Data-driven Dietary Patterns Research Articles

Dietary patterns among European children and their association with adiposity-related outcomes: a multi-country study.

Children's diets in school-age are inherently unhealthy, with few meeting dietary recommendations. Yet, little is known about similarities and differences on dietary patterns across countries and their association with obesity. We aimed to derive dietary patterns in childhood and explore their association with adiposity-related outcomes in childhood and adolescence. This study included data from six European countries (Spain, France, UK, Greece, Lithuania and Norway) during childhood (n = 1597) and adolescence (n = 803). Using a food frequency questionnaire, we derived data-driven dietary patterns through exploratory factor analyses and calculated the Mediterranean KIDMED index. We assessed body mass index z-score (zBMI), fat mass proportion and waist-to-height ratio at both visits. Associations were estimated using generalized linear regressions, adjusted for key-confounders. "Meat", "Dairy", "Western", "Healthy" and "Sweets and fats" dietary patterns were derived. Norwegian children showed better diet quality, with higher consumption of fruits and vegetables, and highest "Healthy pattern" adherence, and Lithuanian children, the worst, with higher sweets consumption, and highest "Western pattern" adherence. Children with lower intake of healthy foods (vegetables, fruits, fish) tended to have higher adiposity, e.g., children with average or low "Healthy pattern" adherence (vs. high) had higher fat mass proportion in childhood (average: β (95% CI) 1.44 (0.48; 2.39), low: 1.10 (0.09; 2.12)). Low adherence to a "Healthy pattern" (vs. high) was associated with increased adolescent zBMI, and child and adolescent waist-to-height ratio. Low "Dairy pattern" adherence (vs. high), was associated with lower zBMI and fat mass in childhood, but not in adolescence. No significant associations were seen with the KIDMED index. Many European children have poor diets and a low adherence to a healthy diet pattern may be of concern for adiposity-related outcomes. Assessment of children's dietary patterns can help tailor dietary advice and provide support for families aiming to prevent future excess weight gain.

Unveiling the Roles of Immune Function and Inflammation in the Associations Between Dietary Patterns and Incident Type 2 Diabetes

Objective To investigate the associations between data-driven dietary patterns, immune function, and incident type 2 diabetes (T2D) and the mediating effects of immune function. Methods This study included 375,665 participants without diabetes at baseline in the UK Biobank study. Dietary patterns were derived through principal component analysis of food frequency questionnaire data. Immune function was assessed using 14 individual inflammatory markers and an integrated low-grade inflammation score (INFLA-score). Cox proportional hazard models were used to estimate the associations of dietary patterns or immune function with incident T2D. Linear regressions were used to estimate the associations of dietary patterns with immune function. Mediating effects of immune function were quantified. Results During a median 14.6-year follow-up, 13,932 participants developed T2D. Four dietary patterns were identified: prudent diet (high in whole grains, vegetables, fruits, fish), wheat/dairy/eggs restrictive diet (limiting these foods), meat-based diet (high in red/processed meat, salt), and full-cream dairy diet (preference for full cream milk or dairy products). The prudent diet was negatively (HRQ4 vs Q1, 0.69 [95% CI, 0.65–0.72]), while the wheat/dairy/eggs restrictive diet (HRQ4 vs Q1, 1.08 [95% CI, 1.03–1.13]), meat-based diet (HRQ4 vs Q1, 1.12 [95% CI, 1.06–1.17]), and full-cream dairy diet (HRQ4 vs Q1, 1.08 [95% CI, 1.03–1.12]) were positively associated with incident T2D (all p for trend ≤0.04). The prudent diet was negatively and the full-cream dairy diet was positively associated with most inflammatory markers. Most inflammatory markers, especially INFLA-score (HR, 1.18 [95% CI, 1.16–1.20]), were positively associated with incident T2D. INFLA-score mediated 13% of the association with incident T2D for the prudent diet and 34% for the full-cream dairy diet. Conclusions This study identified four distinct dietary patterns and a range of inflammatory markers associated with incident T2D. A notable proportion of the associations between dietary patterns and T2D was mediated by immune function.

A Western Dietary Pattern during Pregnancy is Associated with Neurodevelopmental Disorders in Childhood and Adolescence.

Despite the high prevalence of neurodevelopmental disorders, there is a notable gap in clinical studies exploring the impact of maternal diet during pregnancy on child neurodevelopment. This observational clinical study examined the association between pregnancy dietary patterns and neurodevelopmental disorders, as well as their symptoms, in a prospective cohort of 10-year-old children (n=508). Data-driven dietary patterns were derived from self-reported food frequency questionnaires. A Western dietary pattern in pregnancy (per SD change) was significantly associated with attention-deficit / hyperactivity disorder (ADHD) (OR 1.66 [1.21 - 2.27], p=0.002) and autism diagnosis (OR 2.22 [1.33 - 3.74], p=0.002) and associated symptoms (p<0.001). Findings for ADHD were validated in three large (n=59725, n=656, n=348), independent mother-child cohorts. Objective blood metabolome modelling at 24 weeks gestation identified 15 causally mediating metabolites which significantly improved ADHD prediction in external validation. Temporal analyses across five blood metabolome timepoints in two independent mother-child cohorts revealed that the association of Western dietary pattern metabolite scores with neurodevelopmental outcomes was consistently significant in early to mid-pregnancy, independent of later child timepoints. These findings underscore the importance of early intervention and provide robust evidence for targeted prenatal dietary interventions to prevent neurodevelopmental disorders in children.

Dietary pattern and diversity analysis using DietDiveR in R: a cross-sectional evaluation in the National Health and Nutrition Examination Survey

BackgroundThere are few resources available for researchers aiming to conduct 24-h dietary record and recall analysis using R. ObjectivesWe aimed to develop DietDiveR, which is a toolkit of functions written in R for the analysis of recall or record data collected with the Automated Self-Administered 24-h Dietary Assessment Tool or 2-d 24-h dietary recall data from the National Health and Nutrition Examination Survey (NHANES). The R functions are intended for food and nutrition researchers who are not computational experts. MethodsDietDiveR provides users with functions to 1) clean dietary data, 2) analyze 24-h dietary intakes in relation to other study-specific metadata variables, 3) visualize percentages of energy intake from macronutrients, 4) perform principal component analysis or k-means clustering to group participants by similar data-driven dietary patterns, 5) generate foodtrees based on the hierarchical food group information for food items consumed, 6) perform principal coordinate analysis taking food grouping information into account, and 7) calculate diversity metrics for overall diet and specific food groups. DietDiveR includes a self-paced tutorial on a website (https://computational-nutrition-lab.github.io/DietDiveR/). As a demonstration, we applied DietDiveR to a demonstration data set and data from NHANES 2015–2016 to derive a dietary diversity measure of nuts, seeds, and legumes consumption. ResultsAdult participants in the NHANES 2015–2016 cycle were grouped depending on the diversity in their mean consumption of nuts, seeds, and legumes. The group with the highest diversity in nuts, seeds, and legumes consumption had 3.8 cm lower waist circumference (95% confidence interval: 1.0, 6.5) than those who did not consume nuts, seeds, and legumes. ConclusionsDietDiveR enables users to visualize dietary data and conduct data-driven dietary pattern analyses using R to answer research questions regarding diet. As a demonstration of this toolkit, we explored the diversity of nuts, seeds, and legumes consumption to highlight some of the ways DietDiveR can be used for analyses of dietary diversity.

Dietary patterns, untargeted metabolite profiles and their association with colorectal cancer risk

We investigated data-driven and hypothesis-driven dietary patterns and their association to plasma metabolite profiles and subsequent colorectal cancer (CRC) risk in 680 CRC cases and individually matched controls. Dietary patterns were identified from combined exploratory/confirmatory factor analysis. We assessed association to LC–MS metabolic profiles by random forest regression and to CRC risk by multivariable conditional logistic regression. Principal component analysis was used on metabolite features selected to reflect dietary exposures. Component scores were associated to CRC risk and dietary exposures using partial Spearman correlation. We identified 12 data-driven dietary patterns, of which a breakfast food pattern showed an inverse association with CRC risk (OR per standard deviation increase 0.89, 95% CI 0.80–1.00, p = 0.04). This pattern was also inversely associated with risk of distal colon cancer (0.75, 0.61–0.96, p = 0.01) and was more pronounced in women (0.69, 0.49–0.96, p = 0.03). Associations between meat, fast-food, fruit soup/rice patterns and CRC risk were modified by tumor location in women. Alcohol as well as fruit and vegetables associated with metabolite profiles (Q2 0.22 and 0.26, respectively). One metabolite reflecting alcohol intake associated with increased CRC risk, whereas three metabolites reflecting fiber, wholegrain, and fruit and vegetables associated with decreased CRC risk.

Adherence to Data-Driven Dietary Patterns and Lung Cancer Risk: A Systematic Review and Dose-Response Meta-Analysis.

The effect of dietary patterns on lung cancer risk is currently debated. In this study, we evaluated the association between different "a posteriori" dietary patterns and lung cancer risk. The search was carried out (February 2023) through Scopus, Web of Science, and PubMed databases. Meta-analysis was performed by a random-effects model using risk values (RR and OR) extracted from the 12 selected studies. Two main dietary patterns were identified and named "Western/meat" and "Healthy/prudent". The highest adherence to the "Western/meat" dietary pattern significantly increased the lung cancer risk (OR = 1.39; 95% CI: 1.17-1.65; p = 0.0002) while the highest adherence to the "Healthy/prudent" pattern reduced it (OR = 0.65; 95% CI: 0.51-0.83; p = 0.001). A linear trend between both dietary patterns and lung cancer risk was observed. However, a statistically significant inverse dose-response trend was found only for the "Healthy/prudent" dietary pattern (regression coefficient = -0.0031, p = 0.003). Subgroup analyses showed that the "Western/meat" pattern significantly increased the lung cancer risk in former (n = 4) (OR = 1.93, 95% CI: 1.11-3.36) and current smokers (n = 7) (OR = 1.35, 95% CI: 1.06-1.71). Similarly, the "Healthy/prudent" pattern exerts a protective effect on former (n = 4) (OR = 0.61, 95% CI: 0.44-0.85) and current smokers (n = 8) (OR = 0.64, 95% CI: 0.46-0.88). For both dietary patterns, no significant effect was observed on never-smokers.

Identifying Novel Data-Driven Dietary Patterns via Dimensionality Reduction and Associations with Socioeconomic Profile and Health Outcomes in Ireland.

Dietary patterns and body mass index (BMI) play a significant role in the development of noncommunicable diseases (NCDs), which are the leading cause of mortality worldwide, including Ireland. A cross-sectional survey was conducted across Ireland to collate respondents' socioeconomic profiles, health status, and dietary patterns with a representative sample size of 957 adult respondents. Principal component analysis (PCA) and statistical analyses were subsequently employed. To the author's knowledge, this is the first study to use recent (2021) nationally representative data to characterise dietary patterns in Ireland via dimensionality reduction. Five distinct dietary patterns ("meat-focused", "dairy/ovo-focused", "vegetable-focused", "seafood-focused", and "potato-focused") were identified and statistically characterised. The "potato-focused" group exhibited the highest mean BMI (26.88 kg/m2), while the "vegetable-focused" group had the lowest (24.68 kg/m2). "Vegetable-focused" respondents were more likely to be associated with a categorically healthy BMI (OR = 1.90) and urban residency (OR = 2.03). Conversely, "meat-focused" respondents were more likely to have obesity (OR = 1.46) and rural residency (OR = 1.72) along with the "potato-focused" group (OR = 2.15). Results show that data-derived dietary patterns may better predict health outcomes than self-reported dietary patterns, and transitioning to diets focusing on vegetables, seafood, and lower meat consumption may improve health.

Dietary Patterns and Risk of Lung Cancer: A Systematic Review and Meta-Analyses of Observational Studies.

Previous literature reviews summarized the associations between individual foods or food groups and lung cancer risk, but the relationship between dietary patterns and lung cancer riskhas received less attention. We conducted a systematic review and meta-analyses of observational studies on the associations between dietary patterns and lung cancerrisk. PubMed, Embase, and Web of Science were systematically searched from inception to February 2023. Random-effects models were used to pool relative risks (RR) on associations with at least two studies. Twelve studies reported on data-driven dietary patterns, and 17 studies reported on a priori dietary patterns. A prudent dietary pattern (high in vegetables, fruit, fish, and white meat) tended to be associated with a lower risk of lung cancer (RR = 0.81, 95% confidence interval [CI] = 0.66-1.01, n = 5). In contrast, Western dietary patterns, characterized by higher intakes of refined grains and red and processed meat, were significantly positively associated with lung cancer (RR = 1.32, 95% CI = 1.08-1.60, n = 6). Healthy dietary scores were consistently associated with a lower risk of lung cancer (Healthy Eating Index [HEI]: RR = 0.87, 95% CI = 0.80-0.95, n = 4; Alternate HEI: RR = 0.88, 95% CI = 0.81-0.95, n = 4; Dietary Approaches to Stop Hypertension: RR = 0.87, 95% CI = 0.77-0.98, n = 4; Mediterranean diet: RR = 0.87, 95% CI = 0.81-0.93, n = 10) while the dietary inflammatory index was associated with a higher risk of lung cancer (RR = 1.14, 95% CI = 1.07-1.22, n = 6). Our systematicreview indicates dietary patterns characterized by a higher intake of vegetables and fruits, a lower intake of animal products, and anti-inflammation may be associated with a reduced risk of lung cancer.

Associations between dietary patterns and serum uric acid concentrations in children and adolescents: a cross-sectional study.

The serum uric acid (SUA) concentrations in children and adolescents in southeast coastal China are generally high. The relationship between diet and SUA in children and adolescents remains unclear. The objective of the study was to assess the associations between data-driven dietary patterns with SUA concentrations and hyperuricemia in Chinese children and adolescents and to explore the role of food components. This study involved 3383 participants aged 9 to 17 years from a representative nutrition and growth survey conducted in Shenzhen, a southeast coastal city in China. The dietary intake data, obtained from a validated food frequency questionnaire, were categorized into 19 food groups for factor analysis to derive dietary patterns. Weighted least squares regression was performed to examine the associations between dietary patterns and SUA concentrations, logistic regression was used to analyze the relationship between dietary patterns and hyperuricemia, and the relationship between food groups and food components with SUA concentrations was further analyzed. The potential dietary factors contributing to the associations between dietary patterns and SUA concentrations were explored by adjusting various food components. Six dietary patterns were identified by factor analysis, including an ultra-processed diet, plant-based nutritious diet, meat-based diet, soup/seafood/egg diet, vegetarian diet, and mushroom/animal organ diet. After adjusting for confounders, the meat-based diet exhibited a positive correlation with SUA concentrations (β = 4.89; 95% confidence interval (CI): 0.60-9.18; P = 0.03), while the vegetarian diet could reduce the risk of hyperuricemia (odds ratio = 0.88; 95% CI: 0.80-0.98; P = 0.02). In addition, dietary intake of poultry (g per d) (β = 0.09, 95% CI: 0.02, 0.16, P = 0.02), animal organs, blood (g per d) (β = 0.32, 95% CI: 0.12, 0.51, P = 0.002) and hypoxanthine (mg per d) (β = 0.03, 95% CI: 0.01, 0.06, P = 0.02) showed a significantly positive correlation with SUA concentrations, while that of vegetables (g per d) (β = -0.02, 95% CI: -0.03, -0.01, P = 0.03) showed a significantly negative correlation. In summary, for children and adolescents, it is recommended to increase vegetable intake and reduce animal-based food intake in order to control SUA concentration and prevent hyperuricemia. This study was registered at the China Clinical Trials Registry (ChiCTR2100051722).

Long-Term Dietary Patterns Are Reflected in the Plasma Inflammatory Proteome of Patients with Inflammatory Bowel Disease.

Diet plays an important role in the development and progression of inflammatory bowel disease (IBD, comprising Crohn’s disease (CD) and ulcerative colitis (UC)). However, little is known about the extent to which different diets reflect inflammation in IBD beyond measures such as faecal calprotectin or C-reactive protein. In this study, we aimed to unravel associations between dietary patterns and circulating inflammatory proteins in patients with IBD. Plasma concentrations of 73 different inflammation-related proteins were measured in 454 patients with IBD by proximity extension assay (PEA) technology. Food frequency questionnaires (FFQ) were used to assess habitual diet. Principal component analysis (PCA) was performed to extract data-driven dietary patterns. To identify associations between dietary patterns and plasma proteins, we used general linear models adjusting for age, sex, BMI, plasma storage time, smoking, surgical history and medication use. Stratified analyses were performed for IBD type, disease activity and protein intake. A high-sugar diet was strongly inversely associated with fibroblast growth factor-19 (FGF-19) independent of IBD type, disease activity, surgical history and deviance from recommended protein intake (false discovery rate (FDR) < 0.05). Conversely, a Mediterranean-style pattern was associated with higher FGF-19 levels (FDR < 0.05). A pattern characterised by high alcohol and coffee intake was positively associated with CCL11 (eotaxin-1) levels and with lower levels of IL-12B (FDR < 0.05). All results were replicated in CD, whereas only the association with FGF-19 was significant in UC. Our study suggests that dietary habits influence distinct circulating inflammatory proteins implicated in IBD and supports the pro- and anti-inflammatory role of diet. Longitudinal measurements of inflammatory markers, also postprandial, are needed to further elucidate the diet–inflammation relationship.

Diet Quality and Risk of Parkinson's Disease: The Rotterdam Study.

The Mediterranean diet has been associated with the risk of Parkinson’s disease (PD), but limited research has been performed on other dietary patterns. We studied the relationship between overall diet quality and PD risk in the general population. We included 9414 participants from the Rotterdam Study, a prospective population-based study in the Netherlands. Diet was defined using a Dutch diet quality score, a Mediterranean diet score and data-driven dietary patterns constructed with principal component analysis (PCA). During an average follow-up of 14.1 years, PD was diagnosed in 129 participants. We identified a ‘Prudent’, ‘Unhealthy’ and ‘Traditional Dutch’ pattern from the PCA. We found a possible association between the Mediterranean diet (Hazard ratio (HR) per standard deviation (SD) 0.89 (95% confidence interval (CI) 0.74–1.07)), the ‘Prudent’ pattern (HR per SD 0.81 (95% CI 0.61–1.08)) and the risk of PD. However, no associations with PD risk were found for the Dutch diet quality score (HR per SD 0.93 (95% CI 0.77–1.12)), the ‘Unhealthy’ pattern (HR per SD 1.05 (95% CI 0.85–1.29)) or the ‘Traditional Dutch’ pattern (HR per SD 0.90 (95% CI 0.69–1.17)). In conclusion, our results corroborate previous findings of a possible protective effect of the Mediterranean diet. Further research is warranted to study the effect of other dietary patterns on PD risk.

Associations between mother-child dyad dietary patterns and child anthropometric measures among 6-year-old children.

The goals of this study were to study relationships between maternal and children's dietary patterns (DPs) and to assess how children's DP was associated with child anthropometry. This cross-sectional study included 788 pairs of 6-year-old girls and mothers in health centers in Tehran, Iran. Information on dietary intake was collected with a 168-item food frequency questionnaire. Principal component factor analysis was performed to label different data-driven dietary patterns. Three different binary logistic regression models were used to evaluate the associations between child's DPs and child anthropometry. A positive correlation was found between all maternal patterns and child's Western DP (p < 0.001). Maternal prudent and Western DPs were correlated with child's high-protein DP (p < 0.001). Children's high-protein DP was negatively correlated with maternal high fat DP (p < 0.001). Maternal prudent and high fat DPs were correlated with prudent DP in children (p < 0.001). In adjusted models, a child being in the highest compared to the first quartile of the high-protein DP was associated with decreased odds of underweight and wasting (OR 0.43; 95% CI 0.23-0.80).Conclusion: The present study showed inverse associations between a high-protein DP in children and being underweight and wasted. Also, a positive correlation was found between all maternal DPs and children's Western DPs. This correlation should be taken into account while managing child nutrition by means of educating parents on the influence of their own dietary pattern on their children. Moreover, getting enough protein through a balanced diet should be considered in children. What is Known: • Some research exists on the intake of specific foods in relation to risk of abnormal growth in children. • Less is known about the relationship between mothers' and children's food intake. What is New: • Better adherence to a high-protein dietary pattern was significantly associated with lower risk of being both underweight and wasted. • This study suggests that correlation between mothers' and their children's dietary patterns exists, which should be taken into consideration when managing child nutrition.

Dietary Patterns and Risk Factors of Frailty in Lebanese Older Adults.

Factors associated with frailty, particularly dietary patterns, are not fully understood in Mediterranean countries. This study aimed to investigate the association of data-driven dietary patterns with frailty prevalence in older Lebanese adults. We conducted a cross-sectional national study that included 352 participants above 60 years of age. Sociodemographic and health-related data were collected. Food frequency questionnaires were used to elaborate dietary patterns via the K-mean cluster analysis method. Frailty that accounted for 15% of the sample was twice as much in women (20%) than men (10%). Identified dietary patterns included a Westernized-type dietary pattern (WDP), a high intake/Mediterranean-type dietary pattern (HI-MEDDP), and a moderate intake/Mediterranean-type dietary pattern (MOD-MEDDP). In the multivariate analysis, age, waist to height ratio, polypharmacy, age-related conditions, and WDP were independently associated with frailty. In comparison to MOD-MEDDP, and after adjusting for covariates, adopting a WDP was strongly associated with a higher frailty prevalence in men (OR = 6.63, 95% (CI) (1.82–24.21) and in women (OR = 11.54, 95% (CI) (2.02–65.85). In conclusion, MOD-MEDDP was associated with the least prevalence of frailty, and WDP had the strongest association with frailty in this sample. In the Mediterranean sample, a diet far from the traditional one appears as the key deleterious determinant of frailty.

Does diet map with mortality? Ecological association of dietary patterns with chronic disease mortality and its spatial dependence in Switzerland

We investigated the associations between dietary patterns and chronic disease mortality in Switzerland using an ecological design and explored their spatial dependence, i.e. the tendency of near locations to present more similar and distant locations to present more different values than randomly expected. Data of the National Nutrition Survey menuCH (n 2057) were used to compute hypothesis- (Alternate Healthy Eating Index (AHEI)) and data-driven dietary patterns. District-level standardised mortality ratios (SMR) were calculated using the Swiss Federal Statistical Office mortality data and linked to dietary data geographically. Quasipoisson regression models were fitted to investigate the associations between dietary patterns and chronic disease mortality; Moran's I statistics were used to explore spatial dependence. Compared with the first, the fifth AHEI quintile (highest diet quality) was associated with district-level SMR of 0·95 (95 % CI 0·93, 0·97) for CVD, 0·91 (95 % CI 0·88, 0·95) for ischaemic heart disease (IHD), 0·97 (95 % CI 0·95, 0·99) for stroke, 0·99 (95 % CI 0·98, 1·00) for all-cancer, 0·98 (95 % CI 0·96, 0·99) for colorectal cancer and 0·93 (95 % CI 0·89, 0·96) for diabetes. The Swiss traditional and Western-like patterns were associated with significantly higher district-level SMR for CVD, IHD, stroke and diabetes (ranging from 1·02 to 1·08) compared with the Prudent pattern. Significant global and local spatial dependence was identified, with similar results across hypothesis- and data-driven dietary patterns. Our study suggests that dietary patterns partly contribute to the explanation of geographic disparities in chronic disease mortality in Switzerland. Further analyses including spatial components in regression models would allow identifying regions where nutritional interventions are particularly needed.

Data-Driven Dietary Patterns, Nutrient Intake and Body Weight Status in a Cross-Section of Singaporean Children Aged 6–12 Years

Pattern analysis of children’s diet may provide insights into chronic disease risk in adolescence and adulthood. This study aimed to assess dietary patterns of young Singaporean children using cluster analysis. An existing dataset included 15,820 items consumed by 561 participants (aged 6–12 years) over 2 days of dietary recall. Thirty-seven food groups were defined and expressed as a percentage contribution of total energy. Dietary patterns were identified using k-means cluster analysis. Three clusters were identified, “Western”, “Convenience” and “Local/hawker”, none of which were defined by more prudent dietary choices. The “Convenience” cluster group had the lowest total energy intake (mean 85.8 ± SD 25.3% of Average Requirement for Energy) compared to the other groups (95.4 ± 25.9% for “Western” and 93.4 ± 25.3% for “Local/hawker”, p < 0.001) but also had the lowest calcium intake (66.3 ± 34.7% of Recommended Dietary Allowance), similar to intake in the “Local/hawker” group (69.5 ± 38.9%) but less than the “Western” group (82.8 ± 36.1%, p < 0.001). These findings highlight the need for longitudinal analysis of dietary habit in younger Singaporeans in order to better define public health messaging targeted at reducing risk of major noncommunicable disease.

Data-Driven Dietary Patterns and Diet Quality Scores: Reproducibility and Consistency in Sex and Age Subgroups of Poles Aged 15–65 Years

This study aimed to assess: (i) the test–retest reproducibility of identification of data-driven dietary patterns (DPs) derived using a Principal Component Analysis (PCA) and hypothesis-driven DPs (diet quality scores); (ii) the consistency of data-driven DPs with diet quality scores in sex and age subgroups of Poles aged 15–65 years. The study involved 504 subjects (55.6% of females). Data on food consumption frequency (33 food items) were collected twice with a two-week interval using the Dietary Habits and Nutrition Beliefs Questionnaire (KomPAN®) in a self-administered version (test and retest). Two major data-driven DPs (‘Prudent’ and ‘Western’) were identified in the total sample, sex groups and four age groups separately from test and retest data. Two diet quality scores were analysed: Pro-Healthy-Diet-Index-10 (pHDI-10) and Non-Healthy-Diet-Index-14 (nHDI-14). Tucker’s congruence coefficient indicated fair-to-good similarity of data-driven DPs between test and retest for all study subgroups, except for males. Across study subgroups, the intraclass correlation coefficient (ICC) between the test and retest ranged from 0.56 to 0.86 for ‘Prudent’ DP and 0.57 to 0.82 for ‘Western’ DP, with the lowest values in males. The ICC (test vs. retest) ranged from 0.84 to 0.88 for pHDI-10 and 0.75 to 0.88 for nHDI-14. Comparing the data-driven DPs and diet quality scores, the Spearman’s correlations ranged from 0.63 to 0.93 between ‘Prudent’ DP and pHDI-10, and from 0.60 to 0.81 between ‘Western’ DP and nHDI-14. The test–retest reproducibility of data-driven DPs and diet quality scores and their consistency were acceptable in most of the study subgroups, with a tendency to be higher for pro-health than unhealthy DPs. Data-driven DPs were more reproducible in females than males. The reproducibility of diet quality scores tended to be better in males than females and was the highest in 25–44-year-olds. The KomPAN® questionnaire can be recommended to use data-driven DPs and diet quality scores to describe the habitual diet in people aged 15–65 years.

Association between Dietary Patterns and Cardiometabolic Risks among Older Adult Males in Sichuan Province, China: A Cross-sectional Study

Objective: This study aims to identify data-driven dietary patterns and find out the relationship of dietary patterns with different cardiometabolic risks including overweight/obesity, dyslipidemia or high blood pressure (HBP) among older adult males (aged ≥65 years old) residents (>10 years) of Sichuan, Southwestern China. Methods: This cross-sectional study investigated the relationships of dietary patterns with cardiometabolic risks in older adult males (n=1136) aged ≥65 years old referred to the Public Hospital in Sichuan Province, China. A validated semi-quantitative food frequency questionnaire (SFFQ) was used to investigate the correlations between the animal-based and processed food dietary (pattern 1), balanced dietary (pattern 2), and Ovo-Lacto Vegetarian dietary (pattern 3) and different cardiometabolic risks. The correlations between dietary patterns and the laboratory tests were calculated. Results: The animal-based and processed food, balanced, and Ovo-Lacto Vegetarian dietary patterns accounted for 14.83%, 14.36% and 11.86% of the variance, respectively. The Chi-Square test showed the dietary patterns were associated with triglycerides (TG) (P < 0.001), total cholesterol (TC), Systolic blood pressure (SBP), and body mass index (BMI). Adjusted logistic regression analysis showed the animal-based and processed food dietary pattern was positively associated with overweight/obesity (OR: 3.25, 95% CI: 1.94, 5.46) and dyslipidemia (OR: 3.53, 95% CI: 2.00, 6.22). The balanced dietary pattern was negatively associated with overweight/obesity (OR: 0.51, 95% CI: 0.36, 0.72), dyslipidemia (OR: 0.50, 95% CI: 0.35, 0.75) and HBP (OR: 0.54, 95% CI: 0.38, 0.77). The Ovo-Lacto Vegetarian dietary pattern was negatively associated with dyslipidemia (OR: 0.56, 95% CI: 0.39, 0.81) and hyperuricemia (OR: 0.56, 95% CI: 0.39, 0.79). No statistically significant relationship was found between the three dietary patterns and impaired fasting glucose (P: 0.05). Conclusions: Elderly males in Sichuan Province with overweight/obesity, dyslipidemia and high blood pressure seem to have adopted different dietary patterns.

The associations between dietary patterns and cardiovascular risk factors among adults: A cross-sectional study

Cardiovascular diseases (CVDs) are the major causes of death, worldwide. Although for decades the associations between individual foods and nutrients and CVDs have been investigated, little attention has been paid to dietary patterns. Therefore, this study was conducted to examine the association between dietary patterns and CVD risk factors among Iranian adults. This cross-sectional study was performed on 236 adults who attended public health centers. Dietary intakes were collected using a valid food frequency questionnaire. Sociodemographic characteristics, anthropometric measures, and biochemical biomarkers were measured using standardized methods. Dietary patterns derived using the factor analysis. Logistic regression assessed the odds of CVD risk factors across tertiles of data-driven dietary patterns. We identified three dietary patterns. After adjusting for possible confounders, we observed that participants in the third category of the healthy dietary pattern (HDP) had lower odds of low HDL-C (OR=0.26; 95% CI: 0.10-0.64) compared to those in the first category. Adherence to the mixed pattern was associated with increased odds of high serum TC in men only (OR=3.69; 95% CI: 1.06-12.81). However, women with higher adherence to the Western dietary pattern (WDP) had higher odds of high serum TG (OR=5.61; 95% CI: 1.69-18.59), and those with a greater adherence to HDP had lower odds of low HDL-C (OR=0.25; 95% CI: 0.07-0.98). This study showed that adherence to HDP may protect against a low level of HDL-C, whereas mixed and Western-type diets may contribute to high serum TG levels. Future longitudinal studies are needed to assess the potential causality of the observed associations.

Dietary patterns and associations with BMI in low-income, ethnic minority youth in the USA according to baseline data from four randomised controlled trials.

Few studies have derived data-driven dietary patterns in youth in the USA. This study examined data-driven dietary patterns and their associations with BMI measures in predominantly low-income, racial/ethnic minority US youth. Data were from baseline assessments of the four Childhood Obesity Prevention and Treatment Research (COPTR) Consortium trials: NET-Works (534 2-4-year-olds), GROW (610 3-5-year-olds), GOALS (241 7-11-year-olds) and IMPACT (360 10-13-year-olds). Weight and height were measured. Children/adult proxies completed three 24-h dietary recalls. Dietary patterns were derived for each site from twenty-four food/beverage groups using k-means cluster analysis. Multivariable linear regression models examined associations of dietary patterns with BMI and percentage of the 95th BMI percentile. Healthy (produce and whole grains) and Unhealthy (fried food, savoury snacks and desserts) patterns were found in NET-Works and GROW. GROW additionally had a dairy- and sugar-sweetened beverage-based pattern. GOALS had a similar Healthy pattern and a pattern resembling a traditional Mexican diet. Associations between dietary patterns and BMI were only observed in IMPACT. In IMPACT, youth in the Sandwich (cold cuts, refined grains, cheese and miscellaneous) compared with Mixed (whole grains and desserts) cluster had significantly higher BMI (β = 0·99 (95 % CI 0·01, 1·97)) and percentage of the 95th BMI percentile (β = 4·17 (95 % CI 0·11, 8·24)). Healthy and Unhealthy patterns were the most common dietary patterns in COPTR youth, but diets may differ according to age, race/ethnicity or geographic location. Public health messages focused on healthy dietary substitutions may help youth mimic a dietary pattern associated with lower BMI.

Abstract LB-156: Data-driven dietary patterns and their association with metabolic fingerprints and risk of colorectal cancer - a nested case-control study from Northern Sweden

Abstract Background: A diet comprising low fiber intake, high consumption of red meat, and alcohol drinking, are all established risk factors for colorectal cancer (CRC). Identifying metabolic fingerprints associated with data-driven dietary patterns may provide insight into potential mechanisms linking diet and risk of CRC. Objective: The aim of this study was to first identify robust data-driven dietary factors derived from food frequency data and to assess their relationships with CRC risk. Second, to investigate plasma metabolic profiles in relation to CRC-associated diet factors. Methods: We used self-reported food frequency data and fasting plasma samples from 860 incident CRC cases (median 12 years from sampling to diagnosis) individually matched to controls by cohort, sex, age at diagnosis, year of blood draw and data collection (+/-1yr), fasting status and number of sample freeze thaw cycles from the population-based Northern Sweden Health and Disease Study (NSHDS). Diet factors were identified from combined exploratory/confirmatory factor analysis on random half-splits of the dietary data. Factors that appeared reproducible between repeated half-splits were retained, and their associations with CRC risk were assessed by multivariable conditional logistic regression, adjusted for age, BMI, smoking, physical activity, total energy intake, education and marital status. Factors associated with CRC risk were related to LC-MS metabolic profiles using random forest regression. Preliminary Results: We identified 12 dietary factors that were robustly associated with CRC risk: red meat, alcohol, snacks, fish, healthy breakfast, fast food, spread, full fat, low-fat, smoked fish/meat, vegetables, and an additional factor consisting of rice and fruit/syrup soup. Both alcohol (OR 1.16, 95% CI 1.00-1.34, p=0.047, fdr=0.283) and the healthy breakfast factor (OR 0.89, 95%CI 0.80-0.99, p=0.030, fdr=0.283) were associated with CRC in the adjusted model. Of these two factors, alcohol was also weakly associated with the metabolic profile (Q2=0.19). Conclusion: The data-driven factor analysis successfully identified dietary exposures, of which several corresponded to established CRC risk factors. Alcohol and healthy breakfast habits associated with CRC risk after adjustment for potential confounders. We also identified a metabolic profile in plasma potentially linked to alcohol consumption which merits further investigation. Citation Format: Stina Bodén, Rikard Landberg, Sophia Harlid, Ingegerd Johansson, Marc J. Gunter, Richard Palmqvist, Rui Zheng, Bethany Van Guelpen, Carl Brunius. Data-driven dietary patterns and their association with metabolic fingerprints and risk of colorectal cancer - a nested case-control study from Northern Sweden [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-156.