Worldwide dietary patterns and their association with socioeconomic data: an ecological exploratory study

Objective: To identify dietary patterns in food availability data at the global level using multivariate statistical methodology, to associate the identified dietary patterns with socioeconomic data and to analyze the adequacy of the applied statistical methods in data of food availability. Methods: Principal Component Analysis was applied to food availability data of 172 UN registered countries available at FAOSTAT database in Food Balance Sheets section. The Principal Components were correlated with socioeconomic data available from the World Bank database. Results: Five principal components were identified, each characterizing a dietary pattern. The first one, a westernized dietary pattern, was composed of energy-dense and processed foods, foods of animal origin, alcoholic beverages, but also, albeit less, by vegetables, fruits and nuts, being correlated with income, urbanization and trade liberalization. This westernized pattern was characterized more by western, animal origin and processed foods, yet preserving unprocessed and regional foods. The other dietary patterns were three agricultural patterns characterized more by regional foods, especially starchy staples, and one coastal dietary pattern composed of fish and seafoods, being associated with GINI index, poverty, and female labor force. Conclusions: Principal Component Analysis was adequate to identify dietary patterns in food availability data. A westernized dietary pattern was identified, being associated with income, urbanization and trade liberalization. This association did not occur for the remain of the dietary patterns identified, these being less driven by economic development.

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Dietary patterns and depressive symptoms among Iranian women

Journal of Health Psychology ◽

10.1177/1359105320909888 ◽

2020 ◽

pp. 135910532090988

Author(s):

Maryam Lahouti ◽

Roza Zavoshy ◽

Mostafa Noroozi ◽

Reza Rostami ◽

Maryam Gholamalizadeh ◽

...

Keyword(s):

Principal Component Analysis ◽

Depressive Symptoms ◽

Food Frequency Questionnaire ◽

Dietary Patterns ◽

Dietary Pattern ◽

Principal Component ◽

Iranian Women ◽

Food Frequency ◽

Mediterranean Dietary Pattern ◽

Western Dietary Pattern

We aimed to investigate the association between dietary patterns and depressive symptoms among 217 Iranian women aged 20–45 years. In this study, dietary intake was assessed using a valid and reliable semi-quantitative food frequency questionnaire. A principal component analysis was applied to detect the major dietary patterns. The Beck Depression Inventory was used to assess the depressive symptoms. Two major dietary patterns were identified: the “semi-Mediterranean” dietary pattern and the “western” dietary pattern. Participants with the “western” dietary pattern had a higher rate of depressive symptoms ( p < 0.05). However, the “semi-Mediterranean” dietary pattern had no significant association with the depressive symptoms.

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Pre-pregnancy adherences to empirically derived dietary patterns and gestational diabetes risk in a Mediterranean cohort: the Seguimiento Universidad de Navarra (SUN) project

British Journal Of Nutrition ◽

10.1017/s0007114517002537 ◽

2017 ◽

Vol 118 (9) ◽

pp. 715-721 ◽

Cited By ~ 9

Author(s):

Mikel Donazar-Ezcurra ◽

Cristina Lopez-del Burgo ◽

Miguel A. Martinez-Gonzalez ◽

Francisco J. Basterra-Gortari ◽

Jokin de Irala ◽

...

Keyword(s):

Risk Factors ◽

Gestational Diabetes ◽

Dietary Patterns ◽

Dietary Pattern ◽

Principal Component ◽

Low Risk ◽

University Graduates ◽

Processed Foods ◽

Dietary Recommendations ◽

High Consumption

AbstractThe aim of this study was to investigate the association between the adherence to empirically derived dietary patterns and gestational diabetes mellitus (GDM) risk and of healthy lifestyles with the prevention of GDM defining an overall healthy score. The Seguimiento Universidad de Navarra project is a Mediterranean cohort of university graduates started in 1999. We included 3455 pregnant women. During a mean follow-up of 10·3 (sd 3·3) years, we identified 173 incident GDM cases. Two major dietary patterns were identified using principal component analysis: the Western dietary pattern (WDP) (characterised by a high consumption of meat-based products and processed foods) and the Mediterranean dietary pattern (MDP) (characterised by a high consumption of vegetables, fruits, fish and non-processed foods). A low-risk score for GDM was defined taking into account important risk factors (age, BMI and unhealthy dietary pattern) for GDM. Positive association was found in the multivariable model between the highest quartile of adherence to WDP and GDM incidence compared with the lowest quartile (OR 1·56; 95 % CI 1·00, 2·43). No association was found between adherence to the MDP and GDM incidence (OR 1·08; 95 % CI 0·68, 1·70 for the highest quartile compared with the lowest). Women who adhered to all three low-risk factors had a 76 % lower risk of GDM (OR 0·24; 95 % CI 0·10, 0·55) compared with women who did not adhere to any factor before pregnancy. In conclusion, our results reinforce the importance of dietary recommendations and other two factors (low BMI and young age at pregnancy) in pre-gravid women.

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Exploration of the Principal Component Analysis (PCA) Approach in Synthesizing the Diet Quality of the Malaysian Population

Nutrients ◽

10.3390/nu13010070 ◽

2020 ◽

Vol 13 (1) ◽

pp. 70

Author(s):

Asma’ Ali ◽

Barrie M. Margetts ◽

Ahmad Ali Zainuddin

Keyword(s):

Principal Component Analysis ◽

Dietary Patterns ◽

Dietary Pattern ◽

Dietary Assessment ◽

Principal Component ◽

Positive Association ◽

Component Analysis ◽

Peninsular Malaysia ◽

A Posteriori ◽

Malaysian Population

(1) Background: One of the most main dietary assessments is through a posteriori application. Although extensive research has incorporated dietary assessment of a population through a posteriori application, this study is the first to examine the Malaysian population and use an a posteriori method and principal component analysis (PCA) to assess the dietary patterns of the Malaysian population. The correlation between all dietary patterns derived via PCA and selected nutrient intake were determined in this sample of study; (2) Methods: A total of 3063 respondents (18 to 59 years old) covering Peninsular Malaysia, Sabah, and Sarawak, participated in this study. PCA was applied on the food frequency questionnaire collected from the respondents, and descriptive statistics and PCA were performed using SPSS version 21; (3) Results: Six patterns were identified: “traditional”, “ prudent”, “ modern”, “western”, “Chinese”, and “combination” diets. All together, these six patterns were able to explain 45.9% of the total variability. Few components derived from the factor loadings showed positive association with several nutrient markers. The traditional dietary pattern showed a moderate, positive correlation with total protein and total sugar intake, there was a significant moderate correlation between the prudent dietary pattern and dietary fibre, and there was a moderate positive association between the Chinese dietary pattern and total energy; and (4) Conclusions: The exploration of the PCA approach above may provide justification for assessment of dietary patterns rather than reliance on single nutrients or foods to identify potential connections to overall nutritional wellbeing as well as to explore the diet–disease relationship. However, study of pattern analysis must be conducted among the Malaysian population to produce validity and reproducibility for this dietary approach in light of the numerous methodological issues that arise when performing PCA.

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Using both principal component analysis and reduced rank regression to study dietary patterns and diabetes in Chinese adults

Public Health Nutrition ◽

10.1017/s1368980014003103 ◽

2015 ◽

Vol 19 (2) ◽

pp. 195-203 ◽

Cited By ~ 33

Author(s):

Carolina Batis ◽

Michelle A Mendez ◽

Penny Gordon-Larsen ◽

Daniela Sotres-Alvarez ◽

Linda Adair ◽

...

Keyword(s):

Principal Component Analysis ◽

Dietary Patterns ◽

Dietary Pattern ◽

Principal Component ◽

Component Analysis ◽

Model Assessment ◽

Reduced Rank Regression ◽

Nutrition Survey ◽

Rank Regression ◽

Reduced Rank

AbstractObjectiveWe examined the association between dietary patterns and diabetes using the strengths of two methods: principal component analysis (PCA) to identify the eating patterns of the population and reduced rank regression (RRR) to derive a pattern that explains the variation in glycated Hb (HbA1c), homeostasis model assessment of insulin resistance (HOMA-IR) and fasting glucose.DesignWe measured diet over a 3 d period with 24 h recalls and a household food inventory in 2006 and used it to derive PCA and RRR dietary patterns. The outcomes were measured in 2009.SettingAdults (n 4316) from the China Health and Nutrition Survey.ResultsThe adjusted odds ratio for diabetes prevalence (HbA1c≥6·5 %), comparing the highest dietary pattern score quartile with the lowest, was 1·26 (95 % CI 0·76, 2·08) for a modern high-wheat pattern (PCA; wheat products, fruits, eggs, milk, instant noodles and frozen dumplings), 0·76 (95 % CI 0·49, 1·17) for a traditional southern pattern (PCA; rice, meat, poultry and fish) and 2·37 (95 % CI 1·56, 3·60) for the pattern derived with RRR. By comparing the dietary pattern structures of RRR and PCA, we found that the RRR pattern was also behaviourally meaningful. It combined the deleterious effects of the modern high-wheat pattern (high intakes of wheat buns and breads, deep-fried wheat and soya milk) with the deleterious effects of consuming the opposite of the traditional southern pattern (low intakes of rice, poultry and game, fish and seafood).ConclusionsOur findings suggest that using both PCA and RRR provided useful insights when studying the association of dietary patterns with diabetes.

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Association Between Dietary Pattern and Perceived Stress

Current Developments in Nutrition ◽

10.1093/cdn/nzab038_042 ◽

2021 ◽

Vol 5 (Supplement_2) ◽

pp. 430-430

Author(s):

Casey McKenna ◽

Gerard Dempsey ◽

Michael Colabelli ◽

Tharsana Kumarasivam ◽

Rachel Molzon ◽

...

Keyword(s):

Principal Component Analysis ◽

Stress Response ◽

Mediterranean Diet ◽

Perceived Stress ◽

Dietary Patterns ◽

Dietary Pattern ◽

Healthy Lifestyle ◽

Principal Component ◽

Component Analysis ◽

The Mediterranean

Abstract Objectives Recent evidence is pointing toward the effect of nutrients on neurotransmission. Therefore, dietary patterns may impact the stress response as well as mental wellbeing. This study aims to investigate the relationship between dietary patterns and perceived stress as a way to shed light on the impact of diet quality on psychological stress. Methods An anonymous questionnaire combining three validated scales was distributed through several social media platforms. The questionnaire included the Food-Mood Questionnaire, the Perceived Stress Scale, and the Kessler-6 scale as well as questions assessing frequency of consumption of various tyrosine-rich foods. Inclusion criteria included adults 18 years old or older. Results were analyzed using Spearman's Rho correlation and principal component analysis using SPSS Version 24.0. Results Our results indicated that several components of the Mediterranean diet such as whole grains (P < 0.05), dark green leafy vegetables (P < 0.01), fish (P < 0.01), beans (P < 0.05), and red lean meat (P < 0.01) were negatively correlated with perceived stress total score. Fast food was positively correlated with perceived stress total score (P < 0.01). The principal component analysis identified 3 components: a healthy dietary pattern, a healthy lifestyle, and an unhealthy dietary pattern. Interestingly, a healthy lifestyle, which shared multiple components with the Mediterranean diet, was inversely related to perceived stress total score and mental distress total score. Conclusions Our findings suggest that a dietary pattern similar to the Mediterranean diet may be associated with a lower perceived stress response. Funding Sources None.

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Parental dietary patterns and social determinants of children's dietary patterns

Revista de Nutrição ◽

10.1590/1678-98652016000400004 ◽

2016 ◽

Vol 29 (4) ◽

pp. 483-493 ◽

Cited By ~ 1

Author(s):

Rosana SALLES-COSTA ◽

Gabriela dos Santos BARROSO ◽

Maria CABRAL ◽

Maria Beatriz Trindade de CASTRO

Keyword(s):

Principal Component Analysis ◽

Linear Regression ◽

Dietary Patterns ◽

Dietary Pattern ◽

Parental Education ◽

Family Income ◽

Principal Component ◽

Education Level ◽

Demographic Characteristics ◽

Parental Education Level

ABSTRACT Objective To identify dietary patterns in children up to thirty months of age and verify whether they are associated with parental dietary patterns, and socioeconomic and demographic characteristics. Methods This is a cross-sectional study with baseline data from a population-based study composed of 1,085 households from a representative sample of a metropolitan region in Rio de Janeiro, Brazil. The children's food intake was evaluated by two 24-hour recalls, and the dietary patterns were identified by principal component analysis stratified into two groups according to the children's age: 6 to 17 months; and 18 to 30 months. The explanatory variables collected by a structured questionnaire were socioeconomic and demographic characteristics, age at introduction of complementary foods, and parental dietary pattern. A Food Frequency Questionnaire was administered to assess parental dietary pattern, which was determined by principal component analysis. Multivariate linear regression estimated the effect of each explanatory variable on the children's dietary patterns. Results Three dietary patterns were identified in children aged 6-17 months (basic-mixed; mixed-plus; and milk-flours) and two dietary patterns were identified in children aged 18-30 months: basic-mixed and mixed-plus. Multivariate linear regression showed that complementary feeding (b=0.108; p=0.004) was positively associated with the basic-mixed dietary pattern, and family income (b=0.002; p£0.01), with the mixed-plus dietary pattern. A negative association was found between the traditional parental dietary pattern and children's mixed-plus pattern in children aged 6-17 months (b=0.152; p=0.006) and in children aged 18-30 months (b=0.152; p=0.016). In children aged up to 18 months, parental education level (b=0.368; p£0.01) was positively associated with the mixed-plus dietary pattern. Conclusion Family income, parental education level, and parental dietary patterns are associated with children's dietary patterns.

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Abstract P049: Principal Component Analysis of Dietary Patterns and the Risk of Cardiovascular Disease and Mortality in Older British Men

Circulation ◽

10.1161/circ.131.suppl_1.p049 ◽

2015 ◽

Vol 131 (suppl_1) ◽

Author(s):

Janice Atkins ◽

Peter Whincup ◽

Richard Morris ◽

Lucy Lennon ◽

Olia Papacosta ◽

...

Keyword(s):

Cardiovascular Disease ◽

Older Adults ◽

Principal Component Analysis ◽

Risk Factor ◽

Dietary Patterns ◽

Dietary Pattern ◽

Principal Component ◽

Component Analysis ◽

All Cause Mortality ◽

Cvd Mortality

Background: Diet quality is a major risk factor for morbidity and mortality, but few studies have examined the relationship between dietary patterns and the risk of cardiovascular disease (CVD) and mortality in older adults. We examined prospective associations between dietary patterns defined using principal component analysis and the risk of CVD and all-cause mortality in older British men. Methods: 3226 men aged 60-79 years from the British Regional Heart Study, free from CVD at baseline, were followed-up for 11 years. Baseline food frequency questionnaire data were used to generate dietary intake data on 34 food groups. Principal component analysis identified dietary patterns which were then categorised according to quartiles of adherence. Cox proportional hazards regression examined associations between dietary patterns and risk of all-cause mortality, CVD mortality, CVD events and coronary heart disease (CHD) events, adjusting for confounders. Results: Principal component analysis identified three interpretable dietary patterns, which explained 20.8% of the total variance. An ‘unhealthy’ dietary pattern explained the greatest single proportion of the variance (7.9%) and was characterised by consumption of red meat, meat products, white bread, fried potato and eggs. A ‘healthy’ dietary pattern was characterised by consumption of poultry, fish, fruit, vegetables, legumes, pasta, rice, wholemeal bread, eggs and olive oil and explained 7.1% of the variance. Finally, a ‘sweet’ dietary pattern was characterised by consumption of biscuits, puddings, chocolate, sweets, sweet spreads and breakfast cereal and explained 5.8% of the variance. There were 899 deaths, 316 CVD deaths, 569 CVD events and 301 CHD events during follow-up. An ‘unhealthy’ dietary pattern was associated with a graded increase in risk of all-cause mortality, after adjustment for sociodemographic, behavioural and cardiovascular risk factors (highest vs. lowest quartile; HR: 1.44, 95% CI: 1.13-1.84, p-trend = 0.007). No significant associations were seen between the risk of all-cause mortality and the ‘healthy’ diet (highest vs. lowest quartile; HR: 0.83, 95% CI: 0.66-1.04, p-trend = 0.28) or the ‘sweet’ diet (highest vs. lowest quartile; HR: 1.00, 95% CI: 0.77-1.29, p-trend = 0.71). None of the dietary patterns were significantly associated with cardiovascular outcomes (CVD mortality, CVD events or CHD events). Conclusions: Dietary patterns are an important risk factor for all-cause mortality in the elderly. Older adults should avoid a high consumption of components of an ‘unhealthy’ dietary pattern to reduce the risk of all-cause mortality.

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Cardiorespiratory fitness is positively associated with both healthy and western dietary pattern in Iranian middle-aged

International Journal for Vitamin and Nutrition Research ◽

10.1024/0300-9831/a000685 ◽

2020 ◽

pp. 1-10

Author(s):

Hossein Shahinfar ◽

Farhang Djafari ◽

Nadia Babaei ◽

Samira Davarzani ◽

Mojdeh Ebaditabar ◽

...

Keyword(s):

Cardiorespiratory Fitness ◽

Dietary Patterns ◽

Dietary Pattern ◽

Principal Component ◽

Total Sample ◽

Linear Regression Models ◽

Middle Aged ◽

Anthropometric Measures ◽

Western Dietary Pattern ◽

Healthy Dietary Pattern

Abstract. Background: The association between dietary patterns and cardiorespiratory fitness (CRF) is not well established. Objective: We sought to investigate association between a posteriori dietary pattern and CRF in middle-aged adults. Design: Adults (n = 276), aged 20–74 years, who were residents of Tehran, Iran were recruited. Diet was assessed by using a validated 168-item semi-quantitative food frequency questionnaire. Principal component analysis was used to derive dietary patterns. Socio-economic status, anthropometric measures, body composition, and blood pressure were recorded. CRF was assessed by using a graded exercise treadmill test. Analysis of variance and linear regression models were used to discern the association between dietary patterns and CRF. Results: Higher scores of the healthy dietary pattern had no association with VO2max (p = 0.13 ). After controlling for potential confounders, VO2max was positively associated across tertiles of healthy dietary patterns (p < 0.001). Higher adherence to the “mixed” dietary pattern was inversely related to VO2max (p < 0.01). After adjusting for confounders, the significant association disappeared (p = 0.14). Higher scores of the “Western” dietary pattern was not associated with VO2max (p = 0.06). However, after controlling for potential confounders, VO2max was positively associated with the “Western” dietary pattern (p = 0.01). A positive linear association between the “healthy” dietary pattern and CRF for the total sample (R2 = 0.02; p < 0.01) were presented. Conclusions: Overall, our findings suggest that higher adherence to a “healthy” and “Western” dietary pattern was positively associated with CRF. However, further studies are required to examine and clarify the causal relationship between dietary patterns and CRF.

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Stormwater inflow prediction using radar rainfall data compressed by principal component analysis

Water Practice & Technology ◽

10.2166/wpt.2006.017 ◽

2006 ◽

Vol 1 (1) ◽

Author(s):

K. Katayama ◽

K. Kimijima ◽

O. Yamanaka ◽

A. Nagaiwa ◽

Y. Ono

Keyword(s):

Principal Component Analysis ◽

Prediction Model ◽

Principal Components ◽

Prediction Method ◽

Principal Component ◽

Component Analysis ◽

Rainfall Data ◽

Radar Rainfall ◽

Input Variables ◽

Inflow Prediction

This paper proposes a method of stormwater inflow prediction using radar rainfall data as the input of the prediction model constructed by system identification. The aim of the proposal is to construct a compact system by reducing the dimension of the input data. In this paper, Principal Component Analysis (PCA), which is widely used as a statistical method for data analysis and compression, is applied to pre-processing radar rainfall data. Then we evaluate the proposed method using the radar rainfall data and the inflow data acquired in a certain combined sewer system. This study reveals that a few principal components of radar rainfall data can be appropriate as the input variables to storm water inflow prediction model. Consequently, we have established a procedure for the stormwater prediction method using a few principal components of radar rainfall data.

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Evaluation functions for integral mapping

Geodesy and Cartography ◽

10.22389/0016-7126-2017-921-3-24-29 ◽

2017 ◽

Vol 921 (3) ◽

pp. 24-29 ◽

Cited By ~ 2

Author(s):

S.I. Lesnykh ◽

A.K. Cherkashin

Keyword(s):

Principal Component Analysis ◽

Environmental Factors ◽

Principal Components ◽

Principal Component ◽

Evaluation Function ◽

Final Value ◽

Evaluation Functions ◽

Geographical Environment ◽

Environmental Background ◽

Integral Mapping

The proposed procedure of integral mapping is based on calculation of evaluation functions on the integral indicators (II) taking into account the feature of the local geographical environment, when geosystems in the same states in the different environs have various estimates. Calculation of II is realized with application of a Principal Component Analysis for processing of the forest database, allowing to consider in II the weight of each indicator (attribute). The final value of II is equal to a difference of the first (condition of geosystem) and the second (condition of environmental background) principal components. The evaluation functions are calculated on this value for various problems of integral mapping. The environmental factors of variability is excluded from final value of II, therefore there is an opportunity to find the invariant evaluation function and to determine coefficients of this function. Concepts and functions of the theory of reliability for making the evaluation maps of the hazard of functioning and stability of geosystems are used.

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