Browsing by Author "Lisa F. Berkman"

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    Feasibility of an online consensus approach for the diagnosis of cognitive impairment and dementia in rural South Africa
    (2023-03-04) Darina T. Bassil; Meagan T. Farrell; AlbertWeerman; Muqi Guo; Ryan G.Wagner; AdamM. Brickman; M. Maria Glymour; Kenneth M. Langa; Jennifer J. Manly; Brent Tipping; India Butler; Stephen Tollman; Lisa F. Berkman
    INTRODUCTION:We describe the development and feasibility of using an online consensus approach for diagnosing cognitive impairment and dementia in rural South Africa. METHODS: Cognitive assessments, clinical evaluations, and informant interviews from Cognition and Dementia in the Health and Aging in Africa Longitudinal Study (HAALSI Dementia) were reviewed by an expert panel using a web-based platform to assign a diagnosis of cognitively normal, mild cognitive impairment (MCI), or dementia. RESULTS: Six hundred thirty-five participants were assigned a final diagnostic category, with 298 requiring adjudication conference calls. Overall agreement between each rater’s independent diagnosis and final diagnosis (via the portal or consensus conference) was 78.3%. A moderate level of agreement between raters’ individual ratings and the final diagnostic outcomes was observed (average κ coefficient = 0.50).DISCUSSION: Findings show initial feasibility in using an online consensus approach for the diagnosis of cognitive impairment and dementia in remote, rural, and lowresource settings.
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    Long-term household material socioeconomic resources and cognitive health in a population-based cohort of older adults in rural northeast South Africa, 2001–2015
    (2022) Lindsay C. Kobayashi; Chodziwadziwa Whiteson Kabudula; Mohammed U. Kabeto; Xuexin Yu; Stephen M. Tollman; Kathleen Kahn; Lisa F. Berkman; Molly S. Rosenberg
    Material resources owned by households that affect daily living conditions may be salient for cognitive health during aging, especially in low-income settings, but there is scarce evidence on this topic. We investigated relationships between long-term trends in household material resources and cognitive function among older adults in a population-representative study in rural South Africa. Data were from baseline interviews with 4580 adults aged ≥40 in “Health and Ageing in Africa: A Longitudinal Study of an INDEPTH Community in South Africa” (HAALSI) in 2014/2015 linked to retrospective records on their household material resources from the Agincourt Health and Socio-Demographic Surveillance System (HDSS) from 2001 to 2013. Household material resources were assessed biennially in the Agincourt HDSS using a five-point index that captured dwelling materials, water and sanitation, sources of power, livestock, and technological amenities. Cognitive function was assessed in HAALSI and analyzed as a z-standardized latent variable capturing time orientation, episodic memory, and numeracy. We evaluated the relationships between quintiles of each of the mean resource index score, volatility in resource index score, and change in resource index score and subsequent cognitive function, overall and by resource type. Higher mean household resources were positively associated with cognitive function (βadj = 0.237 standard deviation [SD] units for the highest vs. lowest quintile of mean resource index score; 95% CI: 0.163–0.312; p-trend<0.0001), as were larger improvements over time in household resources (βadj = 0.122 SD units for the highest vs. lowest quintile of change in resources; 95% CI: 0.040–0.205; p-trend = 0.001). Results were robust to sensitivity analyses assessing heterogeneity by age and restricting to those with formal education. The findings were largely driven by technological amenities including refrigerators, stoves, telephones, televisions, and vehicles. These amenities may support cognitive function through improving nutrition and providing opportunities for cognitive stimulation through transportation and social contact outside of the home
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    Towards a consensus definition of allostatic load: a multi-cohort, multi-system, multi-biomarker individual participant data (IPD) meta-analysis
    (2023-04-19) Cathal McCrory; Sinead McLoughlin; Richard Layte; Cliona NiCheallaigh; Aisling M. O’Halloran; Henrique Barros; Lisa F. Berkman; Murielle Bochud; Eileen M. Crimmins; Meagan T. Farrell; Silvia Fraga; Emily Grundy; Michelle Kelly-Irving; Dusan Petrovic; Teresa Seeman; Silvia Stringhini; Peter Vollenveiderl; Rose Anne Kenny
    Background: Allostatic load (AL) is a multi-system composite index for quantifying physiological dysregulation caused by life course stressors. For over 30 years, an extensive body of research has drawn on the AL framework but has been hampered by the lack of a consistent definition. Methods: This study analyses data for 67,126 individuals aged 40–111 years participating in 13 different cohort studies and 40 biomarkers across 12 physiological systems: hypothalamic-pituitary-adrenal (HPA) axis, sympathetic-adrenal-medullary (SAM) axis, parasympathetic nervous system functioning, oxidative stress, immunological/inflammatory, cardiovascular, respiratory, lipidemia, anthropometric, glucose metabolism, kidney, and liver. We use individual-participant-data meta-analysis and exploit natural heterogeneity in the number and type of biomarkers that have been used across studies, but a common set of health outcomes (grip strength, walking speed, and self-rated health), to determine the optimal configuration of parameters to define the concept. Results: There was at least one biomarker within 9/12 physiological systems that was reliably and consistently associated in the hypothesised direction with the three health outcomes in the meta-analysis of these cohorts: dehydroepiandrosterone sulfate (DHEAS), low frequency-heart rate variability (LF-HRV), C-reactive protein (CRP), resting heart rate (RHR), peak expiratory flow (PEF), high density lipoprotein cholesterol (HDL-C), waistto-height ratio (WtHR), HbA1c, and cystatin C. An index based on five biomarkers (CRP, RHR, HDL-C, WtHR and HbA1c) available in every study was found to predict an independent outcome – mortality – as well or better than more elaborate sets of biomarkers. Discussion: This study has identified a brief 5-item measure of AL that arguably represents a universal and efficient set of biomarkers for capturing physiological ‘wear and tear’ and a further biomarker (PEF) that could usefully be included in future data collection.