An Association Rule Mining-Based Framework for Understanding Lifestyle Risk Behaviors

Abstract

OBJECTIVES This study investigated the prevalence and patterns of lifestyle risk behaviors in Korean adults. METHODS We utilized data from the Fourth Korea National Health and Nutrition Examination Survey for 14,833 adults (>20 years of age). We used association rule mining to analyze patterns of lifestyle risk behaviors by characterizing non-adherence to public health recommendations related to the Alameda 7 health behaviors. The study variables were current smoking, heavy drinking, physical inactivity, obesity, inadequate sleep, breakfast skipping, and frequent snacking. RESULTS Approximately 72% of Korean adults exhibited two or more lifestyle risk behaviors. Among women, current smoking, obesity, and breakfast skipping were associated with inadequate sleep. Among men, breakfast skipping with additional risk behaviors such as physical inactivity, obesity, and inadequate sleep was associated with current smoking. Current smoking with additional risk behaviors such as inadequate sleep or breakfast skipping was associated with physical inactivity. CONCLUSION Lifestyle risk behaviors are intercorrelated in Korea. Information on patterns of lifestyle risk behaviors could assist in planning interventions targeted at multiple behaviors simultaneously.

DOI: 10.1371/journal.pone.0088859

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@inproceedings{Park2014AnAR, title={An Association Rule Mining-Based Framework for Understanding Lifestyle Risk Behaviors}, author={So Hyun Park and Shin Yi Jang and Ho Young Kim and Seung Wook Lee}, booktitle={PloS one}, year={2014} }