Evaluation of dietary patterns among Norwegian postmenopausal women using plasma carotenoids as biomarkers

Enhancing Capacity for Food and Nutrient Intake Assessment in Population Sciences Research

Nutrition influences health throughout the life course. Good nutrition increases the probability of good pregnancy outcomes, proper childhood development, and healthy aging, and it lowers the probability of developing common diet-related chronic diseases, including obesity, cardiovascular disease, cancer, and type 2 diabetes. Despite the importance of diet and health, studying these exposures is among the most challenging in population sciences research. US and global food supplies are complex; eating patterns have shifted such that half of meals are eaten away from home, and there are thousands of food ingredients with myriad combinations. These complexities make dietary assessment and links to health challenging both for population sciences research and for public health policy and practice. Furthermore, most studies evaluating nutrition and health usually rely on self-report instruments prone to random and systematic measurement error. Scientific advances involve developing nutritional biomarkers and then applying these biomarkers as stand-alone nutritional exposures or for calibrating self-reports using specialized statistics.

Development of a Multibiomarker Panel of Healthy Eating Index in United States Adults: A Machine Learning Approach

BACKGROUND

Dietary and nutritional biomarkers are objective dietary assessment tools that will enable a more accurate and precise determination of diet-disease relations. However, the lack of established biomarker panels for dietary patterns is concerning, as dietary patterns continue to be the focus of dietary guidelines.

OBJECTIVES

We aimed to develop and validate a panel of objective biomarkers that reflects the Healthy Eating Index (HEI) by applying machine learning approaches to the National Health and Nutrition Examination Survey data.

METHODS

Cross-sectional population-based data (eligible criteria: age ≥20 y, not pregnant, no reported supplement use of dedicated vitamin A, D, E, or fish oils; n = 3481) from the 2003 to 2004 cycle of the NHANES were used to develop 2 multibiomarker panels of the HEI, 1 with (primary panel) and 1 without (secondary panel) plasma FAs. Up to 46 blood-based dietary and nutritional biomarkers (24 FAs, 11 carotenoids, and 11 vitamins) were included for variable selection using the least absolute shrinkage and selection operator controlling for age, sex, ethnicity, and education. The explanatory impact of selected biomarker panels was assessed by comparing the regression models with and without the selected biomarkers. In addition, 5 comparative machine learning models were constructed to validate the biomarker selection.

RESULTS

The primary multibiomarker panel (8 FAs, 5 carotenoids, and 5 vitamins) significantly improved the explained variability of the HEI (adjusted R² increased from 0.056 to 0.245). The secondary multibiomarker panel (8 vitamins and 10 carotenoids) had lesser predictive capabilities (adjusted R² increased from 0.048 to 0.189).

CONCLUSIONS

Two multibiomarker panels were developed and validated to reflect a healthy dietary pattern consistent with the HEI. Future research should seek to test these multibiomarker panels in randomly assigned trials and identify whether they have broad application in healthy dietary pattern assessment.

Novel Application of Nutritional Biomarkers From a Controlled Feeding Study and an Observational Study to Characterization of Dietary Patterns in Postmenopausal Women

Dietary guidance emphasizes healthy dietary patterns, but supporting evidence comes from self-reported dietary data, which are prone to measurement error. We explored whether nutritional biomarkers from the Women's Health Initiative Nutrition and Physical Activity Assessment Study Feeding Study (NPAAS-FS) (n = 153; 2010-2014) and the Women's Health Initiative Nutrition and Physical Activity Assessment Study Observational Study (NPAAS-OS) (n = 450; 2006-2009) could identify biomarker signatures of dietary patterns for development of corresponding regression calibration equations to help mitigate measurement error. Fasting blood samples were assayed for a specific panel of vitamins, carotenoids, and phospholipid fatty acids; 24-hour urine samples were assayed for nitrogen, sodium, and potassium levels. Intake records from the NPAAS-FS were used to calculate Healthy Eating Index 2010 (HEI-2010), Alternative Healthy Eating Index 2010 (AHEI-2010), alternative Mediterranean diet (aMED), and Dietary Approaches to Stop Hypertension (DASH) scores. Scores were regressed on blood and urine nutritional measures for discovery of dietary pattern biomarkers using a cross-validated model R2 ≥ 36% criterion (stage 1). Next, stepwise models (P ≤ 0.10 for entry/removal) using NPAAS-OS data were used to regress stage 1 dietary pattern biomarkers on NPAAS-OS self-reported dietary pattern scores using a food frequency questionnaire, a 4-day food record, and a 24-hour recall (stage 2). HEI-2010 and aMED analyses met the cross-validated R2 ≥ 36% criterion in stage 1, while AHEI-2010 and DASH analyses did not. The R2 values for HEI-2010 stage 2 calibration equations were as follows: food frequency questionnaire, 63.5%; 4-day food record, 83.1%; and 24-hour recall, 77.8%. Stage 2 aMED R2 values were 34.9%-46.8%. Dietary pattern biomarkers have potential for calibrating self-reports to enhance studies of diet-disease associations.

Inflammatory, oxidative and DNA damage status in vegetarians: is the future of human diet green?

The health benefit of a vegetarian diet is still under debate as it may result in a higher intake of some beneficial micronutrients, while others may be reduced, thus influencing various metabolic pathways and health-related biomarkers. This scoping review discusses inflammatory, oxidative and DNA damage status in vegetarians and vegans compared to omnivores. Most of the reviewed studies indicated favorable effects of a vegetarian diet on oxidative status compared to omnivores but did not clearly associate particular dietary habits to genome damage. The evidence on the effect of vegetarian diet on the inflammatory and immunological biomarkers is poor, which could at least partly be explained by methodological constraints such as small sample size, short duration of vegetarianism and inconsistent definitions of the omnivorous diet. The only inflammatory biomarker that seems to be associated with the vegetarian diet was inflammatory mediator C-reactive protein, which in several studies showed lower values in vegetarians as compared to omnivores. There were very few studies on immunological markers and the results on the difference between vegetarians and omnivores were inconclusive. Although several biomarkers involved in oxidative stress and inflammation showed a beneficial association with the vegetarian diet, further research in well-defined and sufficiently sized cohorts is needed to provide more evidence.

Interactions of Carbohydrate Intake and Physical Activity with Regulatory Genes Affecting Glycaemia: A Food4Me Study Analysis

INTRODUCTION

Carbohydrate intake and physical activity are related to glucose homeostasis, both being influenced by individual genetic makeup. However, the interactions between these 2 factors, as affected by genetics, on glycaemia have been scarcely reported.

OBJECTIVE

We focused on analysing the interplay between carbohydrate intake and physical activity levels on blood glucose, taking into account a genetic risk score (GRS), based on SNPs related to glucose/energy metabolism.

METHODS

A total of 1,271 individuals from the Food4Me cohort, who completed the nutritional intervention, were evaluated at baseline. We collected dietary information by using an online-validated food frequency questionnaire, a questionnaire on physical activity, blood biochemistry by analysis of dried blood spots, and by analysis of selected SNPs. Fifteen out of 31 SNPs, with recognized participation in carbohydrate/energy metabolism, were included in the component analyses. The GRS included risk alleles involved in the control of glycaemia or energy-yielding processes.

RESULTS

Data concerning anthropometric, clinical, metabolic, dietary intake, physical activity, and genetics related to blood glucose levels showed expected trends in European individuals of comparable sex and age, being categorized by lifestyle, BMI, and energy/carbohydrate intakes, in this Food4Me population. Blood glucose was inversely associated with physical activity level (β = -0.041, p = 0.013) and positively correlated with the GRS values (β = 0.015, p = 0.047). Interestingly, an interaction affecting glycaemia, concerning physical activity level with carbohydrate intake, was found (β = -0.060, p = 0.033), which also significantly depended on the genetic background (GRS).

CONCLUSIONS

The relationships of carbohydrate intake and physical activity are important in understanding glucose homeostasis, where a role for the genetic background should be ascribed.

Associations between dietary patterns and gene expression pattern in peripheral blood mononuclear cells: A cross-sectional study

BACKGROUND AND AIMS

Diet may alter gene expression in immune cells involved in atherosclerotic cardiovascular disease susceptibility. However, we still lack a robust understanding of the association between diet and immune cell-related gene expression in humans. Therefore, we examined associations between dietary patterns (DPs) and gene expression profiles in peripheral blood mononuclear cells (PBMCs) in a population of healthy, Norwegian adults (n = 130 women and 105 men).

METHODS AND RESULTS

We used factor analysis to define a posteriori DPs from food frequency questionnaire-based dietary assessment data. In addition, we derived interpretable features from microarray-based gene expression data (13 967 transcripts) using two algorithms: CIBERSORT for estimation of cell subtype proportions, and weighted gene co-expression network analysis (WGCNA) for cluster discovery. Finally, we associated DPs with either CIBERSORT-predicted PBMC leukocyte distribution or WGCNA gene clusters using linear regression models. We detected three DPs that broadly reflected Western, Vegetarian, and Low carbohydrate diets. CIBERSORT-predicted percentage of monocytes associated negatively with the Vegetarian DP. For women, the Vegetarian DP associated with a large gene cluster consisting of 600 genes mainly involved in regulation of DNA transcription, whereas for men, the Western DP inversely associated with a smaller cluster of 36 genes mainly involved in regulation of metabolic and inflammatory processes. A subsequent protein-protein interaction network analysis suggested that genes within these clusters might physically interact in biological networks.

CONCLUSIONS

Although the present findings are exploratory, our analysis pipeline serves as a useful framework for studying the association between diet and gene expression.

Application of Dried Blood Spot Cards combined with liquid chromatography-tandem mass spectrometry to determine eight fat-soluble micronutrients in human blood

The analysis of the fat-soluble vitamins A and E and lipid micronutrients in blood, such as carotenoids, is an important parameter to monitor the micronutrient status in humans. Although the potential of dried blood spot (DBS) cards, the use of this technique for blood sampling and subsequent analysis of these fat-soluble micronutrients has been poorly or not studied. An analytical method based on DBS cards (FTA® DMPK-A) combined with liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) has been developed and validated for the determination of carotenoids (lutein, zeaxanthin, β-cryptoxanthin and β-carotene), tocopherols (α-tocopherol, γ-tocopherol and δ-tocopherol) and all-trans-retinol in human blood. Under optimum DBS card extraction conditions, the extraction recoveries of the studied compounds were higher than 72%, the sample matrix effect lower than 17%, and the detection limits at hundred nM concentration levels. The developed method was applied to the analysis of human blood, and the concentration ranges obtained fell within the expected ranges previously reported in healthy adults. Moreover, the influence of hematocrit effect was investigated in a range of 25-55% in order to compare the obtained results to those reported in the literature for the analysis of plasma samples. This method represents an improvement over current techniques reported in the literature due to the use of a non-invasive blood collection method, and moreover, this methodology was for the first time 1) validated for the analysis of all-trans-retinol, tocopherols and carotenoids, and 2) applied for the determination of tocopherols in human blood samples.

Diet quality measured by four a priori-defined diet quality indices is associated with lipid-soluble micronutrients in the Multiethnic Cohort Study (MEC)

BACKGROUND/OBJECTIVES

This study examined the long-term relation of lipid-soluble micronutrients with diet quality as assessed by four a priori-defined dietary patterns.

SUBJECTS/METHODS

In a prospective design, nutritional biomarkers (carotenoids, tocopherols, retinol, and coenzyme Q10) were measured using a validated HPLC-based assay. General linear models were applied to obtain covariate-adjusted means of biomarkers for tertiles of four a priori diet quality indices: Healthy Eating Index (HEI) 2010, Alternative HEI (AHEI) 2010, Alternate Mediterranean Diet Score (aMED), and Dietary Approaches to Stop Hypertension (DASH). For a subcohort of 8367 participants within the Multiethnic Cohort (MEC), diet was assessed by a validated quantitative food frequency questionnaire in 1993-96 and serum was collected in 2001-06.

RESULTS

Participants with the highest diet-quality scores had significantly higher serum concentrations of all carotenoids, total tocopherols, and α-tocopherol, whereas γ-tocopherol was inversely associated with diet quality. Adjusted means for the lowest vs. highest tertile of HEI 2010 were 1.2 vs. 1.5 mg/L for total carotenoids, 11.4 vs. 12.3 mg/L for total tocopherols, and 1.9 vs. 1.6 mg/L for γ-tocopherol (ptrend < 0.0001). The associations for the other dietary indices were similar; no indication for sex and ethnic differences was detected. Vegetable and fruit components were major predictors of most circulating micronutrients, but most other components were also associated.

CONCLUSIONS

Higher diet-quality scores measured by four a priori diet quality indices were significantly associated higher serum concentrations of carotenoids and α-tocopherol, whereas γ-tocopherol was inversely associated with diet quality.

Plasma, Urine, and Adipose Tissue Biomarkers of Dietary Intake Differ Between Vegetarian and Non-Vegetarian Diet Groups in the Adventist Health Study-2

BACKGROUND

Differences in food composition, nutrient intake, and various health outcomes have been reported for vegetarians and non-vegetarians in the Adventist Health Study-2 (AHS-2) cohort.

OBJECTIVE

We sought to determine whether biomarkers of dietary intake also differed between individuals classified as vegetarian (vegan, lacto-ovo-vegetarian, pesco-vegetarian, semi-vegetarian) and non-vegetarians based on patterns of consumption of meat, dairy, and eggs.

METHODS

Fasting plasma, overnight urine, and adipose tissue samples were collected from a representative subset of AHS-2 participants classified into 5 diet groups (vegan, lacto-ovo-vegetarian, pesco-vegetarian, semi-vegetarian, non-vegetarian) who also completed food-frequency questionnaires. Diet-related biomarkers including carotenoids, isoflavones, enterolactone, saturated and polyunsaturated fatty acids, and vitamins were analyzed in 840 male and female participants. Multiple linear regression was used to examine the association between diet pattern and biomarker abundance, comparing each of 4 vegetarian dietary groups to non-vegetarians, and adjusted mean values were calculated. Bonferroni correction was applied to control for multiple testing.

RESULTS

Vegans had higher plasma total carotenoid concentrations (1.6-fold, P < 0.0001), and higher excretion of urinary isoflavones (6-fold, P < 0.0001) and enterolactone (4.4-fold) compared with non-vegetarians. Vegans had lower relative abundance of saturated fatty acids including myristic, pentadecanoic, palmitic, and stearic acids (P < 0.0001). Vegans had higher linoleic acid (18:2ω-6) relative to non-vegetarians (23.3% compared with 19.1%) (P < 0.0001), and a higher proportion of total ω-3 fatty acids (2.1% compared with 1.6%) (P < 0.0001). Results overall were similar but less robust for lacto-ovo- and pesco-vegetarians. 1-Methylhistidine was 92% lower in vegans, and lower in lacto-ovo- and pesco-vegetarians by 90% and 80%, respectively, relative to non-vegetarians (P < 0.0001).

CONCLUSION

AHS-2 participants following vegan, and lacto-ovo- or pesco-vegetarian diet patterns have significant differences in plasma, urine, and adipose tissue biomarkers associated with dietary intakes compared with those who consume a non-vegetarian diet. These findings provide some validation for the prior classification of dietary groups within the AHS-2 cohort.

Validity of a Short Food Frequency Questionnaire Assessing Macronutrient and Fiber Intakes in Patients of Han Chinese Descent with Type 2 Diabetes

Few food frequency questionnaires (FFQs) have been developed to assess diet in diabetes patients. This cross-sectional study examined the validity of a 45-item FFQ assessing the intake of macronutrients against three 24-h dietary recalls (24-HDRs) in Taiwan, and compared vegetable and fruit intakes with carotenoid biomarkers. We recruited 126 adults with type 2 diabetes who completed the FFQ and three 24-HDRs administered by a registered dietitian. We measured plasma carotenoids (α-carotene, β-carotene and lutein) in 71 subjects. Partial Pearson correlation coefficients derived from the FFQs and three 24-HDRs and adjusted for energy were of 0.651, 0.587, 0.639 and 0.664 for protein, fat, carbohydrate and fiber, respectively. Cross-classification analysis revealed that 71.5⁻81% of the macronutrients and fiber were categorized into the same or adjacent quartiles by the FFQ and 24-HDRs. Bland⁻Altman plots revealed good agreement for energy/macronutrients/fiber across the range of intakes. Multiple linear regression of backward elimination revealed that tertile levels of dark- or light-colored vegetables obtained by the FFQ were significantly associated with plasma α-carotene and β-carotene, but not lutein. Fruit consumption did not correlate with carotenoid biomarkers. In conclusion, this short FFQ provided a valid assessment of macronutrients and fiber intake in type 2 diabetes patients. Vegetable consumption estimated by the FFQ corresponded to plasma α-carotene and β-carotene concentrations.

Empirically Derived Dietary Patterns in UK Adults Are Associated with Sociodemographic Characteristics, Lifestyle, and Diet Quality

The aim of this study was to examine empirical dietary patterns in UK adults and their association with sociodemographic characteristics, lifestyle factors, self-reported nutrient intake, nutrient biomarkers, and the Nutrient-based Diet Quality Score (NDQS) using National Diet and Nutrition Survey data 2008–2012 (n = 2083; mean age 49 years; 43.3% male). Four patterns explained 13.6% of the total variance: ‘Snacks, fast food, fizzy drinks’ (SFFFD), ‘Fruit, vegetables, oily fish’ (FVOF), ‘Meat, potatoes, beer’ (MPB), and ‘Sugary foods, dairy’ (SFD). ‘SFFFD’ was associated positively with: being male; smoking; body mass index (BMI); urinary sodium; intake of non-milk extrinsic sugars (NMES), fat and starch; and negatively with: age; plasma carotenoids; and NDQS. ‘FVOF’ was associated positively with: being non-white; age; income; socioeconomic classification (National Statistics Socio-economic Classifications; NSSEC); plasma carotenoids; intake of non-starch polysaccharides and polyunsaturated fatty acids. It was negatively associated with: being male, smoking, BMI, urinary sodium, intake of saturated fat; and NMES and NDQS. Whilst the patterns explained only 13.6% of the total variance, they were associated with self-reported nutrient intake, biomarkers of nutrient intake, sociodemographic and lifestyle variables, and the NDQS. These findings provide support for dietary patterns analyses as a means of exploring dietary intake in the UK population to inform public health nutrition policy and guidance.

Association between Diet-Quality Scores, Adiposity, Total Cholesterol and Markers of Nutritional Status in European Adults: Findings from the Food4Me Study

Diet-quality scores (DQS), which are developed across the globe, are used to define adherence to specific eating patterns and have been associated with risk of coronary heart disease and type-II diabetes. We explored the association between five diet-quality scores (Healthy Eating Index, HEI; Alternate Healthy Eating Index, AHEI; MedDietScore, MDS; PREDIMED Mediterranean Diet Score, P-MDS; Dutch Healthy Diet-Index, DHDI) and markers of metabolic health (anthropometry, objective physical activity levels (PAL), and dried blood spot total cholesterol (TC), total carotenoids, and omega-3 index) in the Food4Me cohort, using regression analysis. Dietary intake was assessed using a validated Food Frequency Questionnaire. Participants (n = 1480) were adults recruited from seven European Union (EU) countries. Overall, women had higher HEI and AHEI than men (p < 0.05), and scores varied significantly between countries. For all DQS, higher scores were associated with lower body mass index, lower waist-to-height ratio and waist circumference, and higher total carotenoids and omega-3-index (p trends < 0.05). Higher HEI, AHEI, DHDI, and P-MDS scores were associated with increased daily PAL, moderate and vigorous activity, and reduced sedentary behaviour (p trend < 0.05). We observed no association between DQS and TC. To conclude, higher DQS, which reflect better dietary patterns, were associated with markers of better nutritional status and metabolic health.

Capturing health and eating status through a nutritional perception screening questionnaire (NPSQ9) in a randomised internet-based personalised nutrition intervention: the Food4Me study

BACKGROUND

National guidelines emphasize healthy eating to promote wellbeing and prevention of non-communicable diseases. The perceived healthiness of food is determined by many factors affecting food intake. A positive perception of healthy eating has been shown to be associated with greater diet quality. Internet-based methodologies allow contact with large populations. Our present study aims to design and evaluate a short nutritional perception questionnaire, to be used as a screening tool for assessing nutritional status, and to predict an optimal level of personalisation in nutritional advice delivered via the Internet.

METHODS

Data from all participants who were screened and then enrolled into the Food4Me proof-of-principle study (n = 2369) were used to determine the optimal items for inclusion in a novel screening tool, the Nutritional Perception Screening Questionnaire-9 (NPSQ9). Exploratory and confirmatory factor analyses were performed on anthropometric and biochemical data and on dietary indices acquired from participants who had completed the Food4Me dietary intervention (n = 1153). Baseline and intervention data were analysed using linear regression and linear mixed regression, respectively.

RESULTS

A final model with 9 NPSQ items was validated against the dietary intervention data. NPSQ9 scores were inversely associated with BMI (β = -0.181, p < 0.001) and waist circumference (Β = -0.155, p < 0.001), and positively associated with total carotenoids (β = 0.198, p < 0.001), omega-3 fatty acid index (β = 0.155, p < 0.001), Healthy Eating Index (HEI) (β = 0.299, p < 0.001) and Mediterranean Diet Score (MDS) (β = 0. 279, p < 0.001). Findings from the longitudinal intervention study showed a greater reduction in BMI and improved dietary indices among participants with lower NPSQ9 scores.

CONCLUSIONS

Healthy eating perceptions and dietary habits captured by the NPSQ9 score, based on nine questionnaire items, were associated with reduced body weight and improved diet quality. Likewise, participants with a lower score achieved greater health improvements than those with higher scores, in response to personalised advice, suggesting that NPSQ9 may be used for early evaluation of nutritional status and to tailor nutritional advice.

TRIAL REGISTRATION

NCT01530139 .

Mediterranean Diet Adherence and Genetic Background Roles within a Web-Based Nutritional Intervention: The Food4Me Study

Mediterranean Diet (MedDiet) adherence has been proven to produce numerous health benefits. In addition, nutrigenetic studies have explained some individual variations in the response to specific dietary patterns. The present research aimed to explore associations and potential interactions between MedDiet adherence and genetic background throughout the Food4Me web-based nutritional intervention. Dietary, anthropometrical and biochemical data from volunteers of the Food4Me study were collected at baseline and after 6 months. Several genetic variants related to metabolic risk features were also analysed. A Genetic Risk Score (GRS) was derived from risk alleles and a Mediterranean Diet Score (MDS), based on validated food intake data, was estimated. At baseline, there were no interactions between GRS and MDS categories for metabolic traits. Linear mixed model repeated measures analyses showed a significantly greater decrease in total cholesterol in participants with a low GRS after a 6-month period, compared to those with a high GRS. Meanwhile, a high baseline MDS was associated with greater decreases in Body Mass Index (BMI), waist circumference and glucose. There also was a significant interaction between GRS and the MedDiet after the follow-up period. Among subjects with a high GRS, those with a high MDS evidenced a highly significant reduction in total carotenoids, while among those with a low GRS, there was no difference associated with MDS levels. These results suggest that a higher MedDiet adherence induces beneficial effects on metabolic outcomes, which can be affected by the genetic background in some specific markers.

The effect of under-reporting of energy intake on dietary patterns and on the associations between dietary patterns and self-reported chronic disease in women aged 50–69 years

The aim of this cross-sectional study was to investigate whether under-reporting of energy intake affects derived dietary patterns and the association between dietary patterns and self-reported chronic disease. Diets of 6204 women aged 50–69 years participating in the Norwegian Breast Cancer Screening Program were assessed using a 253-item FFQ. We identified dietary patterns using principal component analysis. According to the revised Goldberg cut-off method, women with a ratio of reported energy intake:estimated BMR<1·10 were classified as low energy reporters (n 1133, 18 %). We examined the associations between dietary patterns and self-reported chronic diseases by log-binomial regression, and the results are presented as prevalence ratios (PR) and CI. ‘Prudent’, ‘Western’ and ‘Continental’ dietary patterns were identified among all reporters and plausible reporters. The PR expressing the associations between the ‘Western’ and ‘Prudent’ dietary pattern scores and self-reported chronic diseases were consistently highest among plausible reporters except for joint/muscle/skeletal disorders. The largest difference in PR among plausible v. all reporters was found for the association between the ‘Prudent’ pattern and diabetes (PR for highest v. lowest tertile: PRall reporters 2·16; 95 % CI 1·50, 3·13; Ptrend<0·001; PRplausible reporters 2·86; 95 % CI 1·81, 4·51; Ptrend<0·001). In conclusion, our results suggest that under-reporting can result in systematic error that can affect the association between dietary pattern and disease. In studies of dietary patterns, investigators ought to consider reporting effect estimates both for all individuals and for plausible reporters.

Dietary patterns of women aged 50-69 years and associations with nutrient intake, sociodemographic factors and key risk factors for non-communicable diseases

OBJECTIVE

In women, the risk for non-communicable diseases increases after menopause. We aimed to identify major dietary patterns and study their associations with nutrient intake, sociodemographic factors and risk factors for non-communicable diseases among women aged 50-69 years.

DESIGN

A cross-sectional study. Food intake was recorded by a 253-item FFQ. Dietary patterns were identified using principal component analysis. The associations between the dietary patterns and nutrients were described by Pearson's correlation coefficients and multiple regression analysis was used to examine the associations between the dietary patterns and age, education, BMI, physical activity and smoking.

SETTING

The Norwegian Breast Cancer Screening Programme.

SUBJECTS

Women (n 6298) aged 50-69 years.

RESULTS

Three dietary patterns were identified: 'Prudent', 'Western' and 'Continental'. Adherence to the 'Prudent' pattern was related to older age, higher education, higher BMI, more physical activity (P trend<0·001) and being a non-smoker (P<0·001). Adherence to the 'Western' pattern was related to older age, lower education, higher BMI, less physical activity (0·001≤P trend≤0·006) and lower alcohol intake (r =-0·28). Adherence to the 'Continental' pattern was related to younger age, higher education, higher BMI, less physical activity, (P trend<0·001), being a smoker (P<0·001) and higher alcohol intake (r=0·36).

CONCLUSIONS

Three distinct dietary patterns were identified. High adherence to a 'Prudent' pattern was associated with a healthy lifestyle, while high adherence to a 'Western' or 'Continental' pattern was associated with an unhealthy lifestyle. These findings are valuable knowledge for health authorities when forming strategies to promote a healthier lifestyle among women.