Multimorbidity and Comorbidity of Chronic Diseases among the Senior Australians: Prevalence and Patterns
Multimorbidity and Comorbidity of Chronic Diseases among the Senior Australians: Prevalence and Patterns
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DOI：
10.1371/journal.pone.0083783
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发表时间：
2014-01-08
期刊：
影响因子：
3.7
通讯作者：
McRae, Ian S.
中科院分区：
文献类型：
--
作者：
Islam, M. Mofizul;Valderas, Jose M.;McRae, Ian S.
了解慢性病的模式和识别常见的慢性病集群可以帮助政策制定者，研究人员和临床医生更好地了解护理过程的需求，并可能节省提供者和患者的时间和成本。然而，只有有限的研究已经在这一领域进行，和模糊性仍然存在，因为这些有限的以前的研究使用不同的方法来确定共同的集群和结果可能会有所不同的方法。本研究使用四种方法估计常见慢性病的患病率并检查疾病的共病：（i）识别最常见的共病对和三联体;（ii）进行疾病聚类分析，（iii）主成分分析，（iv）潜在类别分析。数据收集使用问卷邮寄到一个横截面样本的老年澳大利亚人，4574个答复。82%的受访者报告至少患有一种慢性疾病，超过52%的受访者报告至少患有两种慢性疾病。患有任何慢性疾病的受访者平均有2.4种共病。确定了三个确定的慢性病组：（i）哮喘、支气管炎、关节炎、骨质疏松症和抑郁症;（ii）高血压和糖尿病;（iii）癌症，心脏病和中风在不同的分析中单独组成一组或“附属”于不同的组。这些群体在各种方法中基本上是一致的。稳定性和敏感性分析也支持各组的一致性。研究结果的一致性表明，疾病的共同发生超出了偶然性，共同发生的模式对临床医生，患者，政策制定者和研究人员都很重要。需要进一步的研究提供强有力的证据基础，以确定共病群体，这将受益于适当的指导方针，为护理和管理的患者与特定的疾病集群。
Understanding patterns and identifying common clusters of chronic diseases may help policymakers, researchers, and clinicians to understand the needs of the care process better and potentially save both provider and patient time and cost. However, only limited research has been conducted in this area, and ambiguity remains as those limited previous studies used different approaches to identify common clusters and findings may vary with approaches. This study estimates the prevalence of common chronic diseases and examines co-occurrence of diseases using four approaches: (i) identification of the most occurring pairs and triplets of comorbid diseases; performing (ii) cluster analysis of diseases, (iii) principal component analysis, and (iv) latent class analysis. Data were collected using a questionnaire mailed to a cross-sectional sample of senior Australians, with 4574 responses. Eighty-two percent of respondents reported having at least one chronic disease and over 52% reported having at least two chronic diseases. Respondents suffering from any chronic diseases had an average of 2.4 comorbid diseases. Three defined groups of chronic diseases were identified: (i) asthma, bronchitis, arthritis, osteoporosis and depression; (ii) high blood pressure and diabetes; and (iii) cancer, with heart disease and stroke either making a separate group or "attaching" themselves to different groups in different analyses. The groups were largely consistent across the approaches. Stability and sensitivity analyses also supported the consistency of the groups. The consistency of the findings suggests there is co-occurrence of diseases beyond chance, and patterns of co-occurrence are important for clinicians, patients, policymakers and researchers. Further studies are needed to provide a strong evidence base to identify comorbid groups which would benefit from appropriate guidelines for the care and management of patients with particular disease clusters.