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Patterns and Determinants of Multimorbidity in Older Adults: Study in Health-Ecological Perspective

Author

Listed:
  • Yiming Chen

    (School of Health Management, Southern Medical University, Guangzhou 510515, China)

  • Lei Shi

    (School of Health Management, Southern Medical University, Guangzhou 510515, China)

  • Xiao Zheng

    (Department of Health Management, Shunde Hospital, Southern Medical University, Foshan 528399, China)

  • Juan Yang

    (School of Health Management, Bengbu Medical College, Bengbu 233030, China)

  • Yaqing Xue

    (School of Health Management, Southern Medical University, Guangzhou 510515, China)

  • Shujuan Xiao

    (School of Health Management, Southern Medical University, Guangzhou 510515, China)

  • Benli Xue

    (School of Health Management, Southern Medical University, Guangzhou 510515, China)

  • Jiachi Zhang

    (School of Health Management, Southern Medical University, Guangzhou 510515, China)

  • Xinru Li

    (School of Health Management, Southern Medical University, Guangzhou 510515, China)

  • Huang Lin

    (School of Health Management, Southern Medical University, Guangzhou 510515, China)

  • Chao Ma

    (School of Health Management, Southern Medical University, Guangzhou 510515, China)

  • Chichen Zhang

    (School of Health Management, Southern Medical University, Guangzhou 510515, China
    Department of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
    Institute of Health Management, Southern Medical University, Guangzhou 510515, China)

Abstract

(1) Background: Multimorbidity has become one of the key issues in the public health sector. This study aims to explore the patterns and health-ecological factors of multimorbidity in China to propose policy recommendations for the management of chronic diseases in the elderly. (2) Methods: A multi-stage random sampling method was used to conduct a questionnaire survey on 3637 older adults aged 60 and older in Shanxi, China. Association rule mining analysis (ARM) and network analysis were applied to analyze the patterns of multimorbidity. The health-ecological model was adopted to explore the potential associated factors of multimorbidity in a multidimensional perspective. A hierarchical multiple logistic model was employed to investigate the association strengths reflected by adjusted odds ratios and 95% confidence. (3) Results: Multimorbidity occurred in 20.95% of the respondents. The graph of network analysis showed that there were 6 combinations of chronic diseases with strong association strengths and 14 with moderate association strengths. The results of the ARM were similar to the network analysis; six dyadic chronic disease combinations and six triadic ones were obtained. Hierarchical multiple logistic regression indicated that innate personal traits (age, history of genetics, and body mass index), behavioral lifestyle (physical activity levels and medication adherence), interpersonal network (marital status), and socioeconomic status (educational level) were the common predictors of multimorbidity for older adults, among which, having no family history was found to be a relative determinant as a protective factor for multimorbidity after controlling the other covariates. (4) Conclusions: multimorbidity was prevalent in older adults and most disease combinations are associated with hypertension, followed by diabetes. This shows that diabetes and hypertension have a high prevalence among older adults and have a wide range of associations with other chronic diseases. Exploring the patterns and associated factors of multimorbidity will help the country prevent complications and avoid the unnecessary use of the health service, adopting an integrated approach to managing multimorbidity rather than an individual disease-specific approach and implementing different strategies according to the location of residence.

Suggested Citation

  • Yiming Chen & Lei Shi & Xiao Zheng & Juan Yang & Yaqing Xue & Shujuan Xiao & Benli Xue & Jiachi Zhang & Xinru Li & Huang Lin & Chao Ma & Chichen Zhang, 2022. "Patterns and Determinants of Multimorbidity in Older Adults: Study in Health-Ecological Perspective," IJERPH, MDPI, vol. 19(24), pages 1-15, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:16756-:d:1002777
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    References listed on IDEAS

    as
    1. 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.
    2. Ying Pin Chua & Ying Xie & Poay Sian Sabrina Lee & Eng Sing Lee, 2021. "Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review," IJERPH, MDPI, vol. 18(4), pages 1-12, February.
    3. Grant Stafford & Noemí Villén & Albert Roso-Llorach & Amelia Troncoso-Mariño & Mònica Monteagudo & Concepción Violán, 2021. "Combined Multimorbidity and Polypharmacy Patterns in the Elderly: A Cross-Sectional Study in Primary Health Care," IJERPH, MDPI, vol. 18(17), pages 1-22, September.
    4. Trias Mahmudiono & Calista Segalita & Richard R. Rosenkranz, 2019. "Socio-Ecological Model of Correlates of Double Burden of Malnutrition in Developing Countries: A Narrative Review," IJERPH, MDPI, vol. 16(19), pages 1-23, October.
    5. Shan-Shan Yao & Xiangfei Meng & Gui-Ying Cao & Zi-Ting Huang & Zi-Shuo Chen & Ling Han & Kaipeng Wang & He-Xuan Su & Yan Luo & Yonghua Hu & Beibei Xu, 2020. "Associations between Multimorbidity and Physical Performance in Older Chinese Adults," IJERPH, MDPI, vol. 17(12), pages 1-14, June.
    6. Fangfang Hu & Lingzhong Xu & Jinling Zhou & Jiao Zhang & Zhaorong Gao & Zhuang Hong, 2020. "Association between Overweight, Obesity and the Prevalence of Multimorbidity among the Elderly: Evidence from a Cross-Sectional Analysis in Shandong, China," IJERPH, MDPI, vol. 17(22), pages 1-10, November.
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