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Patterns of Multimorbidity in Adults: An Association Rules Analysis Using the Korea Health Panel

Author

Listed:
  • Yoonju Lee

    (College of Nursing, Pusan National University, Yangsan 50612, Korea)

  • Heejin Kim

    (Department of Nursing, The Graduate School, Pusan National University, Yangsan 50612, Korea)

  • Hyesun Jeong

    (Department of Nursing, The Graduate School, Pusan National University, Yangsan 50612, Korea)

  • Yunhwan Noh

    (Department of Statistics, The Graduate School, Pusan National University, Busan 46241, Korea)

Abstract

This study aimed to identify the prevalence and patterns of multimorbidity among Korean adults. A descriptive study design was used. Of 11,232 adults aged 18 and older extracted from the 2014 Korean Health Panel Survey, 7118 had one or more chronic conditions. The chronic conditions code uses the Korean Standard Classification of Diseases. Association rule analysis and network analysis were conducted to identify patterns of multimorbidity among 4922 participants with multimorbidity. The prevalence of multimorbidity in the overall population was 34.8%, with a higher prevalence among women (40.8%) than men (28.6%). Hypertension had the highest prevalence in both men and women. In men, diabetes mellitus and hypertension yielded the highest probability of comorbidity (10.04%). In women, polyarthrosis and hypertension yielded the highest probability of comorbidity (12.51%). The results of the network analysis in four groups divided according to gender and age showed different characteristics for each group. Public health practitioners should adopt an integrated approach to manage multimorbidity rather than an individual disease-specific approach, along with different strategies according to age and gender groups.

Suggested Citation

  • Yoonju Lee & Heejin Kim & Hyesun Jeong & Yunhwan Noh, 2020. "Patterns of Multimorbidity in Adults: An Association Rules Analysis Using the Korea Health Panel," IJERPH, MDPI, vol. 17(8), pages 1-14, April.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:8:p:2618-:d:344230
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    References listed on IDEAS

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    1. Karolina Agur & Gary McLean & Kate Hunt & Bruce Guthrie & Stewart W. Mercer, 2016. "How Does Sex Influence Multimorbidity? Secondary Analysis of a Large Nationally Representative Dataset," IJERPH, MDPI, vol. 13(4), pages 1-12, March.
    2. Jin Yong Lee & Sang Jun Eun & Hyun Joo Kim & Min-Woo Jo, 2016. "Finding the Primary Care Providers in the Specialist-Dominant Primary Care Setting of Korea: A Cluster Analysis," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-18, August.
    3. Hahsler, Michael & Grün, Bettina & Hornik, Kurt, 2005. "arules - A Computational Environment for Mining Association Rules and Frequent Item Sets," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i15).
    4. David E. V. Olivares & Frank R. V. Chambi & Evelyn M. M. Chañi & Winston J. Craig & Sandaly O. S. Pacheco & Fabio J. Pacheco, 2017. "Risk Factors for Chronic Diseases and Multimorbidity in a Primary Care Context of Central Argentina: A Web-Based Interactive and Cross-Sectional Study," IJERPH, MDPI, vol. 14(3), pages 1-22, March.
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