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

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.

2015 ◽  
Vol 19 (7) ◽  
pp. 1279-1287 ◽  
Author(s):  
Anna S Howe ◽  
Paula ML Skidmore ◽  
Winsome R Parnell ◽  
Jyh Eiin Wong ◽  
Alexandra C Lubransky ◽  
...  

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.


2001 ◽  
Vol 4 (4) ◽  
pp. 903-908 ◽  
Author(s):  
Susan E McCann ◽  
John Weiner ◽  
Saxon Graham ◽  
Jo L Freudenheim

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.


Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Brittain Heindl ◽  
George Howard ◽  
Elizabeth A Jackson

Introduction: The incidence of stroke is higher in rural areas. Hypertension is the leading risk factor for stroke, but the difference in systolic blood pressure (SBP) for those living in rural and urban areas is unknown. Hypothesis: We hypothesized that rural residence is associated with higher SBP levels, and this difference is modified by race, sex, and United States (US) division. Methods: We analyzed 26,113 participants enrolled in the REasons for Geographic And Racial Differences in Stroke (REGARDS) Study, recruited between 2003 and 2007. Participants were grouped based on the Rural-Urban Commuting Area (RUCA) scheme into urban, large-rural, and small-isolated rural groups. Resting SBP was measured during the initial home visit. Differences in percentiles of SBP distribution were compared using multivariate models with adjustment for age, race, sex, and US Census Bureau division. Results: Of the participants, 20,976 (80.3%) were classified as urban, 3,020 (11.6%) as large-rural, and 2,137 (8.2%) as small-isolated rural, reflecting the distribution of the population. The large-rural group had a 0.09 mmHg higher mean SBP compared to the urban group (95% CI, 0.33 to 1.52 mmHg, p = 0.0023), but the difference in SBP at the 95th percentile between these groups was 3.23 mmHg (95% CI, 1.43 to 4.73 mmHg, p = 0.0006). A similar difference was present between the small-isolated rural and urban groups at the highest percentiles. No urban-rural interaction was observed by race, sex, or US division. However, large SBP differences were present between US divisions, especially at the highest percentiles. To illustrate, SBP at the 95th percentile was 9.51 mmHg higher in the East North Central division than in the Pacific (95% CI, 6.41 to 12.61 mmHg, p < 0.0001). Conclusions: Residence in a rural area is associated with higher SBP, with larger differences at the highest percentiles of distribution. SBP differences are present between US divisions, independent of urban-rural status.


2013 ◽  
Vol 17 (7) ◽  
pp. 1476-1485 ◽  
Author(s):  
Kate Northstone ◽  
Andrew DAC Smith ◽  
Victoria L Cribb ◽  
Pauline M Emmett

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.


2001 ◽  
Vol 4 (5) ◽  
pp. 989-997 ◽  
Author(s):  
Susan E McCann ◽  
James R Marshall ◽  
John R Brasure ◽  
Saxon Graham ◽  
Jo L Freudenheim

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.


2012 ◽  
Vol 109 (10) ◽  
pp. 1881-1891 ◽  
Author(s):  
Andrew D. A. C. Smith ◽  
Pauline M. Emmett ◽  
P. K. Newby ◽  
Kate Northstone

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.


2008 ◽  
Vol 99 (5) ◽  
pp. 1099-1106 ◽  
Author(s):  
Kate Northstone ◽  
Pauline M. Emmett

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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