sizes were estimated using natural portions and commonly used household measures. Frequency and portion size of consumed foods were multiplied to obtain intakes in grams per day. Subsequently, the average daily nutrient intakes were calculated using the Dutch food composition table (NEVO) (2011) [19]. The FFQ included information on all major nutrients and food groups, and was validated for total energy, macronutrients, dietary fibre, and selected vitamins [20,21,22]. For this study, dairy products were clustered as total dairy, skimmed dairy, semi-skimmed dairy, full-fat dairy, non-fermented dairy, fermented dairy, total milk, total yoghurt, total cheese, Dutch cheese, chocolate milk, buttermilk, and custard. Additionally, milk and yoghurt were subdivided according to their fat content, and cheese was subdivided into total cheese and Dutch cheese (Table 1). Only products that were queried in sufficient detail and could be classified by fat content based on the Dutch Commodities Act Dairy could be classified based on fat content [23]. All dietary variables were adjusted for energy according to the residual method, as suggested by Willet and colleagues [24].
Table 1.
Dairy Product Group | Dairy Intake (g/day) | Included Dairy Products * | |
---|---|---|---|
Median | IQR | ||
Classified by fat content | |||
Total dairy | 325 | 201–428 | All dairy products, except butter |
Skimmed dairy | 32 | 0–150 | Skimmed milk (11%), skimmed yoghurt (30%), buttermilk (59%) |
Semi-skimmed dairy | 62 | 11–169 | Semi-skimmed milk (61%), semi-skimmed yoghurt (34%), 20/30+ cheese (3%), 40+ cheese (2%) |
Full-fat dairy | 54 | 20–120 | Full-fat milk (16%), Full-fat yoghurt (27%), custard (27%), 48+ cheese (5%), full-fat cheese (1%), milk-based ice cream (8%), cream (16%) |
Total milk | 30 | 0–149 | Skimmed milk (13%), semi-skimmed milk (65%), full-fat milk (22%) |
(Semi-)skimmed milk | 7 | 0–150 | Skimmed milk (13%), semi-skimmed milk (87%) |
Full-fat milk | 0 | 0–0 | Full-fat milk |
Total yoghurt | 90 | 18–146 | Skimmed yoghurt (34%), semi-skimmed yoghurt (33%), full-fat yoghurt (33%) |
(Semi-)skimmed yoghurt | 54 | 0–129 | Skimmed yoghurt (52%), semi-skimmed yoghurt (48%) |
Full-fat yoghurt | 0 | 0–10 | Full-fat yoghurt |
Total cheese vs. Dutch cheese | |||
Total cheese | 31 | 20–47 | All types of cheese; Dutch cheese (66%), other cheese (34%), |
Dutch cheese | 20 | 13–34 | 20+/30+ cheese (26%), 40+ cheese (14%), 48+ cheese (60%) |
Individual main groups | |||
Chocolate milk | 0 | 0–13 | All types of chocolate milk |
Buttermilk | 0 | 0–40 | All types of buttermilk |
Custard | 0 | 0–28 | Mousse (30%), full-fat custard (70%) |
Fermented vs. non-fermented | |||
Fermented dairy | 158 | 75–235 | All types of yoghurt (57%), buttermilk (22%), cheese (21%) and quark (0.01%) |
Non-fermented dairy | 97 | 24–192 | All types of milk (70%), chocolate milk (16%), milk-based ice cream (0.07%), cream (0.08%) and custard (14%) |
* Proportions of included dairy products in the dairy groups are expressed as a percentage.
2.3. Cognitive Performance
Cognitive performance was assessed at baseline according to a standard protocol. The measurements were performed during a 1-h session at one of the study centres by well-trained staff. The tests were performed in a room with as few stimuli as possible. Only the interviewer and participant were present in this room. The participants practiced each test before it was administered. Global cognitive performance was assessed with the MMSE [25]. An extensive neuropsychological test battery was used to assess four cognitive domains. The domain attention and working memory was evaluated using the Digit Span forward and backward from the Wechsler Adult Intelligence Test (number of correct items) [26]. The domain executive functioning was evaluated using the Trail Making Test (TMT) part-B (seconds) [26], the Stroop Color-Word Test part-III (seconds) [27], and the Letter Fluency (number of correct items) test [28]. The domain information processing speed was assessed with the TMT part-A (seconds) [29], the Stroop Color-Word Test part-I and II (seconds) [27], and the Symbol Digit Modalities Test (SDMT) (number of correct items) [30]. To control for motor speed, interference measures were calculated for the TMT (TMT part-B/TMT part-A) and the Stroop Color-Word Test (Time needed Stroop part-III—[mean time needed for Stroop part-I and II]). The domain episodic memory was evaluated using the Rey Auditory Verbal Learning Test (number of correct words), which was used to assess immediate and delayed recall, as well as word list recognition [31]. For each domain, individual Z-scores were calculated resulting in compound scores for the different neuropsychological domains [32].
2.4. Biochemical Analyses
Blood samples were obtained from participants who came in the morning to the research centre or to external locations in the living area of participants. Participants were instructed to fast overnight, or to take only a light breakfast. Blood sampling was performed by a skilled nurse. The samples were stored at −80 °C until further analyses. The plasma glucose concentrations were analysed using a hexokinase method and insulin levels were determined using an immunometric assay.
2.5. Covariates
Height and weight were measured at one of the study centres; body mass index (BMI) was calculated as weight/height2. Data on education level (primary, secondary, or higher education), smoking status (non-smoker, current smoker, former smoker), physical activity (kcal/d) [33], and alcohol consumption (light, moderate, excessive) [34] were collected by means of self-reported questionnaires which were filled in at the participant’s home.
2.6. Statistical Analyses
Participant characteristics were reported as mean with standard deviation (mean ± SD), or n with percentages (n, (%)). Medians with interquartile ranges (median (IQR)) were used to report skewed variables. Chi-square tests were performed to assess the differences in the categorical variables over tertiles of total dairy intake. Kruskal–Wallis tests were performed for skewed continuous variables and one-way ANOVA of normally distributed variables. Linear regression analyses, as well as logistic analyses, were conducted to quantify the associations between dairy intake and cognitive performance, resulting in either β’s (g/day) or odds ratios (ORs) (100 g/day, with the exception of cheese, which was analysed per 30 g/day), respectively. As the rare disease assumption applied to this study, calculated ORs can be interpreted as prevalence ratios (PR) [35]. PRs were calculated by tertiles of dairy intake or for consumers vs. non-consumers (if less than 300 consumers), which resulted in the probability of being a poor cognitive performer (i.e., belonging to the poorest 10% of the population). A population-based 10% cut-off point is commonly used in cognitive research [36] and has been shown to be predictive for cognitive impairment [37]. All analyses were adjusted for age, sex (Model 1), BMI, education, smoking, alcohol consumption, habitual physical activity (Model 2), and total energy intake (Model 3). Also, the impact of the dietary factors, including total energy intake, meat, fish, vegetables, fruit, and bread, were examined by individually adding these variables to Model 3. To explore potential mediation by markers of glucose homeostasis in the associations between dairy intake and domain-specific cognitive performance, plasma glucose and plasma insulin were added, independently, to the fully adjusted model (Model 4, data not shown in tables). The analyses were adjusted for multiple comparisons using Benjamini–Hochberg correction for a false discovery rate of 0.20 [38]. Adjusted p-values smaller than the false discovery rate (0.20) are significant. The analyses were performed by using IBM SPSS Statistics Version 22.
3. Results
Population characteristics are shown in Table 2. Participants were on average ± SD 71.9 ± 5.1 years old, had a mean BMI of 27.1 ± 3.7 kg/m2, and a mean MMSE score of 28.4 ± 1.7. Sixty percent of this population was men, 34% completed higher education, and 59% were former smokers. The mean plasma glucose concentration was 5.8 ± 1.4 mmol/L and the median (IQR) insulin concentration was 65 (40–126) pmol/L. The median total dairy intake was 325 (201–428) g/day. The analyses over tertiles of total dairy intake indicated statistically significant differences for the intake of alcohol, fruit, bread, proteins, carbohydrates, fat, and fibre.
Table 2.
Tertiles of Total Dairy Intake | |||||||||
---|---|---|---|---|---|---|---|---|---|
Total Population | T1 ≤235 (g/day) |
T2 236–374 (g/day) |
T3 ≥375 (g/day) |
p * | |||||
n | 619 | 206 | 207 | 206 | |||||
Total dairy intake, g/day | 325 | 201–428 | 162 | 90–201 | 325 | 273–348 | 482 | 428–546 | <0.0001 |
Sex, men (%) | 369 | 60 | 120 | 58 | 109 | 53 | 138 | 68 | 0.006 |
Age, y | 71.9 | 5.1 | 72.3 | 5.5 | 71.5 | 4.8 | 72.1 | 5.0 | 0.25 |
BMI, kg/m2 | 27.1 | 3.7 | 27.2 | 3.9 | 27.2 | 3.7 | 27.0 | 3.6 | 0.87 |
Glucose, mmol/L † | 5.8 | 1.4 | 5.8 | 1.4 | 5.8 | 1.4 | 5.8 | 1.4 | 0.98 |
Insulin, pmol/L ‡ | 65 | 40–126 | 68 | 41–120 | 64 | 41–134 | 65 | 39–125 | 0.99 |
Smoking, n (%) | 0.32 | ||||||||
Non | 189 | 30 | 55 | 27 | 70 | 33 | 64 | 31 | |
Current | 65 | 11 | 28 | 13 | 18 | 9 | 19 | 9 | |
Former | 365 | 59 | 123 | 60 | 119 | 58 | 123 | 60 | |
Physical activity (kcal/day) | 599 | 362–875 | 578 | 367–858 | 636 | 373–941 | 605 | 354–854 | 0.41 |
Education, n (%) | 0.38 | ||||||||
Primary | 261 | 42 | 93 | 45 | 77 | 38 | 91 | 44 | |
Secondary | 148 | 24 | 42 | 20 | 59 | 28 | 47 | 23 | |
Higher | 210 | 34 | 71 | 35 | 71 | 34 | 68 | 33 | |
Alcohol intake, n (%) | 0.002 | ||||||||
Light | 397 | 64 | 127 | 62 | 120 | 58 | 150 | 73 | |
Moderate | 204 | 33 | 68 | 33 | 84 | 41 | 52 | 26 | |
Excessive | 18 | 3 | 11 | 5 | 3 | 1 | 4 | 1 | |
MMSE (range 0–30) § | 28.4 | 1.7 | 28.3 | 1.8 | 28.4 | 1.6 | 28.3 | 1.6 | 0.76 |
Energy, kcal/day | 1948.1 | 497.3 | 1967.3 | 485.9 | 1913.6 | 486.3 | 1963.3 | 519.6 | 0.47 |
Protein, En% | 15 | 5 | 13 | 4 | 16 | 4 | 17 | 4 | <0.0001 |
Carbohydrates, En% | 45 | 6 | 39 | 6 | 45 | 5 | 50 | 5 | <0.0001 |
Total fat, En% | 36 | 7 | 32 | 6 | 36 | 7 | 39 | 7 | <0.0001 |
Fibre, g/day | 24 | 6 | 22 | 6 | 24 | 6 | 26 | 7 | <0.0001 |
Meat, g/day | 73 | 49–97 | 73 | 47–94 | 73 | 53–95 | 74 | 47–100 | 0.83 |
Fruits, g/day | 172 | 92–254 | 149 | 73–236 | 174 | 92–259 | 193 | 109–267 | 0.003 |
Fish, g/day | 11 | 4–18 | 10 | 4–18 | 11 | 4–20 | 11 | 4–17 | 0.74 |
Bread, g/day | 112 | 79–148 | 106 | 76–142 | 112 | 80–150 | 116 | 83–154 | 0.02 |
Vegetables, g/day | 118 | 81–166 | 111 | 72–142 | 117 | 84–160 | 121 | 86–177 | 0.10 |
Data are expressed as mean (SD), median (IQR) or n (%). * Chi-squared tests for categorical variables, Kruskal–Wallis for medians of continuous variables and one-way ANOVA for means of continuous variables. † Data available for n = 610. ‡ Data available for n = 609. § Data available for n = 617.
In Table 3 and Table 4, associations between dairy consumption and cognitive performance (domain z-scores) are presented, quantified using β’s and PRs. After full adjustment, no significant associations were observed between any of the dairy groups and attention working memory or episodic memory, or between non-fermented dairy products and any of the cognitive domains. Conversely, significant associations were observed between higher fermented dairy, skimmed milk and buttermilk intakes, and better executive functioning, β ± SD: 0.04 ± 0.02, p = 0.03, β ± SD: 0.05 ± 0.02, p = 0.01 and β ± SD: 0.08 ± 0.03, p = 0.02. Logistic regression analyses suggested a 43% non-significant lower probability of a poor performance for information processing speed for a 100 g increase in buttermilk intake (PR 0.57, 95% CI 0.31–1.06). Finally, associations were also observed for another fermented product, namely cheese, where a 30 g increase in Dutch cheese intake was associated with a 33% significant lower probability of a poor performance on the domain information processing speed (PR 0.67, 95% CI 0.47–0.97). For all associations, additional adjustment for plasma glucose or plasma insulin did not alter the results (data not shown).
Table 3.
Model 1 | Model 2 | Model 3 | Model 3 PR by 100 g/d |
||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
β | SE | p * | β | SE | p * | β | SE | p * | PR ** | 95% CI | |
AWM | |||||||||||
Total dairy | 0.01 | 0.02 | 0.62 | 0.01 | 0.02 | 0.80 | 0.02 | 0.02 | 0.78 | 0.98 | 0.88–1.09 |
Skimmed dairy | 0.05 | 0.03 | 0.54 | 0.03 | 0.03 | 0.80 | 0.03 | 0.03 | 0.78 | 0.98 | 0.76–1.26 |
Semi-skimmed dairy | −0.02 | 0.03 | 0.66 | −0.01 | 0.03 | 0.80 | −0.01 | 0.03 | 0.78 | 0.92 | 0.72–1.17 |
Full-fat dairy | −0.04 | 0.04 | 0.91 | 0.00 | 0.04 | 0.96 | 0.01 | 0.04 | 0.78 | 0.85 | 0.59–1.24 |
Fermented dairy | 0.03 | 0.03 | 0.62 | 0.02 | 0.03 | 0.80 | 0.01 | 0.03 | 0.78 | 0.92 | 0.72–1.17 |
Non-Fermented dairy | 0.01 | 0.06 | 0.62 | 0.04 | 0.05 | 0.80 | 0.04 | 0.05 | 0.78 | 0.81 | 0.52–1.27 |
EF | |||||||||||
Total dairy | 0.01 | 0.02 | 0.66 | 0.01 | 0.01 | 0.72 | 0.01 | 0.01 | 0.72 | 1.01 | 0.85–1.21 |
Skimmed dairy | 0.07 | 0.02 | 0.01 | 0.05 | 0.02 | 0.06 | 0.05 | 0.02 | 0.06 | 0.96 | 0.73–1.26 |
Semi-skimmed dairy | −0.03 | 0.02 | 0.27 | −0.02 | 0.02 | 0.54 | −0.02 | 0.02 | 0.56 | 1.17 | 0.94–1.47 |
Full-fat dairy | −0.05 | 0.03 | 0.22 | −0.02 | 0.03 | 0.68 | −0.03 | 0.03 | 0.63 | 1.08 | 0.76–1.55 |
Fermented dairy | 0.06 | 0.02 | 0.03 | 0.04 | 0.02 | 0.09 | 0.04 | 0.02 | 0.09 | 0.92 | 0.71–1.19 |
Non-Fermented dairy | −0.02 | 0.04 | 0.66 | 0.00 | 0.04 | 0.94 | 0.00 | 0.04 | 1.00 | 1.07 | 0.66–1.72 |
IPS | |||||||||||
Total dairy | −0.01 | 0.02 | 0.62 | −0.01 | 0.02 | 0.56 | −0.01 | 0.02 | 0.66 | 0.91 | 0.75–1.10 |
Skimmed dairy | 0.06 | 0.03 | 0.12 | 0.04 | 0.02 | 0.36 | 0.04 | 0.02 | 0.36 | 0.87 | 0.65–1.15 |
Semi-skimmed dairy | −0.04 | 0.02 | 0.21 | −0.04 | 0.02 | 0.36 | −0.04 | 0.02 | 0.36 | 1.00 | 0.78–1.27 |
Full-fat dairy | −0.05 | 0.04 | 0.22 | −0.03 | 0.04 | 0.56 | −0.02 | 0.04 | 0.66 | 1.12 | 0.78–1.61 |
Fermented dairy | 0.03 | 0.02 | 0.26 | 0.02 | 0.02 | 0.56 | 0.02 | 0.02 | 0.66 | 0.86 | 0.66–1.13 |
Non-Fermented dairy | −0.06 | 0.05 | 0.28 | −0.03 | 0.05 | 0.56 | −0.03 | 0.05 | 0.66 | 0.85 | 0.53–1.36 |
EM | |||||||||||
Total dairy | −0.02 | 0.02 | 0.68 | −0.01 | 0.02 | 0.69 | −0.01 | 0.02 | 0.57 | 1.08 | 0.92–1.27 |
Skimmed dairy | 0.03 | 0.02 | 0.42 | 0.03 | 0.02 | 0.48 | 0.03 | 0.02 | 0.46 | 0.97 | 0.76–1.23 |
Semi-skimmed dairy | −0.04 | 0.02 | 0.42 | −0.04 | 0.02 | 0.48 | −0.04 | 0.02 | 0.46 | 1.18 | 0.95–1.45 |
Full-fat dairy | 0.02 | 0.03 | 0.79 | 0.04 | 0.03 | 0.56 | 0.04 | 0.03 | 0.46 | 0.75 | 0.50–1.13 |
Fermented dairy | −0.01 | 0.02 | 0.79 | −0.01 | 0.02 | 0.94 | −0.01 | 0.02 | 0.92 | 1.09 | 0.87–1.37 |
Non-Fermented dairy | −0.01 | 0.05 | 0.79 | −0.00 | 0.04 | 0.94 | −0.01 | 0.04 | 0.92 | 0.99 | 0.63–1.57 |
Associations are adjusted for age, sex (Model 1), BMI, education, smoking, alcohol consumption, habitual physical activity (Model 2), total energy intake, dietary factors (Model 3). * Adjusted p-value using method by Benjami-Hochberg ** Total cheese and Dutch cheese by 30 g increase. AWM, attention and working memory; EF executive function; EM, episodic memory; IPS, information processing speed; PR, prevalence ratio.
Table 4.
Model 1 | Model 2 | Model 3 | Model 3 PR by 100 g/d ** |
||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
β | SE | p * | β | SE | p * | β | SE | p * | PR ** | 95% CI | |
AWM | |||||||||||
Total milk | −0.01 | 0.03 | 0.97 | −0.01 | 0.03 | 0.94 | −0.01 | 0.03 | 0.88 | 0.97 | 0.75–1.24 |
Semi/skimmed milk | −0.02 | 0.03 | 0.97 | −0.01 | 0.03 | 0.94 | −0.01 | 0.03 | 0.88 | 1.03 | 0.79–1.33 |
Full-fat milk | −0.05 | 0.08 | 0.97 | −0.03 | 0.08 | 0.94 | −0.03 | 0.08 | 0.88 | 1.74 | 0.52–1.74 |
Total yoghurt | 0.02 | 0.04 | 0.97 | 0.01 | 0.04 | 0.94 | 0.02 | 0.04 | 0.88 | 0.79 | 0.54–1.14 |
Semi/skimmed yoghurt | 0.04 | 0.04 | 0.97 | 0.03 | 0.04 | 0.94 | 0.03 | 0.04 | 0.88 | 0.72 | 0.48–1.09 |
Full-fat yoghurt | −0.02 | 0.08 | 0.97 | −0.06 | 0.08 | 0.94 | −0.05 | 0.08 | 0.88 | 0.91 | 0.35–1.81 |
Total cheese | −0.00 | 0.04 | 0.97 | −0.03 | 0.04 | 0.94 | −0.02 | 0.04 | 0.88 | 1.29 | 0.93–1.81 |
Dutch cheese | 0.04 | 0.05 | 0.97 | 0.00 | 0.05 | 0.99 | 0.01 | 0.05 | 0.92 | 0.99 | 0.66–1.49 |
Chocolate milk | −0.01 | 0.07 | 0.97 | 0.04 | 0.06 | 0.94 | 0.05 | 0.06 | 0.88 | 0.76 | 0.41–1.39 |
Buttermilk | 0.06 | 0.05 | 0.97 | 0.03 | 0.04 | 0.94 | 0.03 | 0.04 | 0.88 | 0.95 | 0.65–1.40 |
Custard | −0.08 | 0.10 | 0.97 | 0.06 | 0.09 | 0.94 | 0.06 | 0.09 | 0.88 | 0.87 | 0.39–1.93 |
EF | |||||||||||
Total milk | −0.02 | 0.06 | 0.39 | −0.01 | 0.02 | 0.79 | −0.02 | 0.02 | 0.68 | 1.15 | 0.90–1.47 |
Semi/skimmed milk | −0.03 | 0.02 | 0.40 | −0.02 | 0.02 | 0.70 | −0.03 | 0.02 | 0.72 | 1.21 | 0.94–1.56 |
Full-fat milk | −0.03 | 0.06 | 0.75 | −0.02 | 0.06 | 0.81 | −0.02 | 0.06 | 0.76 | 1.23 | 0.69–2.20 |
Total yoghurt | 0.03 | 0.03 | 0.46 | 0.03 | 0.03 | 0.70 | 0.02 | 0.03 | 0.46 | 0.92 | 0.63–1.35 |
Semi/skimmed yoghurt | 0.04 | 0.03 | 0.40 | 0.04 | 0.03 | 0.70 | 0.04 | 0.03 | 0.66 | 0.98 | 0.67–1.44 |
Full-fat yoghurt | 0.03 | 0.06 | 0.75 | −0.01 | 0.06 | 0.84 | −0.02 | 0.06 | 0.76 | 1.09 | 0.51–2.31 |
Total cheese | 0.01 | 0.03 | 0.76 | −0.01 | 0.03 | 0.81 | −0.02 | 0.03 | 0.72 | 0.78 | 0.51–1.18 |
Dutch cheese | 0.07 | 0.04 | 0.33 | 0.03 | 0.04 | 0.70 | 0.02 | 0.04 | 0.72 | 0.95 | 0.65–1.40 |
Chocolate milk | −0.02 | 0.05 | 0.75 | 0.02 | 0.05 | 0.81 | 0.03 | 0.05 | 0.72 | 0.80 | 0.47–1.38 |
Buttermilk | 0.10 | 0.03 | 0.03 | 0.08 | 0.03 | 0.19 | 0.08 | 0.03 | 0.19 | 0.99 | 0.66–1.50 |
Custard | −0.20 | 0.07 | 0.03 | −0.09 | 0.07 | 0.70 | −0.09 | 0.07 | 0.66 | 1.15 | 0.57–2.34 |
IPS | |||||||||||
Total milk | −0.02 | 0.03 | 0.67 | −0.01 | 0.02 | 0.70 | −0.01 | 0.03 | 0.84 | 1.01 | 0.75–1.34 |
Semi/skimmed milk | −0.04 | 0.03 | 0.33 | −0.04 | 0.03 | 0.51 | −0.04 | 0.03 | 0.44 | 1.04 | 0.79–1.36 |
Full-fat milk | 0.05 | 0.07 | 0.67 | 0.05 | 0.07 | 0.70 | 0.05 | 0.07 | 0.77 | 1.09 | 0.56–2.12 |
Total yoghurt | −0.03 | 0.04 | 0.67 | −0.04 | 0.03 | 0.70 | −0.04 | 0.03 | 0.64 | 1.09 | 0.77–1.53 |
Semi/skimmed yoghurt | −0.01 | 0.04 | 0.87 | −0.02 | 0.04 | 0.70 | −0.02 | 0.04 | 0.83 | 1.07 | 0.75–1.53 |
Full-fat yoghurt | −0.08 | 0.07 | 0.48 | −0.12 | 0.07 | 0.39 | −0.12 | 0.07 | 0.39 | 1.43 | 0.71–2.89 |
Total cheese | 0.02 | 0.04 | 0.75 | −0.01 | 0.04 | 0.88 | −0.00 | 0.04 | 0.96 | 0.80 | 0.54–1.18 |
Dutch cheese | 0.09 | 0.04 | 0.26 | 0.05 | 0.04 | 0.55 | 0.05 | 0.04 | 0.61 | 0.67 | 0.47–0.97 |
Chocolate milk | −0.06 | 0.06 | 0.48 | −0.03 | 0.05 | 0.70 | −0.03 | 0.05 | 0.83 | 0.94 | 0.54–1.62 |
Buttermilk | 0.11 | 0.04 | 0.11 | 0.08 | 0.04 | 0.33 | 0.08 | 0.04 | 0.33 | 0.57 | 0.31–1.06 |
Custard | −0.15 | 0.08 | 0.26 | −0.04 | 0.08 | 0.70 | −0.03 | 0.08 | 0.84 | 1.15 | 0.53–2.48 |
EM | |||||||||||
Total milk | 0.00 | 0.02 | 0.98 | 0.00 | 0.02 | 0.97 | 0.00 | 0.03 | 0.97 | 1.03 | 0.79–1.35 |
Semi/skimmed milk | 0.00 | 0.02 | 0.98 | 0.00 | 0.02 | 0.97 | 0.00 | 0.02 | 0.97 | 1.07 | 0.84–1.37 |
Full-fat milk | 0.04 | 0.06 | 0.92 | 0.04 | 0.06 | 0.95 | 0.04 | 0.06 | 0.97 | 0.86 | 0.41–1.77 |
Total yoghurt | −0.04 | 0.03 | 0.80 | −0.03 | 0.03 | 0.86 | −0.03 | 0.03 | 0.86 | 1.22 | 0.89–1.69 |
Semi/skimmed yoghurt | −0.05 | 0.03 | 0.80 | −0.04 | 0.03 | 0.83 | −0.04 | 0.03 | 0,74 | 1.29 | 0.94–1.78 |
Full-fat yoghurt | 0.07 | 0.06 | 0.80 | 0.06 | 0.06 | 0.83 | 0.07 | 0.06 | 0.74 | 0.74 | 0.35–1.53 |
Total cheese | −0.03 | 0.03 | 0.88 | −0.04 | 0.03 | 0.83 | −0.04 | 0.03 | 0.74 | 1.19 | 0.84–1.68 |
Dutch cheese | 0.01 | 0.04 | 0.92 | −0.01 | 0.04 | 0.97 | −0.01 | 0.04 | 0.97 | 1.40 | 0.89–2.21 |
Chocolate milk | −0.04 | 0.05 | 0.88 | −0.02 | 0.05 | 0.97 | −0.02 | 0.05 | 0.97 | 0.87 | 0.50–1.51 |
Buttermilk | 0.04 | 0.04 | 0.80 | 0.04 | 0.04 | 0.83 | 0.04 | 0.04 | 0.74 | 0.89 | 0.59–1.34 |
Custard | −0.02 | 0.08 | 0.92 | 0.02 | 0.08 | 0.97 | 0.03 | 0.08 | 0.70 | 0.48 | 0.18–1.29 |
Associations are adjusted for age, sex (Model 1), BMI, education, smoking, alcohol consumption, habitual physical activity (Model 2), total energy intake, dietary factors (Model 3). * Adjusted p-value using method by Benjamini–Hochberg ** Total cheese and Dutch cheese by 30 g increase. AWM, attention and working memory; EF executive function; EM, episodic memory; IPS, information processing speed; PR, prevalence ratio.
4. Discussion
In this study, higher intake levels of fermented dairy, skimmed dairy, and buttermilk were associated with better executive functioning scores. Moreover, an association was observed between higher Dutch cheese intakes, and better information processing speed scores. No associations were observed between total dairy consumption, dairy product consumption classified by fat content, or non-fermented dairy consumption, and the four cognitive domains.
To date, six cross-sectional [13,14,15,39,40,41] and four prospective studies [12,42,43,44] have investigated associations between dairy intake and cognition. Most studies were conducted in adults aged ≥55 years [12,14,39,40,41,42,43,44] and used a global dementia screening tool such as the MMSE [13,39,40,41,42]. Our null findings for total dairy consumption are in line with two previous studies [12,15], but in contrast to three other studies [13,14,39]. In the Maine-Syracuse Longitudinal Study (MSLS), participants regularly consuming dairy had a lower odds of having a low global cognitive performance (OR: 0.15, 95% CI: 0.07–0.34), visual-spatial memory (OR: 0.34, 95% CI: 0.15–0.77), working memory (OR:0.28, 95%: CI: 0.13–0.58), and executive function (OR:0.39, 95% CI: 0.18–0.85), compared to participants never/rarely consuming dairy [13]. In the NHANES study, dairy consumption was associated with higher story recall (49.6 ± 0.7 vs. 43.7 ± 1.3, p = 0.0001) and Digit Symbol Substitution Test (DSST) (51.5 ± 1.9 to 46.2 ± 3.0, p = 0.009) percentile scores [14]. In line with this, Lee and colleagues [39] observed a positive correlation between total dairy intake and cognitive performance in women (r = 0.173, p < 0.01).
In our study, analyses exploring the impact of dairy products subdivided by fat content (i.e., skimmed, semi-skimmed, and full-fat dairy) only showed a positive association between skimmed dairy consumption (of which 59% was buttermilk) and executive functioning. The results of the MSLS, where milk consumption was classified by fat content, do not suggest different associations with cognitive performance [13]. In contrast, the consumption of full-cream milk was associated with impaired cognitive function (OR = 0.59, 95% CI: 0.37–0.94) among older Australian men [42]. Among middle-aged South Australians, whole fat ice-cream consumption was inversely associated with memory (β = −0.13, p < 0.001) and whole fat cream was positively associated with cognitive failures (β = 0.09, p < 0.05) in men, whereas low fat yoghurt intake was positively associated with memory recall in men (β = 0.10, p = 0.03) [15].
We observed significant associations of total fermented dairy consumption and buttermilk with cognitive performance. Up to now, none of the observational studies have examined the association between fermented dairy and cognitive performance or decline. However, one randomized, double-blind and controlled trial, including 60 patients with Alzheimer’s disease, assessed the effects of supplementation of fermented milk with a mixture of probiotics for 12 weeks on cognitive performance and showed a significant improvement in the MMSE score compared to the control group supplemented with milk (−5.03 ± 3.00%, p < 0.001) [45].
As potential dairy product effects may be related to particular product-specific nutrients, we hypothesised that more detailed analyses on the product level could provide more insight into the potential link between dairy product intake and cognitive performance. With respect to the individual product groups, we can conclude that our null findings for milk are in line with five other studies [13,15,40,41,44]. Conversely, the SU.VI.MAX-2 study showed lower verbal memory scores among consumers with high milk intake compared to consumers with low milk intake (mean difference T3 vs. T1 = −0.99, (−1.83–−0.15)) [12]. Pertaining to cheese, we observed that an increase of 30 g in Dutch cheese consumption was associated with a 33% lower probability of having a poor information processing speed. In line with this, the NHANES study showed higher information processing scores (DSST scores 52.0 ± 0.8 vs. 48.4 ± 1.2, p = 0.02) and higher story recall scores (51.9 ± 0.9 vs. 47.3 ± 0.7, p =< 0.0001) among cheese consumers compared to non-consumers [14]. Moreover, higher cheese intake was associated with a reduced probability of cognitive impairment in the State-wide Survey of Alabama’s Elderly (OR = 0.68, 95% CI 0.47–0.99) [41]. Conversely, four other studies did not observe associations between total cheese intake and cognition [12,13,15,44]. Our null findings for yoghurt intake and cognitive performance are in line with three other studies [12,13,44], but in contrast to one study showing positive associations between total yoghurt (β = 0.12, p < 0.05) and low-fat yoghurt (β = 0.10, p = 0.03) with quality of memory recall in men [15]. Although there do not seem to be specific patterns in methodological characteristics explaining the different findings of the summarized studies, null-associations seem to be somewhat more common in studies using global dementia screening tools.
Up to now, research on the underlying mechanisms explaining associations between dairy consumption and cognitive performance is in its very early stages. In our study, total fermented dairy, buttermilk, and Dutch cheese, which are all fermented dairy products, were associated with cognitive performance. As experimental studies have suggested an important role for gut microbiota in the central nervous system, called the gut–brain axis [46], these associations may be explained by the probiotic effect of lactic acid bacteria [6]. More specifically, pre-clinical studies have indicated that probiotics attenuate pro-inflammatory cytokines, decrease oxidative stress, and increase brain-derived neurotrophic factor, and as such may promote neuronal growth and survival [6,47]. Probiotics have also been related to an increase in tryptophan, which enhances the synthesis of serotonin in the brain [6,48]. Furthermore, fermented dairy products are rich in vitamin K2, which tends to be relatively high in Dutch cheeses [49]. Evidence is increasing that vitamin K2 is positively associated with cognition. Vitamin K2 is involved in the synthesis of sphingolipids and the biological activation of vitamin K-dependent proteins. Insufficient levels may cause dysfunction in the CNS [50]. Lastly, bioactive peptides have been shown to exert various activities affecting the cardiovascular, digestive, immune, and nervous systems [51]. For instance, middle-aged Gouda cheese has been suggested to contain blood pressure-reducing peptides with potent angiotensin-converting enzyme inhibitory activity [6,51].
Finally, there are also some limitations and strengths of the present study that need to be discussed. First, as results are based on cross-sectional data, it is not possible to draw any conclusions regarding causality. Secondly, our participants had slightly elevated homocysteine concentrations and consequently the results may not be generalizable to general older populations. Thirdly, some individual dairy products were consumed by a relatively low number of participants, which may have attenuated potential associations. Furthermore, dairy intake and cognitive performance were not assessed at the exact same time. However, as the FFQ measures habitual food intake and older adults are assumed to have reasonably stable eating patterns, we do not expect a substantial impact on the results. Moreover, the FFQ did not distinguish between fermented and non-fermented cheeses. However, as most cheeses are fermented with exception of fresh cheeses, we also do not expect a major impact of this drawback. Furthermore, dairy consumption in our population was relatively high. It may be that participants with the lowest dairy intakes had such high dairy intakes, being either favourable or non-favourable, already reaching the plateau in detecting associations between even higher intakes and cognitive performance. Finally, the fact that the questionnaire was only completed by 665 of 856 participants may relate to the fact that FFQs are limited by various methodological factors and burdensome for participants. For instance, FFQs are long questionnaires that may take up to 90 min to complete [52]. Although we did not ask participants why FFQs were not returned, practical experience has taught us that this is a major factor. Moreover, FFQs rely on memory, i.e., in recalling types of foods eaten, frequency and portion sizes; difficulties in recalling diet may have been a reason for participants for not returning the FFQ as well. The strengths of this study include the use of an extensive cognitive test battery, the possibility to adjust for a large number of potentially relevant covariates, the possibility to study a broad variety of dairy subgroups and the use of the Benjamini–Hochberg method to correct for multiple testing. In fact, to the best of our knowledge, this is the first observational study examining the association between fermented dairy consumption and cognitive performance.
5. Conclusions
The findings of this study in Dutch older adults show some positive associations between the intake of fermented dairy and skimmed dairy, in particular buttermilk, and executive functioning and/or information processing speed. No associations were observed for attention working memory and episodic memory. To confirm our results, further studies are needed using cognitive measures with sufficient sensitivity, including neuropsychological test batteries and more advanced imaging techniques, and detailed information on habitual dairy intake.
Acknowledgments
The authors gratefully thank all study participants, and all dedicated co-workers who helped this trial to succeed.
Author Contributions
Conceptualization E.M.B.-B.; methodology E.M.B.-B.; formal analysis E.M.B.-B.; writing—original draft preparation L.C.d.G. and E.M.B.-B.; writing—review and editing E.M.B.-B. and O.v.d.R.; visualisation L.C.d.G.; supervision E.M.B.-B. and E.J.M.F.; funding acquisition L.C.P.G.M.d.G. All authors have read and agreed to the published version of the manuscript.
Funding
This research was supported by The Netherlands Organization for Health Research and Development, the Hague (ZonMw, Grant 6130.0031), unrestricted grant from NZO (Dutch Dairy Association), Zoetermeer; NCHA (Netherlands Consortium Healthy Ageing), Leiden/Rotterdam; Ministry of Economic Affairs, Agriculture and Innovation (project KB-15-004-003), the Hague. Wageningen University, Wageningen; VU University Medical Center, Amsterdam; Erasmus MC, Rotterdam. All organizations are based in the Netherlands.
Conflicts of Interest
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
References
- 1.Nederland A. Wat Is Dementia? [(accessed on 13 December 2018)]; Available online: https://www.alzheimer-nederland.nl/dementie.
- 2.Elias M.F., Beiser A., Wolf P., Au R., White R.F., D’Agostino R.B. The preclinical phase of Alzheimer disease: A 22-year prospective study of the Framingham cohort. Arch. Neurol. 2000;57:808–813. doi: 10.1001/archneur.57.6.808. [DOI] [PubMed] [Google Scholar]
- 3.Mangialasche F., Solomon A., Winblad B., Mecocci P., Kivipelto M. Alzheimer’s disease: Clinical trials and drug development. Lancet Neurol. 2010;9:702–716. doi: 10.1016/S1474-4422(10)70119-8. [DOI] [PubMed] [Google Scholar]
- 4.Bryan J. Mechanisms and evidence for the role of nutrition in cognitive ageing. Ageing Int. 2004;29:28–45. doi: 10.1007/s12126-004-1008-1. [DOI] [Google Scholar]
- 5.Solfrizzi V., Panza F., Capurso A. The role of diet in cognitive decline. J. Neural Transm. 2003;110:95–110. doi: 10.1007/s00702-002-0766-8. [DOI] [PubMed] [Google Scholar]
- 6.Bailey R., Arab L. Nutritional prevention of cognitive decline. Adv. Nutr. Int. Rev. J. 2012;3:732–733. doi: 10.3945/an.112.002667. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Camfield D.A., Owen L., Scholey A.B., Pipingas A., Stough C. Dairy constituents and neurocognitive health in ageing. Br. J. Nutr. 2011;106:159–174. doi: 10.1017/S0007114511000158. [DOI] [PubMed] [Google Scholar]
- 8.Elwood P.C., Pickering J.E., Givens D.I., Gallacher J.E. The consumption of milk and dairy foods and the incidence of vascular disease and diabetes: An overview of the evidence. Lipids. 2010;45:925–939. doi: 10.1007/s11745-010-3412-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Engberink M.F., Geleijnse J.M., de Jong N., Smit H.A., Kok F.J., Verschuren W.M.M. Dairy intake, blood pressure, and incident hypertension in a general Dutch population. J. Nutr. 2009;39:582–587. doi: 10.3945/jn.108.093088. [DOI] [PubMed] [Google Scholar]
- 10.Kalmijn S. Fatty acid intake and the risk of dementia and cognitive decline: A review of clinical and epidemiological studies. J. Nutr. Health Aging. 1999;4:202–207. [PubMed] [Google Scholar]
- 11.Crichton G.E., Bryan J., Murphy K.J., Buckley J. Review of dairy consumption and cognitive performance in adults: Findings and methodological issues. Dement. Geriatr. Cogn. Disord. 2010;30:352–361. doi: 10.1159/000320987. [DOI] [PubMed] [Google Scholar]
- 12.Kesse-Guyot E., Assmann K.E., Andreeva V.A., Ferry M., Hercberg S., Galan P. Consumption of dairy products and cognitive functioning: Findings from the SU. VI. MAX 2 study. J. Nutr. Health Aging. 2016;20:128–137. doi: 10.1007/s12603-015-0593-x. [DOI] [PubMed] [Google Scholar]
- 13.Crichton G.E., Elias M.F., Dore G.A., Robbins M.A. Relation between dairy food intake and cognitive function: The Maine-Syracuse Longitudinal Study. Int. Dairy J. 2012;22:15–23. doi: 10.1016/j.idairyj.2011.08.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Park K.M., Fulgoni V.L. The association between dairy product consumption and cognitive function in the National Health and Nutrition Examination Survey. Br. J. Nutr. 2013;109:1135–1142. doi: 10.1017/S0007114512002905. [DOI] [PubMed] [Google Scholar]
- 15.Crichton G.E., Murphy K.J., Bryan J. Dairy intake and cognitive health in middle-aged South Australians. Asia Pac. J. Clin. Nutr. 2010;19:161–171. [PubMed] [Google Scholar]
- 16.Van Wijngaarden J.P., Dhonukshe-Rutten R.A.M., van Schoor N.M., van der Velde N., Swart K.M.A., Enneman A.W., van Dijk S.C., Brouwer-Brolsma E.M., Zillikens M.C., van Meurs J.B.J., et al. Rationale and design of the B-PROOF study, a randomized controlled trial on the effect of supplemental intake of vitamin B 12 and folic acid on fracture incidence. BMC Geriatr. 2011;11:1. doi: 10.1186/1471-2318-11-80. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Rhee J.J., Sampson L., Cho E., Hughes M.D., Hu F.B., Willett W.C. Comparison of methods to account for implausible reporting of energy intake in epidemiologic studies. Am. J. Epidemiol. 2015;181:225–233. doi: 10.1093/aje/kwu308. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.The Dutch Nutrition Centre . Zo eet Nederland: Resultaten van de Voedselconsumptiepeiling 1997–1998 (Results of the Dutch Food Consumption Survey 1997/1998) Voedingscentrum; Den Haag, The Netherlands: 1998. [Google Scholar]
- 19.The Dutch National Institute for Public Health and the Environment (RIVM) Nevo-Tabel. Nederlands Voedingsstoffenbestand 2011. Voedingscentrum; Den Haag, The Netherlands: 2011. [Google Scholar]
- 20.Feunekes G.I., Van Staveren W.A., De Vries J.H., Burema J., Hautvast J.G. Relative and biomarker-based validity of a food-frequency questionnaire estimating intake of fats and cholesterol. Am. J. Clin. Nutr. 1993;58:489–496. doi: 10.1093/ajcn/58.4.489. [DOI] [PubMed] [Google Scholar]
- 21.Siebelink E., Geelen A., de Vries J.H.M. Self-reported energy intake by FFQ compared with actual energy intake to maintain body weight in 516 adults. Br. J. Nutr. 2011;106:274–281. doi: 10.1017/S0007114511000067. [DOI] [PubMed] [Google Scholar]
- 22.Streppel M.T., De Vries J.H., Meijboom S., Beekman M., de Craen A.J.M., Slagboom P.E., Feskens E.J.M. Relative validity of the food frequency questionnaire used to assess dietary intake in the Leiden longevity study. Nutr. J. 2013;12:75. doi: 10.1186/1475-2891-12-75. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Overheid.nl. Warenwetbesluit Zuivel. [(accessed on 20 December 2018)]; Available online: http://wetten.overheid.nl/BWBR0006982/2016-02-19.
- 24.Willett W.C., Howe G.R., Kushi L.H. Adjustment for total energy intake in epidemiologic studies. Am. J. Clin. Nutr. 1997;65:1220–1228. doi: 10.1093/ajcn/65.4.1220S. [DOI] [PubMed] [Google Scholar]
- 25.Folstein M.F., Folstein S.E., McHugh P.R. “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician. J. Psychiatr. Res. 1975;12:189–198. doi: 10.1016/0022-3956(75)90026-6. [DOI] [PubMed] [Google Scholar]
- 26.Wechsler D. Manual for the Adult Intelligence Scale-Revised. Psychological Corporation; New York, NY, USA: 1981. [Google Scholar]
- 27.Stroop J.R. Studies of interference in serial verbal reactions. J. Exp. Psychol. 1935;18:643. doi: 10.1037/h0054651. [DOI] [Google Scholar]
- 28.Lezak M.D. Neuropsychological Assessment. Oxford University Press; New York, NY, USA: 2004. [Google Scholar]
- 29.Reitan R.M. Validity of the trail-making test as an indicator of organic brain damage. Percept Mot Skills. 1958;8112:201–210. [Google Scholar]
- 30.Smith A. Symbol Digits Modalities Test. Western Psychological Services; Los Angeles, CA, USA: 1982. [Google Scholar]
- 31.Brand N., Jolles J. Learning and retrieval rate of words presented auditorily and visually. J. Gen. Psychol. 1985;112:201–210. doi: 10.1080/00221309.1985.9711004. [DOI] [PubMed] [Google Scholar]
- 32.Brouwer-Brolsma E.M., Dhonukshe-Rutten R.A., van Wijngaarden J.P., van de Zwaluw N.L., in’t Veld P.H., Wins S., Swart K.M.A., Enneman A.W., Ham A.C., van Dijk S.C., et al. Cognitive performance: A cross-sectional study on serum vitamin D and its interplay with glucose homeostasis in Dutch older adults. J. Am. Med. Dir. Assoc. 2015;16:621–627. doi: 10.1016/j.jamda.2015.02.013. [DOI] [PubMed] [Google Scholar]
- 33.Stel V.S., Smit J.H., Pluijm S.M., Visser M., Deeg D.J.H., Lips P. Comparison of the LASA Physical Activity Questionnaire with a 7-day diary and pedometer. J. Clin. Epidemiol. 2004;57:252–258. doi: 10.1016/j.jclinepi.2003.07.008. [DOI] [PubMed] [Google Scholar]
- 34.Garretsen H.F.L. Probleemdrinken: Prevalentiebepaling, Beïnvloedende Factoren en Preventiemogelijkheden. Swets Zeitlinger; Lisse, The Netherlands: 1983. [Google Scholar]
- 35.Yaffe K., Krueger K., Cummings S.R., Blackwell T., Henderson V.W., Sarkar S., Ensrud K., Grady D. Effect of raloxifene on prevention of dementia and cognitive impairment in older women: The Multiple Outcomes of Raloxifene Evaluation (MORE) randomized trial. Am. J. Psychiatry. 2005;162:683–690. doi: 10.1176/appi.ajp.162.4.683. [DOI] [PubMed] [Google Scholar]
- 36.Barros A.J., Hirakata V.N. Alternatives for logistic regression in cross-sectional studies: An empirical comparison of models that directly estimate the prevalence ratio. BMC Med. Res. Methodol. 2003;3:21. doi: 10.1186/1471-2288-3-21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Ganguli M., Belle S., Ratcliff G., Seaberg E., Huff F.J., von der Porten K., Kuller L.H. Sensitivity and specificity for dementia of population-based criteria for cognitive impairment: The MoVIES project. J. Gerontol. 1993;48:M152–M161. doi: 10.1093/geronj/48.4.M152. [DOI] [PubMed] [Google Scholar]
- 38.Benjamini Y., Hochberg Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B (Methodol. ) 1995;57:289–300. doi: 10.1111/j.2517-6161.1995.tb02031.x. [DOI] [Google Scholar]
- 39.Lee L., Kang S.A., Lee H.O., Lee B.H., Park J.S., Kim J.H., Jung I.K., Park Y.J., Lee J.E. Relationships between dietary intake and cognitive function level in Korean elderly people. Public Health. 2001;115:133–138. doi: 10.1016/S0033-3506(01)00432-2. [DOI] [PubMed] [Google Scholar]
- 40.Ávila-Funes J.A., Garant M., Aguilar-Navarro S. Relationship between determining factors for depressive symptoms and for dietary habits in older adults in Mexico. Rev. Panam. Salud Pública. 2006;19:321–330. doi: 10.1590/s1020-49892006000500005. [DOI] [PubMed] [Google Scholar]
- 41.Rahman A., Sawyer Baker P., Allman R.M., Zamrini E. Dietary factors and cognitive impairment in community-dwelling elderly. J. Nutr. Health Aging. 2007;11:49. [PubMed] [Google Scholar]
- 42.Almeida O.P., Norman P., Hankey G., Jamrozik K., Flicker L. Successful mental health aging: Results from a longitudinal study of older Australian men. Am. J. Geriatr. Psychiatry. 2006;14:27–35. doi: 10.1097/01.JGP.0000192486.20308.42. [DOI] [PubMed] [Google Scholar]
- 43.Eskelinen M.H., Ngandu T., Helkala E.L., Tuomiletho J., Nissinen A., Soininen H., Kivipelto M. Fat intake at midlife and cognitive impairment later in life: A population-based CAIDE study. Int. J. Geriatr. Psychiatry. 2008;23:741. doi: 10.1002/gps.1969. [DOI] [PubMed] [Google Scholar]
- 44.Vercambre M.N., Boutron-Ruault M., Ritchie K., Clavel-Chapelon F., Berr C. Long-term association of food and nutrient intakes with cognitive and functional decline: A 13-year follow-up study of elderly French women. Br. J. Nutr. 2009;102:419–427. doi: 10.1017/S0007114508201959. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Akbari E., Asemi Z., Kakhaki R.Z., Bahmani F., Kouchaki E., Tamtaji O.R., Ali Hamidi G.A., Salami M. Effect of probiotic supplementation on cognitive function and metabolic status in Alzheimer’s disease: A randomized, double-blind and controlled trial. Front. Aging Neurosci. 2016;8:256. doi: 10.3389/fnagi.2016.00256. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Hemarajata P., Versalovic J. Effects of probiotics on gut microbiota: Mechanisms of intestinal immunomodulation and neuromodulation. Ther. Adv. Gastroenterol. 2013;6:39–51. doi: 10.1177/1756283X12459294. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Ohsawa K., Nakamura F., Uchida N., Mizuno S., Yokogoshi H. Lactobacillus helveticus-fermented milk containing lactononadecapeptide (NIPPLTQTPVVVPPFLQPE) improves cognitive function in healthy middle-aged adults: A randomised, double-blind, placebo-controlled trial. Int. J. Food Sci. Nutr. 2018;69:369–376. doi: 10.1080/09637486.2017.1365824. [DOI] [PubMed] [Google Scholar]
- 48.Tillisch K., Labus J., Kilpatrick L., Jian Z., Stains J., Ebrat B., Guyonnet D., Legrain-Raspaud S., Trotin B., Naliboff B., et al. Consumption of fermented milk product with probiotic modulates brain activity. Gastroenterology. 2013;144:1394–1401. doi: 10.1053/j.gastro.2013.02.043. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Vermeer C., Raes J., van’t Hoofd C., Knapen M.H.J., Xanthoulea S. Menaquinone Content of Cheese. Nutrients. 2018;10:446. doi: 10.3390/nu10040446. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Ferland G., Vitamin K. An emerging nutrient in brain function. Biofactors. 2012;38:151–157. doi: 10.1002/biof.1004. [DOI] [PubMed] [Google Scholar]
- 51.Korhonen H., Pihlanto A. Bioactive peptides: Production and functionality. Int. Dairy J. 2006;16:945–960. doi: 10.1016/j.idairyj.2005.10.012. [DOI] [Google Scholar]
- 52.Brouwer-Brolsma E.M., Lucassen D., de Rijk M.G., Slotegraaf A., Perenboom C., Borgonjen K., Siebelink E., Feskens E.J., de Vries J.H. Dietary Intake Assessment: From Traditional Paper-Pencil Questionnaires to Technology-Based Tools. Int. Symp. Environ. Softw. Syst. 2020;554:7–23. [Google Scholar]