Little relation of adult age with cognition after controlling general influences

An analysis of dynamic, bidirectional associations between memory and verbal fluency with depressive symptoms in middle- and older-aged adults: A cohort study

OBJECTIVES

This study compared two approaches to analyzing bidirectional associations between aspects of cognition-specifically, verbal memory and fluency-and depression using multi-wave longitudinal data. The cross-lagged panel model (CLPM) does not distinguish between- versus within-person variation, whereas the random-intercepts CLPM (RI-CLPM) partitions variation into a stable, trait-like component that varies across individuals and a wave-specific deviation that varies within individuals.

METHODS

Observational study of 47,719 adults ages 45 to 95 from the Survey of Health, Ageing, and Retirement in Europe (mean age = 63 years, SD = 9 years at first assessment; 57 % female). Participants completed at least four of 8 biennial waves of data collection from 2004 and 2020. Depressive symptoms were assessed by the EURO-D. Cognition was assessed by animal fluency, and immediate and delayed word recall. Multi-group CLPMs and RI-CLPMs were fit on middle-aged (45-65 year) and older (65+ years) males and females.

RESULTS

The estimates from the CLPMs indicated bidirectionality in the associations between cognition and depression, whereas the RI-CLPMs provided clearer evidence that changes in depression may produce subsequent changes in cognition, rather than vice versa. Prospective associations were small and consistent across age, sex and cognitive measure.

LIMITATIONS

Measures of executive function-a domain of cognition affected by aging and related to mood-were not available.

CONCLUSIONS

CLPMs and RI-CLPMs address conceptually distinct questions about how verbal memory and fluency may be dynamically related to depression, and therefore, produce different inferences from the same data about how these aspects of cognition and depression are related.

Longitudinal Stability of Intellectual Functioning in Autism Spectrum Disorder: From Age 3 Through Mid-adulthood

Intelligence (IQ) scores are used in educational and vocational planning for individuals with autism spectrum disorder (ASD) yet little is known about the stability of IQ throughout development. We examined longitudinal age-related IQ stability in 119 individuals with ASD (3-36 years of age at first visit) and 128 typically developing controls. Intelligence measures were collected over a 20-year period. In ASD, Full Scale (FSIQ) and Verbal (VIQ) Intelligence started lower in childhood and increased at a greater rate with age relative to the control group. By early adulthood, VIQ and working memory stabilized, whereas nonverbal and perceptual scores continued to change. Our results suggest that in individuals with ASD, IQ estimates may be dynamic in childhood and young adulthood.

Cognition in Healthy Aging

The study of cognitive change across a life span, both in pathological and healthy samples, has been heavily influenced by developments in cognitive psychology as a theoretical paradigm, neuropsychology and other bio-medical fields; this alongside the increase in new longitudinal and cohort designs, complemented in the last decades by the evaluation of experimental interventions. Here, a review of aging databases was conducted, looking for the most relevant studies carried out on cognitive functioning in healthy older adults. The aim was to review not only longitudinal, cross-sectional or cohort studies, but also by intervention program evaluations. The most important studies, searching for long-term patterns of stability and change of cognitive measures across a life span and in old age, have shown a great range of inter-individual variability in cognitive functioning changes attributed to age. Furthermore, intellectual functioning in healthy individuals seems to decline rather late in life, if ever, as shown in longitudinal studies where age-related decline of cognitive functioning occurs later in life than indicated by cross-sectional studies. The longitudinal evidence and experimental trials have shown the benefits of aerobic physical exercise and an intellectually engaged lifestyle, suggesting that bio-psycho-socioenvironmental factors concurrently with age predict or determine both positive or negative change or stability in cognition in later life.

Normative data for the oldest old: Trail Making Test A, Symbol Digit Modalities Test, Victoria Stroop Test and Parallel Serial Mental Operations

Normative data for evaluating cognitive function in the oldest old, aged 85 years and above, are currently sparse. The normative values used in clinical practice are often derived from younger old persons, from small sample sizes or from broad age spans (e.g. >75 years) resulting in a risk of misjudgment in assessments of cognitive decline. This longitudinal study presents normative values for the Trail Making Test A (TMT-A), the Symbol Digit Modalities Test (SDMT), the Victoria Stroop Test (VST) and the Parallel Serial Mental Operations (PaSMO) from cognitively intact Swedes aged 85 years and above. 207 participants, born in 1922, were tested at 85, 90 (n = 68) and 93 (n = 35) years of age with a cognitive screening test battery. The participants were originally recruited for participation in the Elderly in Linköping Screening Assessment. Normative values are presented as mean values and standard deviations, with and without adjustment for education. There were no clinically important differences between genders, but education had a significant effect on test results for the 85-year-olds. Age effects emerged in analyses of those participants who completed the entire study and were evident for TMT-A, SDMT, VST1 and PaSMO. When comparisons can be made, our results are in accordance with previous data for TMT-A, SDMT and VST, and we present new normative values for PaSMO.

Coupled cognitive changes in adulthood: A meta-analysis

With advancing age, healthy adults typically exhibit decreases in performance across many different cognitive abilities such as memory, processing speed, spatial ability, and abstract reasoning. However, there are marked individual differences in rates of cognitive decline, with some adults declining steeply and others maintaining high levels of functioning. To move toward a comprehensive understanding of cognitive aging, it is critical to know whether individual differences in longitudinal changes interrelate across different cognitive abilities. We identified 89 effect sizes representing shared variance in longitudinal cognitive change from 22 unique datasets composed of more than 30,000 unique individuals, which we meta-analyzed using a series of multilevel metaregression models. An average of 60% of the variation in cognitive changes was shared across cognitive abilities. Shared variation in changes increased with age, from approximately 45% at age 35 years to approximately 70% at age 85 years. There was a moderate-to-strong correspondence (r = .49, congruence coefficient = .98) between the extent to which a variable indicated general intelligence and the extent to which change in that variable indicated a general factor of aging-related change. Shared variation in changes did not differ substantially across cognitive ability domain classifications. In a sensitivity analysis based on studies that carefully controlled for dementia, shared variation in longitudinal cognitive changes remained at upward of 60%, and age-related increases in shared variation in cognitive changes continued to be evident. These results together provide strong evidence for a general factor of cognitive aging that strengthens with advancing adult age. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Why is cognitive change more negative with increased age?

OBJECTIVE

The primary goal of the current study was to investigate factors contributing to more negative cognitive change at older ages.

METHOD

Longitudinal data on 12 cognitive tests were examined in 2,637 adults ranging from 18 to 85 years of age. Because both the intervals between measurement occasions and the number of occasions varied across participants, it was possible to investigate effects of interval and number of measurement occasions on cognitive change in adults of different ages. In addition, about 1/2 of the participants performed alternate versions of the tests on a second and third session on the first occasion, which allowed change to be monitored over intervals of less than 1 week.

RESULTS

Regression analyses revealed that cognitive change was more negative with increases in the interval between occasions but was more positive with additional measurement occasions. Both the effects of interval and of number of measurement occasions were similar across adulthood. Increased age was associated with more positive gains over a period of a few days but was associated with more negative declines when the intervals between occasions averaged about 3 years.

CONCLUSIONS

This combination of results suggests that longitudinal change in cognitive functioning is more negative at older ages not because of greater declines with increases in the interval between measurement occasions, or because of smaller gains with additional measurements. Instead most of the age differences in change may be due to greater losses of benefits associated with the initial assessment over intervals of months or more from the initial assessment. (PsycINFO Database Record

Shared and unique influences on age-related cognitive change

OBJECTIVE

Decompose cognitive change into influences unique to particular cognitive domains, and influences shared across different cognitive domains.

METHOD

A total of 2,546 adults between 18 and 95 years of age performed a battery of 12 cognitive tests on 2 occasions separated by an average of 3 years. An estimate of general cognitive functioning based on the first principal factor was regressed from the observed cognitive scores to derive an estimate of specific influences on each measure, and this value was subtracted from the observed score to provide an estimate of general influences on the measure. Longitudinal change was assessed by the (T2 - T1) difference between scores on the 2 occasions.

RESULTS

Although increased age was associated with specific influences on speed in cross-sectional comparisons, and in memory change in longitudinal comparisons among older adults, most of the relations between age and cognitive functioning in both cross-sectional and longitudinal comparisons were manifested as general influences shared with other cognitive measures.

CONCLUSIONS

Differences in cognitive functioning associated with aging are often attributed to domain-specific effects, but results from this and other recent studies suggest that large proportions of the age differences are associated with general influences shared across different types of cognitive measures. (PsycINFO Database Record