Background: Past studies have demonstrated how single non-communicable diseases (NCDs) affect health care utilisation and quality of life (QoL), but not how different NCD combinations interact to affect these. Our study aims to investigate the prevalence of NCD dyad and triad combinations, and the implications of different NCD dyad combinations on health care utilisation and QoL.
Methods: Our study utilised cross-sectional data from the WHO SAGE study to examine the most prevalent NCD combinations in six large middle-income countries (MICs). Subjects were mostly aged 50 years and above, with a smaller proportion aged 18 to 49 years. Multivariable linear regression was applied to investigate which NCD dyads increased or decreased health care utilisation and QoL, compared with subjects with only one NCD.
Results: The study included 41 557 subjects. Most prevalent NCD combinations differed by subgroups, including age, gender, income, and residence (urban vs rural). Diabetes, stroke, and depression had the largest effect on increasing mean number of outpatient visits, increasing mean number of hospitalisation days, and decreasing mean QoL scores, respectively. Out of the 36 NCD dyads in our study, thirteen, four, and five dyad combinations were associated with higher or lower mean number of outpatient visits, mean number of hospitalisations, or mean QoL scores, respectively, compared with treating separate patients with one NCD each. Dyads of depression were associated with fewer mean outpatient visits, more hospitalisations, and lower mean QoL scores, compared to patients with one NCD. Dyads of hypertension and diabetes were also associated with a reduced mean number of outpatient visits.
Conclusions: Certain NCD combinations increase or decrease health care utilisation and QoL substantially more than treating separate patients with one NCD each. Health systems should consider the needs of patients with different multimorbidity patterns to effectively respond to the demands on health care utilisation and to mitigate adverse effects on QoL.