Sociodemographic characteristics and dietary patterns in cardiometabolic risk subjects

2019 ◽  
Vol 121 (11) ◽  
pp. 2780-2790 ◽  
Author(s):  
Brenda Kelly Souza Silveira ◽  
Juliana Farias de Novaes ◽  
Sarah Aparecida Vieira ◽  
Daniela Mayumi Usuda Prado Rocha ◽  
Arieta Carla Gualandi Leal ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Dietary Patterns ◽  
Cardiovascular Health ◽  
Cardiometabolic Risk ◽  
Principal Component ◽  
Component Analysis ◽  
Unhealthy Lifestyle ◽  
Cross Sectional ◽  
Content Type ◽  
Traditional Pattern

Purpose The purpose of this paper is to examine the associations of dietary patterns with sociodemographic and lifestyle characteristics in a cardiometabolic risk population. Design/methodology/approach In this cross-sectional study data from 295 (n=123 men/172 women, 42±16 years) participants in a Cardiovascular Health Care Program were included. After a 24-hour recall interview the dietary patterns were determined using principal component analysis. Sociodemographic, clinical and lifestyle data were collected by medical records. Findings Subjects with diabetes and hypertension had a higher adherence in the “traditional” pattern (rice, beans, tubers, oils and meats). Poisson regression models showed that male subjects with low schooling and smokers had greater adherence to the “traditional” pattern. Also, students, women, and those with higher schooling and sleeping =7 h/night showed higher adherence to healthy patterns (whole grains, nuts, fruits and dairy). Women, young adults and those with higher schooling and fewer sleep hours had greater adherence to healthy dietary patterns. Those with low schooling and unhealthy lifestyle showed more adherence to the “traditional” pattern. Social implications The results indicate the importance to personalized nutritional therapy and education against cardiometabolic risk, considering the dietary patterns specific to each population. Originality/value Socioeconomic and lifestyle characteristics can influence dietary patterns and this is one of the few studies that investigated this relationship performing principal component analysis.

scholarly journals Characterising 3D spherical packings by principal component analysis

2019 ◽  
Vol 37 (3) ◽  
pp. 1023-1041 ◽  
Author(s):  
Tingting Zhao ◽  
Y.T. Feng ◽  
Yuanqiang Tan
Keyword(s):  
Principal Component Analysis ◽  
Gaussian Quadrature ◽  
Three Dimensional ◽  
Principal Component ◽  
Component Analysis ◽  
Particle Packing ◽  
Cross Sectional ◽  
Content Type ◽  
Computer Methods ◽  
Novel Approach

Purpose The purpose of this paper is to extend the previous study [Computer Methods in Applied Mechanics and Engineering 340: 70-89, 2018] on the development of a novel packing characterising system based on principal component analysis (PCA) to quantitatively reveal some fundamental features of spherical particle packings in three-dimensional. Design/methodology/approach Gaussian quadrature is adopted to obtain the volume matrix representation of a particle packing. Then, the digitalised image of the packing is obtained by converting cross-sectional images along one direction to column vectors of the packing image. Both a principal variance (PV) function and a dissimilarity coefficient (DC) are proposed to characterise differences between different packings (or images). Findings Differences between two packings with different packing features can be revealed by the PVs and DC. Furthermore, the values of PV and DC can indicate different levels of effects on packing caused by configuration randomness, particle distribution, packing density and particle size distribution. The uniformity and isotropy of a packing can also be investigated by this PCA based approach. Originality/value Develop an alternative novel approach to quantitatively characterise sphere packings, particularly their differences.

scholarly journals Compositional principal component analysis generates gut microbiota profiles that associate with children's diet and body composition

2020 ◽  
Vol 79 (OCE2) ◽  
Author(s):  
Claudia Leong ◽  
Jillian J. Haszard ◽  
Anne-Louise M. Heath ◽  
Gerald W. Tannock ◽  
Blair Lawley ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Body Composition ◽  
Body Size ◽  
Gut Microbiota ◽  
Dietary Patterns ◽  
Principal Component ◽  
Component Analysis ◽  
Z Score ◽  
Cross Sectional ◽  
The Impact

AbstractGut microbiota data obtained by DNA sequencing are not only complex because of the number of taxa that may be detected within human cohorts, but also compositional because characteristics of the microbiota are described in relative terms (e.g., “relative abundance” of particular bacterial taxa expressed as a proportion of the total abundance of taxa). Nutrition researchers often use standard principal component analysis (PCA) to derive dietary patterns from complex food data, enabling each participant's diet to be described in terms of the extent to which it fits their cohort's dietary patterns. However, compositional PCA methods are not commonly used to describe patterns of microbiota in the way that dietary patterns are used to describe diets. This approach would be useful for identifying microbiota patterns that are associated with diet and body composition. The aim of this study is to use compositional PCA to describe gut microbiota profiles in 5 year old children and explore associations between microbiota profiles, diet, body mass index (BMI) z-score, and fat mass index (FMI) z-score. This study uses a cross-sectional data for 319 children who provided a faecal sample at 5 year of age. Their primary caregiver completed a 123-item quantitative food frequency questionnaire validated for foods of relevance to the gut microbiota. Body composition was determined using dual-energy x-ray absorptiometry, and BMI and FMI z-scores calculated. Compositional PCA identified and described gut microbiota profiles at the genus level, and profiles were examined in relation to diet and body size. Three gut microbiota profiles were found. Profile 1 (positive loadings on Blautia and Bifidobacterium; negative loadings on Bacteroides) was not related to diet or body size. Profile 2 (positive loadings on Bacteroides; negative loadings on uncultured Christensenellaceae and Ruminococcaceae) was associated with a lower BMI z-score (r = -0.16, P = 0.003). Profile 3 (positive loadings on Faecalibacterium, Eubacterium and Roseburia) was associated with higher intakes of fibre (r = 0.15, P = 0.007); total (r = 0.15, P = 0.009), and insoluble (r = 0.13, P = 0.021) non-starch polysaccharides; protein (r = 0.12, P = 0.036); meat (r = 0.15, P = 0.010); and nuts, seeds and legumes (r = 0.11, P = 0.047). Further regression analyses found that profile 2 and profile 3 were independently associated with BMI z-score and diet respectively. We encourage fellow researchers to use compositional PCA as a method for identifying further links between the gut, diet and obesity, and for developing the next generation of research in which the impact on body composition of dietary interventions that modify the gut microbiota is determined.

scholarly journals Identification of dietary patterns by principal component analysis in schoolchildren in the South of Brazil and associated factors

2020 ◽  
Vol 20 (3) ◽  
pp. 735-745
Author(s):  
Gabriela Rodrigues Bratkowski ◽  
Vanessa Backes ◽  
Maria Teresa Olinto ◽  
Ruth Liane Henn
Keyword(s):  
Principal Component Analysis ◽  
Dietary Patterns ◽  
Associated Factors ◽  
Principal Component ◽  
First Grade ◽  
Component Analysis ◽  
Cross Sectional Study ◽  
The South ◽  
Cross Sectional ◽  
South Of Brazil

Abstract Objectives: to identify dietary patterns (DP) and associated factors in first grade school-children in elementary schools in the South of Brazil. Methods: school-based cross-sectional study, with a non-probabilistic sample of 782 schoolchildren aged 6 to 8. Food intake was assessed by a food frequency questionnaire. DP were identified using the principal component analysis and the prevalence ratios were obtained by Poisson regression with a robust variance. Results: four DP were identified and accounted for 25.3% of the total variance: "fruit, vegetables and fish" (8.5%), "sweets and salty snacks" (7.0%), "dairy, ham and biscuits" (5.0%) and "common Brazilian food" (4.8%). After the adjustment, breakfast habit and lower frequency of meals in front of a screen increased the probability of adherence to a high consumption of DP of "fruit, vegetables and fish". The maternal schooling level was linearly and inversely associated with DP of "sweets and salty snacks" and "common Brazilian food", and positively related to the DP of "dairy, ham and biscuits". Schoolchildren with food inse-curity and sufficiently active had higher probability of adherence to DP of "common Brazilian food". Conclusions: four DP were identified and associated with food insecurity, maternal socioeconomic characteristics and schoolchildren’s behavioral characteristics.

scholarly journals “Traditional” and “Healthy” Dietary Patterns Are Associated with Low Cardiometabolic Risk in Brazilian Subjects

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Brenda Kelly Souza Silveira ◽  
Juliana Farias de Novaes ◽  
Nínive de Almeida Reis ◽  
Larissa Pereira Lourenço ◽  
Ana Helena Moretto Capobiango ◽  
...  
Keyword(s):  
Dietary Patterns ◽  
Cardiovascular Health ◽  
Cardiometabolic Risk ◽  
Principal Component ◽  
Care Program ◽  
Bivariate Analysis ◽  
Risk Markers ◽  
Negatively Associated ◽  
Cardiometabolic Risk Markers ◽  
Traditional Pattern

This study aimed at determining the dietary patterns and investigating their association with cardiometabolic risk markers in a brazilian population at risk. This transversal study was carried out with data of 265 patients (n = 123 M/172 W, age 42 ± 16 years) of the Cardiovascular Health Care Program—PROCARDIO-UFV, Brazil—who had their first appointment between 2012 and 2017. A 24-hour recall was applied. The dietary patterns were determined by Principal Component Analysis. Anthropometric, clinical-metabolic, sociodemographic, and lifestyle data were collected through medical record analysis. Five patterns were identified: “Traditional”, “Caloric”, “Unhealthy”, “Healthy,” and “Healthy Snacks”. In bivariate analysis, the “Healthy” pattern was negatively associated with WC (waist circunference), BMI (body mass index), WHR (waist-to-hip ratio), SBP (systolic blood pressure), fasting glucose, TG/HDL, LDL/HDL, and TG/HDL values and positively to HDL. The “Traditional” pattern was positively associated with adiposity indicators (WC, BMI, and WHR) and negatively associated with body fat, TyG (triglyceride-glucose index), HDL, and LDL (P<0.05). However, in adjusted models of Poisson regression, individuals with positive factor score (higher adherence) in the “Traditional” and “Healthy” patterns had less occurrence of abdominal obesity (PR 0.85; 95% CI 0.74–0.99/PR 0.88; 95% CI 0.02–0.76), as well as dyslipidemia (PR 0.06; 95% CI 0.02–0.51/PR 0.03; 95% CI 0.01–0.27), diabetes (PR 0.05; 95% CI 0.01–0.45/PR 0.02; 95% CI 0.01–021), and hypertension (PR 0.06; 95% CI 0.02–0.50/PR 0.02; 95% CI 0.01–0.21). A greater adherence to the “Healthy” pattern was associated with lower values to cardiometabolic risk markers and less occurrence of chronic diseases, while the “Traditional” pattern presented contradictory results.

A principal component analysis of the determinants of spatial disparity between rural and urban localities of Ghana

2017 ◽  
Vol 44 (6) ◽  
pp. 715-731 ◽  
Author(s):  
Ivy Drafor
Keyword(s):  
Principal Component Analysis ◽  
Rural Areas ◽  
Urban Areas ◽  
Principal Component ◽  
Component Analysis ◽  
Spatial Inequality ◽  
Necessary Condition ◽  
Spatial Disparity ◽  
Content Type ◽  
Rural And Urban

Purpose The purpose of this paper is to analyse the spatial disparity between rural and urban areas in Ghana using the Ghana Living Standards Survey’s (GLSS) rounds 5 and 6 data to advance the assertion that an endowed rural sector is necessary to promote agricultural development in Ghana. This analysis helps us to know the factors that contribute to the depravity of the rural sectors to inform policy towards development targeting. Design/methodology/approach A multivariate principal component analysis (PCA) and hierarchical cluster analysis were applied to data from the GLSS-5 and GLSS-6 to determine the characteristics of the rural-urban divide in Ghana. Findings The findings reveal that the rural poor also spend 60.3 per cent of their income on food, while the urban dwellers spend 49 per cent, which is an indication of food production capacity. They have low access to information technology facilities, have larger household sizes and lower levels of education. Rural areas depend a lot on firewood for cooking and use solar/dry cell energies and kerosene for lighting which have implications for conserving the environment. Practical implications Developing the rural areas to strengthen agricultural growth and productivity is a necessary condition for eliminating spatial disparities and promoting overall economic development in Ghana. Addressing rural deprivation is important for conserving the environment due to its increased use of fuelwood for cooking. Absence of alternatives to the use of fuelwood weakens the efforts to reduce deforestation. Originality/value The application of PCA to show the factors that contribute to spatial inequality in Ghana using the GLSS-5 and GLSS-6 data is unique. The study provides insights into redefining the framework for national poverty reduction efforts.

scholarly journals Theoretical and empirical dimensions of the Aberdeen Glaucoma Questionnaire: a cross sectional survey and principal component analysis

2013 ◽  
Vol 13 (1) ◽  
Author(s):  
Maria Prior ◽  
Craig R Ramsay ◽  
Jennifer M Burr ◽  
Susan E Campbell ◽  
David J Jenkinson ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Cross Sectional Survey ◽  
Cross Sectional

scholarly journals Principal component analysis reveals gender-specific predictors of cardiometabolic risk in 6th graders

2012 ◽  
Vol 11 (1) ◽  
pp. 146 ◽  
Author(s):  
Mark D Peterson ◽  
Dongmei Liu ◽  
Heidi B IglayReger ◽  
William A Saltarelli ◽  
Paul S Visich ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cardiometabolic Risk ◽  
Principal Component ◽  
Component Analysis ◽  
6Th Graders ◽  
Gender Specific

Factorial analysis of stress factors among the sample of Lebanese police officers

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fadi Afif Fayyad ◽  
Filip Vladimir Kukić ◽  
Nemanja Ćopić ◽  
Nenad Koropanovski ◽  
Milivoj Dopsaj
Keyword(s):  
Principal Component Analysis ◽  
Police Officers ◽  
Psychological Health ◽  
Social Life ◽  
Principal Component ◽  
Component Analysis ◽  
Stress Factors ◽  
Research Approach ◽  
Content Type ◽  
Stress Management Training

PurposeThe purpose of the study is to determine the prevalence of stress and to identify the occupational stressors among Lebanese police officers.Design/methodology/approachOperational Police Stress Questionnaire (PSQ-op) was addressed to 100 randomly selected male Lebanese Police officers. Twenty items from the PSQ-op were run through the principal component analysis to determine the most significant factors of stress and loading within each of the factors.FindingsThe results indicated that 59% of officers reported moderate stress level and 41% reported strenuous stress. Principal component analysis identified six independent factors or stress among Lebanese police officers explaining in total 72.1% of the total variance: excessive workload (30.6%), social-life time management (12.8%), occupational fitness (9.1%), success-related stress (8.6%), physical and psychological health (5.8%), and working alone at night (5.2%).Research limitations/implicationsThis research approach encountered some limitations so further research must: use a larger sample size, include female gender and identify other sources of stressors mainly organizational or job context stressors.Originality/valueAddressing and understanding stress factors among Lebanese police officers helps improving awareness and developing individualized treatment strategies leading police officers to engage in stress-management training to learn coping strategies and use effective tools for preventing stress before it becomes chronic.

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