Evidence map›Paper›PMID 40069951›Full record

ArticleAmerican journal of epidemiology2026

Are we there yet? Estimating the waves of follow-up required for stable effect estimates in cognitive aging research.

Mary C Thoma, Jingxuan Wang, Elizabeth Rose Mayeda, Charles E McCulloch, Eleanor Hayes-Larson, Jacqueline M Torres, M Maria Glymour

Abstract read
In one paragraph

Article in American journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

7 authors.

Mary C ThomaDepartment of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0002-6856-9282
Jingxuan WangDepartment of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0002-9387-0480
Elizabeth Rose MayedaDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0002-6326-0163
Charles E McCullochDepartment of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0002-1279-6179
Eleanor Hayes-LarsonLeonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, United States.ORCID 0000-0001-8299-2389
Jacqueline M TorresDepartment of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, San Francisco, CA, United States.ORCID 0000-0002-1579-6107
M Maria GlymourDepartment of Epidemiology, School of Public Health, Boston University, Boston, MA, United States.ORCID 0000-0001-9644-3081

Funding

Project 4: Social isolation as a driver of AD/ADRD incidence and disparitiesP01AG082653 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Jacqueline Marie Torres · 2024 to 2026
$23.6M
Translational Epidemiology - Training for Research on Aging and Chronic diseaseT32AG049663 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Elizabeth Rose Mayeda, Mark J Pletcher · 2016 to 2026
$5.8M
Building an unbiased pooled cohort for the study of lifecourse social and vascular determinants of Alzheimer's Disease and Related DisordersR01AG072681 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GLYMOUR, MEDELLENA MARIA, ZEKI AL HAZZOURI, ADINA · 2021 to 2025
$4.0M
Effects of lifecourse traumatic stress on late-life cognitive decline, dementia, and neuroimaging biomarkersR00AG075317 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Eleanor Louise Hayes-Larson · 2024 to 2026
$742k
The Impact of SARS-CoV-2 Infection and Vaccination on the Risk of Alzheimer’s Disease and Related DementiasF99AG083306 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WANG, JINGXUAN · 2023 to 2025
$72k
NIA NIH HHS F99 AG083306NIA NIH HHS P01 AG082653NIA NIH HHS R00 AG075317NIA NIH HHS R01 AG072681NIA NIH HHS T32 AG049663US National Institutes of Health, National Institute on Aging F99AG083306US National Institutes of Health, National Institute on Aging K99/R00AG075317US National Institutes of Health, National Institute on Aging P01AG082653US National Institutes of Health, National Institute on Aging R01AG072681US National Institutes of Health, National Institute on Aging T32AG049663
6 · The paper itself

Abstract

Cognitive aging research relies on longitudinal data, but extended follow-up is costly. The extent to which estimates and precision from data with shorter follow-up diverge from estimates based on longer follow-up is unknown. The necessary follow-up period may depend on model specification, i.e., modeling the timescale as time-since-baseline or current age. We used data on adults age 65+ from the 2006-2018 U.S. Health and Retirement Study. For associations of 8 commonly studied dementia risk factors with cognitive decline, we compared coefficients and variance estimates to results from benchmark models (i.e., using 7 waves and/or specifying time-since-baseline). We varied the hypothetical follow-up length (1-7 waves, representing 0-12 years of follow-up) and timescale specification. Among individuals 65-80 years old at baseline, estimates of cognitive change in models with <4 waves of follow-up differed meaningfully in terms of both coefficients and variance from estimates using full follow-up, regardless of timescale specification. Differences by length of follow-up time were less pronounced among those >80 years of age at baseline, in part due to sample attrition. In models assuming equal follow-up duration, estimates of cognitive change specified by current age differed from estimates using time-since-baseline but were more precise, especially with shorter follow-up.

Indexed as

Cognitive AgingCognitive DysfunctionAgedAged, 80 and overDementiaFemaleFollow-Up StudiesHumansLongitudinal StudiesMaleRisk FactorsTime FactorsUnited Statescognitive declinedementialongitudinal studystudy designtimescale specification

Identifiers

PMID40069951
PMCPMC13017650

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.