Identifying co-occurrence and clustering of chronic diseases using latent class analysis: cross-sectional findings from SAGE South Africa Wave 2

Chidumwa, Glory; Maposa, Innocent; Corso, Barbara; Minicuci, Nadia; Kowal, Paul; Micklesfield, Lisa K.; Ware, Lisa J.

doi:10.1136/bmjopen-2020-041604

Cited by 13 publications

(27 citation statements)

References 32 publications

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“…The comorbidity clusters identi ed in our study are similar to those in previous studies (39,40). A systematic review of comorbidity patterns from 39 studies conducted in 12 countries identi ed hypertension and arthritis as the most frequent comorbidity combination (40).…”

Section: Discussionsupporting

confidence: 86%

“…A systematic review of comorbidity patterns from 39 studies conducted in 12 countries identi ed hypertension and arthritis as the most frequent comorbidity combination (40). Another study conducted in South Africa found two distinct comorbidity clusters comprising hypertension and diabetes and cardiopulmonary diseases such as angina, asthma and chronic lung disease (39). In our study, 72.3% of the participants were classi ed under minimal comorbidity, 18.9% under hypertension and arthritis class and 8.9% under cardiopulmonary class.…”

Section: Discussionmentioning

confidence: 44%

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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

Otieno

Asiki

Wilunda

et al. 2022

Preprint

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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.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 44%

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

Otieno

Asiki

Wilunda

et al. 2022

Preprint

View full text Add to dashboard Cite

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“…The largest disease class in our study was "Diabetes and Hypertension." This combination of diseases has been previously identified in the literature both regionally [53][54][55][56] and internationally [57]. A multi-country study based in sub-Saharan Africa found that hypertension was the most common co-morbidity in a cohort of diabetes patients and was present in approximately 71% of patients with diabetes [58].…”

Section: Discussionmentioning

confidence: 58%

Inequity in the Distribution of Non-Communicable Disease Multimorbidity in Adults in South Africa: An Analysis of Prevalence and Patterns

Roomaney¹,

Wyk²,

Cois

et al. 2022

Int J Public Health

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Objectives: The present study examined the prevalence and patterns of non-communicable disease multimorbidity by wealth quintile among adults in South Africa.Methods: The South African National Income Dynamics Study Wave 5 was conducted in 2017 to examine the livelihoods of individuals and households. We analysed data in people aged 15 years and older (N = 27,042), including self-reported diagnosis of diabetes, stroke, heart disease and anthropometric measurements. Logistic regression and latent class analysis were used to analyse factors associated with multimorbidity and common disease patterns.Results: Multimorbidity was present in 2.7% of participants. Multimorbidity was associated with increasing age, belonging to the wealthiest quintile group, increasing body mass index and being a current smoker. Having secondary education was protective against multimorbidity. Three disease classes of multimorbidity were identified: Diabetes and Hypertension; Heart Disease and Hypertension; and Stroke and Hypertension.Conclusion: Urgent reforms are required to improve health systems responsiveness to mitigate inequity in multimorbidity patterns in the adult population of South Africa as a result of income inequality.

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“…depression, cognitive impairment, edentulism and obesity as a disease condition) and therefore reported higher prevalence of multimorbidity. A recent analysis of Wave 2 SAGE (2014/2015) [ 47 ] of adults aged 45 years and older, included fewer disease conditions than Garin et al . [ 20 ] (7 vs. 12); reported a multimorbidity prevalence of 21%.…”

Section: Discussionmentioning

confidence: 99%

One in five South Africans are multimorbid: An analysis of the 2016 demographic and health survey

et al. 2022

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Multimorbidity is a global research priority, yet relatively little is known about it in low and middle income countries. South Africa has the largest burden of HIV worldwide but also has a growing burden of non-communicable diseases; potentially leading to uncommon disease combinations. Information about the prevalence of multimorbidity and factors associated with it can assist in healthcare planning and targeting groups of people for interventions. This study aimed to determine the prevalence of multimorbidity by age and sex, as well as factors associated with multimorbidity in people 15 years and older. This study analyses the nationally representative 2016 South African Demographic Health Survey. The sample included 10 336 people who participated in the Adult Health questionnaire and approximately 7 961 people who provided biomarkers. Multivariate logistic regression was used to measure the association of multimorbidity with age, sex, living in an urban or rural area, education level, wealth level, employment status, body mass index, current alcohol or tobacco use. All analyses were conducted using STATA 15. Multimorbidity was present in 20.7% (95% CI: 19.5%– 21.9%) of participants; in 14.8% (95% CI: 13.4% - 16.3%) of males and 26.2% (95% CI: 24.7–27.7%) of females. Multimorbidity increased with age; with the highest odds in the 55–64 years old age group (OR: 24.910, 95% CI: 14.901–41.641, p < 0.001) compared to those aged 15–24 years. The odds of multimorbidity was also higher in young females compared to young males (OR: 2.734, 95% CI: 1.50–4.99, p = 0.001). Possessing tertiary education (OR: 0.722, 95% CI: 0.537–0.97, p = 0.031), being employed (OR: 0.813, 95% CI: 0.675–0.979, p = 0.029) or currently using alcohol (OR: 0.815, 95% CI: 0.686–0.968, p = 0.02) was protective against multimorbidity. Multimorbidity is prevalent within the South African population, with females and older adults being most affected. However, multimorbidity is also observed in younger adults and most likely driven by the high prevalence of HIV and hypertension.

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Identifying co-occurrence and clustering of chronic diseases using latent class analysis: cross-sectional findings from SAGE South Africa Wave 2

Cited by 13 publications

References 32 publications

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

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

Inequity in the Distribution of Non-Communicable Disease Multimorbidity in Adults in South Africa: An Analysis of Prevalence and Patterns

One in five South Africans are multimorbid: An analysis of the 2016 demographic and health survey

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