scholarly journals Associations between markers of subclinical atherosclerosis and dietary patterns derived by principal components analysis and reduced rank regression in the Multi-Ethnic Study of Atherosclerosis (MESA)

2007 ◽  
Vol 85 (6) ◽  
pp. 1615-1625 ◽  
Author(s):  
Jennifer A Nettleton ◽  
Lyn M Steffen ◽  
Matthias B Schulze ◽  
Nancy S Jenny ◽  
R Graham Barr ◽  
...  
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Dietary Patterns ◽  
Subclinical Atherosclerosis ◽  
Reduced Rank Regression ◽  
Ethnic Study ◽  
Rank Regression ◽  
Reduced Rank ◽  
Components Analysis

scholarly journals Is principal components analysis necessary to characterise dietary behaviour in studies of diet and disease?

2001 ◽  
Vol 4 (4) ◽  
pp. 903-908 ◽  
Author(s):  
Susan E McCann ◽  
John Weiner ◽  
Saxon Graham ◽  
Jo L Freudenheim
Keyword(s):  
New York ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Dietary Patterns ◽  
Fruits And Vegetables ◽  
Disease Status ◽  
Dietary Behaviour ◽  
Food Groups ◽  
Processed Meats ◽  
Components Analysis

AbstractObjective:To assess the relative ability of principal components analysis (PCA)-derived dietary patterns to correctly identify cases and controls compared with other methods of characterising food intake.Subjects:Participants in this study were 232 endometrial cancer cases and 639 controls from the Western New York Diet Study, 1986–1991, frequency-matched to cases on age and county of residence.Design:Usual intake in the year preceding interview of 190 foods and beverages was collected during a personal interview using a detailed food-frequency questionnaire. Principal components analysis identified two major dietary patterns which we labelled ‘healthy’ and ‘high fat’. Classification on disease status was assessed with separate discriminant analyses (DAs) for four different characterisation schemes: stepwise DA of 168 food items to identify the subset of foods that best discriminated between cases and controls; foods associated with each PCA-derived dietary pattern; fruits and vegetables (47 items); and stepwise DA of USDA-defined food groups (fresh fruit, canned/frozen fruit, raw vegetables, cooked vegetables, red meat, poultry, fish and seafood, processed meats, snacks and sweets, grain products, dairy, and fats).Results:In general, classification of disease status was somewhat better among cases (54.7% to 67.7%) than controls (54.0% to 63.1%). Correct classification was highest for fruits and vegetables (67.7% and 62.9%, respectively) but comparable to that of the other schemes (49.5% to 66.8%).Conclusions:Our results suggest that the use of principal components analysis to characterise dietary behaviour may not provide substantial advantages over more commonly used, less sophisticated methods of characterising diet.

scholarly journals Dietary patterns in UK adolescents obtained from a dual-source FFQ and their associations with socio-economic position, nutrient intake and modes of eating

2013 ◽  
Vol 17 (7) ◽  
pp. 1476-1485 ◽  
Author(s):  
Kate Northstone ◽  
Andrew DAC Smith ◽  
Victoria L Cribb ◽  
Pauline M Emmett
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Dietary Patterns ◽  
Data Set ◽  
Sociodemographic Differences ◽  
Traditional Health ◽  
Parents And Children ◽  
Components Analysis ◽  
Positive Correlations ◽  
Dietary Data

AbstractObjectiveTo derive dietary patterns using principal components analysis from separate FFQ completed by mothers and their teenagers and to assess associations with nutrient intakes and sociodemographic variables.DesignTwo distinct FFQ were completed by 13-year-olds and their mothers, with some overlap in the foods covered. A combined data set was obtained.SettingAvon Longitudinal Study of Parents and Children (ALSPAC), Bristol, UK.SubjectsTeenagers (n 5334) with adequate dietary data.ResultsFour patterns were obtained using principal components analysis: a ‘Traditional/health-conscious’ pattern, a ‘Processed’ pattern, a ‘Snacks/sugared drinks’ pattern and a ‘Vegetarian’ pattern. The ‘Traditional/health-conscious’ pattern was the most nutrient-rich, having high positive correlations with many nutrients. The ‘Processed’ and ‘Snacks/sugared drinks’ patterns showed little association with important nutrients but were positively associated with energy, fats and sugars. There were clear gender and sociodemographic differences across the patterns. Lower scores were seen on the ‘Traditional/health conscious’ and ‘Vegetarian’ patterns in males and in those with younger and less educated mothers. Higher scores were seen on the ‘Traditional/health-conscious’ and ‘Vegetarian’ patterns in girls and in those whose mothers had higher levels of education.ConclusionsIt is important to establish healthy eating patterns by the teenage years. However, this is a time when it is difficult to accurately establish dietary intake from a single source, since teenagers consume increasing amounts of foods outside the home. Further dietary pattern studies should focus on teenagers and the source of dietary data collection merits consideration.

scholarly journals Rurality and dietary patterns: associations in a UK cohort study of 10-year-old children

2014 ◽  
Vol 18 (8) ◽  
pp. 1436-1443 ◽  
Author(s):  
Tim T Morris ◽  
Kate Northstone
Keyword(s):  
Cohort Study ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Dietary Patterns ◽  
Rural Areas ◽  
Dietary Pattern ◽  
Urban Areas ◽  
Urban Group ◽  
Urban Rural ◽  
Components Analysis

AbstractObjectiveDespite differences in obesity and ill health between urban and rural areas in the UK being well documented, very little is known about differences in dietary patterns across these areas. The present study aimed to examine whether urban/rural status is associated with dietary patterns in a population-based UK cohort study of children.DesignDietary patterns were obtained using principal components analysis and cluster analysis of 3 d diet records collected from children at 10 years of age. Rurality was obtained from the 2001 UK Census urban/rural indicator at the time of dietary assessment. General linear models were used to examine the relationship between rurality and dietary pattern scores from principal components analysis; multinomial logistic regression was used to assess the association between rurality and dietary clusters.SettingThe Avon Longitudinal Study of Parents and Children (ALSPAC), South West England.SubjectsChildren (n 5677) aged 10 years (2817 boys and 2860 girls).ResultsAfter adjustment, increases in rurality were associated with increased scores on the ‘health awareness’ dietary pattern (β=0·35; 95 % CI 0·14, 0·56; P<0·001 for the most rural compared with the most urban group) and lower scores on the ‘packed lunch/snack’ dietary pattern (β=−0·39; 95 % CI −0·59, −0·19; P<0·001 for the most rural compared with the most urban group). The odds ratio for participants being in the ‘healthy’ compared with the ‘processed’ dietary cluster for the most rural areas was 1·61 (95 % CI 1·05, 2·49; P=0·02) compared with those in the most urban areas.ConclusionsThere is evidence to suggest that differences exist in dietary patterns between rural and urban areas. Similar results were found using two different methods of dietary pattern analysis, showing that children residing in rural households were more likely to consume healthier diets than those in urban households.

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 Analysis of patterns of food intake in nutritional epidemiology: food classification in principal components analysis and the subsequent impact on estimates for endometrial cancer

2001 ◽  
Vol 4 (5) ◽  
pp. 989-997 ◽  
Author(s):  
Susan E McCann ◽  
James R Marshall ◽  
John R Brasure ◽  
Saxon Graham ◽  
Jo L Freudenheim
Keyword(s):  
New York ◽  
Endometrial Cancer ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Dietary Patterns ◽  
Disease Risk ◽  
Nutritional Epidemiology ◽  
Food Groups ◽  
Diet Study ◽  
Components Analysis

AbstractObjective:To assess the effect of different methods of classifying food use on principal components analysis (PCA)-derived dietary patterns, and the subsequent impact on estimation of cancer risk associated with the different patterns.Methods:Dietary data were obtained from 232 endometrial cancer cases and 639 controls (Western New York Diet Study) using a 190-item semi-quantitative food-frequency questionnaire. Dietary patterns were generated using PCA and three methods of classifying food use: 168 single foods and beverages; 56 detailed food groups, foods and beverages; and 36 less-detailed groups and single food items.Results:Classification method affected neither the number nor character of the patterns identified. However, total variance explained in food use increased as the detail included in the PCA decreased (~8%, 168 items to ~17%, 36 items). Conversely, reduced detail in PCA tended to attenuate the odds ratio (OR) associated with the healthy patterns (OR 0.55, 95% confidence interval (CI) 0.35–0.84 and OR 0.77, 95% CI 0.49–1.20, 168 and 36 items, respectively) but not the high-fat patterns (OR 0.95, 95% CI 0.57–1.58 and OR 0.85, 0.51–1.40, 168 and 36 items, respectively).Conclusions:Greater detail in food-use information may be desirable in determination of dietary patterns for more precise estimates of disease risk.

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