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

Einsele, Farshideh; Sadeghi-Reeves, Leila; Ingold, Rolf; Jenzer, Helena (2015). A Study about Discovery of Critical Food Consumption Patterns Linked with Lifestyle Diseases using Data Mining Methods Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, pp. 239-245. 10.5220/0005170402390245

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Background: To date, the analysis of the implications of dietary patterns on lifestyle diseases is based on data coming either from clinical studies or food surveys, both comprised of a limited number of participants. This article demonstrates that linking big data from a grocery store sales database with demographical and health data by using data mining tools such as classification and association rules is a powerful way to determine if a specific population subgroup is at particular risk for developing a lifestyle disease based on its food consumption patterns. Objective: The objective of the study was to link big data from grocery store sales with demographic and health data to discover critical food consumption patterns linked with lifestyle diseases known to be strongly tied with food consumption.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

Department of Business
Department of Health Professions

Name:

Einsele, Farshideh; Sadeghi-Reeves, Leila; Ingold, Rolf and Jenzer, Helena

ISBN:

978-989-758-068-0

Language:

English

Submitter:

Admin import user

Date Deposited:

16 Oct 2019 10:59

Last Modified:

16 Oct 2019 10:59

Publisher DOI:

10.5220/0005170402390245

Related URLs:

Uncontrolled Keywords:

Data Mining, Association rules, Nutritional Patterns, Knowledge Interpretation, Lifestyle Diseases, Demographic, Customer Profiles, Disease Diagnosis

ARBOR DOI:

10.24451/arbor.7750

URI:

https://arbor.bfh.ch/id/eprint/7750

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