Building an Integrated Relational Database from Swiss Nutrition’s (menuCH) and Multiple Swiss Health Datasets Acquired from 1992 to 2012 for Data Mining Purposes

Lustenberger, Timo; Jenzer, Helena; Einsele, Farshideh (8 July 2021). Building an Integrated Relational Database from Swiss Nutrition’s (menuCH) and Multiple Swiss Health Datasets Acquired from 1992 to 2012 for Data Mining Purposes In: Proceedings of the 10th International Conference on Data Science,Technology and Applications (DATA2021) 1 (pp. 150-156). Setúbal, Portugal: Science and Technology Publications, LDA (SciTePress) 10.5220/0010512701500156

[img]
Preview
Text
lustenberger-data.pdf - Published Version
Available under License Creative Commons: Attribution-Noncommercial-No Derivative Works (CC-BY-NC-ND).

Download (1MB) | Preview

Objective: The objective of the study was to integrate a large database from Swiss nutrition national survey (menu-CH) with 5 extensive databases derived from 5 consecutive Swiss health national surveys from 1992 to 2012 for data mining purposes. Each database has additionally a demographic base data. An integrated Swiss database is built to later discover critical food consumption patterns linked with lifestyle diseases known to be strongly tied with food consumption and compare the derived rules with the rules resulted with a previous study which used a significantly smaller database. Design: Swiss nutrition national survey (menuCH) with approx. 2000 respondents from two different surveys, one by Phone and the other by questionnaire along with Swiss health national surveys from 1992 to 2012 with over than 100000 respondents were pre-processed, cleaned, transformed and finally integrated to a unique relational database. Results: The result of this study is an integrated relational database from the Swiss nutritional and 20 years of Swiss health data.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

Business School > Institute for Applied Data Science & Finance
Business School > Institute for Applied Data Science & Finance > Applied Data Science
Business School

Name:

Lustenberger, Timo;
Jenzer, Helena and
Einsele, Farshideh

Subjects:

R Medicine > RA Public aspects of medicine
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
T Technology > T Technology (General)

ISSN:

9781713839934

ISBN:

978-989-758-521-0

Publisher:

Science and Technology Publications, LDA (SciTePress)

Language:

English

Submitter:

Farshideh Einsele

Date Deposited:

07 Jul 2023 10:06

Last Modified:

07 Jul 2023 10:06

Publisher DOI:

10.5220/0010512701500156

Related URLs:

Uncontrolled Keywords:

Health Informatics, Data Mining, Nutritional and Health Databases, Nutritional and Chronical Databases, Modelling and Managing Large Data Systems, Data Management for Analytics, Large Scale Databases, Database Architecture and Performance.

ARBOR DOI:

10.24451/arbor.19500

URI:

https://arbor.bfh.ch/id/eprint/19500

Actions (login required)

View Item View Item
Provide Feedback