Evidence map›Paper›PMID 39577957›Full record

ArticleThe Lancet. Global health2024

Estimating dementia prevalence using remote diagnoses and algorithmic modelling: a population-based study of a rural region in South Africa.

Meagan T Farrell, Darina T Bassil, Muqi Guo, M Maria Glymour, Ryan G Wagner, Stephen Tollman, Kenneth M Langa, Adam M Brickman, Jennifer J Manly, Lisa F Berkman

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Lancet. Global health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Effect of a cash transfer intervention on memory decline and dementia probability in older adults in rural South Africa.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Trial
  2. Article
  3. Review
  4. Article
  5. Article
  6. Sensory impairment and dementia risk among older adults in rural South Africa.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Meagan T FarrellHarvard Center for Population and Development Studies, Harvard University, Cambridge, MA, USA. Electronic address: mfarrell@hsph.harvard.edu.
Darina T BassilHarvard Center for Population and Development Studies, Harvard University, Cambridge, MA, USA.
Muqi GuoHarvard Center for Population and Development Studies, Harvard University, Cambridge, MA, USA; Department of Global Health and Population, Harvard T H Chan School of Public Health, Harvard University, Cambridge, MA, USA.
M Maria GlymourDepartment of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
Ryan G WagnerMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Stephen TollmanMRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; INDEPTH Network, Accra, Ghana.
Kenneth M LangaInstitute for Healthcare Policy and Innovation and Institute for Social Research, University of Michigan, Ann Arbor, MI, USA; Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA; Veterans Affairs Center for Clinical Management Research, Ann Arbor, MI, USA.
Adam M BrickmanTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Gertrude H Sergievsky Center, and Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.
Jennifer J ManlyTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Gertrude H Sergievsky Center, and Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.
Lisa F BerkmanHarvard Center for Population and Development Studies, Harvard University, Cambridge, MA, USA; Department of Social and Behavioral Sciences, Harvard T H Chan School of Public Health, Harvard University, Cambridge, MA, USA; MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.

Funding

SOCIAL AND ECONOMIC PREDICTORS OF PHYSICAL AND COGNITIVE FUNCTIONP01AG041710 · NIA · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Julia Katherine Rohr · 2013 to 2026
$37.3M
NIA NIH HHS P01 AG041710
6 · The paper itself

Abstract

backgroundDementia is a leading cause of global death and disability. High-quality data describing dementia prevalence and burden remain scarce in sub-Saharan Africa. Health and Aging in Africa: A Longitudinal Study in South Africa (HAALSI) fills evidence gaps with longitudinal data on cognition, biomarkers, and everyday function in a population-based cohort of Black South Africans, aged 40 years and older, in a rural subdistrict. This study uses consensus diagnoses and prediction algorithms to estimate dementia prevalence.

methodsData were from eligible HAALSI Wave 2 respondents aged 50 years or older (n=3662) and were collected between September, 2019, and January, 2020. An enriched sub-cohort (ie, including a high proportion of individuals with cognitive impairment; n=632) completed a battery of rigorous neuropsychological and clinical assessments and received expert classification of cognitively unimpaired, mild cognitive impairment, or dementia. Logistic regression was used to predict dementia status within the sub-cohort using predictor variables from the parent HAALSI wave. Coefficients were applied to the parent cohort to obtain dementia probability scores and calculate dementia prevalence. Optimal probability cut points to classify individual cases were selected for each model.

findingsWhen the sub-cohort was reweighted to reflect the full HAALSI population, the estimated prevalence of dementia was 18% (95% CI 15-22), with steep age gradients. Four models of increasing complexity showed good discrimination between dementia and non-dementia (area under receiver operating characteristic curves 0·78-0·84; classification accuracy 74-81%). Model-based dementia prevalence estimates aligned closely with weighted prevalence; model performance was consistent in cross-validated datasets.

interpretationHAALSI is among the first studies to use algorithmic methods to describe dementia prevalence in a population-based sample in South Africa. These efforts could provide a foundation to expand understanding of dementia epidemiology in a region of the world experiencing rapid population ageing.

fundingNational Institute on Aging.

Indexed as

AlgorithmsDementiaRural PopulationAgedAged, 80 and overFemaleHumansLongitudinal StudiesMaleMiddle AgedPrevalenceSouth Africa

Identifiers

PMID39577957
PMCPMC11987161

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.