全国代表性人群样本中的多重疾病与健康相关生活质量（HRQoL）：计数法与聚类法定义多重疾病对HRQoL的影响
Multimorbidity and health-related quality of life (HRQoL) in a nationally representative population sample: implications of count versus cluster method for defining multimorbidity on HRQoL.
作者信息
Wang Lili, Palmer Andrew J, Cocker Fiona, Sanderson Kristy
机构信息
Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool Street, Hobart, TAS, 7000, Australia.
Monash Centre for Occupation and Environmental Health (MonCOEH), Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia.
出版信息
Health Qual Life Outcomes. 2017 Jan 9;15(1):7. doi: 10.1186/s12955-016-0580-x.
BACKGROUND
No universally accepted definition of multimorbidity (MM) exists, and implications of different definitions have not been explored. This study examined the performance of the count and cluster definitions of multimorbidity on the sociodemographic profile and health-related quality of life (HRQoL) in a general population.
METHODS
Data were derived from the nationally representative 2007 Australian National Survey of Mental Health and Wellbeing (n = 8841). The HRQoL scores were measured using the Assessment of Quality of Life (AQoL-4D) instrument. The simple count (2+ & 3+ conditions) and hierarchical cluster methods were used to define/identify clusters of multimorbidity. Linear regression was used to assess the associations between HRQoL and multimorbidity as defined by the different methods.
RESULTS
The assessment of multimorbidity, which was defined using the count method, resulting in the prevalence of 26% (MM2+) and 10.1% (MM3+). Statistically significant clusters identified through hierarchical cluster analysis included heart or circulatory conditions (CVD)/arthritis (cluster-1, 9%) and major depressive disorder (MDD)/anxiety (cluster-2, 4%). A sensitivity analysis suggested that the stability of the clusters resulted from hierarchical clustering. The sociodemographic profiles were similar between MM2+, MM3+ and cluster-1, but were different from cluster-2. HRQoL was negatively associated with MM2+ (β: -0.18, SE: -0.01, p < 0.001), MM3+ (β: -0.23, SE: -0.02, p < 0.001), cluster-1 (β: -0.10, SE: 0.01, p < 0.001) and cluster-2 (β: -0.36, SE: 0.01, p < 0.001).
CONCLUSIONS
Our findings confirm the existence of an inverse relationship between multimorbidity and HRQoL in the Australian population and indicate that the hierarchical clustering approach is validated when the outcome of interest is HRQoL from this head-to-head comparison. Moreover, a simple count fails to identify if there are specific conditions of interest that are driving poorer HRQoL. Researchers should exercise caution when selecting a definition of multimorbidity because it may significantly influence the study outcomes.
背景
目前尚无关于多病共存（MM）的普遍接受的定义，不同定义的影响也未得到探讨。本研究考察了多病共存的计数和聚类定义在一般人群的社会人口学特征及健康相关生活质量（HRQoL）方面的表现。
方法
数据来源于具有全国代表性的2007年澳大利亚全国心理健康与幸福调查（n = 8841）。使用生活质量评估（AQoL - 4D）工具测量HRQoL得分。采用简单计数法（2种及以上和3种及以上疾病情况）和层次聚类法来定义/识别多病共存的聚类。使用线性回归评估不同方法定义的HRQoL与多病共存之间的关联。
结果
使用计数法定义的多病共存评估结果显示，患病率为26%（MM2 +）和10.1%（MM3 +）。通过层次聚类分析确定的具有统计学意义的聚类包括心脏或循环系统疾病（CVD）/关节炎（聚类1，9%）和重度抑郁症（MDD）/焦虑症（聚类2，4%）。敏感性分析表明聚类的稳定性源于层次聚类。MM2 +、MM3 +和聚类1之间的社会人口学特征相似，但与聚类2不同。HRQoL与MM2 +（β： - （此处原文有误，推测应为 - 0.18），SE： - 0.01，p < 0.001）、MM3 +（β： - 0.23，SE： - 0.02，p < 0.001）、聚类1（β： - 0.10，SE：0.01，p < 0.001）和聚类2（β： - 0.36，SE：0.01，p < 0.001）呈负相关。
结论
我们的研究结果证实了澳大利亚人群中多病共存与HRQoL之间存在负相关关系，并表明当关注的结果是HRQoL时，通过这种直接比较，层次聚类方法是有效的。此外，简单计数法无法确定是否存在导致HRQoL较差的特定关注疾病情况。研究人员在选择多病共存的定义时应谨慎，因为它可能会显著影响研究结果。
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