To examine the association between dietary habits, cognitive functioning and brain volumes in older individuals, data from 194 cognitively healthy individuals who participated in the Prospective Investigation of the Vasculature in Uppsala Seniors cohort were used. At age 70, participants kept diaries of their food intake for 1week. These records were used to calculate a Mediterranean diet (MeDi) score (comprising dietary habits traditionally found in Mediterranean countries, e.g. high intake of fruits and low intake of meat), with higher scores indicating more pronounced MeDi-like dietary habits. Five years later, participants' cognitive capabilities were examined by the seven minute screening (7MS) (a cognitive test battery used by clinicians to screen for dementia), and their brain volumes were measured by volumetric magnetic resonance imaging. Multivariate linear regression analyses were constructed to examine the association between the total MeDi score and cognitive functioning and brain volumes. In addition, possible associations between MeDi's eight dietary features and cognitive functioning and brain volumes were investigated. From the eight dietary features included in the MeDi score, pertaining to a low consumption of meat and meat products was linked to a better performance on the 7MS test (P=0.001) and greater total brain volume (i.e. the sum of white and gray matter, P=0.03) when controlling for potential confounders (e.g. BMI) in the analysis. Integrating all dietary features into the total MeDi score explained less variance in cognitive functioning and brain volumes than its single dietary component meat intake. These observational findings suggest that keeping to a low meat intake could prove to be an impact-driven public health policy to support healthy cognitive aging, when confirmed by longitudinal studies. Further, they suggest that the MeDi score is a construct that may mask possible associations of single MeDi features with brain health domains in elderly populations.

Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist–hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006–0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.

Dietary patterns derived by statistical procedures is a way to identify overall dietary habits in specific populations. The aim of this study was to identify and characterise dietary patterns in Swedish adults using data from the national dietary survey Riksmaten adults 2010-11 (952 women, 788 men). Principal component analyses were used and two patterns were identified in both sexes: a healthy pattern loading positively on vegetables, fruits, fish and seafood, and vegetable oils, and negatively on refined bread and fast food, and a Swedish traditional pattern loading positively on potatoes, meat and processed meat, full-fat milk products, sweet bakery products, sweet condiments and margarine. In addition, a light-meal pattern was identified in women with positive loadings on fibre-rich bread, cheese, rice, pasta and food grain dishes, substitute products for meat and dairy products, candies and tea. The healthy pattern was positively correlated to dietary fibre (r 0·51-0·58) and n-3 (r 0·25-0·31) (all P < 0·0001), and had a higher nutrient density of folate, vitamin D and Se. The Swedish traditional and the light-meal pattern were positively correlated to added sugar (r 0·20-0·25) and the Swedish traditional also to SFA (r 0·13-0·21) (all P < 0·0001); both patterns were in general negatively correlated to micronutrients. Dietary pattern scores were associated with, for example, age, physical activity, education and income. In conclusion, we identified three major dietary patterns among Swedish adults. The patterns can be further used for examining the association between whole diet and health outcomes. Dietary pattern analysis has become a popular method for studying overall diet and associations between diet and disease risk. Pre-specified indices are used to measure adherence to recommendations or diets with hypothesised health implications, whereas data-driven methods, often factor or cluster analysis, are applied to identify underlying food patterns in a population empirically (1,2) . Participants' adherence to the dietary patterns can then serve as a holistic measure of their diet in assessment of diet-disease relationships. Such a holistic approach has several methodological advantages, as it includes unexplored dietary factors and nutrient interactions and increases the chance of detecting small but meaningful associations as they add up in the context of a whole diet, and at the same time not impeded by the disadvantages of correlated intakes (1,3) . Indeed, throughout the past decades, dietary patterns have been related to multiple health outcomes, mainly morbidity and mortality from CVD and cancer, longevity and neurodegenerative diseases (4)(5)(6)(7)(8)(9)(10)(11) . From the perspective of public health promotion, dietary patterns reflect the foods commonly consumed together. Hence, promoting healthy dietary patterns, in addition to targeted food-based dietary guidelines, might be a useful approach in order to improve diet and health in a population. Understanding the underlying dietary habi...

Whether loci that influence fasting glucose (FG) and fasting insulin (FI) levels, as identified by genome-wide association studies, modify associations of diet with FG or FI is unknown. We utilized data from 15 U.S. and European cohort studies comprising 51,289 persons without diabetes to test whether genotype and diet interact to influence FG or FI concentration. We constructed a diet score using study-specific quartile rankings for intakes of whole grains, fish, fruits, vegetables, and nuts/seeds (favorable) and red/processed meats, sweets, sugared beverages, and fried potatoes (unfavorable). We used linear regression within studies, followed by inverse-variance-weighted meta-analysis, to quantify 1) associations of diet score with FG and FI levels and 2) interactions of diet score with 16 FG-associated loci and 2 FI-associated loci. Diet score (per unit increase) was inversely associated with FG (β = -0.004 mmol/L, 95% confidence interval: -0.005, -0.003) and FI (β = -0.008 ln-pmol/L, 95% confidence interval: -0.009, -0.007) levels after adjustment for demographic factors, lifestyle, and body mass index. Genotype variation at the studied loci did not modify these associations. Healthier diets were associated with lower FG and FI concentrations regardless of genotype at previously replicated FG- and FI-associated loci. Studies focusing on genomic regions that do not yield highly statistically significant associations from main-effect genome-wide association studies may be more fruitful in identifying diet-gene interactions.

In the present study, we tested whether elderly with a high dietary intake of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) would have higher cognitive test scores and greater brain volume than those with low dietary intake of these fatty acids. Data were obtained from the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) cohort. The dietary intake of EPA and DHA was determined by a 7-day food protocol in 252 cognitively healthy elderly (122 females) at the age of 70 years. At age 75, participants' global cognitive function was examined, and their brain volumes were measured by magnetic resonance imaging (MRI). Three different multivariate linear regression models were applied to test our hypothesis: model A (adjusted for gender and age), model B (additionally controlled for lifestyle factors, e.g., education), and model C (further controlled for cardiometabolic factors, e.g., systolic blood pressure). We found that the self-reported 7-day dietary intake of EPA and DHA at the age of 70 years was positively associated with global gray matter volume (P < 0.05, except for model C) and increased global cognitive performance score (P < 0.05). However, no significant associations were observed between the dietary intake of EPA and DHA and global white matter, total brain volume, and regional gray matter, respectively. Further, no effects were observed when examining cognitively impaired (n = 27) elderly as separate analyses. These cross-sectional findings suggest that dietary intake of EPA and DHA may be linked to improved cognitive health in late life but must be confirmed in patient studies.

Dietary pattern analyses have increased the possibilities to detect associations between diet and disease. However, studies on dietary pattern and prostate cancer are scarce. Food intake data in the Uppsala Longitudinal Study of Adult Men cohort was determined by 7-day food records. Adherence to a modified Mediterranean Diet Score (mMDS) and a low carbohydrate-high protein (LCHP) score were grouped as low, medium, or high in the whole study population (n = 1,044) and in those identified as adequate reporters of energy intake (n = 566), respectively. Prostate cancer risk was analyzed with Cox proportional hazard regression (median follow-up 13 years) and competing risk of death was considered. There were no associations between dietary patterns and prostate cancer (n = 133) in the whole study population. Among adequate reporters the mMDS was not associated with prostate cancer (n = 72). The LCHP score was inversely related to prostate cancer in adequate reporters, adjusted hazard ratios; 0.55 (0.32-0.96) for medium and 0.47 (0.21-1.04) for high compared to low adherent participants (P-for-trend 0.04). Risk relations were not attributable to competing risk of death. In this study, a LCHP diet was associated with lower prostate cancer incidence. Relations emerged in adequate reporters, underscoring the importance of high-quality dietary data.

Dietary patterns were associated in diverse manners with circulating levels of environmental contaminants in this elderly Swedish population. Following the WHO dietary recommendations seems to be associated with a lower burden of environmental contaminants.

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