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.

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.

scholarly journals Patterns of Beverages Consumed and Risk of Incident Kidney Disease

2018 ◽  
Vol 14 (1) ◽  
pp. 49-56 ◽  
Author(s):  
Casey M. Rebholz ◽  
Bessie A. Young ◽  
Ronit Katz ◽  
Katherine L. Tucker ◽  
Teresa C. Carithers ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Principal Components Analysis ◽  
Sex Education ◽  
Principal Components ◽  
Disease Risk ◽  
Dietary Guidelines ◽  
Sugar Sweetened Beverages ◽  
Sweetened Beverages ◽  
Components Analysis

Background and objectivesSelected beverages, such as sugar-sweetened beverages, have been reported to influence kidney disease risk, although previous studies have been inconsistent. Further research is necessary to comprehensively evaluate all types of beverages in association with CKD risk to better inform dietary guidelines.Design, setting, participants, & measurementsWe conducted a prospective analysis in the Jackson Heart Study, a cohort of black men and women in Jackson, Mississippi. Beverage intake was assessed using a food frequency questionnaire administered at baseline (2000–2004). Incident CKD was defined as onset of eGFR<60 ml/min per 1.73 m2 and ≥30% eGFR decline at follow-up (2009–13) relative to baseline among those with baseline eGFR ≥60 ml/min per 1.73 m2. Logistic regression was used to estimate the association between the consumption of each individual beverage, beverage patterns, and incident CKD. Beverage patterns were empirically derived using principal components analysis, in which components were created on the basis of the linear combinations of beverages consumed.ResultsAmong 3003 participants, 185 (6%) developed incident CKD over a median follow-up of 8 years. At baseline, mean age was 54 (SD 12) years, 64% were women, and mean eGFR was 98 (SD 18) ml/min per 1.73 m2. After adjusting for total energy intake, age, sex, education, body mass index, smoking, physical activity, hypertension, diabetes, HDL cholesterol, LDL cholesterol, history of cardiovascular disease, and baseline eGFR, a principal components analysis–derived beverage pattern consisting of higher consumption of soda, sweetened fruit drinks, and water was associated with significantly greater odds of incident CKD (odds ratio tertile 3 versus 1 =1.61; 95% confidence interval, 1.07 to 2.41).ConclusionsHigher consumption of sugar-sweetened beverages was associated with an elevated risk of subsequent CKD in this community-based cohort of black Americans.

scholarly journals Principal components analysis of diet and alternatives for identifying the combination of foods that are associated with the risk of disease: a simulation study

2014 ◽  
Vol 112 (1) ◽  
pp. 61-69 ◽  
Author(s):  
Ioannis Bakolis ◽  
Peter Burney ◽  
Richard Hooper
Keyword(s):  
Logistic Regression ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Multiple Testing ◽  
Propensity Scores ◽  
Disease Association ◽  
Nutritional Epidemiology ◽  
False Discovery ◽  
Risk Of Disease ◽  
Components Analysis

Dietary patterns derived empirically using principal components analysis (PCA) are widely employed for investigating diet–disease relationships. In the present study, we investigated whether PCA performed better at identifying such associations than an analysis of each food on a FFQ separately, referred to here as an exhaustive single food analysis (ESFA). Data on diet and disease were simulated using real FFQ data and by assuming a number of food intakes in combination that were associated with the risk of disease. In each simulation, ESFA and PCA were employed to identify the combinations of foods that are associated with the risk of disease using logistic regression, allowing for multiple testing and adjusting for energy intake. ESFA was also separately adjusted for principal components of diet, foods that were significant in the unadjusted ESFA and propensity scores. For each method, we investigated the power with which an association between diet and disease could be identified, and the power and false discovery rate (FDR) for identifying the specific combination of food intakes. In some scenarios, ESFA had greater power to detect a diet–disease association than PCA. ESFA also typically had a greater power and a lower FDR for identifying the combinations of food intakes that are associated with the risk of disease. The FDR of both methods increased with increasing sample size, but when ESFA was adjusted for foods that were significant in the unadjusted ESFA, FDR were controlled at the desired level. These results question the widespread use of PCA in nutritional epidemiology. The adjusted ESFA identifies the combinations of foods that are causally linked to the risk of disease with low FDR and surprisingly good power.

scholarly journals Cardiorespiratory fitness is positively associated with a healthy dietary pattern in New Zealand adolescents

2015 ◽  
Vol 19 (7) ◽  
pp. 1279-1287 ◽  
Author(s):  
Anna S Howe ◽  
Paula ML Skidmore ◽  
Winsome R Parnell ◽  
Jyh Eiin Wong ◽  
Alexandra C Lubransky ◽  
...  
Keyword(s):  
New Zealand ◽  
Principal Components Analysis ◽  
Cardiorespiratory Fitness ◽  
Principal Components ◽  
Dietary Patterns ◽  
Dietary Pattern ◽  
Fruits And Vegetables ◽  
Total Sample ◽  
Components Analysis ◽  
Online Lifestyle

AbstractObjectiveTo examine the association between cardiorespiratory fitness and dietary patterns in adolescents.DesignFood choice was assessed using the validated New Zealand Adolescent FFQ. Principal components analysis was used to determine dietary patterns. Trained research assistants measured participants’ height and body mass. Cardiorespiratory fitness was assessed in a subset of participants using the multistage 20 m shuttle run. The level and stage were recorded, and the corresponding VO2max was calculated. Differences in mean VO2max according to sex and BMI were assessed using t tests, while associations between cardiorespiratory fitness and dietary patterns were examined using linear regression analyses adjusted for age, sex, school attended, socio-economic deprivation and BMI.SettingSecondary schools in Otago, New Zealand.SubjectsStudents (n 279) aged 14–18 years who completed an online lifestyle survey during a class period.ResultsPrincipal components analysis produced three dietary patterns: ‘Treat Foods’, ‘Fruits and Vegetables’ and ‘Basic Foods’. The 279 participants who provided questionnaire data and completed cardiorespiratory fitness testing had a mean age of 15·7 (sd 0·9) years. Mean VO2max was 45·8 (sd 6·9) ml/kg per min. The ‘Fruits and Vegetables’ pattern was positively associated with VO2max in the total sample (β=0·04; 95 %CI 0·02, 0·07), girls (β=0·06; 95 % CI 0·03, 0·10) and boys (β=0·03; 95 % CI 0·01, 0·05).ConclusionsThese results indicate that increase in cardiorespiratory fitness was associated with a healthier dietary pattern, suggesting both should be targeted as part of a global lifestyle approach. Longitudinal studies are needed to confirm this association in relation to health outcomes in New Zealand adolescents.

scholarly journals Dietary patterns obtained through principal components analysis: the effect of input variable quantification

2012 ◽  
Vol 109 (10) ◽  
pp. 1881-1891 ◽  
Author(s):  
Andrew D. A. C. Smith ◽  
Pauline M. Emmett ◽  
P. K. Newby ◽  
Kate Northstone
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Dietary Patterns ◽  
Food Preferences ◽  
Food Group ◽  
Weight Percentage ◽  
Parents And Children ◽  
Diet Diary ◽  
Components Analysis ◽  
Input Variables

Principal components analysis (PCA) is a popular method for deriving dietary patterns. A number of decisions must be made throughout the analytic process, including how to quantify the input variables of the PCA. The present study aims to compare the effect of using different input variables on the patterns extracted using PCA on 3-d diet diary data collected from 7473 children, aged 10 years, in the Avon Longitudinal Study of Parents and Children. Four options were examined: weight consumed of each food group (g/d), energy-adjusted weight, percentage contribution to energy of each food group and binary intake (consumed/not consumed). Four separate PCA were performed, one for each intake measurement. Three or four dietary patterns were obtained from each analysis, with at least one component that described ‘more healthy’ and ‘less healthy’ diets and one component that described a diet with high consumption of meat, potatoes and vegetables. There were no obvious differences between the patterns derived using percentage energy as a measurement and adjusting weight for total energy intake, compared to those derived using gram weights. Using binary input variables yielded a component that loaded positively on reduced fat and reduced sugar foods. The present results suggest that food intakes quantified by gram weights or as binary variables both resulted in meaningful dietary patterns and each method has distinct advantages: weight takes into account the amount of each food consumed and binary intake appears to describe general food preferences, which are potentially easier to modify and useful in public health settings.

scholarly journals A comparison of methods to assess changes in dietary patterns from pregnancy to 4 years post-partum obtained using principal components analysis

2008 ◽  
Vol 99 (5) ◽  
pp. 1099-1106 ◽  
Author(s):  
Kate Northstone ◽  
Pauline M. Emmett
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Dietary Patterns ◽  
Post Partum ◽  
Cross Sectional ◽  
Time Points ◽  
Applied Method ◽  
Parents And Children ◽  
Components Analysis ◽  
Time Point

Few studies have examined the longitudinal nature of dietary patterns obtained using principal components analysis (PCA); the methods used are inconsistent. This paper investigates the methodologies used to assess stability and changes in such patterns. Pregnant women recorded frequency of consumption of various food items as part of regular self-completed questionnaires in the Avon Longitudinal Study of Parents and Children. This was repeated when their children were 4 years of age; 8953 women provided data at both times. Dietary patterns were identified using PCA and component scores were calculated at each time point. Additional ‘applied’ scores were created at 4 years using the loadings obtained from the PCA on the pregnancy data. Correlations were similar for each component across the time points, though slightly larger using the applied method. The applied scores were considerably lower on average than those obtained from separate PCA at 4 years. Women's scores decreased on ‘health conscious’ and ‘confectionery’ components while ‘processed’ and ‘vegetarian’ scores both increased over the 4-year period. In contrast, applied scores were systematically lower for all components. When split into quintiles, weighted κ was slightly higher between pregnancy and applied 4-year scores compared to the separate scores. In this cohort it was felt that the ‘applied’ method to obtain scores at the second time point was inappropriate, primarily due to the differences in FFQ between the two time points. We recommend that future studies using such ‘applied’ scores compare them with cross-sectional scores and consider the implications of any differences.

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