Multimorbidity patterns and the association with health status of the oldest-old in long-term care facilities in China: a two-step analysis

被引:1
|
作者
Chen, Hong-Li [1 ]
Yu, Xiao-Hong [1 ]
Yin, Yue-Heng [1 ]
Shan, En-Fang [1 ]
Xing, Ying [1 ]
Min, Min [2 ,3 ]
Ding, Ya-Ping [1 ]
Fei, Yang [1 ]
Li, Xian-Wen [1 ]
机构
[1] Nanjing Med Univ, Sch Nursing, Nanjing, Jiangsu, Peoples R China
[2] Landsea Long Term Care Facil, Nanjing, Jiangsu, Peoples R China
[3] Xia Man Yun Jian Social Welf Dev Ctr, Shanghai, Peoples R China
关键词
Multimorbidity pattern; Health status; Oldest-old; Younger-old; Long-term care facility; QUALITY-OF-LIFE; CARDIOVASCULAR-DISEASE; INTERNATIONAL CLASSIFICATION; COGNITIVE IMPAIRMENT; KNEE OSTEOARTHRITIS; PARKINSONS-DISEASE; PREVALENCE; DISABILITY; DISORDERS; BALANCE;
D O I
10.1186/s12877-023-04507-8
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
BackgroundThe increasing prevalence of multimorbidity has created a serious global public health problem in aging populations. Certain multimorbidity patterns across different age ranges and their association with health status remain unclear. The main aim of this study is to identify multimorbidity patterns discrepancies and associated health status between younger-old and oldest-old.MethodsThe Ethics Committee of Nanjing Medical University approved the study protocol (No.2019-473). Convenience sampling method was used to recruit older adults aged >= 60 years with multimorbidity from July to December 2021 from 38 Landsea long-term care facilities in China. The multimorbidity patterns were analyzed using network analysis and two-step cluster analysis. One-Way ANOVA was utilized to explore their association with health status including body function, activity of daily living, and social participation. A Sankey diagram visualized the flow of health status within different multimorbidity patterns. This study is reported following the STROBE guidelines.ResultsA total of 214 younger-old (60-84 years) and 173 oldest-old (>= 85 years) were included. Leading coexisting diseases were cardiovascular disease (CD), metabolic and endocrine disease (MED), neurological disease (ND), and orthopedic disease (OD). Cluster 1 (53, 24.8%) of CD-ND (50, 94.3%; 31, 58.8%), cluster 2 (39, 18.2%) of MED-ND-CD (39, 100%; 39, 100%; 37, 94.9%), cluster 3 (37, 17.3%) of OD-CD-MED-ND (37, 100%; 33, 89.2%; 27, 73.0%; 16, 43.2%), and cluster 4 (34, 15.9%) of CD-MED (34, 100%; 34, 100%) were identified in the younger-old. In the oldest-old, the primary multimorbidity patterns were: cluster 1 (33, 19.1%) of CD-respiratory disease-digestive disease-urogenital disease (CD-RD-DSD-UD) (32, 97.0%; 9, 27.3%; 8, 24.2%; 7, 21.2%), cluster 2 (42, 24.3%) of ND-CD-MED (42, 100%; 35, 83.3%; 14, 33.3%), cluster 3 (28, 16.2%) of OD-CD-MED (28, 100%; 25, 89.3%; 18, 64.3%), and cluster 4 (35, 20.2%) of CD-MED (35, 100%; 35, 100%). Younger-old with CD-ND or MED-ND-CD, and oldest-old with ND-CD-MED have worse health status compared with other multimorbidity patterns (e.g., CD-MED and OD-CD-MED).ConclusionDiscrepancies in common patterns of multimorbidity across age groups suggest that caregivers in long-term care facilities should consider changes in multimorbidity patterns with ageing when developing prevention plans for individualized management. Neurological disease concurrent with other diseases was the major determinant of health status, especially for the oldest-old. Interventions targeting multimorbidity need to be focused, yet generic. It is essential to assess complex needs and health outcomes that arise from different multimorbidity patterns and manage them through an interdisciplinary approach and consider their priorities to gain high-quality primary care for older adults living in long-term care facilities.
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