Impact of multimorbidity on change in quality of life in a multi-ethnic Asian population: a longitudinal study

BACKGROUND: The increasing burden of multimorbidity is associated with a risk of poorer health outcomes and mortality; however, evidence on its long-term impact on quality of life (QoL) remains limited. This study aims to explore the association of multimorbidity and multimorbidity clusters with QoL over a five-year period in a multiethnic, semi-rural cohort across different age groups. METHODS: This study utilized two-wave data from 8280 participants aged 18 years and above, collected as part of health surveys in 2013 and 2018 at the South East Asia Community Observatory (SEACO) Health and Demographic Surveillance System (HDSS) site in Malaysia. Multimorbidity was defined as having two or more of the following eight self-reported chronic conditions: diabetes, hypertension, heart disease, stroke, kidney disease (chronic kidney disease, end-stage renal failure), arthritis, asthma, and obesity. QoL was assessed using the WHOQOL-BREF, a 26-item questionnaire comprising four domains (physical, psychological, social relationships, and environmental health). Multivariable linear regression models were used for both count and clusters of chronic conditions to evaluate the association between multimorbidity and change in QoL over 5 years. RESULTS: At baseline, multimorbidity was significantly associated with better QoL in the social relationships domain only. Multimorbidity at baseline was not significantly associated with the change in QoL over 5 years across any age group. Two clusters of multimorbidity were identified: [1] cardiometabolic and musculoskeletal conditions and [2] cardiorespiratory and renal conditions. Among younger adults (18–34 years), cluster 1 was associated with improvement in the psychological domain (ß: 4.54, SE: 2.25, p-value = 0.03), whereas among adults (35–59 years), cluster 2 was associated with a decline in social relationships (ß: -6.57, SE: 2.87, p-value = 0.01). CONCLUSIONS: The study findings highlight that clinicians and policymakers need to focus on developing age-tailored interventions. Moreover, a simple count of chronic conditions fails to fully capture whether a certain group of conditions is resulting in a decline in QoL. Therefore, a cluster-based approach could provide a more useful insight.