Evidence map›Paper›PMID 41020424›Full record

ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2025

Dementia prevalence in the Wisconsin Longitudinal Study.

Victoria J Williams, Ralph Trane, Kamil Sicinski, Carol Roan, Kate Lange, Kerryann DiLoreto, Brittani Strait, Anne Fischer, Grete Wichmann, Garrett Wartenweiler and 6 more

Abstract read
In one paragraph

Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Victoria J WilliamsDepartment of Medicine, Division of Geriatrics and Gerontology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA.
Ralph TraneDepartment of Medicine, Division of Geriatrics and Gerontology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA.
Kamil SicinskiCenter for Demography of Health and Aging, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Carol RoanDepartment of Sociology, Center for Demography and Ecology, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Kate LangeDepartment of Medicine, Division of Geriatrics and Gerontology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA.
Kerryann DiLoretoUniversity of Wisconsin Survey Center (UWSC), Sterling Hall, Madison, Wisconsin, USA.
Brittani StraitDepartment of Medicine, Division of Geriatrics and Gerontology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA.
Anne FischerDepartment of Medicine, Division of Geriatrics and Gerontology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA.
Grete WichmannUniversity of Wisconsin Survey Center (UWSC), Sterling Hall, Madison, Wisconsin, USA.
Garrett WartenweilerUniversity of Wisconsin Survey Center (UWSC), Sterling Hall, Madison, Wisconsin, USA.
Nicole CookeDepartment of Medicine, Division of Geriatrics and Gerontology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA.
Emma HenningDepartment of Medicine, Division of Geriatrics and Gerontology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA.
Sterling C JohnsonDepartment of Medicine, Division of Geriatrics and Gerontology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA.
Michal EngelmanCenter for Demography of Health and Aging, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Pamela HerdCenter for Demography of Health and Aging, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Sanjay AsthanaDepartment of Medicine, Division of Geriatrics and Gerontology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA.

Funding

Wisconsin longitudinal study: Initial lifetime's impact on Alzheimer's disease and related disorders (WLS-ILIAD)R01AG060737 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Sanjay Asthana, Michal Engelman · 2018 to 2026
$56.8M
NIA NIH HHS R01 AG060737
6 · The paper itself

Abstract

introductionWhile there is growing appreciation of the importance of sociobiological determinants of dementia, few lifespan cohorts offer well-characterized dementia outcomes to explore these aims. We sought to identify dementia prevalence in the Wisconsin Longitudinal Study (WLS), one of the most comprehensive lifespan cohort studies in the United States. Highlights We found dementia prevalence in the WLS to be 8.9% when this large population-based cohort was sampled at a mean age of 81. Of the identified dementia cases, 79% were clinically determined to be due to a presumed underlying etiology of AD. The targeted multiphased assessment approach used to classify dementia in WLS will be iteratively repeated over time to capture new dementia incidence, complemented by parallel efforts to link WLS with Medicare claims data to identify additional dementia cases among non-respondents or those not selected into the ILIAD sampling frame. Ongoing data collection efforts include in-home blood collection efforts to characterize plasma levels of AD biomarkers in the WLS cohort. When resultant dementia classifications are combined with the robust prospectively collected life course data covering a wide array of socioeconomic, educational, occupational, social, behavioral, and physical health variables, the WLS dataset offers an unparalleled opportunity to investigate the sociobiological determinants of late-life dementia.

methodsUsing a targeted multiphased assessment approach, participants were first screened for dementia risk using a phone-based cognitive assessment. Those scoring below cut-off underwent additional cognitive/medical assessment to determine a consensus-based cognitive diagnosis and suspected underlying etiology.

resultsCognitive status was determined for 5414 participants, with a dementia prevalence of 8.9% when assessed at a mean age of 81 years. DISCUSSION: The WLS offers prospectively collected data covering nearly every facet of participant's lives from high school to late life. When combined with newly defined dementia outcomes, the WLS dataset offers a valuable resource to explore full life course determinants of dementia.

Indexed as

DementiaAgedAged, 80 and overFemaleHumansLongitudinal StudiesMalePrevalenceWisconsinalzheimer's diseasedementiaepidemiologic determinantshealth risk behaviorsprevalence

Identifiers

PMID41020424
PMCPMC12477634

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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.