Effect of Aging on Educational Differences in the Risk of Cognitive Impairment: A Gender-Specific Analysis Using Korean Longitudinal Study of Aging (2006–2016)

Kim, Roeul; Chung, Woojin

doi:10.3390/healthcare10061062

Cited by 7 publications

(8 citation statements)

References 67 publications

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“…The demographics analysis showed that age and education were highly correlated with the K-MoCA score as previous studies have consistently shown [33][34][35]. Age independently accounted for close to 6% of MoCA score variance, whereas years of education accounted for almost 16% of the variation.…”

Section: Discussionsupporting

confidence: 61%

Approximation of Cognitive Performance Using an Elastic Net Regression Model Trained on Gait, Visual, Auditory, Postural, and Olfactory Function Features

Kostic,

Kwak,

Lee

et al. 2024

Applied Sciences

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When dementia is diagnosed, it is most often already past the point of irreversible neuronal deterioration. Neuropsychological tests are frequently used in clinical settings; however, they must be administered properly and are oftentimes conducted after cognitive impairment becomes apparent or is raised as a concern by the patient or a family member. It would be beneficial to develop a non-invasive system for approximating cognitive scores which can be utilized by a general practitioner without the need for cognitive testing. To this end, gait, visual, auditory, postural, and olfactory function parameters, reported history of illness, and personal habits were used to train an elastic-net regression model in predicting the cognitive score. Community-dwelling men (N = 104) above the age of sixty-five participated in the current study. Both individual variables and principal components of the motor and sensory functions were included in the elastic-net regression model, which was trained on 70% of the dataset. The years of education, limits of stability testing time, regular ophthalmological exams, postural testing time principal component, better ear score on the sentence recognition test, and olfactory discrimination score largely contributed to explaining over 40% of the variance in the cognitive score.

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Section: Discussionsupporting

confidence: 61%

Approximation of Cognitive Performance Using an Elastic Net Regression Model Trained on Gait, Visual, Auditory, Postural, and Olfactory Function Features

Kostic,

Kwak,

Lee

et al. 2024

Applied Sciences

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show abstract

“…Brain health and age-related cognitive decline have been studied extensively. The course and extent of cognitive deterioration are influenced by various factors, such as lifestyle, education, genetics and cognitive engagement [ 57 , 58 ]. A recent study by Lin et al [ 58 ], using data of 17030 participants from the UK Biobank, identified several significant features that were meaningfully associated with brain and cognitive maintenance.…”

Section: Discussionmentioning

confidence: 99%

“…Generally, it has been frequently found that women are more likely than men to suffer from cognitive impairment [ 57 , 67 , 68 , 69 ]. Furthermore, an examination of 34 439 elderly individuals with normal cognition revealed that women might have greater cognitive reserve but faster cognitive decline than men [ 68 ].…”

Section: Discussionmentioning

confidence: 99%

The Influence of Age, Gender and Education on Neuropsychological Test Scores: Updated Clinical Norms for Five Widely Used Cognitive Assessments

Scheffels,

Ballasch,

Scheichel

et al. 2023

JCM

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Background: Sociodemographic effects (i.e., age, gender, education) have been shown to influence neuropsychological test scores. The current retrospective, quasi-epidemiological work provides age-, gender- and education-corrected clinical norms for five common cognitive assessments. Methods: In total, test scores of 4968 patients from the University Hospital of Cologne (Department of Neurology), recruited between 2009 and 2020, were analyzed retrospectively. Conducted tests were the Mini-Mental State Examination (MMSE), F-A-S Test (FAS), Rey–Osterrieth Complex Figure Test (ROCFT) and Trail Making Test, Part A and B (TMT-A/-B). Using multiple linear regression analyses, test scores were analyzed for sociodemographic influences (age, gender, education). Based on these analyses, norms were generated by first separating patients into different age groups stratified by educational level and (if necessary) gender. Subsequently, percentile ranks and z-scores for a subsample including only individuals without dementia were calculated. Results: Lower age and higher educational level predicted better test scores (MMSE, FAS, ROCFT) and completion times (TMT-A/-B). Additionally, produced words on the FAS and remembered drawings from the ROCFT were influenced by gender, with females having better FAS but lower ROCFT (delayed recall) scores than males. Considering these effects, clinical norms were provided for the five cognitive assessments. Conclusions: We found influences of age, gender and education on test scores, although they are frequently not or only partially considered for test score interpretation. With the provided norms, neuropsychologists can make more profound evaluations of cognitive performance. A user-friendly Microsoft Excel file is offered to assist this process.

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“…[1][2][3] Previous studies have shown that cognitive function can be influenced by various factors, including genetic and environmental factors. 4,5 Numerous studies have consistently identified age, education, sex, 6 health habits such as drinking and smoking, 7 depression, 8 sleep issues, 9 social factors (activity level and occupation), 9 and body mass index (BMI) 10 as factors affecting cognitive function among young adults. Identifying factors associated with cognitive decline might help in enhancing cognitive function through appropriate measures.…”

Section: Introductionmentioning

confidence: 99%

Night Screen Time is Associated with Cognitive Function in Healthy Young Adults: A Cross-Sectional Study

Shalash,

Arumugam,

Qadah

et al. 2024

JMDH

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Background:In recent years, a significant shift toward remote work, virtual education, and social distancing measures was witnessed, thereby leading people to increasingly depend on digital devices for communication, work, and entertainment. This increased exposure to screens has raised concerns regarding its potential impact on cognitive function. Purpose: This study investigated the relationship between screen time and cognitive function among healthy young adults. Methods: One hundred forty-five healthy individuals (mean age 21.55 ± 2.84 years) participated in this cross-sectional study. Sociodemographic information including age, sex, height, weight, and level of education were obtained. Participants reported screen time using a screen time questionnaire. Cognitive function tests including, Paced Auditory Serial Addition Task (PASAT), Montreal Cognitive Assessment (MoCA) and Symbol Digit Modalities Test (SDMT) were conducted. Multilinear regression analyses were used to examine the associations between age, sex, level of education, screen time, and cognitive function. Results: One hundred thirty-nine participants (76 women) completed the study. Increased night screen time, bachelor's educational level, and women were associated with lower PASAT scores (R2=0.258; p≤0.047). Moreover, increased night screen time was associated with lower MoCA scores (R2=0.029; p=0.035). However, no associations were found between night screen time and SDMT scores. Conclusion: Participants who had higher night screen exposure had lower cognitive scores in the information speed processing, working memory, calculation, and attention domains. Considering these findings, this study emphasizes on the importance of setting a future recommended screen time guidelines for young adults as well as to promote healthy cognitive habits in order to preserve cognitive function and reduce the risk of developing neurodegenerative disease in the future. Future prospective cohort studies involving a more diverse age range is needed.

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Effect of Aging on Educational Differences in the Risk of Cognitive Impairment: A Gender-Specific Analysis Using Korean Longitudinal Study of Aging (2006–2016)

Cited by 7 publications

References 67 publications

Approximation of Cognitive Performance Using an Elastic Net Regression Model Trained on Gait, Visual, Auditory, Postural, and Olfactory Function Features

Approximation of Cognitive Performance Using an Elastic Net Regression Model Trained on Gait, Visual, Auditory, Postural, and Olfactory Function Features

The Influence of Age, Gender and Education on Neuropsychological Test Scores: Updated Clinical Norms for Five Widely Used Cognitive Assessments

Night Screen Time is Associated with Cognitive Function in Healthy Young Adults: A Cross-Sectional Study

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