Modest validity and fair reproducibility of dietary patterns derived by cluster analysis

Funtikova, Anna N.; Benítez-Arciniega, Alejandra A.; Fitó, Montserrat

doi:10.1016/j.nutres.2014.12.011

Cited by 12 publications

(10 citation statements)

References 10 publications

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“…Thus, we are not able to look at these DPs as a whole. Although in our study we did not use the recommended methods to evaluate food consumption, the DPs found in our study are similar to those found in other studies of DPs analysis, namely in terms of food content of fruit, vegetables, and meat (63, 64). To examine the association between food consumption, socioeconomic factors, lifestyle behaviors, and health outcomes we used a DP approach ( a posteriori defined DPs), which has the advantage to take into account the synergistic effects of the different nutrients and foods.…”

Section: Discussionsupporting

confidence: 87%

“…Besides, according to a study conducted to analyze the validity and reproducibility of a posteriori DPs using food consumption data collected by two distinct methods (food frequency questionnaire and 24-h recall), two DPs similar to those that we found in our study were also found: “fruit and vegetables” DP and “meat” DP. This suggests a reasonable reproducibility of the DPs derived from the different method used to assess food consumption (64). Other limitation is the cross-sectional design, where causal associations are unable to be identified.…”

Section: Discussionmentioning

confidence: 85%

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Dietary Patterns Characterized by High Meat Consumption Are Associated with Other Unhealthy Life Styles and Depression Symptoms

et al. 2017

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ObjectiveWe aimed to identify dietary patterns (DPs) of Portuguese adults, to assess their socioeconomic, demographic, lifestyle determinants, and to identify their impact on health.DesignEpiDoC 2 study included 10,153 Portuguese adults from the EpiDoC Cohort, a population-based study. In this study, trained research assistants using computer-assisted telephone interview collected socioeconomic, demographic, dietary, lifestyles, and health information from March 2013 to July 2015. Cluster analysis was performed, based on questions regarding the number of meals, weekly frequency of soup consumption, vegetables, fruit, meat, fish, dairy products, and daily water intake. Factors associated with DP were identified through logistic regression models.ResultsTwo DPs were identified: the “meat dietary pattern” and the “fruit & vegetables dietary pattern.” After multivariable adjustment, women (OR = 0.52; p < 0.001), older adults (OR = 0.97; p < 0.001), and individuals with more years of education (OR = 0.96; p = 0.025) were less likely to adopt the “meat dietary pattern,” while individuals in a situation of job insecurity/unemployment (OR = 1.49; p = 0.013), Azores island residents (OR = 1.40; p = 0.026), current smoking (OR = 1.58; p = 0.001), daily alcohol intake (OR = 1.46; p = 0.023), and physically inactive (OR = 1.86; p < 0.001) were positively and significantly associated with “meat dietary pattern.” Moreover, individuals with depression symptoms (OR = 1.50; p = 0.018) and the ones who did lower number of medical appointments in the previous year (OR = 0.98; p = 0.025) were less likely to report this DP.ConclusionOur results suggest that unhealthy DPs (meat DP) are part of a lifestyle behavior that includes physical inactivity, smoking habits, and alcohol consumption. Moreover, depression symptoms are also associated with unhealthy DPs.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 85%

Dietary Patterns Characterized by High Meat Consumption Are Associated with Other Unhealthy Life Styles and Depression Symptoms

et al. 2017

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“…Descriptive methods include cluster analysis (CA), association rules (AR) and PCA . CA is widely used in dietary patterns research . CA enables a form of data reduction where many variables can be reduced to groups of descriptive categories.…”

Section: Discussionmentioning

confidence: 99%

Data mining: Potential applications in research on nutrition and health

Batterham

Neale

Martin

et al. 2017

Nutrition & Dietetics

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“…Adamczyk et al [7] aimed to examine the possibility of using cluster analysis to assess physical activity of dairy cows milked in the Voluntary Milking System while taking into account environmental conditions. In diet research, Funtikova et al [8] used clustering analysis to define the validity and reproducibility of the dietary patterns. In addition, clustering analysis is used in other fields.…”

Section: Related Workmentioning

confidence: 99%

Clustering Analysis on the Introduction of Talents in Colleges

Fang¹

2018

IJDST

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Abstract:With the development of economy and technology, introducing and training talents have become the key driving force in the world which can enhance the competitive strength of the whole countries. Therefore, the strategies of strengthening the universities and colleges with more talented people and making efforts to implement the construction of "Double top" are put forward in the same time. Methods of clustering analysis have been widely used in the actual researches. In this study, an effective clustering analysis model by comparing the clustering analysis under different dimensionality reduction methods is established. Firstly, preprocess the data about talent introduction which is collected from Zhejiang University of Finance and Economics, and use Principal Component Analysis (PCA), Weighted Principal Component Analysis (Weighted-PCA) and Random Forest (RF) to reduce the dimensions of the data. Next, use K-means clustering algorithm and K-medoids clustering algorithm to cluster the preprocessed data. The classification results indicate that the K-medoids algorithm with Weighted-PCA is superior to other clustering methods in this illustrative case. In addition, the experiment divides talents into high-end talents and mid-end talents. By looking into the analysis of the characteristics of the clustering results, some targeted advices on the talents introduction in colleges can be provided.

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Modest validity and fair reproducibility of dietary patterns derived by cluster analysis

Cited by 12 publications

References 10 publications

Dietary Patterns Characterized by High Meat Consumption Are Associated with Other Unhealthy Life Styles and Depression Symptoms

Dietary Patterns Characterized by High Meat Consumption Are Associated with Other Unhealthy Life Styles and Depression Symptoms

Data mining: Potential applications in research on nutrition and health

Clustering Analysis on the Introduction of Talents in Colleges

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