Growth Mixture Modeling of Loneliness Trajectories in Older Adults - The Role of Cognitive Function

Sep 29, 2026

Loneliness is a growing public health concern among older adults in the United States, with significant implications for cognitive function. Using conditional growth mixture modeling (GMM-CV), the study examines longitudinal loneliness trajectories and whether cognitive function—immediate word recall, delayed word recall, and serial 7s—predicts trajectory membership. Data from 3,944 older adults across eight Health and Retirement Study waves (2006–2020) identify three classes: low-stable, high-decreasing, and moderate-increasing loneliness. Results show cognition relates to the loneliness slope, suggesting cognitive enhancement as a potential intervention.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages1

Reading Time3 min

AccessFree to download

Loneliness and cognitive implications

Data source and modeling approach

Identified loneliness trajectory classes

Cognitive predictors of trajectory and slope

640 Innovation in Aging, 2025, Vol. 9, No. S2 trajectories. Data were drawn from a sample of 3,944 older adults (Mage = 68.74) using eight waves of the Health and Retirement Study (HRS) data from 2006–2020. Data from every two years were pooled to increase the sample size and create four time points. GMM-CV in Mplus identified three distinct loneliness trajectories best fit the Data: LL= -25,495 .269, BIC=51,214 .097, SSABIC=51,128.303, Entropy=0.814, Adj. LMR-LRT (.52)=245.630, BLRT(.51)=255.518. The three identified classes were: Class 1: Low-Stable Loneliness (75 .6%), Class 2: High-Decreasing Loneliness (13.1%), and Class 3: Moderate-Increasing Loneliness (11.3%). The mean group differences revealed significant group differences in immediate word recall at time 1 (F=3.19, p=.04) and time 4 (F=3.9, p=.02), delayed word recall at time 1 (F = 3.31, p=.037) and time 4 (F = 3.11, p=.045), while no significant effect was found for serial 7s at time 1 (F=2.33, p=.098) and time 4 (F=.068, p=.934). Immediate word recall at time 4 exhibited a significant negative effect on the loneliness slope, indicating that higher cognition scores were associated with a less steep increase in loneliness over time. These findings suggest enhancing cognitive function as a potential intervention to reduce loneliness in later life. Future research should explore underlying mechanisms and moderating factors. Abstract citation ID: igaf122.2188 GROWTH MIXTURE MODELING OF LONELINESS TRAJECTORIES IN OLDER ADULTS: THE ROLE OF COGNITIVE FUNCTION Elnaz Abaei, and Peter Martin, Iowa State University, Ames, Iowa, United States Loneliness is a growing public health concern among older adults in the United States, with significant implications for cognitive function. This study utilized conditional growth mixture modeling (GMM-CV) to investigate the longitudinal trajectories of loneliness and how cognitive function (measured by immediate word recall, delayed word recall, and serial 7s) predicted these

FAQs

What method was used to study loneliness over time?

The study applied conditional growth mixture modeling (GMM-CV) to identify distinct longitudinal loneliness trajectories and assess predictors of trajectory membership.

How many loneliness trajectory classes were identified, and what were they?

Three classes were identified: low-stable loneliness (75.6%), high-decreasing loneliness (13.1%), and moderate-increasing loneliness (11.3%).

Which cognitive measures predicted changes in loneliness over time?

Immediate word recall at time 4 showed a significant negative effect on the loneliness slope, indicating higher cognition scores were linked to a less steep increase in loneliness. Significant group differences were also observed for immediate and delayed word recall at specific time points.

Sep 29, 2026

Upload by Olivia Brown