Modelling healthy ageing in South Africa: a network analysis of intrinsic capacities.

Background The rapidly increasing older adult population in sub-Saharan Africa necessitates an understanding of how health domains interact to shape healthy ageing. Existing approaches overlook complex interdependencies between cognitive, physical, emotional, and functional capacities. This study ap...

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Publicado en:Age & Ageing Vol. 55; no. 3; pp. 1 - 10
Autores principales: Ugwu, Lawrence Ejike, Idemudia, Erhabor Sunday
Formato: Artículo
Publicado: Oxford University Press / USA Mar2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2026
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      pub: Oxford University Press / USA
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        10.1093/ageing/afag074
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        atl: Modelling healthy ageing in South Africa: a network analysis of intrinsic capacities.
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        au:
          Ugwu, Lawrence Ejike
          Idemudia, Erhabor Sunday
        affil:
          North-West University - Mafikeng Campus – Humanities, Humanities, North-West University, Mafikeng South Africa, North West Province, Mahikeng 2790, South AfricaCentre for Applied Psychology and Public Health Research in Africa (CAPPHRA), Enugu, 400001, Nigeria
          North-West University - Mafikeng Campus – Humanities, Humanities, North-West University, Mafikeng South Africa, North West Province, Mahikeng 2790, South Africa
      su:
        South Africa
        Self-evaluation
        Cross-sectional method
        Sex distribution
        Socioeconomic factors
        Emotions
        Physical fitness
        Active aging
        Activities of daily living
        Mental depression
        Statistical models
        Cognitive testing
        Center for Epidemiologic Studies Depression Scale
        Descriptive statistics
        Gait in humans
        Longitudinal method
        Geriatric assessment
        Cognition disorders
        Data analysis software
        Grip strength
        Sensitivity & specificity (Statistics)
      sug:
        subj:
          Self-evaluation
          Cross-sectional method
          Sex distribution
          Socioeconomic factors
          Emotions
          Physical fitness
          Active aging
          Activities of daily living
          Mental depression
          South Africa
          Fitness and Recreational Sports Centers
          Statistical models
          Cognitive testing
          Center for Epidemiologic Studies Depression Scale
          Descriptive statistics
          Gait in humans
          Longitudinal method
          Geriatric assessment
          Cognition disorders
          Data analysis software
          Grip strength
          Sensitivity & specificity (Statistics)
      keyword:
        activities of daily living
        activities of daily living (ADL)
        africa south of the sahara
        cognition
        cognitive ability
        cognitive function
        copyrightHolder:British Geriatrics Society
        copyrightYear:2026
        depressive disorders
        emotions
        functional ability
        gender
        gender differences
        healthy aging
        https://dx.doi.org/10.1093/ageing/afag074
        inLanguage:en
        intrinsic capacity
        mental processes
        mental recall
        network analysis
        older adult
        older people
        physical function
        publisher:Oxford University Press
        rural health
        sameAs:https://pubmed.ncbi.nlm.nih.gov/41934515/
        socioeconomic factors
        south africa
        sub-Saharan Africa
        world health organization
        activities of daily living
        activities of daily living (ADL)
        africa south of the sahara
        cognition
        cognitive ability
        cognitive function
        copyrightHolder:British Geriatrics Society
        copyrightYear:2026
        depressive disorders
        emotions
        functional ability
        gender
        gender differences
        healthy aging
        https://dx.doi.org/10.1093/ageing/afag074
        inLanguage:en
        intrinsic capacity
        mental processes
        mental recall
        network analysis
        older adult
        older people
        physical function
        publisher:Oxford University Press
        rural health
        sameAs:https://pubmed.ncbi.nlm.nih.gov/41934515/
        socioeconomic factors
        south africa
        sub-Saharan Africa
        world health organization
      ab: Background The rapidly increasing older adult population in sub-Saharan Africa necessitates an understanding of how health domains interact to shape healthy ageing. Existing approaches overlook complex interdependencies between cognitive, physical, emotional, and functional capacities. This study applies network analysis to model these relationships in a large cohort of older adults in rural South Africa. Methods We analysed data from 4783 participants (aged ≥40) in the 2021–2022 wave of the HAALSI study. Mixed Graphical Models (MGMs) were estimated from a mixed correlation matrix to assess conditional associations among 12 variables spanning cognitive function, depressive symptoms, physical capacity, self-rated health, and socioeconomic status. Central and bridge nodes were identified, and gender-stratified networks were compared. Results The network revealed strong interconnectivity among intrinsic capacity domains. Cognitive function (delayed recall) and functional ability (ADL limitations) emerged as the most central nodes, with self-rated health and depressive symptoms as key bridges. While global network strength and structure did not differ significantly by gender, men's networks were anchored around cognitive function, whereas women's were more centred on physical functioning. Depressive symptom clustering was denser among women. Conclusions Intrinsic capacity domains are tightly coupled in rural South African older adults; cognition and ADL limitations are pivotal. Subtle gender differences in network structure suggest a need for tailored, multidomain interventions. These findings support the WHO Healthy Ageing framework and highlight the utility of network models for identifying intervention leverage points in low-resource settings.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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