Dietary prevention is increasingly recognized as a necessary strategy against the current epidemic of obesity and related metabolic disorders. Epidemiological studies and dietary interventions strongly support that high intake of whole grain foods and legumes are beneficial in the prevention and management of type 2 diabetes (T2DM), management of T1DM [1], and for weight control [2]. Foods with low glycemic index (GI) have further proven beneficial in the prevention and treatment of the metabolic syndrome (MetS), obesity, T2DM, and cardiovascular disease [3–6]. Other dietary measures, such as the inclusion of foods rich in omega-3 fatty acids [7] or polyphenols (e.g. berries) [8], have shown cardioprotective effects by improving blood lipid profile, lowering blood pressure, and positively affecting inflammatory markers [7, 9].

Obesity, insulin resistance and T2DM are closely associated with chronic inflammation, predominately in adipose tissue [10, 11]. Interestingly, peripheral inflammatory cytokines can be actively transported across the blood–brain-barrier, or induce expression of cytokines in the brain; causing impairment of neuronal function [12, 13]. Also, reduced insulin receptor signalling compromizes neuroplasticity; indicative of a link between chronic low grade inflammation, insulin resistance, and cognitive impairment [14, 15]. T2DM and the MetS are associated with an increased risk of cognitive decline [16]. Consequently, a diet that prevents metabolic disorders might be expected to prevent an associated cognitive decline.

Certain foods or dietary patterns, e.g. polyphenol rich foods (e.g. berries and cocoa) [17–19], and low GI foods [20, 21], may improve cognitive functions and/or prevent cognitive decline. In prospective cohort- [22] and cross-sectional [23] studies of middle aged and elderly populations, higher proportions of n-3 polyunsaturated fatty acids (n-3 PUFA) in plasma were linked to a lower risk of cognitive decline, and a number of studies reveal that higher fish consumption promote better cognitive functions [24–28]. However, few studies have examined the possibilities to beneficially influence cardiometabolic risk markers and measures of cognitive performance by dietary means in apparently healthy subjects. Previously, we reported that an “active” dietary regime, gathering different anti-inflammatory food concepts, markedly reduced acknowledged cardiometabolic risk markers, as well as reduced predicted cardiovascular events in healthy overweighed subjects (BMI, mean ± SEM: 28.5 ± 0.3 kg/m2) [29]. The diet was e.g. rich in low glycemic impact meals, antioxidant-rich foods, oily fish and rapeseed oil as sources of omega-3 fatty acids, viscous dietary fibers, soybeans, whole barley kernel products, almonds, stanols, and included also a probiotic strain. The rationale for investigating a healthy cohort was that the overall purpose of the study relates to dietary prevention, which in shorter interventions preferably is evaluated before manifest metabolic diseases have been developed.

The present paper is an extension to the study described above [29], now with the purpose to, in the same cohort, report the impact of the active diet on measures of cognitive functions. The purpose was in addition to evaluate cognitive performance in relation to results on cardiometabolic risk variables (BMI, blood pressure, glucose, insulin, cholesterol, triglycerides, free fatty acids, lipoprotein A-1 and B, hs-CRP, HbA1c, interleukin-6, TNF-α, and PAI-1). Fourty-four overweight but otherwise healthy subjects (50–73 years, BMI 25–33 kg/m2) participated in the study (randomized controlled crossover design). The active diet was compared with a control diet devoid of the active components/features. Each diet was consumed during four weeks with a four week washout period in-between.

Subjects and methods

Information regarding the subjects, diets (active and control), and study protocol for metabolic measurements are thoroughly described elsewhere (J Tovar et. al. 2012 [29]), and just briefly described in this paper. The present paper instead focuses on new data related to the cognitive aspects.

The study was approved by the Regional Ethical Review Board, Lund, Sweden (Dnr 593/2008).

Subjects

Inclusion criteria were age between 50 and 73 years, BMI 25–33 kg/m2, and fasting plasma glucose concentration ≤ 6.1 mmol/L. In total, 44 (36 females, 8 men) healthy subjects between 50 and 73 years of age (mean 63.3 ± 0.8 years) without any known medical condition or cognitive decline were included in the study. The subjects were overweight or slightly obese, but otherwise healthy (BMI (mean ± SEM): 28.5 ± 0.3 kg/m2). BMI of two subjects were 25 kg/m2, 34 subjects had BMI between 25–30 kg/m2, and eight subjects had BMI 30–33 kg/m2. More detailed description of subjects characteristics have been presented previously [29].

Study protocol

The study had a randomized, controlled, balanced crossover design. One active- and one control diet were included in the study (described below). Twenty subjects started with the active diet and 24 subjects with the control diet. Each diet period lasted four weeks, with a four-week washout period in-between. The whole trial included four clinical visits, one before and one after each diet phase. Cognitive tests were performed after each diet period, i.e. at visits no. two and four, whereas metabolic risk markers were determined at fasting at all four visits.

Before each intervention period (visits no. one and three), the participants performed test versions of the Selective Attention (SA) test and got thorough information regarding the Rey Auditory-Verbal Learning test (RAVLT) (the tests are described below). No specific screening for possible cognitive decline was carried out prior to the enrollment. However, performance in the pilot version of the SA-test at visit no. one was taken as a measure of the subjects' cognitive abilities to conduct the study in an adequate manner. In addition the participants underwent a medical examination at the first visit. All participants were considered qualified to participate in the study.

At the cognitive test days (visit no. two and four), the subjects arrived fasting in the morning between 7.30 am and 8.15 am (individually standardized). After resting for 15 minutes in a sitting position, physiological test parameters were determined, including weight, blood pressure, blood glucose, insulin, cholesterol (total cholesterol, LDL (low density lipoprotein), and HDL (high density lipoprotein)), triglycerides, free fatty acids, lipoprotein A-1 and B, hs-CRP (high-sensitivity C-reactive protein), HbA1c (glycated hemoglobin), inflammatory markers (IL-6 (interleukin-6), TNF-α (tumor necrosis factor alpha)), and PAI-1 (plasminogen activator inhibitor 1). A detailed description of the test variables and methods used have been presented previously [29]. The first SA-test was performed after obtaining the fasting metabolic test variables, and thereafter subjects were provided a standardized breakfast consisting of a white wheat bread (75.5 g) (Dollar Storfranska, Lockarps bakery, Malmö, Sweden) and apricot marmalade (27.7 g) (Ica, Sweden), corresponding to 55 g available carbohydrates in total. Water, 100 ml, and a plain cup of decaffeinated coffee or tea (150 ml) were served with the bread. The breakfast was supposed to be consumed within 15 min. Two of the participants were unable to eat the whole bread serving at the first experimental day (visit no. two). The leftovers were weighted and registered, and the subjects were served the same amounts of bread at the second experimental day (visit no. four). The cognitive tests were performed repeatedly up to 120 min after the start of the breakfast. A time schedule for execution of cognitive tests is presented in Table 1.

Table 1 Time schedule for execution of cognitive tests Full size table

Test- and control diets

The diets included (active diet and control diet) were non vegetarian, and designed in close agreement with the Nordic Nutrition Recommendations [30]. The active diet contained foods, food components, and food concepts, with documented potential to reduce sub-clinical inflammation and cardiometabolic risk, such as:

a) foods with high anti-oxidative capacity (anti-inflammatory effects [31], may improve blood pressure and blood lipids [8], suggested to be beneficial to cognitive functions [19]). b) fatty fish (contain long chain n-3 PUFA, known to have anti-inflammatory and triglyceride-lowering properties [32, 33], and are suggested to improve working memory capacity [34]). Rapeseed oil was included to provide additional n-3-PUFA. c) prebiotic carbohydrates intrinsic in barley kernel products and whole grain rye foods, and products rich in dietary fibre from oat. Included was also bread supplemented with guar gum, which is a highly viscous fibre. Viscous fibre (in barley, oat, and guar gum) may lower the GI, and the indigestible carbohydrates included in the products can have prebiotic effects and improve glycaemic regulation, reduce satiety, and reduce inflammatory markers in a 10-14 h perspective [35, 36]. d) Low-GI foods/meals (reduce the risk of T2DM [37] and the MetS [38], reduce inflammatory tonus [39] and may be beneficial to cognitive functions [20, 21]). e) products that improve the blood lipid profile (soybeans, a margarine enriched in stanol esters, and dry almonds [40]).

In addition the active diet included a probiotic strain (Lactobacillus plantarum Heal19, DSM 15313) with health benefits on the gut microflora. The control diet contained a similar distribution of energy providing nutrients, but essentially lacked the active food components or food concepts.

The daily energy intake was based on gender, and supplied 2,500-2,600 Kcal/d for men and 2,000-2,100 Kcal/d for women, including foods both from plant and animal origin. The nutritional profiles are presented in Table 2. The mean daily quantities of the different active foods or food components in the active diet, and the main functional properties that were considered for their inclusion, have been summarized in Table 3. The products have been described in more detail previously [29].

Table 2 Nutritional profiles of the control and active diet Full size table

Table 3 Proposed functional action and average content of active components in the active diet Full size table

Participants were provided with a 14-day menu plan which was repeated during the last two weeks. They had to follow the recipes in detail for breakfast, lunch, dinner and snacks (cooking procedures, and quantities by e.g. weighing the food ingredients). Since the purpose was that the study would be carried out under a constant weight, subjects had to weigh themselves at home once a week. If there was a discrepancy (up or down) by more than a kg compared with the beginning of a diet period, they were instructed to contact a nutritionist who was attached to the study in order to get help to adjust energy intake. They received a check list to fill in to check off every day that all active food components were consumed, and they had to make a note to describe any deviation from the menu. A limited amount of alcohol (30 and 37 g ethanol/wk for women and men, respectively), was allowed during the intervention period. The volunteers’ ordinary coffee and tea drinking habits were maintained during the trial.

Cognitive tests

The rationale for the choice of cognitive tests was to include a broad variety of aspect of cognitive functions that are sensitive to metabolic disturbance. The SA-test covers several domains and cognitive aspects, e.g. working memory, attention and choice reaction time. The SA-test is of short duration, slightly less than 10 min, and in this respect making it suitable for repeated testing. We have previously included the SA-test in investigations of food effects on cognitive functions, and investigations of relationships between cognitive functions and metabolic parameters (glucose tolerance), with good results [21, 51]. The time points for the SA-test were chosen to cover several aspects with respect to glucose concentrations, and metabolism and its regulation; fasting stage, the postprandial peak increase in blood glucose, and later postprandial phase. The RAVLT took 1 hour to perform, making it difficult to repeat, however word lists have been used extensively with respect to investigations of cognitive effects of metabolic disorders (e.g. Hassenstab JJ et. al 2010 [52]).

Selective attention (SA)

The test was computerized, based on spatial perception, and primarily measured the ability to sustain a prolonged attention, and to control and split the attention to the entire picture on the computer screen [21, 51]. The SA-test also included aspects of the working memory i.e. simultaneous temporary storing and processing of information. The SA was measured using a test made up of 96 pictures, each shown for two seconds on the screen. The pictures consisted of a square on a white background, divided into four smaller squares. One of the smaller squares was red, one was green, and two squares were uncolored (white), resulting in a total of 12 unique picture combinations. The subjects had to remember the positions of the colored squares, and to compare each new picture that emerged on the screen with the preceding one. Each time a new picture emerged, either the green, the red or none of the colored squares were positioned in the same position compared with the previous picture. Within two seconds, the subjects were supposed to indicate by pressing one of three different keys on the keyboard, which of the three possible alternatives that occurred for each new picture. The SA-test was performed at fasting and at 45, and 120 minutes after start of the standardized breakfast. The SA-test began with a short training session, and took approximately 10 min to perform. The test was scored with the number of correct responses (CR, total 95 credits) and for the reaction time (RT) needed to give the response (i.e. press one of the keys).

The Rey Auditory-Verbal Learning test (RAVLT)

The RAVLT [53] was used to measure aspects of learning and memory. The test was modified to avoid ceiling effects. A list of 30 common nouns (originally 15), were read to the subjects, separated by 2 seconds, in 5 consecutive trials. Each reading of a list was followed by an immediate free recall where the nouns were recalled and written down on paper within 2 minutes. Results after the 5th reading measured best learning, and the mean of trials no. 1–5 was a measure of mean learning. In a 6th trial, an interference list of 30 new common nouns were presented, follow by an immediate recall (measuring proactive interference (PI) from list 1). In a 7th trial, the subjects were supposed to recall the first list, without a new reading (measuring retroactive interference (RI) from list 2). After a 20 minute break, in trial no. 8, without an additional reading, the subjects were asked to again recall the first list (delayed recall). The next trial (trial no. 9) was a recognition test. The subjects were given a list with 100 nouns (modified from 50) of which 30 were from the first list, 30 from the second list, and 40 were new nouns. They were asked to, within 3 minutes, identify the 30 words that appeared on the first list. In the last trial (no. 10), the first list was presented on a paper in a different order than the original list (list no. one). They were asked to mark which words (10 nouns) that appeared fist on the original list, which words that appeared in the middle of the list (10 nouns) and which were in the end of the list (10 nouns) (memory of temporal order The test was scored for correct recalled nouns in trials no. 1–8, mean learning (mean of trials no. 1–5), best learning (trial no, 5), recognition (trial no.9), and memory of temporal order (trial no. 10). The total RAVLT took approximately 60 minutes to perform.

Calculations and statistical methods

A power calculation was performed based on cardiometabolic test markers (plasma LDL-cholesterol and hs-CRP) in the parallel study [29]. Based on this power calculation it was decided to include 44 subjects. This is close to the number of subjects (40 subjects) that have been included in previous meal studies and interventions, using a corresponding SA-test [21, 34]. The results are expressed as means ± SEM. The influence of the active- and control diets on the cognitive tests was analyzed by repeated measures ANOVA at the test points, with order of diets, time point of the test, and diets as independent variables, and performance in cognitive tests as dependent variables. Statistical calculations were performed in Stat View 5.0 and SuperAnova 1.11. Significant differences in cognitive performance depending on diet sequence (cognitive test day one or two) were investigate with ANOVA (general linear model), in MINITAB Statistical Software (release 14; Minitab, Minitab Inc, State College, PA). Participants acted as their own control.

Multiple linear regression analysis was performed to examine relationships between cardiometabolic risk markers (independent variables) and performance in cognitive tests (dependent outcome variables), using STATA software package (release 10). A large number of cardiometabolic risk markers were determined (described above). To lower the number of risk markers, and to determine and avoid multicollinearity, pair-wise relationships were examined prior to regression analyses, using Pearson correlations in MINITAB Statistical Software (release 14; Minitab, Minitab Inc, State College, PA). Cardiometabolic risk markers with no tendency to be related with cognitive performance were eliminated. Pearson correlations in all possible pair-wise combinations of the cardiometabolic risk markers were performed. Five cardiometabolic risk markers (systolic blood pressure and fasting concentrations of: total cholesterol, insulin, glucose, ApoA1) were identified as non-linearly combined and included into the multiple regression models (model no. 1). Further backward stepwise analysis was conducted by checking the significance of the cardiometabolic risk markers and including in the model only those which were statistically significant (model 2). Furthermore, model 1 and model 2 were adjusted for age of the test subjects (model 3 and model 4, respectively). All models were tested for the normality of residuals. Data were tested for outliers, and no extreme or influential data were identified. In the case of a skewed distribution, variables were transformed accordingly before further analyses were performed (SA-tests: correct responses, and RAVLT: mean of trial 1–5 and trial 8 after both active- and control diet, and trial 7 after control diet, were analysed as their square values, trial no. 6 were analysed as there square roots, and cubic transformation were applied for trial no. 9 after both the active- and control diet). Regression analyses were based on data obtained from cognitive tests and risk markers determined at the same visits, generating separate regression analyses after the active diet and control diet, respectively.

Ten-year coronary heart disease risk was calculated with the Framingham Study equation [54], considering age, gender, total cholesterol, HDL-cholesterol, smoking and systolic BP values, and the Reynolds Risk Score [55], which also incorporates CRP values. Relations between Framingham- and Reynolds Risk Score and cognitive performance were evaluated with pairwise Pearson correlations.

Statistical evaluations of cardiometabolic risk variables are described elsewhere [29]. Values of P < 0.05 were considered statistically significant.