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Use of latent class analysis to identify multimorbidity patterns and associated factors in Korean adults aged 50 years and older

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  • Bomi Park
  • Hye Ah Lee
  • Hyesook Park

Abstract

Introduction: Multimorbidity associated with significant disease and economic burdens is common among the aged. We identified chronic disease multimorbidity patterns in Koreans 50 years of age or older, and explored whether such patterns were associated with particular sociodemographic factors and health-related quality-of-life. Methods: The multimorbidity patterns of 10 chronic diseases (hypertension, dyslipidemia, stroke, osteoarthritis, tuberculosis, asthma, allergic rhinitis, depression, diabetes mellitus, and thyroid disease) were identified via latent class analysis of data on 8,370 Korean adults aged 50+ years who participated in the sixth Korean National Health and Nutrition Examination Survey (2013–2015). The associations between multimorbidity patterns, and sociodemographic factors and health-related quality of life, were subjected to regression analysis. Results: Three patterns of multimorbidity were identified: 1) a relatively healthy group (60.4% of the population); 2) a ‘cardiometabolic conditions’ group (27.8%); and, 3) an ‘arthritis, asthma, allergic rhinitis, depression, and thyroid disease’ group (11.8%). The female (compared to male) gender was associated with an increased likelihood of membership of the cardiometabolic conditions group (odds ratio [OR] = 1.32, 95% confidence interval [CI] = 1.15–1.51) and (to a much greater extent) the arthritis, asthma, allergy, depression, and thyroid disease group (OR = 4.32, 95% CI = 3.30–5.66). Low socioeconomic status was associated with membership of the two multimorbidity classes. Membership of the arthritis, asthma, allergy, depression, and thyroid disease group was associated with a significantly poorer health-related quality-of-life than was membership of the other two groups. Conclusion: The co-occurrence of chronic diseases was not attributable to chance. Multimorbidity patterns were associated with sociodemographic factors and quality-of-life. Our results suggest that targeted, integrated public health and clinical strategies dealing with chronic diseases should be based on an understanding of multimorbidity patterns; this would improve the quality-of-life of vulnerable multimorbid adults.

Suggested Citation

  • Bomi Park & Hye Ah Lee & Hyesook Park, 2019. "Use of latent class analysis to identify multimorbidity patterns and associated factors in Korean adults aged 50 years and older," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-13, November.
    • Handle: RePEc:plo:pone00:0216259
    DOI: 10.1371/journal.pone.0216259
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    1. Ingmar Schäfer & Eike-Christin von Leitner & Gerhard Schön & Daniela Koller & Heike Hansen & Tina Kolonko & Hanna Kaduszkiewicz & Karl Wegscheider & Gerd Glaeske & Hendrik van den Bussche, 2010. "Multimorbidity Patterns in the Elderly: A New Approach of Disease Clustering Identifies Complex Interrelations between Chronic Conditions," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-10, December.
    2. M Mofizul Islam & Jose M Valderas & Laurann Yen & Paresh Dawda & Tanisha Jowsey & Ian S McRae, 2014. "Multimorbidity and Comorbidity of Chronic Diseases among the Senior Australians: Prevalence and Patterns," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-11, January.
    3. Inge Kirchberger & Christa Meisinger & Margit Heier & Anja-Kerstin Zimmermann & Barbara Thorand & Christine S Autenrieth & Annette Peters & Karl-Heinz Ladwig & Angela Döring, 2012. "Patterns of Multimorbidity in the Aged Population. Results from the KORA-Age Study," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-7, January.
    4. Mohammad Akhtar Hussain & Judith M Katzenellenbogen & Frank M Sanfilippo & Kevin Murray & Sandra C Thompson, 2018. "Complexity in disease management: A linked data analysis of multimorbidity in Aboriginal and non-Aboriginal patients hospitalised with atherothrombotic disease in Western Australia," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-18, August.
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    2. Yaqin Zhong & Hanqing Xi & Xiaojun Guo & Tiantian Wang & Yanan Wang & Jian Wang, 2022. "Gender and Socioeconomic Differences in the Prevalence and Patterns of Multimorbidity among Middle-Aged and Older Adults in China," IJERPH, MDPI, vol. 19(24), pages 1-11, December.
    3. Hsin-En Ho & Chih-Jung Yeh & James Cheng-Chung Wei & Wei-Min Chu & Meng-Chih Lee, 2022. "Trends of Multimorbidity Patterns over 16 Years in Older Taiwanese People and Their Relationship to Mortality," IJERPH, MDPI, vol. 19(6), pages 1-12, March.
    4. Javier Alvarez-Galvez & Esther Ortega-Martin & Begoña Ramos-Fiol & Victor Suarez-Lledo & Jesus Carretero-Bravo, 2023. "Epidemiology, mortality, and health service use of local-level multimorbidity patterns in South Spain," Nature Communications, Nature, vol. 14(1), pages 1-16, December.

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