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Related Experiment Video

Updated: Feb 2, 2026

Murine Drinking Models in the Development of Pharmacotherapies for Alcoholism: Drinking in the Dark and Two-bottle Choice
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Developing the High-Risk Drinking Scorecard Model in Korea.

Jun-Tae Han1, Il-Su Park2, Suk-Bok Kang3

  • 1Department of Student Aid Policy Research, Korea Student Aid Foundation, Daegu, Korea.

Osong Public Health and Research Perspectives
|November 8, 2018
PubMed
Summary

A new scorecard identifies key factors for high-risk drinking, including demographics and lifestyle. This tool helps understand drinking risks more easily.

Keywords:
Korea Community Health Surveydata mininghigh-risk drinkingscorecardweighted multiple logistic regression

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Area of Science:

  • Public Health
  • Health Informatics
  • Epidemiology

Background:

  • High-risk drinking poses significant public health challenges.
  • Effective tools are needed to identify and communicate these risks.

Purpose of the Study:

  • To develop a high-risk drinking scorecard.
  • To utilize cross-sectional data from the 2014 Korea Community Health Survey.

Main Methods:

  • Data from 149,592 subjects were analyzed.
  • A scorecard model was developed using data mining and weighted multiple logistic regression.

Main Results:

  • Key risk factors identified: gender, age, education, occupation, health check-ups, depressive symptoms, physical activity, mental stress, smoking, obesity, and breakfast habits.
  • Men aged 30-59, office/sales workers, and current smokers showed higher risks.
  • Gender, age, education, and smoking status were the most influential factors.

Conclusions:

  • A credit risk scorecard system can quantify high-risk drinking.
  • This system aids medical providers and the public in understanding drinking dangers.