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Quality of life and multiple long-term conditions in Southeast Asia: a systematic review and meta-analysis
Quality of life and multiple long-term conditions in Southeast Asia: a systematic review and meta-analysis
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Quality of life and multiple long-term conditions in Southeast Asia: a systematic review and meta-analysis
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Quality of life and multiple long-term conditions in Southeast Asia: a systematic review and meta-analysis
Quality of life and multiple long-term conditions in Southeast Asia: a systematic review and meta-analysis

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Quality of life and multiple long-term conditions in Southeast Asia: a systematic review and meta-analysis
Quality of life and multiple long-term conditions in Southeast Asia: a systematic review and meta-analysis
Journal Article

Quality of life and multiple long-term conditions in Southeast Asia: a systematic review and meta-analysis

2026
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Overview
This review systematically synthesised the evidence on quality of life measures and outcomes for people living with multiple long-term conditions in the Southeast Asia region. Results were analysed using a combination of methods, meta-analysis for studies where the same quality of life score was reported across three or more cohorts, and descriptive narrative synthesis. In total, 34 studies comprising 11,876 participants were included in the narrative synthesis and 14 of these were included in meta-analysis. The most common quality of life tools used included WHOQOL-BREF ( n  = 8) and EQ-5D-5L ( n  = 3) with pooled mean values of 70.47 (95% CI: 62.71 to 78.24) and 0.76 (95% CI: 0.67 to 0.84) respectively, indicating reduced but good quality of life. As healthcare systems adapt to the evolving challenges associated with multiple long-term conditions, understanding the tools and measures used to assess quality of life in different contexts becomes imperative to account for disease combinations and cultural nuances. People living with multiple long-term conditions often experience reduced quality of life, but evidence from Southeast Asia is fragmented. Here the authors show that commonly used tools indicate moderately reduced yet generally good quality of life, highlighting the need for context-sensitive measurement approaches.