Evidence map›Paper›PMID 41803975›Full record

ArticleBiology of sex differences2026

Evaluating sex and gender as separate and interactive predictors of memory aging trajectory classes: an integrative data-driven approach.

Linzy Bohn, Paige Vandenberg, Harrison Fah, M Natasha Rajah, Gillian Einstein, Roger A Dixon

Abstract read
In one paragraph

Article in Biology of sex differences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Linzy BohnDepartment of Psychology, University of Alberta, P-217 Biological Sciences Building, Edmonton, T6G 2E9, AB, Canada. linzy@ualberta.ca.
Paige VandenbergDepartment of Psychology, University of Alberta, P-217 Biological Sciences Building, Edmonton, T6G 2E9, AB, Canada.
Harrison FahNeuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada.
M Natasha RajahDepartment of Psychology, Toronto Metropolitan University, Toronto, ON, Canada.
Gillian EinsteinDepartment of Psychology, University of Toronto, Toronto, ON, Canada.
Roger A DixonDepartment of Psychology, University of Alberta, P-217 Biological Sciences Building, Edmonton, T6G 2E9, AB, Canada.

Funding

Alberta Innovates #G2020000063CIHR 163902NIA NIH HHS AG008235
6 · The paper itself

Abstract

backgroundA priority in aging and dementia research is to integrate sex (biological attribute) and gender (sociocultural/behavioural characteristics) in theories, designs, analyses, and intervention protocols. We recently reported a data-mining procedure for operationalizing empirically-derived composite gender variables in archival databases. The present study extends the prior cross-sectional approach by examining sex and gender as separate and interactive predictors of longitudinal data-driven memory trajectory classes.

methodsParticipants (N = 746) contributed baseline data for binary sex (female/male), education (years), and empirically-derived composite variables representing complementary gender facets. These facets included Manual Tasks and Physical Activities; Social and Household Management; Leisure, Socializing, and Travel; Cognitive Activity and Brain Games; Health Perceptions and Practices; and Subjective Memory Beliefs. We integrated these into a longitudinal episodic memory trajectory distribution spanning 42 years (53-95) of aging. Data-driven latent class growth analysis (LCGA) on the trajectory distribution identified discriminable classes. Using the R3STEP approach, we separately tested sex, gender facets, and education as predictors of membership in the higher (healthier) trajectory classes relative to the lowest (benchmark) class. We then included interaction terms to test for sex moderation of gender effects. Finally, we identified all genotyped participants and tested whether sex and gender effects were moderated by Apolipoprotein E (APOE).

resultsLCGA revealed three memory classes: High-Stable (highest level/relatively stable), Moderate/Normal-Declining (average level/moderate decline), and Low-Declining (lowest level/steepest decline). Several variables separately predicted High-Stable membership. For sex, females were more likely than males to belong to this class. For gender, (a) higher scores for Social and Household Management, Cognitive Activity and Brain Games, and Subjective Memory Beliefs predicted High-Stable membership; and (b) higher scores for Manual Tasks and Physical Activities and Health Perceptions and Practices decreased the likelihood of High-Stable membership (relative to Low-Declining). Moderate/Normal-Declining membership was predicted by Social and Household Management (higher). For education, more years predicted High-Stable membership. Moderation analyses indicated that gender effects were consistent across both sexes and APOE carrier status.

conclusionsData-driven analyses show that biological sex and measurable facets of gender differentially contribute to memory trajectory patterns over a 42-year span of cognitively unimpaired aging.

Indexed as

AgingMemoryMemory, EpisodicSex CharacteristicsAgedAged, 80 and overApolipoproteins EFemaleHumansLongitudinal StudiesMaleMiddle AgedApolipoproteins EApolipoprotein ECognitively unimpaired agingGenderLatent class growth analysisMemory trajectoriesRandom forest analysisRisk and protective factorsSexVictoria Longitudinal Study

Identifiers

PMID41803975
PMCPMC13085552

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LicenceCC BY
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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.