Identifying cardiovascular risk factor-related dietary patterns with reduced rank regression and random forest in the EPIC-NL cohort

Analysis of Dietary Patterns Associated with Kidney Stone Disease Based on Data-Driven Approaches: A Case-Control Study in Shanghai

The main objective of this study was to analyze dietary patterns using data-driven approaches and to explore preventive or risk dietary factors for kidney stone disease (KSD). A case-control matching study was conducted in adults (n = 6396) from a suburb of Shanghai. A food frequency questionnaire was used to assess the consumption of various types of food, and B-ultrasound was used to identify kidney stones. Principal component analysis and regression were used to generate dietary patterns and further explore the relationship between dietary patterns and KSD. LASSO regression and post-selection inference were used to identify food groups most associated with KSD. Among males, the "balanced but no-sugary-beverages pattern" (OR = 0.78, p < 0.05) and the "nuts and pickles pattern" (OR = 0.84, p < 0.05) were protective dietary patterns. Among females, "high vegetables and low-sugary-beverages pattern" (OR = 0.83, p < 0.05) and "high-crustaceans and low-vegetables pattern" (OR = 0.79, p < 0.05) were protective dietary patterns, while the "comprehensive pattern with a preference for meat" (OR = 1.06, p < 0.05) and "sugary beverages pattern" (OR = 1.16, p < 0.05) were risk dietary patterns. We further inferred that sugary beverages (p < 0.05) were risk factors and pickles (p < 0.05) and crustaceans (p < 0.05) were protective factors.

Dietary patterns explaining variations in blood biomarkers in young adults are associated with the 30-year predicted cardiovascular disease risks in midlife: A follow-up study

BACKGROUND AND AIMS

To examine a combined effect of dietary intakes, blood lipid and insulin resistance in young adulthood on the risk of predicted CVD through midlife.

METHODS AND RESULTS

Data of young adults from a birth cohort study in Australia were used. Reduced rank regression (RRR) and partial least squares (PLS) methods identified dietary patterns rich in meats, refined grains, processed and fried foods, and high-fat dairy and low in whole grains and low-fat dairy from dietary intakes obtained at 21-years, and blood lipids and measures of insulin resistance measured at 30-years of age. Using standard CVD risk factors measured at 30-years of age, the Framingham Heart Study risk-prediction algorithms were used to calculate the 30-year predicted Framingham CVD risk scores. The scores represent Hard CVD events; coronary death, myocardial infarction and stroke and Full CVD events; Hard CVD plus coronary insufficiency and angina pectoris, transient ischaemic attack, intermittent claudication, and congestive heart failure in midlife. Sex-specific upper quartiles of CVD risk scores were used to define high-risk groups. Modified Poisson regression models were used to estimate relative risks (RRs) with 95% CI. Greater adherence to the diet identified applying RRR in young adulthood was associated with higher risks of predicted Hard CVD (RR: 1.60; 1.14, 2.25) and Full CVD (RR: 1.46; 1.04, 2.05) events in midlife. The diet from PLS showed similar trend of association for the risk of predicted Hard CVD events (RR: 1.49; 1.03, 2.16) in adjusted models.

CONCLUSION

Dietary patterns associated with variations in blood lipids and insulin resistance in young adulthood are associated with increased risks of predicted CVD events in midlife. The findings suggest that diet induced altered blood lipids and insulin resistance in the life course of young adulthood could increase the risks of CVD events in later life.

A comparison of principal component analysis, partial least-squares, and reduced-rank regressions in the identification of dietary patterns associated with hypertension: YaHS-TAMYZ and Shahedieh cohort studies

Limited data exist on the advantage of data reduction hybrid methodologies for evaluating the relationship between dietary patterns (DPs) and chronic diseases and they have led to inconsistent results. This study aimed to investigate the association between DPs extracted using principal component analysis (PCA), partial least-squares (PLS), and reduced-rank regressions (RRRs) in identifying DPs associated with hypertension (HTN) risk. The current study was conducted in the context of two cohort studies accomplished in Iran. DPs were generated using PCA, PLS, and RRR methods. Log-binomial logistic regression test was used to assess the association between DPs and the risk of HTN. From a total of 12,403 included participants aged 20-70 years, 507 incident cases of confirmed HTN were identified. The PCA-DP2 was associated with HTN in the fully adjusted model (T3 vs. T1: RR: 0.737, 95% CI: 0.57-0.93, P _trend = 0.013). The PLS-DP2 and HTN risk were inversely associated in the multivariate model (T3 vs. T1: RR: 0.704, 95% CI: 0.54-0.91, P _trend = 0.013). The RRR-DP2 was associated with an increased risk of HTN (T3 vs. T1: RR: 1.412, 95% CI: 1.11-1.80, P _trend = 0.007). Our findings suggest that the RRR method reveals stronger results in association with HTN risk. However, further investigations are required to confirm the association between DPs derived by PLS and RRR methods by incorporating biomarkers related to HTN as the response variables.

Visceral adiposity-related dietary patterns and the risk of cardiovascular disease in Iranian adults: A population-based cohort study

Background

Visceral obesity is a significant predictor of cardiovascular disease (CVD). Diet may associate with CVD risk through its effects on visceral adiposity. This study aimed to find dietary patterns (DPs) related to indicators of visceral adiposity and to determine whether the DPs were associated with CVD risk.

Methods

This prospective study included 2,496 participants of the Tehran Lipid and Glucose Study (TLGS) without CVD, who were followed from the third study examination (2005–2008; baseline) to March 2018. DPs at baseline were determined using reduced rank regression (RRR) and partial least squares regression (PLS). The response variables were age and BMI-adjusted waist circumference (WC) and age-adjusted visceral adiposity index (VAI).

Results

Two and three DPs were retained with RRR and PLS, respectively. The first patterns of each method were mainly characterized by adjusted-WC (RRR: 10.8%, PLS: 8.6%); none of them were associated with CVD risk. The second pattern of RRR and the third pattern of PLS were mainly explained by adjusted-VAI (RRR: 3.3, PLS: 2.1%). After adjusting for CVD risk factors, the hazard ratios [95% confidence intervals (CI)] for CVD in the second and third tertiles of the RRR-pattern 2 were 1.76 (1.15, 2.69) and 1.55 (1.00, 2.43) vs. the first tertile (p-trend: 0.058). This pattern had high positive loadings for non-leafy vegetables, pickled vegetables, fried vegetables, and bread and high negative loadings for eggs, cakes, butter, jam-honey, red meat, poultry, fish, juice, non-fermented dairy, and fruits. Per one SD increase in PLS-pattern 3 score, the risk of CVD was 19% higher (95%CI = 3–38%). This positive association was also observed across tertiles of the pattern (p-trend: 0.032). This pattern was characterized by high intakes of leafy vegetables, non-leafy vegetables, organ meat, soft drinks, olive oil, pickled vegetables, fried vegetables, and bread and low intakes of biscuits, cakes, butter, eggs, and non-fermented dairy.

Conclusion

For each of the RRR and PLS approaches, a visceral-related DP that was positively linked to CVD was identified. These two patterns had a modest correlation. The pattern generated by PLS explained more variations in food groups and offered stronger evidence of association with CVD than the RRR-derived pattern.

Using Multiple Statistical Methods to Derive Dietary Patterns Associated with Cardiovascular Disease in Patients with Type 2 Diabetes: Results from a Multiethnic Population-Based Study

Background

There are few reports on the relationship between dietary patterns and cardiovascular disease (CVD) risk in patients with type 2 diabetes (T2D). This study aimed to explore relationships between dietary patterns and CVD risk in the T2D population using multiple statistical analysis methods.

Methods

A total of 2,984 patients with T2D from the Xinjiang Multi-Ethnic Cohort, 555 of whom were suffering from CVD, were enrolled in this study. Participants' dietary intake was measured by the semiquantitative food frequency questionnaire (FFQ). Three statistical methods were used to construct dietary patterns, including principal component analysis (PCA) method, reduced-rank regressions (RRR) method, and partial least-squares regression (PLS) method. Then, the association between dietary patterns and CVD risk in T2D patients was analyzed by logistic regression. After excluding participants with CVD, the associations between dietary patterns and 10-year CVD risk scores were subsequently evaluated to reduce reverse causality.

Results

In this study, four dietary patterns were identified by three methods. Adjustment for confounding factors, subjects with the highest scores on the "high-protein and high-carbohydrate" patterns derived from PCA, RRR, and PLS had higher odds of CVD than those with the lowest scores (OR: 2.89, 95% CI: 2.11-3.96, P _trend < 0.001; OR: 2.96, 95% CI: 2.17-4.03, P _trend < 0.001; OR: 2.01, 95% CI: 1.50-2.70, P _trend < 0.001, respectively). However, the dietary pattern of PCA-prudent was not significantly related to the odds of having CVD in T2D patients (adjusted OR_Q4vsQ1: 0.93, 95% CI: 0.70-1.24, P _trend =0.474). Interestingly, we also found significant associations between "high-protein and high-carbohydrate" patterns and the elevated predicted 10-year CVD risk in T2D patients (all P _trend < 0.05).

Conclusion

The positive correlation between "high-protein and high-carbohydrate" patterns and CVD risk in T2D patients was robust across all three data-driven approaches. These findings may have public health significance, encouraging an emphasis on food choices in the usual diet and promoting nutritional interventions for patients with T2D to prevent CVD.

Dietary patterns derived by reduced rank regression and non-communicable disease risk

Most current nutrition policies and dietary recommendations still reflect decades of research addressing the mechanism of action or health risks of individual nutrients. Yet, most high-income countries including the UK are far from reaching the dietary intakes which are recommended for good health. Food-based dietary patterns (DPs) can help target specific combinations of foods that are associated with disease risk, recognising the coexistence of multiple nutrients within foods and their potential synergistic effects. Reduced rank regression (RRR) has emerged as a useful exploratory approach which uses a priori knowledge of the pathway from diet to disease to help identify DPs which are associated with disease risk in a particular population. Here we reviewed the literature with a focus on longitudinal cohort studies using RRR to derive DPs and reporting associations with non-communicable disease risk. We also illustrated the application of the RRR approach using data from the UK Biobank study, where we derived DPs that explained high variability in a set of nutrient response variables. The main DP was characterised by high intakes of chocolate and confectionery, butter and low-fibre bread, and low intakes of fresh fruit and vegetables and showed particularly strong associations with CVD, type 2 diabetes and all-cause mortality, which is consistent with previous studies that derived 'Western' or unhealthy DPs. These recent studies conducted in the UK Biobank population together with evidence from previous cohort studies contribute to the emerging evidence base to underpin food-based dietary advice for non-communicable disease prevention.

Associations between dietary patterns and cardiovascular disease risk in Canadian adults: a comparison of partial least squares, reduced rank regression, and the simplified dietary pattern technique

BACKGROUND

Hybrid methodologies have gained continuing interest as unique data reduction techniques for establishing a direct link between dietary exposures and clinical outcomes.

OBJECTIVES

We aimed to compare partial least squares (PLS) and reduced rank regression (RRR) in identifying a dietary pattern associated with a high cardiovascular disease (CVD) risk in Canadian adults, construct PLS- and RRR-based simplified dietary patterns, and assess associations between the 4 dietary pattern scores and CVD risk.

METHODS

Data were collected from 24-h dietary recalls of adult respondents in the 2 cycles of the nationally representative Canadian Community Health Survey (CCHS)-Nutrition: CCHS 2004 linked to health administrative databases (n = 12,313) and CCHS 2015 (n = 14,020). Using 39 food groups, PLS and RRR were applied for identification of an energy-dense (ED), high-saturated-fat (HSF), and low-fiber-density (LFD) dietary pattern. Associations of the derived dietary pattern scores with lifestyle characteristics and CVD risk were examined using weighted multivariate regression and weighted multivariable-adjusted Cox proportional hazard models, respectively.

RESULTS

PLS and RRR identified highly similar ED, HSF, and LFD dietary patterns with common high positive loadings for fast food, carbonated drinks, salty snacks, and solid fats, and high negative loadings for fruit, dark green vegetables, red and orange vegetables, other vegetables, whole grains, and legumes and soy (≥|0.17|). Food groups with the highest loadings were summed to form simplified pattern scores. Although the dietary patterns were not significantly associated with CVD risk, they were positively associated with 402-kcal/d higher energy intake (P-trends < 0.05) and higher obesity risk (PLS: OR: 2.09; 95% CI: 1.62, 2.70; RRR: OR: 1.76; 95% CI: 1.44, 2.17) (P-trends < 0.0001) in the fourth quartiles.

CONCLUSIONS

PLS and RRR were shown to be equally effective for the derivation of a high-CVD-risk dietary pattern among Canadian adults. Further research is warranted on the role of major dietary components in cardiovascular health.

A non-traditional dietary pattern increases risk of coronary artery disease in the Nepalese population

OBJECTIVES

Several dietary patterns are associated with cardiovascular diseases. Traditional, Western, Mediterranean, and vegetarian are common dietary patterns, derived from principal component analysis (PCA) of dietary food intakes associated with cardiovascular diseases; however, these patterns were derived mostly from the diet habits of people in Western and European countries. Therefore, the present study aimed to determine dietary patterns linked with coronary artery disease (CAD) in the Nepalese population.

METHODS

Food frequency questionnaires were used to estimate dietary intakes in 306 people with CAD and 306 people in a control group matched for age and sex. PCA was performed to deduce the dietary patterns, and conditional logistic regression was executed to determine the association of the dietary patterns with CAD.

RESULTS

The component of PCA with higher loadings of refined grain, sugar, and meat and lower loadings of milk, whole grain, and fruit was named the non-traditional dietary pattern in the present study. We found a 34% increased risk of CAD (odds ratio, 1.34; 95% confidence interval, 1.14-1.58; P < 0.001) associated with this dietary pattern after adjusting for smoking, physical activity, and cardiometabolic risk factors. Dietary-pattern scores were further categorized into tertiles, and the third tertile was observed with significanly higher odds of CAD than the first tertile (odds ratio, 2.32; 95% confidence interval, 1.3-4.14; P for trend = 0.004).

CONCLUSIONS

PCA-derived non-traditional dietary patterns can be a risk for developing CAD in Nepalese people. However, further cohort studies or randomized community trials are suggested to confirm our findings.

Interactions between dietary patterns and genetic factors in relation to incident dementia among 70-year-olds

PURPOSE

To investigate potential interactions between dietary patterns and genetic factors modulating risk for Alzheimer's disease (AD) in relation to incident dementia.

METHODS

Data were derived from the population-based Gothenburg H70 Birth Cohort Studies in Sweden, including 602 dementia-free 70-year-olds (examined 1992-93, or 2000-02; 64% women) followed for incident dementia until 2016. Two factors from a reduced rank regression analysis were translated into dietary patterns, one healthy (e.g., vegetables, fruit, and fish) and one western (e.g., red meat, refined cereals, and full-fat dairy products). Genetic risk was determined by APOE ε4 status and non-APOE AD-polygenic risk scores (AD-PRSs). Gene-diet interactions in relation to incident dementia were analysed with Cox regression models. The interaction p value threshold was < 0.1.

RESULTS

There were interactions between the dietary patterns and APOE ε4 status in relation to incident dementia (interaction p value threshold of < 0.1), while no evidence of interactions were found between the dietary patterns and the AD-PRSs. Those with higher adherence to a healthy dietary pattern had a reduced risk of dementia among ε4 non-carriers (HR: 0.77; 95% CI: 0.61; 0.98), but not among ε4 carriers (HR: 0.86; CI: 0.63; 1.18). Those with a higher adherence to the western dietary pattern had an increased risk of dementia among ε4 carriers (HR: 1.37; 95% CI: 1.05; 1.78), while no association was observed among ε4 non-carriers (HR: 0.99; CI: 0.81; 1.21).

CONCLUSIONS

The results of this study suggest that there is an interplay between dietary patterns and APOE ε4 status in relation to incident dementia.

Advances in dietary pattern analysis in nutritional epidemiology

Background and Purpose

It used to be a common practice in the field of nutritional epidemiology to analyze separate nutrients, foods, or food groups. However, in reality, nutrients and foods are consumed in combination. The introduction of dietary patterns (DP) and their analysis has revolutionized this field, making it possible to take into account the synergistic effects of foods and to account for the complex interaction among nutrients and foods. Three approaches of DP analysis exist: (1) the hypothesis-based approach (based on prior knowledge regarding the current understanding of dietary components and their health relation), (2) the exploratory approach (solely relying on dietary intake data), and (3) the hybrid approach (a combination of both approaches). During the recent past, complementary approaches for DP analysis have emerged both conceptually and methodologically.

Method

We have summarized the recent developments that include incorporating the Treelet transformation method as a complementary exploratory approach in a narrative review.

Results

Uses, peculiarities, strengths, limitations, and scope of recent developments in DP analysis are outlined. Next, the narrative review gives an overview of the literature that takes into account potential relevant dietary-related factors, specifically the metabolome and the gut microbiome in DP analysis. Then the review deals with the aspect of data processing that is needed prior to DP analysis, particularly when dietary data arise from assessment methods other than the long-established food frequency questionnaire. Lastly, potential opportunities for upcoming DP analysis are summarized in the outlook.

Conclusion

Biological factors like the metabolome and the microbiome are crucial to understand diet-disease relationships. Therefore, the inclusion of these factors in DP analysis might provide deeper insights.

A review of statistical methods for dietary pattern analysis

Background

Dietary pattern analysis is a promising approach to understanding the complex relationship between diet and health. While many statistical methods exist, the literature predominantly focuses on classical methods such as dietary quality scores, principal component analysis, factor analysis, clustering analysis, and reduced rank regression. There are some emerging methods that have rarely or never been reviewed or discussed adequately.

Methods

This paper presents a landscape review of the existing statistical methods used to derive dietary patterns, especially the finite mixture model, treelet transform, data mining, least absolute shrinkage and selection operator and compositional data analysis, in terms of their underlying concepts, advantages and disadvantages, and available software and packages for implementation.

Results

While all statistical methods for dietary pattern analysis have unique features and serve distinct purposes, emerging methods warrant more attention. However, future research is needed to evaluate these emerging methods’ performance in terms of reproducibility, validity, and ability to predict different outcomes.

Conclusion

Selection of the most appropriate method mainly depends on the research questions. As an evolving subject, there is always scope for deriving dietary patterns through new analytic methodologies.

Dietary patterns related to cardiovascular disease based on reduced rank regression analysis of healthy middle-aged Koreans: data from the community-based Korean Genome and Epidemiology Study (KoGES) cohort

BACKGROUND

Dietary patterns (DPs) provide a comprehensive picture of the foods consumed by an individual.

OBJECTIVES

Using 12-y follow-up data from the Korean Genome Epidemiology Study (KoGES), we determined the associations of DPs with incident cardiovascular disease (CVD) using reduced rank regression (RRR).

METHODS

This study analyzed the data of 7354 CVD-free subjects aged 40-69 y drawn from the community-based KoGES cohort. Based on the daily intake of 26 food groups at baseline, we identified DPs based on retinol, vitamin B-2 (riboflavin), and vitamin B-3 (niacin) intakes using RRR. The effects of the DPs on incident CVD were assessed using HRs with 95% CIs. Furthermore, using a marginal structural model, the association between DPs and incident CVD was evaluated after adjusting for time-varying confounders.

RESULTS

The incidence of CVD during the follow-up period was 3.7 per 1000 person-years (n = 274). The identified DP accounted for 28.99% of the variation in the response variables (i.e., the intake amounts of all 3 nutrients) and was characterized by high intakes of eggs, fish, milk, and dairy products. The effect of DP quintile on incident CVD differed by sex (Pinteraction = 0.03); the highest DP quintile was associated with a protective effect against the development of CVD in women (HR: 0.44; 95% CI: 0.22, 0.89), but not in men (HR: 1.57; 95% CI: 0.82, 3.00), compared with the lowest quintile. Even after adjusting for time-dependent variables, the effect of DP on incident CVD was significant in women (HR: 0.43; 95% CI: 0.22, 0.84), but not in men (HR: 1.49; 95% CI: 0.71, 3.10).

CONCLUSIONS

In this study, we identified DPs related to CVD, and a DP characterized by high intakes of eggs, fish, milk, and dairy products protected against incident CVD in women.

Food Liking-Based Diet Quality Indexes (DQI) Generated by Conceptual and Machine Learning Explained Variability in Cardiometabolic Risk Factors in Young Adults

The overall pattern of a diet (diet quality) is recognized as more important to health and chronic disease risk than single foods or food groups. Indexes of diet quality can be derived theoretically from evidence-based recommendations, empirically from existing datasets, or a combination of the two. We used these methods to derive diet quality indexes (DQI), generated from a novel dietary assessment, and to evaluate relationships with cardiometabolic risk factors in young adults with (n = 106) or without (n = 106) diagnosed depression (62% female, mean age = 21). Participants completed a liking survey (proxy for usual dietary consumption). Principle component analysis of plasma (insulin, glucose, lipids) and adiposity (BMI, Waist-to-Hip ratio) measures formed a continuous cardiometabolic risk factor score (CRFS). DQIs were created: theoretically (food/beverages grouped, weighted conceptually), empirically (grouping by factor analysis, weights empirically-derived by ridge regression analysis of CRFS), and hybrid (food/beverages conceptually-grouped, weights empirically-derived). The out-of-sample CRFS predictability for the DQI was assessed by two-fold and five-fold cross validations. While moderate consistencies between theoretically- and empirically-generated weights existed, the hybrid outperformed theoretical and empirical DQIs in cross validations (five-fold showed DQI explained 2.6% theoretical, 2.7% empirical, and 6.5% hybrid of CRFS variance). These pilot data support a liking survey that can generate reliable/valid DQIs that are significantly associated with cardiometabolic risk factors, especially theoretically- plus empirically-derived DQI.

Dietary patterns and cancer risk

Over the past decade, the search for dietary factors on which to base cancer prevention guidelines has led to the rapid expansion of the field of dietary patterns and cancer. Multiple systematic reviews and meta-analyses have reported epidemiological associations between specific cancer types and both data-driven dietary patterns determined by empirical analyses and investigator-defined dietary indexes based on a predetermined set of dietary components. New developments, such as the use of metabolomics to identify objective biomarkers of dietary patterns and novel statistical techniques, could provide further insights into the links between diet and cancer risk. Although animal models of dietary patterns are limited, progress in this area could identify the potential mechanisms underlying the disease-specific associations observed in epidemiological studies. In this Review, we summarize the current state of the field, provide a critical appraisal of new developments and identify priority areas for future research. An underlying theme that emerges is that the effectiveness of different dietary pattern recommendations in reducing risk could depend on the type of cancer or on other risk factors such as family history, sex, age and other lifestyle factors or comorbidities as well as on metabolomic signatures or gut microbiota profiles.

Identification of dietary patterns associated with elevated blood pressure among Lebanese men: A comparison of principal component analysis with reduced rank regression and partial least square methods

BACKGROUND

To examine the associations of dietary patterns with odds of elevated Blood Pressure (BP) among Lebanese adult males using principal component analysis (PCA), and compare the results to two other data reduction methods, including reduced rank regression (RRR) and partial least-squares (PLS) regression.

METHODS

Data from the National Nutrition and Non-Communicable Disease Risk Factor Survey conducted in Lebanon between years 2008 and 2009 were used. Dietary intake data were collected by a 61-item food frequency questionnaire (FFQ). In addition, anthropometric and blood pressure measurements were obtained following standard techniques. For the purpose of this study, data of males older than 20 years with no history of chronic diseases were selected (n = 673). Elevated BP was indicated if the systolic blood pressure was > = 130mm Hg and/or the diastolic blood pressure > = 85 mm Hg. Dietary patterns were constructed using PCA, PLS and RRR and compared based on the performance to identify plausible patterns associated with elevated BP. For PLS and RR, the response variables were BMI, waist circumference and percent body fat. Multiple logistic regression was used to evaluate the associations between the dietary pattern scores of each method and risk of elevated BP.

RESULTS

Three dietary patterns were identified using PCA: Western, Traditional Lebanese, and Fish and alcohol. Both the Western and the Traditional Lebanese patterns were associated with higher odds of elevated BP in the study population (OR = 1.23, CI 1.03, 1.46; OR = 1.29, CI 1.09, 1.52 respectively). The comparison among the three methods for dietary patterns derivation showed that PLS and RRR derived patterns explained greater variance in the outcome (PCA: 1.2%; PLS: 14.1%; RRR: 15.36%) and were significantly associated with elevated BP, while the PCA dietary patterns were descriptive of the study population's real dietary habits (PCA: 23.6%; PLS: 19.8%; RRR: 11.3%).

CONCLUSIONS

The Western and Traditional Lebanese dietary patterns were associated with higher odds of elevated BP among Lebanese males. The findings of this study showed that, compared to PCA, the use of RRR method resulted in more significant associations with the outcome while the PCA-derived patterns were more related to the real habits in the study population.

A Western dietary pattern is prospectively associated with cardio-metabolic traits and incidence of the metabolic syndrome

The aim of this study was to derive dietary patterns associated with cardio-metabolic traits and to examine whether these predict prospective changes in these traits and incidence of the metabolic syndrome (iMetS). Subjects from the Malmö Diet and Cancer Study cardiovascular cohort without cardio-metabolic disease and related drug treatments at baseline (n 4071; aged 45-67 years, 40 % men) were included. We applied reduced rank regression on thirty-eight foods to derive patterns that explain variation in response variables measured at baseline (waist circumference, TAG, HDL- and LDL-cholesterol, systolic and diastolic blood pressure, fasting glucose and insulin). Patterns were examined in relation to change in cardio-metabolic traits and iMetS in subjects who were re-examined after 16·7 years (n 2704). Two dietary patterns ('Western' and 'Drinker') were retained and explained 3·2 % of the variation in response variables. The 'Western' dietary pattern was inversely associated with HDL-cholesterol and positively with all other response variables (both at baseline and follow-up), but there was no association with LDL at follow-up. After adjustment for potential confounders, the 'Western' dietary pattern was associated with higher risk of iMetS (hazard ratio Q4 v. Q1: 1·47; 95 % CI 1·23, 1·77; P trend=1·5×10-5). The 'Drinker' dietary pattern primarily explained variation in HDL and was not associated with iMetS. In conclusion, this study supports current food-based dietary guidelines suggesting that a 'Western' dietary pattern with high intakes of sugar-sweetened beverages and red and processed meats and low intakes of wine, cheese, vegetables and high-fibre foods is associated with detrimental effects on cardio-metabolic health.

"Traditional" and "Healthy" Dietary Patterns Are Associated with Low Cardiometabolic Risk in Brazilian Subjects

This study aimed at determining the dietary patterns and investigating their association with cardiometabolic risk markers in a brazilian population at risk. This transversal study was carried out with data of 265 patients (n = 123 M/172 W, age 42 ± 16 years) of the Cardiovascular Health Care Program-PROCARDIO-UFV, Brazil-who had their first appointment between 2012 and 2017. A 24-hour recall was applied. The dietary patterns were determined by Principal Component Analysis. Anthropometric, clinical-metabolic, sociodemographic, and lifestyle data were collected through medical record analysis. Five patterns were identified: "Traditional", "Caloric", "Unhealthy", "Healthy," and "Healthy Snacks". In bivariate analysis, the "Healthy" pattern was negatively associated with WC (waist circunference), BMI (body mass index), WHR (waist-to-hip ratio), SBP (systolic blood pressure), fasting glucose, TG/HDL, LDL/HDL, and TG/HDL values and positively to HDL. The "Traditional" pattern was positively associated with adiposity indicators (WC, BMI, and WHR) and negatively associated with body fat, TyG (triglyceride-glucose index), HDL, and LDL (P < 0.05). However, in adjusted models of Poisson regression, individuals with positive factor score (higher adherence) in the "Traditional" and "Healthy" patterns had less occurrence of abdominal obesity (PR 0.85; 95% CI 0.74-0.99/PR 0.88; 95% CI 0.02-0.76), as well as dyslipidemia (PR 0.06; 95% CI 0.02-0.51/PR 0.03; 95% CI 0.01-0.27), diabetes (PR 0.05; 95% CI 0.01-0.45/PR 0.02; 95% CI 0.01-021), and hypertension (PR 0.06; 95% CI 0.02-0.50/PR 0.02; 95% CI 0.01-0.21). A greater adherence to the "Healthy" pattern was associated with lower values to cardiometabolic risk markers and less occurrence of chronic diseases, while the "Traditional" pattern presented contradictory results.

A hybrid data mining model for diagnosis of patients with clinical suspicion of dementia

BACKGROUND AND OBJECTIVE

Given the phenomenon of aging population, dementias arise as a complex health problem throughout the world. Several methods of machine learning have been applied to the task of predicting dementias. Given its diagnostic complexity, the great challenge lies in distinguishing patients with some type of dementia from healthy people. Particularly in the early stages, the diagnosis positively impacts the quality of life of both the patient and the family. This work presents a hybrid data mining model, involving the mining of texts integrated to the mining of structured data. This model aims to assist specialists in the diagnosis of patients with clinical suspicion of dementia.

METHODS

The experiments were conducted from a set of 605 medical records with 19 different attributes about patients with cognitive decline reports. Firstly, a new structured attribute was created from a text mining process. It was the result of clustering the patient's pathological history information stored in an unstructured textual attribute. Classification algorithms (naïve bayes, bayesian belief networks and decision trees) were applied to obtain Alzheimer's disease and mild cognitive impairment predictive models. Ensemble methods (Bagging, Boosting and Random Forests) were used in order to improve the accuracy of the generated models. These methods were applied in two datasets: one containing only the original structured data; the other containing the original structured data with the inclusion of the new attribute resulting from the text mining (hybrid model).

RESULTS

The models' accuracy metrics obtained from the two different datasets were compared. The results evidenced the greater effectiveness of the hybrid model in the diagnostic prediction for the pathologies of interest.

CONCLUSIONS

When analysing the different methods of classification and clustering used, the better rates related to the precision and sensitivity of the pathologies under study were obtained with hybrid models with support of ensemble methods.

Sex consideration in diet-biomarker-related indices: a systematic review

OBJECTIVE

An index of biomarkers derived from dietary factors (diet-biomarker-related index) identifies foods and nutrients that encompass physiological potentials and provides scientific evidence for dietary patterns that increase the risk of disease associated with specific biomarkers. Although men and women have different dietary patterns and physiological characteristics, sex is not often considered when investigators develop a diet-biomarker-related index. We aimed to review whether epidemiological studies developed diet-biomarker-related indices in a sex-specific way.

DESIGN

We systematically searched for epidemiological studies that developed diet-biomarker-related indices, including (i) biomarker prediction indices that include dietary factors as explanatory variables and (ii) dietary patterns to explain biomarker variations, in the PubMed and EMBASE databases. We qualitatively reviewed the sex consideration in index development.

RESULTS

We identified seventy-nine studies that developed a diet-biomarker-related index. We found that fifty-four studies included both men and women. Of these fifty-four studies, twenty-nine (53·7 %) did not consider sex, eleven (20·3 %) included sex in the development model, seven (13·0 %) considered sex but did not include sex in the development model, and seven (13·0 %) derived a diet-biomarker-related index for men and women separately. A list of selected dietary factors that explained levels of biomarkers generally differed by sex in the studies that developed a diet-biomarker-related index in a sex-specific way.

CONCLUSIONS

Most studies that included both men and women did not develop the diet-biomarker-related index in a sex-specific way. Further research is needed to identify whether a sex-specific diet-biomarker-related index is more predictive of the disease of interest than an index without sex consideration.

Dietary patterns within educational groups and their association with CHD and stroke in the European Prospective Investigation into Cancer and Nutrition-Netherlands cohort

Higher-educated people often have healthier diets, but it is unclear whether specific dietary patterns exist within educational groups. We therefore aimed to derive dietary patterns in the total population and by educational level and to investigate whether these patterns differed in their composition and associations with the incidence of fatal and non-fatal CHD and stroke. Patterns were derived using principal components analysis in 36 418 participants of the European Prospective Investigation into Cancer and Nutrition-Netherlands cohort. Self-reported educational level was used to create three educational groups. Dietary intake was estimated using a validated semi-quantitative FFQ. Hazard ratios were estimated using Cox Proportional Hazard analysis after a mean follow-up of 16 years. In the three educational groups, similar 'Western', 'prudent' and 'traditional' patterns were derived as in the total population. However, with higher educational level a lower population-derived score for the 'Western' and 'traditional' patterns and a higher score on the 'prudent' pattern were observed. These differences in distribution of the factor scores illustrate the association between education and food consumption. After adjustments, no differences in associations between population-derived dietary patterns and the incidence of CHD or stroke were found between the educational groups (P interaction between 0·21 and 0·98). In conclusion, although in general population and educational groups-derived dietary patterns did not differ, small differences between educational groups existed in the consumption of food groups in participants considered adherent to the population-derived patterns (Q4). This did not result in different associations with incident CHD or stroke between educational groups.

Nutrient-Derived Dietary Patterns and Their Association With Metabolic Syndrome in a Japanese Population

Background

Nutrients have been proposed to be related to metabolic syndrome (MetS). The aims of this study were to identify dietary patterns that correlated with several nutrients using reduced rank regression (RRR) and to examine the association between extracted dietary patterns and prevalence of MetS in a Japanese population.

Methods

The study population comprised 1,092 Japanese men and women (35–69 years old) who had participated in the baseline survey of the Japan Multi-Institutional Collaborative Cohort Study in Tokushima Prefecture. Dietary patterns were derived with RRR using 46 food items as predictors and six established nutrients (potassium, calcium, vitamin D, vitamin C, insoluble dietary fiber, and carotene) as response variables. Associations between extracted dietary patterns and MetS were then examined with logistic regression models.

Results

Among the six dietary patterns, dietary pattern 1 (DP1) explained the largest proportion (60.1%) of variance in the six nutrients. Therefore, only DP1 was selected for further analysis. DP1 was characterized by high intake frequency of vegetables, fruits, fish and small fish, natto (fermented soybeans), and deep-fried tofu. After adjustment for potential confounders, significant inverse associations were found between DP1 score and MetS (odds ratio [OR] for each quartile: 1.00, 0.58, 0.60, 0.52; P_trend = 0.02); DP1 and high blood pressure (P_trend = 0.0002); and DP1 and high blood glucose (P_trend = 0.02).

Conclusion

A dietary pattern characterized by high intake of vegetables, fruits, fish and small fish, natto, and deep-fried tofu was associated with reduced prevalence of MetS in a Japanese population.

Dietary patterns by reduced rank regression are associated with obesity and hypertension in Australian adults

Evidence linking dietary patterns (DP) and obesity and hypertension prevalence is inconsistent. We aimed to identify DP derived from energy density, fibre and sugar intakes, as well as Na, K, fibre, SFA and PUFA, and investigate associations with obesity and hypertension. Adults (n 4908) were included from the cross-sectional Australian Health Survey 2011–2013. Two 24-h dietary recalls estimated food and nutrient intakes. Reduced rank regression derived DP with dietary energy density (DED), fibre density and total sugar intake as response variables for obesity and Na:K, SFA:PUFA and fibre density as variables for hypertension. Poisson regression investigated relationships between DP and prevalence ratios (PR) of overweight/obesity (BMI≥25 kg/m2) and hypertension (blood pressure≥140/90 mmHg). Obesity-DP1 was positively correlated with fibre density and sugars and inversely with DED. Obesity-DP2 was positively correlated with sugars and inversely with fibre density. Individuals in the highest tertile of Obesity-DP1 and Obesity-DP2, compared with the lowest, had lower (PR 0·88; 95 % CI 0·81, 0·95) and higher (PR 1·09; 95 % CI 1·01, 1·18) prevalence of obesity, respectively. Na:K and SFA:PUFA were positively correlated with Hypertension-DP1 and inversely correlated with Hypertension-DP2, respectively. There was a trend towards higher hypertension prevalence in the highest tertile of Hypertension-DP1 compared with the lowest (PR 1·18; 95 % CI 0·99, 1·41). Hypertension-DP2 was not associated with hypertension. Obesity prevalence was inversely associated with low-DED, high-fibre and high-sugar (natural sugars) diets and positively associated with low-fibre and high-sugar (added sugars) diets. Hypertension prevalence was higher on low-fibre and high-Na and SFA diets.

Associations between explorative dietary patterns and serum lipid levels and their interactions with ApoA5 and ApoE haplotype in patients with recently diagnosed type 2 diabetes

Aims

In patients with type 2 diabetes (T2D), responsiveness of serum lipid concentrations to dietary patterns may vary by genotype. The aims of the present study were to identify explorative dietary patterns and to examine their independent associations with serum lipid levels and interactions with apolipoprotein (Apo)A5 and ApoE variants among patients recently diagnosed with T2D.

Methods

Within a cross-sectional analysis, participants of the German Diabetes Study (n = 348) with mean T2D duration of 6 months were investigated for fasting serum lipid levels, ApoA5 and ApoE genotypes; food consumption frequencies were assessed by a food propensity questionnaire. Dietary patterns were derived using principal component analysis (PCA) and reduced rank regression (RRR), which extracts patterns explaining variation in serum lipid concentrations.

Results

PCA yielded interpretable dietary patterns which were, however, not related to serum lipid levels. Relevance of the RRR patterns varied by genotype: a preferred consumption of fruit gum, fruit juice, and potato dumpling, whilst avoiding fruits and vegetables independently associated with higher triglyceride levels among ApoA5*2. Patients in the highest compared to the lowest tertile of pattern adherence had 99 % higher triglycerides. Lower consumption frequencies of butter, cream cake, French fries, or high-percentage alcoholic beverages were independently related to lower LDL-cholesterol among ApoE2 carriers, with those in the highest compared to the lowest tertile of pattern adherence having 40 % lower LDL-cholesterol (both P_interaction < 0.05).

Conclusions

Our explorative data analyses suggest that associations of dietary patterns with triglycerides and LDL-cholesterol differ by ApoA5 and ApoE haplotype in recently diagnosed T2D.

Trial registration Clinicaltrials.gov: NCT01055093. Date of registration: January 22, 2010 (retrospectively registered). Date of enrolment of first participant to the trial: September 2005

Electronic supplementary material

The online version of this article (doi:10.1186/s12933-016-0455-9) contains supplementary material, which is available to authorized users.