Tan Michelle M C, Hanlon Charlotte, Muniz-Terrera Graciela, Benaglia Tatiana, Ismail Roshidi, Mohan Devi, Konkoth Ann Breeze Joseph, Reidpath Daniel, Pinho Pedro José M Rebello, Allotey Pascale, Kassim Zaid, Prina Matthew, Su Tin Tin
Department of Health Service and Population Research, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, De Crespigny Park, London, UK.
Global Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Sunway City, Selangor, Malaysia.
BMC Med. 2025 Jan 6;23(1):5. doi: 10.1186/s12916-024-03796-z.
We aimed to identify specific multimorbidity latent classes among multi-ethnic community-dwelling adults aged ≥ 18 years in Malaysia. We further explored the risk factors associated with these patterns and examined the relationships between the multimorbidity patterns and 11-year all-cause mortality risk, as well as health-related quality of life (HRQoL).
Using data from 18,101 individuals (aged 18-97 years) from the baseline Census 2012, Health Round 2013, and Verbal Autopsies 2012-2023 of the South East Asia Community Observatory (SEACO) health and demographic surveillance system, latent class analysis was performed on 13 chronic health conditions to identify statistically and clinically meaningful groups. Multinomial logistic regression and Cox proportional hazards regression models were conducted to investigate the adjusted association of multimorbidity patterns with the risk factors and mortality, respectively. HRQoL was analyzed by linear contrasts in conjunction with ANCOVA adjusted for baseline confounders.
Four distinct multimorbidity latent classes were identified: (1) relatively healthy (n = 10,640); (2) cardiometabolic diseases (n = 2428); (3) musculoskeletal, mobility and sensory disorders (n = 2391); and (4) complex multimorbidity (a group with more severe multimorbidity with combined profiles of classes 2 and 3) (n = 699). Significant variations in associations between socio-demographic characteristics and multimorbidity patterns were discovered, including age, sex, ethnicity, education level, marital status, household monthly income and employment status. The complex multimorbidity group had the lowest HRQoL across all domains compared to other groups (p < 0.001), including physical health, psychological, social relationships and environment. This group also exhibited the highest mortality risk over 11 years even after adjustment of confounders (age, sex, ethnicity, education and employment status), with a hazard of death of 1.83 (95% CI 1.44-2.33), followed by the cardiometabolic group (HR 1.42, 95% CI 1.18-1.70) and the musculoskeletal, mobility and sensory disorders group (HR 1.29, 95% CI 1.04-1.59).
Our study advances the understanding of the complexity of multimorbidity and its implications for health outcomes and healthcare delivery. The findings suggest the need for integrated healthcare approaches that account for the clusters of multiple conditions and prioritize the complex multimorbidity cohort. Further longitudinal studies are warranted to explore the underlying mechanisms and evolution of multimorbidity patterns.
我们旨在确定马来西亚年龄≥18岁的多民族社区居住成年人中的特定多病共患潜在类别。我们进一步探讨了与这些模式相关的风险因素，并研究了多病共患模式与11年全因死亡风险以及健康相关生活质量（HRQoL）之间的关系。
利用东南亚社区观察站（SEACO）健康和人口监测系统2012年基线普查、2013年健康调查以及2012 - 2023年死因口头尸检中的18101名个体（年龄18 - 97岁）的数据，对13种慢性健康状况进行潜在类别分析，以确定具有统计学和临床意义的组。分别进行多项逻辑回归和Cox比例风险回归模型，以研究多病共患模式与风险因素和死亡率的调整后关联。通过线性对比结合对基线混杂因素进行调整的协方差分析来分析HRQoL。
确定了四个不同的多病共患潜在类别：（1）相对健康（n = 10640）；（2）心血管代谢疾病（n = 2428）；（3）肌肉骨骼、运动和感觉障碍（n = 2391）；以及（4）复杂多病共患（一类具有更严重多病共患情况，合并了第2类和第3类特征）（n = 699）。发现社会人口学特征与多病共患模式之间的关联存在显著差异，包括年龄、性别、种族、教育水平、婚姻状况、家庭月收入和就业状况。与其他组相比，复杂多病共患组在所有领域的HRQoL最低（p < 0.001），包括身体健康、心理、社会关系和环境。即使在调整混杂因素（年龄、性别、种族、教育和就业状况）后，该组在11年期间也表现出最高的死亡风险，死亡风险为1.83（95%CI 1.44 - 2.33），其次是心血管代谢组（HR 1.42，95%CI 1.18 - 1.70）和肌肉骨骼、运动和感觉障碍组（HR 1.29，95%CI 1.04 - 1.59）。
我们的研究推进了对多病共患复杂性及其对健康结果和医疗服务影响的理解。研究结果表明需要综合医疗方法，该方法应考虑多种疾病的聚集情况，并将复杂多病共患队列作为优先事项。有必要进行进一步的纵向研究，以探索多病共患模式的潜在机制和演变。
