» Articles » PMID: 33514578

Identifying Co-occurrence and Clustering of Chronic Diseases Using Latent Class Analysis: Cross-sectional Findings from SAGE South Africa Wave 2

Overview
Journal BMJ Open
Specialty General Medicine
Date 2021 Jan 30
PMID 33514578
Citations 10
Authors
Affiliations
Soon will be listed here.
Abstract

Objectives: To classify South African adults with chronic health conditions for multimorbidity (MM) risk, and to determine sociodemographic, anthropometric and behavioural factors associated with identified patterns of MM, using data from the WHO's Study on global AGEing and adult health South Africa Wave 2.

Design: Nationally representative (for ≥50-year-old adults) cross-sectional study.

Setting: Adults in South Africa between 2014 and 2015.

Participants: 1967 individuals (men: 623 and women: 1344) aged ≥45 years for whom data on all seven health conditions and socioeconomic, demographic, behavioural, and anthropological information were available.

Measures: MM latent classes.

Results: The prevalence of MM (coexistence of two or more non-communicable diseases (NCDs)) was 21%. The latent class analysis identified three groups namely: minimal MM risk (83%), concordant (hypertension and diabetes) MM (11%) and discordant (angina, asthma, chronic lung disease, arthritis and depression) MM (6%). Using the minimal MM risk group as the reference, female (relative risk ratio (RRR)=4.57; 95% CI (1.64 to 12.75); p =0.004) and older (RRR=1.08; 95% CI (1.04 to 1.12); p<0.001) participants were more likely to belong to the concordant MM group, while tobacco users (RRR=8.41; 95% CI (1.93 to 36.69); p=0.005) and older (RRR=1.09; 95% CI (1.03 to 1.15); p=0.002) participants had a high likelihood of belonging to the discordant MM group.

Conclusion: NCDs with similar pathophysiological risk profiles tend to cluster together in older people. Risk factors for MM in South African adults include sex, age and tobacco use.

Citing Articles

Caring for the "Osteo-Cardiovascular Faller": Associations between Multimorbidity and Fall Transitions among Middle-Aged and Older Chinese.

Yu M, Ren L, Yang R, Jiang Y, Cui S, Wang J Health Data Sci. 2025; 5:0151.

PMID: 39973978 PMC: 11836196. DOI: 10.34133/hds.0151.


Latent class analysis of chronic disease co-occurrence, clustering and their determinants in India using Study on global AGEing and adult health (SAGE) India Wave-2.

Shri N, Singh S, Singh S J Glob Health. 2024; 14:04079.

PMID: 38940270 PMC: 11212113. DOI: 10.7189/jogh.14.04079.


A pathological convergence theory for non-communicable diseases.

Padron-Monedero A Aging Med (Milton). 2024; 6(4):328-337.

PMID: 38239708 PMC: 10792334. DOI: 10.1002/agm2.12273.


Cardiometabolic multimorbidity 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 P, Asiki G, Wilunda C, Wami W, Agyemang C PLOS Glob Public Health. 2023; 3(8):e0002215.

PMID: 37585386 PMC: 10431646. DOI: 10.1371/journal.pgph.0002215.


Social determinants of multimorbidity patterns: A systematic review.

Alvarez-Galvez J, Ortega-Martin E, Carretero-Bravo J, Perez-Munoz C, Suarez-Lledo V, Ramos-Fiol B Front Public Health. 2023; 11:1081518.

PMID: 37050950 PMC: 10084932. DOI: 10.3389/fpubh.2023.1081518.


References
1.
Ware L, Chidumwa G, Charlton K, Schutte A, Kowal P . Predictors of hypertension awareness, treatment and control in South Africa: results from the WHO-SAGE population survey (Wave 2). J Hum Hypertens. 2018; 33(2):157-166. DOI: 10.1038/s41371-018-0125-3. View

2.
Lalkhen H, Mash R . Multimorbidity in non-communicable diseases in South African primary healthcare. S Afr Med J. 2015; 105(2):134-8. DOI: 10.7196/samj.8696. View

3.
Afshar S, Roderick P, Kowal P, Dimitrov B, Hill A . Multimorbidity and the inequalities of global ageing: a cross-sectional study of 28 countries using the World Health Surveys. BMC Public Health. 2015; 15:776. PMC: 4534141. DOI: 10.1186/s12889-015-2008-7. View

4.
Mahomed O, Asmall S . Professional nurses' perceptions and experiences with the implementation of an integrated chronic care model at primary healthcare clinics in South Africa. Curationis. 2017; 40(1):e1-e6. PMC: 6091616. DOI: 10.4102/curationis.v40i1.1708. View

5.
Schouw D, Mash R, Kolbe-Alexander T . Transforming the workplace environment to prevent non-communicable chronic diseases: participatory action research in a South African power plant. Glob Health Action. 2018; 11(1):1544336. PMC: 6263095. DOI: 10.1080/16549716.2018.1544336. View