A Study about Discovery of Critical Food Consumption Patterns Linked with Lifestyle Diseases using Data Mining Methods

Einsele, Farshideh; Sadeghi, Leila; Ingold, Rolf; Jenzer, Helena

doi:10.5220/0005170402390245

Cited by 9 publications

(10 citation statements)

References 3 publications

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“…The study of nutritional patterns using data extraction methods, based on correlations between food groups, has been proposed in nutritional epidemiology by most researchers (8) . For this purpose the statistical techniques used are: factor analysis, cluster analysis and low rank regression (44) .…”

Section: Dietary Pattern Methodologymentioning

confidence: 99%

“…These diseases include obesity, high blood pressure, CVD, type-2 diabetes, neoplasms and many more. Dietary patterns play an important role in health and therefore in the prevention of chronic diseases (8) . Dietary patterns could as such provide a clearer, more accurate picture of a person's eating behaviour (9) .…”

mentioning

confidence: 99%

“…These models represent the interaction of all food choices that form a complete food pattern. These patterns are influenced by many factors, such as climate, demographics, religion, culture and others (8) .…”

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confidence: 99%

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The relationship between lifestyle components and dietary patterns

et al. 2020

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We conducted a narrative review on the interaction between dietary patterns with demographic and lifestyle variables in relation to health status assessment. The food pattern has the advantage of taking into account the correlations that may exist between foods or groups of foods, but also between nutrients. It is an alternative and complementary approach in analysing the relationship between nutrition and the risk of chronic diseases. For the determination of dietary patterns one can use indices/scores that evaluate the conformity of the diet with the nutrition guidelines or the established patterns (a priori approach). The methods more commonly used are based on exploratory data (a posteriori): cluster analysis and factor analysis. Dietary patterns may vary according to sex, socio-economic status, ethnicity, culture and other factors, but more, they may vary depending on different associations between these factors. The dietary pattern exerts its effects on health in a synergistic way or even in conjunction with other lifestyle factors, and we can therefore refer to a ‘pattern of lifestyle’.

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Section: Dietary Pattern Methodologymentioning

confidence: 99%

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confidence: 99%

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The relationship between lifestyle components and dietary patterns

et al. 2020

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“…A small number of studies have applied data mining techniques to nutritional data. These have focused primarily on dietary pattern analysis, exploring which dietary components are predictive of a range of health outcomes (6)(7)(8)(9) . However, we are not aware of any other uses of data mining to identify which foods are predictive of achievement, or not, of key dietary recommendations.…”

Section: Data Mining An Overviewmentioning

confidence: 99%

Identifying small groups of foods that can predict achievement of key dietary recommendations: data mining of the UK National Diet and Nutrition Survey, 2008–12

Giabbanelli

Adams

2016

Public Health Nutr.

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ObjectiveMany dietary assessment methods attempt to estimate total food and nutrient intake. If the intention is simply to determine whether participants achieve dietary recommendations, this leads to much redundant data. We used data mining techniques to explore the number of foods that intake information was required on to accurately predict achievement, or not, of key dietary recommendations.DesignWe built decision trees for achievement of recommendations for fruit and vegetables, sodium, fat, saturated fat and free sugars using data from a national dietary surveillance data set. Decision trees describe complex relationships between potential predictor variables (age, sex and all foods listed in the database) and outcome variables (achievement of each of the recommendations).SettingUK National Diet and Nutrition Survey (NDNS, 2008–12).SubjectsThe analysis included 4156 individuals.ResultsInformation on consumption of 113 out of 3911 (3 %) foods, plus age and sex was required to accurately categorize individuals according to all five recommendations. The best trade-off between decision tree accuracy and number of foods included occurred at between eleven (for fruit and vegetables) and thirty-two (for fat, plus age) foods, achieving an accuracy of 72 % (for fat) to 83 % (for fruit and vegetables), with similar values for sensitivity and specificity.ConclusionsUsing information on intake of 113 foods, it is possible to predict with 72–83 % accuracy whether individuals achieve key dietary recommendations. Substantial further research is required to make use of these findings for dietary assessment.

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“…▶ Mustererkennung in der Ernährung [34] Im Bereich Public Health und Prävention ist nach wie vor zu klären, welche Muster im Ernährungsverhalten und im Lifestyle die Prävalenz bestimmter "Volkskrankheiten" bei einigen Patienten stark und bei anderen gar nicht beeinflussen. Der Tab.…”

Section: Mehrwerte In Public Health Nutritionunclassified

Weiterentwicklung der Curricula in Ernährung und Diätetik – Pharmakologie füllt Lücken, schafft Klarheit und bringt Mehrwerte

Jenzer

Sadeghi

2016

Aktuel Ernahrungsmed

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Zusammenfassung Hintergrund: Bisherige Auffassungen ?ber gesunde Lebensmittel und Ern?hrungsverhalten werden in neuen Publikationen relativiert. Die Ern?hrungsfachkr?fte haben einen Handlungsbedarf, bestehende Mehrwerte aufzuzeigen und neue zu kreieren. Speziell wird der Frage nachgegangen, ob synergistische Kenntnisse in Ern?hrungswissenschaft und in Pharmakologie (und Toxikologie) einen wesentlichen Mehrwert f?r bessere Resultate der Ern?hrungstherapien darstellen k?nnen. Material und Methodik: Eine Auswahl Referenzen von Pubmed, Embase, ScienceDirect und Google Scholar dienten als Grundlage f?r die Evaluation des Stellenwerts der Pharmakologie f?r die Ern?hrungsfachkr?fte. Zudem wurden Kursevaluationen der seit 2012 an der Berner Fachhochschule BFH angebotenen Pharmakologie Weiterbildungskurse f?r die Disziplin Ern?hrung und Di?tetik herangezogen. Da die Fragestellung neu ist, wird aus Fallbeispielen durch vollst?ndige Induktion eine Allgemeinaussage abgeleitet. Ergebnisse: Mehrwerte k?nnen dank Pharmakologie in Public Health Nutrition oder in interdisziplin?rer individualisierter Ern?hrungstherapie geschaffen werden. Die Gesamtbev?lkerung kann von der Mustererkennung in der Ern?hrung profitieren, w?hrend f?r einzelne Patienten oder Gruppen von Patienten Mehrwerte durch Investitionen in die verbesserte Betreuung der enteralen und parenteralen Ern?hrung, in die F?rderung der Wundheilung durch geeignete Ern?hrung, genderadaptierte Ern?hrungstherapie, Anpassung der Kostformen bei Dysphagiepatienten sowie in Nutrigenomics, Food-Drug-Interaktionen und Screening von unerw?nschten Wirkungen entstehen k?nnen. Schlussfolgerung: Um Mehrwerte f?r die Ern?hrung und Di?tetik erschlie?en zu k?nnen, ist die Aus-, Weiter- und Fortbildung entsprechend auszurichten, um neue Managed-Care-Aufgaben ?bernehmen zu k?nnen. Die Vermittlung eines Pharmakologie-Basiswissens ist das geeignete Mittel, um die Kompetenz und Sicherheit zur Erkennung und Triage von Food-Drug-Interaktionen zu erlangen. F?r die ?ffentliche Hand hat au?erdem die Kostformanpassung bei Dysphagiepatienten das Potenzial f?r einen volkswirtschaftlichen Sparbeitrag und f?r ein verbessertes klinisches Outcome.

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A Study about Discovery of Critical Food Consumption Patterns Linked with Lifestyle Diseases using Data Mining Methods

Cited by 9 publications

References 3 publications

The relationship between lifestyle components and dietary patterns

The relationship between lifestyle components and dietary patterns

Identifying small groups of foods that can predict achievement of key dietary recommendations: data mining of the UK National Diet and Nutrition Survey, 2008–12

Weiterentwicklung der Curricula in Ernährung und Diätetik – Pharmakologie füllt Lücken, schafft Klarheit und bringt Mehrwerte

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