Objectives: Very old adults aged 80+ years old belong to the fastest growing population segment in many countries. Nevertheless, this age group is often underrepresented in studies of cognitive aging. The goal of this study was to examine individual and environmental socio-economic resources as correlates of cognitive aging in very old age.
Method: We used two waves of data from 2017-2018 and 2019-2021 as part of NRW80+, a survey of a population-based sample of very old individuals who are registered with their main residence in North-Rhine Westphalia, the most populous federal state in Germany. The analyses are based on data from 797 participants, who provided data on at least one cognitive test at both waves. Individual socio-economic resources included education, income, wealth, and occupational prestige. Environmental factors were assessed at the municipality level, including population density, unemployment, (public) transportation, broadband availability, healthcare, and libraries. Control variables included age, sex, marital/partner status, living alone, and living in a nursing care institution. Data were analyzed with latent difference score models.
Results: Education and wealth were independently associated with better cognitive function at baseline. None of the individual socio-economic variables was significantly related to change in cognitive function. Beyond these individual characteristics and control variables, higher population density and higher broadband availability, but also higher unemployment rate were associated with better baseline cognitive function. Greater distance to highways, but also fewer hospital beds and a higher number of residents per medical doctor were associated with less decline.
Discussion: Our findings suggest that individual socio-economic resources continue to be associated with better cognitive function in very old age, but are unrelated to short-term cognitive decline. In addition, there is some evidence for associations of baseline cognitive function and cognitive change with environmental factors over and above individual resources. Implications for future research are discussed.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.socscimed.2024.117544 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Within-subject reliability, occasion specificity, and validity of fluctuations of the Stroop and go/no-go tasks in ecological momentary assessment.
Behav Res Methods
December 2024
Department of Psychology, Bielefeld University, Universitätsstraße 25, 33615, Bielefeld, Germany.
Following the (revised) latent state-trait theory, the present study investigates the within-subject reliability, occasion specificity, common consistency, and construct validity of cognitive control measures in an intensive longitudinal design. These indices were calculated applying dynamic structural equation modeling while accounting for autoregressive effects and trait change. In two studies, participants completed two cognitive control tasks (Stroop and go/no-go) and answered questions about goal pursuit, self-control, executive functions, and situational aspects, multiple times per day.
View Article and Find Full Text PDFA tribute to Laszlo Zaborszky: pioneering discoveries in the basal forebrain and inspiring generations of neuroscientists.
Brain Struct Funct
December 2024
School of Medicine, Department of Neuropharmacology, Western Sydney University, Locked Bag 1797, Penrith, NSW, 2751, Australia.
This editorial celebrates the 80th birthday of Distinguished Professor Laszlo Zaborszky, co-founder of Brain Structure and Function, and reflects on his monumental contributions to neuroscience, particularly his pioneering work on the cholinergic basal forebrain. Professor Zaborszky's research has reshaped our understanding of this brain region's organization and function, uncovering its critical role in cognitive processes such as learning, memory, and attention. His findings have challenged longstanding assumptions, demonstrating that the cholinergic projections to the cortex are highly organized, with implications for neurodegenerative diseases like Alzheimer's.
View Article and Find Full Text PDFGenetic polymorphism in β-site amyloid precursor protein-cleaving enzyme 1 affects the structure of medial temporal lobe and cognition in Alzheimer's disease: an exploratory study.
Eur Arch Psychiatry Clin Neurosci
December 2024
Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui, China.
The β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) gene polymorphism (rs638405) has been widely reported to be associated with Alzheimer's disease (AD) risk. However, studies on the relationship between BACE1 gene polymorphism (rs638405), brain volume, and cognition in AD patients remain scarce. To investigate the effect of genetic polymorphism in BACE1 on gray matter volume (GMV) and cognition in AD, this study recruited 111 cognitively unimpaired (CU) controls and 144 AD patients.
View Article and Find Full Text PDFA chain mediation model reveals the association between depression and cognitive function in the elderly.
Sci Rep
December 2024
School of Humanities and Management, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
The purpose of this study was to explore the relationship between depression, cognitive function, social activities and activities of daily living ( ADL ), and verify whether social activities and ADL have a chain mediating effect between depression and cognitive function. Using the data of the fourth phase of the China Health and Retirement Longitudinal Study ( CHARLS ), 7547 elderly samples were studied. Correlation analysis and Bootstrap method were used to analyze the data to test whether social activities and ADL played a chain mediating role between depression and cognitive function in the elderly.
View Article and Find Full Text PDFConceptual understanding and cognitive patterns construction for physical education teaching based on deep learning algorithms.
Sci Rep
December 2024
School of Marxism, China University of Political Science and Law (CUPL), Beijing, 100091, China.
To improve students' understanding of physical education teaching concepts and help teachers analyze students' cognitive patterns, the study proposes an association learning-based method for understanding physical education teaching concepts using deep learning algorithms, which extracts image features related to teaching concepts using convolutional neural networks. Moreover, a neurocognitive diagnostic model based on hypergraph convolution is constructed to mine the data of students' long-term learning sequences and identify students' cognitive outcomes. The findings revealed that the highest accuracy of the association graph convolutional neural network was 0.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!