scholarly journals Methodological approaches to study dietary patterns in relation to risk of coronary heart disease and stroke

2006 ◽  
Vol 95 (5) ◽  
pp. 860-869 ◽  
Author(s):  
Matthias B. Schulze ◽  
Kurt Hoffmann
Keyword(s):  
Dietary Patterns ◽  
Scientific Evidence ◽  
Nutritional Epidemiology ◽  
Reduced Rank Regression ◽  
Rank Regression ◽  
Exploratory Approach ◽  
Long Time ◽  
Approaches To Study ◽  
Dietary Pattern Analysis ◽  
Dietary Components

Dietary pattern analysis, which reflects the complexity of dietary intake, has received considerable attention by nutritional epidemiology. For a long time, two general approaches have been used to define these summary variables in observational studies. The exploratory approach is based only on the data of the study, whereas the hypothesis-oriented approach constructs pattern variables based on scientific evidence available before the study. Recently, a new statistical method, reduced rank regression, was applied to nutritional epidemiology that is exploratory by nature, but can use scientific evidence by focusing on disease-related dietary components or biomarkers. Several studies, both observational and clinical, suggest that dietary patterns may predict the risk of CHD and stroke. In the present review, we describe the results of these studies and the available evidence regarding the relationships between dietary patterns and risk of CVD and we discuss limitations and strengths of the statistical methods used toextract dietary patterns.

scholarly journals Advances in dietary pattern analysis in nutritional epidemiology

2021 ◽  
Author(s):  
Christina-Alexandra Schulz ◽  
Kolade Oluwagbemigun ◽  
Ute Nöthlings
Keyword(s):  
Synergistic Effects ◽  
Hybrid Approach ◽  
Transformation Method ◽  
Narrative Review ◽  
Nutritional Epidemiology ◽  
Food Groups ◽  
Related Factors ◽  
Exploratory Approach ◽  
Recent Developments ◽  
Dietary Pattern Analysis

Abstract 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.

scholarly journals Dietary Patterns in Primary School are of Prospective Relevance for the Development of Body Composition in Two German Pediatric Populations

Nutrients ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1442 ◽  
Author(s):  
Maike Wolters ◽  
Gesa Joslowski ◽  
Sandra Plachta-Danielzik ◽  
Marie Standl ◽  
Manfred Müller ◽  
...  
Keyword(s):  
Body Composition ◽  
Primary School ◽  
Dietary Patterns ◽  
Fast Food ◽  
Principal Component ◽  
Food Group ◽  
Study Cohort ◽  
Reduced Rank Regression ◽  
Rank Regression ◽  
Frequent Consumption

This study performed comparative analyses in two pediatric cohorts to identify dietary patterns during primary school years and examined their relevance to body composition development. Nutritional and anthropometric data at the beginning of primary school and two or four years later were available from 298 and 372 participants of IDEFICS-Germany (Identification and prevention of Dietary-induced and lifestyle-induced health Effects In Children and infants Study) and the KOPS (Kiel Obesity Prevention Study) cohort, respectively. Principal component analyses (PCA) and reduced rank regression (RRR) were used to identify dietary patterns at baseline and patterns of change in food group intake during primary school years. RRR extracted patterns explaining variations in changes in body mass index (BMI), fat mass index (FMI), and waist-to-height-ratio (WtHR). Associations between pattern adherence and excess gain in BMI, FMI, or WtHR (>75th percentile) during primary school years were examined using logistic regression. Among PCA patterns, only a change towards a more Mediterranean food choice during primary school years were associated with a favorable body composition development in IDEFICS-Germany (p < 0.05). In KOPS, RRR patterns characterized by a frequent consumption of fast foods or starchy carbohydrate foods were consistently associated with an excess gain in BMI and WtHR (all p < 0.005). In IDEFICS-Germany, excess gain in BMI, FMI, and WtHR were predicted by a frequent consumption of nuts, meat, and pizza at baseline and a decrease in the consumption frequency of protein sources and snack carbohydrates during primary school years (all p < 0.01). The study confirms an adverse impact of fast food consumption on body composition during primary school years. Combinations of protein and carbohydrate sources deserve further investigation.

scholarly journals Comparison of two statistical approaches to predict all-cause mortality by dietary patterns in German elderly subjects

2005 ◽  
Vol 93 (5) ◽  
pp. 709-716 ◽  
Author(s):  
Kurt Hoffmann ◽  
Heiner Boeing ◽  
Paolo Boffetta ◽  
Gabriele Nagel ◽  
Philippos Orfanos ◽  
...  
Keyword(s):  
Dietary Patterns ◽  
Saturated Fat ◽  
Principal Component ◽  
Energy Sources ◽  
Elderly Subjects ◽  
Monounsaturated Fat ◽  
Reduced Rank Regression ◽  
Rank Regression ◽  
Relative Risks ◽  
All Cause Mortality

Dietary patterns are comprehensive variables of dietary intake appropriate to model the complex exposure in nutritional research. The objectives of this study were to identify dietary patterns by applying two statistical methods, principal component analysis (PCA) and reduced rank regression (RRR), and to assess their ability to predict all-cause mortality. Motivated by previous studies we chose percentages of energy from different macronutrients as response variables in the RRR analysis. We used data from 9356 German elderly subject enrolled in the European Prospective Investigation into Cancer and Nutrition study. The first RRR pattern, subjects which explained 30·8 % of variation in energy sources and especially much variation in intake of saturated fat, monounsaturated fat and carbohydrates was a significant predictor of all-cause mortality. The pattern score had high positive loadings in all types of meat, butter, sauces and eggs, and was inversely associated with bread and fruits. After adjustment for other known risk factors, the relative risks from the lowest to highest quintiles of the first RRR pattern score were 1·0, 1·01, 0·96, 1·32, 1·61 (P for trend: 0·0004). In contrast, the first two PCA patterns explaining 19·7 % of food intake variation but only 7·0 % of variation in energy sources were not related to mortality. These results suggest that variation in macronutrients is meaningful for mortality and that the RRR method is more appropriate than the classic PCA method to identify dietary patterns relevant to mortality.

Dietary patterns, approaches, and multicultural perspectiveThis is one of a selection of papers published in the CSCN–CSNS 2009 Conference, entitled Can we identify culture-specific healthful dietary patterns among diverse populations undergoing nutrition transition?

2010 ◽  
Vol 35 (2) ◽  
pp. 211-218 ◽  
Author(s):  
Katherine L. Tucker
Keyword(s):  
Dietary Patterns ◽  
The United States ◽  
Healthy Eating Index ◽  
United States Department ◽  
Diverse Populations ◽  
Reduced Rank Regression ◽  
Linear Combinations ◽  
Rank Regression ◽  
Reduced Rank ◽  
Nutrition Research

Nutrition research has traditionally focused on single nutrients in relation to health. However, recent appreciation of the complex synergistic interactions among nutrients and other food constituents has led to a growing interest in total dietary patterns. Methods of measurement include summation of food or nutrient recommendations met, such as the United States Department of Agriculture Healthy Eating Index; data-driven approaches — principal components (PCA) and cluster analyses — which describe actual intake patterns in the population; and, most recently, reduced rank regression, which defines linear combinations of food intakes that maximally explain intermediate markers of disease. PCA, a form of factor analysis, derives linear combinations of foods based on their intercorrelations. Cluster analysis groups individuals into maximally differing eating patterns. These approaches have now been used in diverse populations with good reproducibility. In contrast, because it is based on associations with outcomes rather than on coherent behavioral patterns, reduced rank regression may be less reproducible, but more research is needed. However, it is likely to yield useful information for hypothesis generation. Together, the focus on dietary patterns has been fruitful in demonstrating the powerful protective associations of healthy or prudent dietary patterns, and the higher risk associations of Western or meat and refined grains patterns. The field, however, has not fully addressed the effects of diet in subpopulations, including ethnic minorities. Depending on food group coding, subdietary patterns may be obscured or artificially separated, leading to potentially misleading results. Further attention to the definition of the dietary patterns of different populations is critical to providing meaningful results. Still, dietary pattern research has great potential for use in nutrition policy, particularly as it demonstrates the importance of total diet in health promotion.

scholarly journals Relationship Between Dietary Patterns Derived by Reduced Rank Regression and Risk of Depression in American Adults

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 464-464
Author(s):  
Peng Zhao ◽  
Yemian Li ◽  
Jingxian Wang ◽  
Yuhui Yang ◽  
Danmeng Liu ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Dietary Patterns ◽  
Dietary Pattern ◽  
The United States ◽  
Reduced Rank Regression ◽  
Eating Pattern ◽  
Rank Regression ◽  
Reduced Rank ◽  
High Adherence ◽  
Response Variables

Abstract Objectives Depression is one of the most serious mental disorder worldwide. Published studies indicated that nutrients such as folic acid and magnesium may provide a protective effect against it. The purpose of this study was to analyze whether dietary patterns defined by nutrients are associated with the risk of depression. Methods Research data content of 23 464 adults was obtained from the NHANES database. Dietary data were assessed with a valid food frequency questionnaire. Dietary patterns were derived by reduced rank regression with EPA + DHA, folate, Mg and Zn as response variables. The Patient Health Questionnaire was used to assess depressive symptoms (cutoff = 10). We applied logistic regression analyses to test the association between dietary patterns and depressive symptoms. Finally, all samples were divided into three groups: low, medium and high adherence to dietary patterns according to the trinomial score of dietary patterns, and the differences of depression risk among the three groups were compared. Results In total, 3 020 cases with depression were observed. We identified a dietary pattern that was strongly associated with EPA + DHA, folate, Mg and Zn (response variables) intake, which was also characterized by the consumption of vegetables, grains, meat, nuts, beans, peas, and lentils, milk, cheese, oils and solid fats. After adjustment for confounders, a statistically significant association was observed (OR = 0.42, 95%CI: 0.36,0.50; P &lt; 0.001). In addition, compared with the low-adherence group, increasing adherence to this dietary pattern significantly reduced the risk of depression (medium-adherence: OR = 0.62, 95%CI: 0.55,0.71; high-adherence: OR = 0.43, 95%CI: 0.36,0.51; P &lt; 0.001). Conclusions Adults living in the United States have been linked to a lower risk of depression with a high-nutrient eating pattern. Funding Sources National Natural Science Foundation of China and National Key R&D Program of China.

scholarly journals Is the Canadian Healthy Eating Index 2007 an Appropriate Diet Indicator of Metabolic Health? Insights from Dietary Pattern Analysis in the PREDISE Study

Nutrients ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1597 ◽  
Author(s):  
Jacynthe Lafrenière ◽  
Élise Carbonneau ◽  
Catherine Laramée ◽  
Louise Corneau ◽  
Julie Robitaille ◽  
...  
Keyword(s):  
Healthy Eating ◽  
Diet Quality ◽  
Dietary Pattern ◽  
Prevalence Ratio ◽  
Healthy Eating Index ◽  
Dietary Intakes ◽  
Reduced Rank Regression ◽  
Rank Regression ◽  
Binomial Regression ◽  
Dietary Pattern Analysis

The objective of this study was to identify key elements from the 2007 Canada’s Food Guide that should be included in a diet quality score aiming to reflect the risk of metabolic syndrome (MetS). Dietary intakes of 998 adults (mean age: 43.2 years, 50% women) were used to obtain the Canadian Healthy Eating Index 2007 (C-HEI 2007) and Alternative Healthy Eating Index 2010 (AHEI) scores, as well as a dietary pattern (DP) generated by the reduced rank regression (RRR) method. Based on these three scores, a modified version of the C-HEI 2007 (Modified C-HEI) was then proposed. The prevalence ratio (PR) of MetS was examined across diet quality scores using multivariate binomial regression analysis. A higher AHEI, Modified C-HEI, and a lower score for DP were all associated with a significantly lower prevalence of MetS (PR = 0.42; 95% confidence interval (CI) 0.28, 0.64; PR = 0.39; 95% CI 0.23, 0.63; and PR = 0.48; 95% CI 0.31, 0.74, respectively), whereas C-HEI 2007 was not (PR = 0.68; 95% CI 0.47, 1.00). Results suggest that a Modified C-HEI that considers key elements from the C-HEI 2007 and the AHEI, as well the DP, shows that participants with a higher score are less likely to have MetS.

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