title: An association rule mining-based framework for understanding lifestyle risk behaviors.
abstract: OBJECTIVE
  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.
  
  
  CONCLUSIONS
  Lifestyle risk behaviors are intercorrelated in Korea. Information on patterns of lifestyle risk behaviors could assist in planning interventions targeted at multiple behaviors simultaneously.
authors.affiliation: Graduate School of Public Health, Seoul National University, Seoul, Korea.
authors.forename: So Hyun
authors.initials: SH
authors.lastname: Park
authors.affiliation: Cardiovascular Imaging Center, Samsung Medical Center, Seoul, Korea.
authors.forename: Shin Yi
authors.initials: SY
authors.lastname: Jang
authors.affiliation: Graduate School of Public Health, Seoul National University, Seoul, Korea.
authors.forename: Ho
authors.initials: H
authors.lastname: Kim
authors.affiliation: Graduate School of Public Health, Seoul National University, Seoul, Korea.
authors.forename: Seung Wook
authors.initials: SW
authors.lastname: Lee
mesh_terms: D000328:Adult; D000368:Aged; D000428:Alcohol Drinking / Q000453:epidemiology* / Q000523:psychology; D057225:Data Mining; D015444:Exercise; D005247:Feeding Behavior / Q000523:psychology; D005260:Female; D006801:Humans; D008019:Life Style / Q000208:ethnology; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology* / Q000523:psychology; D056910:Republic of Korea / Q000453:epidemiology; D012309:Risk-Taking; D057185:Sedentary Behavior; D012892:Sleep Deprivation / Q000453:epidemiology* / Q000523:psychology; D012907:Smoking / Q000453:epidemiology* / Q000523:psychology; D011795:Surveys and Questionnaires