Cardiometabolic comorbidities and associated patterns of healthcare utilization and quality of life: results from the Study on Global AGEing and Adult Health (SAGE) Wave 2 in Ghana

Abstract

Abstract Background Understanding the patterns of comorbidities, defined as the co-occurrence of more than one chronic condition, is important for planning health system capacity and response. In this study, we identified classes of adults with cardiometabolic comorbidities and assessed the association of different comorbidity combinations with healthcare utilization and quality of life (QoL). Methods Data were from the World Health Organization (WHO) study on global AGEing and adult health Wave 2 (2015) conducted in Ghana. We analysed the clustering of cardiometabolic diseases including angina, stroke, diabetes, and hypertension with unrelated conditions such as asthma, chronic lung disease, arthritis, cataract and depression. Healthcare utilization was measured as the frequency of outpatient visits and hospitalization in the past 12 months. The QoL index was constructed using the WHOQoL instrument and recorded in tertiles labelled as poor, moderate and high. The clusters of adults with comorbidities were identified using latent class analysis (LCA). We used negative binomial regression and ordinal logistic regression to determine the association of comorbidity combinations with healthcare utilization and QoL. Results Data from 1,538 adults aged over 50 years who had used outpatient care in the 12 months preceding the survey were analysed. LCA identified three distinct patterns of comorbidities: minimal cardiometabolic comorbidities (72.3%), hypertension and arthritis (18.9%), and cardiopulmonary diseases, hypertension, angina, chronic lung disease, and asthma (8.9%). Relative to the minimal comorbidity class, hypertension and arthritis comorbidity was associated with a higher frequency of outpatient visits [β = 0.2; 95% CI 0.1 to 0.4] and hospitalization [β = 0.7; 95% CI 0.2 to 1.2]. However, cardiopulmonary comorbidity was associated with a higher frequency of hospitalization [β = 1.1; 95% CI 0.2 to 1.9] and not outpatient visits. Compared to the participants with minimal cardiometabolic comorbidities, the odds of moderate and high quality of life were lower among participants with hypertension and arthritis comorbidity [aOR = 0.5; 95% CI 0.3 to 0.6] and cardiopulmonary comorbidities [aOR = 0.3; 95% CI 0.2 to 0.5]. Conclusion Our findings show that cardiometabolic comorbidities among older persons in Ghana cluster together in distinct patterns that differ in healthcare utilization. This evidence may be used in healthcare planning to optimize treatment and care.