Scholarlink

Introduction <p>Rural South Africa is undergoing an epidemiological transition characterised by rising mortality from chronic non-communicable diseases (NCDs) alongside that from persistent infectious diseases. We aimed to investigate trends in the prevalence of chronic disease and multimorbidity clustering among deceased individuals in rural northeast South Africa from 2012 to 2022.</p> Methods <p>Verbal autopsy data for 5,892 deceased individuals collected from the Agincourt Health and socio-Demographic Surveillance System (HDSS) study area in Bushbuckridge, Mpumalanga Province, from 2012 to 2022 were analysed. We identified reported chronic diseases prior to death and applied cluster analysis, partitioning around medoids (PAM) and latent class analysis (LCA) to identify patterns of co-occurring diseases (multimorbidity clusters). Temporal trends in disease prevalence were assessed using descriptive statistics. Multinomial logistic regression models were used to examine associations of cluster membership with various behavioral factors.</p> Results <p>Over the 11-year period, the prevalence of hypertension among the deceased individuals rose from approximately 25% in 2012 to over 50% by 2022, that of diabetes increased from 10% and reached ~ 25% and that of dementia increased from 1% to over 5%. In contrast, the number of deaths that were reported to have had tuberculosis prior to their deaths declined markedly TB reducing from 23% to 11%. HIV prevalence fluctuated within a narrow range around 20% (approximately 18–22%). The proportion of deceased individuals with multimorbidity (≥ 2 chronic conditions) increased, and complex multimorbidity (≥ 3 conditions) nearly doubled between 2012 and 2019 (from 8% to 15%), with relative stability observed in the 2020–2022 period. Over time, multimorbidity clusters shifted from an initial dominance of HIV/TB comorbidity to later patterns dominated by cardiometabolic conditions (hypertension and diabetes), HIV–hypertension, and an emerging neurodegenerative illnesses cluster. Older adults (≥ 65 years) and females experienced the highest multimorbidity burden and were more likely to belong to complex disease clusters.</p> Conclusions <p>Morbidity patterns in this rural population have shifted toward chronic NCDs and multimorbidity. Characterising these trends and identifying disease clusters is essential for targeting patient-centred care early on. Our findings underscore the importance of integrating care for NCDs and infectious diseases in rural health systems to address the growing multimorbidity burden, with particular focus on older adults and women.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Evolution of chronic diseases and multimorbidity clusters among the deceased in rural northeast South Africa (2012–2022): insights from verbal autopsy data

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月23日

查看全文
  • Cyril Tamuka Chironda,
  • Tobias Chirwa,
  • Farai Mlambo,
  • Rumbidzai Mupfuti,
  • Daniel Ohene-Kwofie,
  • Belinda J Njiro,
  • Jean Juste Harrisson Bashingwa,
  • Stephen Tollman,
  • Kathleen Kahn,
  • F. Xavier Gomez-Olive,
  • Chodziwadziwa. W. Kabudula

摘要

Introduction

Rural South Africa is undergoing an epidemiological transition characterised by rising mortality from chronic non-communicable diseases (NCDs) alongside that from persistent infectious diseases. We aimed to investigate trends in the prevalence of chronic disease and multimorbidity clustering among deceased individuals in rural northeast South Africa from 2012 to 2022.

Methods

Verbal autopsy data for 5,892 deceased individuals collected from the Agincourt Health and socio-Demographic Surveillance System (HDSS) study area in Bushbuckridge, Mpumalanga Province, from 2012 to 2022 were analysed. We identified reported chronic diseases prior to death and applied cluster analysis, partitioning around medoids (PAM) and latent class analysis (LCA) to identify patterns of co-occurring diseases (multimorbidity clusters). Temporal trends in disease prevalence were assessed using descriptive statistics. Multinomial logistic regression models were used to examine associations of cluster membership with various behavioral factors.

Results

Over the 11-year period, the prevalence of hypertension among the deceased individuals rose from approximately 25% in 2012 to over 50% by 2022, that of diabetes increased from 10% and reached ~ 25% and that of dementia increased from 1% to over 5%. In contrast, the number of deaths that were reported to have had tuberculosis prior to their deaths declined markedly TB reducing from 23% to 11%. HIV prevalence fluctuated within a narrow range around 20% (approximately 18–22%). The proportion of deceased individuals with multimorbidity (≥ 2 chronic conditions) increased, and complex multimorbidity (≥ 3 conditions) nearly doubled between 2012 and 2019 (from 8% to 15%), with relative stability observed in the 2020–2022 period. Over time, multimorbidity clusters shifted from an initial dominance of HIV/TB comorbidity to later patterns dominated by cardiometabolic conditions (hypertension and diabetes), HIV–hypertension, and an emerging neurodegenerative illnesses cluster. Older adults (≥ 65 years) and females experienced the highest multimorbidity burden and were more likely to belong to complex disease clusters.

Conclusions

Morbidity patterns in this rural population have shifted toward chronic NCDs and multimorbidity. Characterising these trends and identifying disease clusters is essential for targeting patient-centred care early on. Our findings underscore the importance of integrating care for NCDs and infectious diseases in rural health systems to address the growing multimorbidity burden, with particular focus on older adults and women.