Objectives: This paper models cognitive aging, across mid and late life, and estimates birth cohort and sex differences in both initial levels and aging trajectories over time in a sample with multiple cohorts and a wide span of ages.
Methods: The data used in this study came from the first 9 waves of the English Longitudinal Study of Ageing, spanning 2002-2019. There were n = 76,014 observations (proportion male 45%). Dependent measures were verbal fluency, immediate recall, delayed recall, and orientation. Data were modeled using a Bayesian logistic growth curve model.
Results: Cognitive aging was substantial in 3 of the 4 variables examined. For verbal fluency and immediate recall, males and females could expect to lose about 30% of their initial ability between the ages of 52 and 89. Delayed recall showed a steeper decline, with males losing 40% and females losing 50% of their delayed recall ability between ages 52 and 89 (although females had a higher initial level of delayed recall). Orientation alone was not particularly affected by aging, with less than a 10% change for either males or females. Furthermore, we found cohort effects for initial ability level, with particularly steep increases for cohorts born between approximately 1930 and 1950.
Discussion: These cohort effects generally favored later-born cohorts. Implications and future directions are discussed.
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http://dx.doi.org/10.1093/geronb/gbad089 | DOI Listing |
Clinicoecon Outcomes Res
January 2025
Public Systems Group, Indian Institute of Management Ahmedabad, Ahmedabad, Gujarat, India.
Introduction: Clinical trials are critical for drug development and patient care; however, they often need more efficient trial design and patient enrolment processes. This research explores integrating machine learning (ML) techniques to address these challenges. Specifically, the study investigates ML models for two critical aspects: (1) streamlining clinical trial design parameters (like the site of drug action, type of Interventional/Observational model, etc) and (2) optimizing patient/volunteer enrolment for trials through efficient classification techniques.
View Article and Find Full Text PDFFront Neurol
January 2025
School of Public Health, Shanxi Medical University, Taiyuan, China.
Background: Cognitive impairment (CI) is a condition in which an individual experiences noticeable impairment in thinking abilities. Long-term exposure to aluminum (Al) can cause CI. This study aimed to determine the relationship between CI and MRI-related changes in postroom workers exposed to Al.
View Article and Find Full Text PDFJ Alzheimers Dis
January 2025
Centre for Brain Research, Indian Institute of Science, Bengaluru, Karnataka, India.
Background: Subjective cognitive decline (SCD) is the early predementia syndrome. that occurs even before the development of objective cognitive decline. SCD plus refers to an additional set of criteria that increases the likelihood of developing mild cognitive impairment and further progressing to Alzheimer's disease (AD).
View Article and Find Full Text PDFInt J Ophthalmol
January 2025
Eye Hospital, China Academy of Chinese Medical Sciences, Beijing 100040, China.
Aim: To assess the relationship between dietary inflammatory index (DII) and prevalence of glaucoma among individuals aged 40y and above in the United States.
Methods: Participants were drawn from 2 cycles of the National Health and Nutrition Examination Survey (NHANES, 2005-2008) for a cross-sectional study. DII was calculated from 24-hour dietary recall questionnaire conducted by experienced researchers and data analyzed in R according to the NHANES user guide, "Stratified Multi-stage Probability Sampling".
J Gerontol B Psychol Sci Soc Sci
January 2025
Department of Public Health Sciences, University of Chicago, Chicago, Illinois, USA.
Objectives: Cognition consists of specific domains that are differentially linked to health outcomes. We provide guidance on how to derive cognitive domains in the National Social Life, Health, and Aging Project (NSHAP) study. We suggest the use of a bifactor analysis to derive cognitive domains.
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