Midlife level and 15-year changes in general cognitive ability in a sample of men: The role of education, early adult ability, BMI, and pulse pressure

Cognitive Change Before Old Age (11 to 70) Predicts Cognitive Change During Old Age (70 to 82)

Identifying predictors of cognitive decline in old age helps us understand its mechanisms and identify those at greater risk. Here, we examined how cognitive change from ages 11 to 70 is associated with cognitive change at older ages (70 to 82 years) in the Lothian Birth Cohort 1936 longitudinal study (N = 1,091 at recruitment). Using latent-growth-curve models, we estimated rates of change from ages 70 to 82 in general cognitive ability (g) and in three cognitive domains: visuospatial, memory, and processing speed. We found that g accounted for 71.3% of interindividual change variance. Greater cognitive gain from ages 11 to 70 predicted slower decline in g over 12 subsequent years (β = 0.163, p = .001), independently of cognitive level in childhood and at age 70, and domain-specific change beyond g. These results contribute to the goal of identifying people at higher risk of age-related cognitive decline.

Biological and environmental predictors of heterogeneity in neurocognitive ageing: Evidence from Betula and other longitudinal studies

Individual differences in cognitive performance increase with advancing age, reflecting marked cognitive changes in some individuals along with little or no change in others. Genetic and lifestyle factors are assumed to influence cognitive performance in ageing by affecting the magnitude and extent of age-related brain changes (i.e., brain maintenance or atrophy), as well as the ability to recruit compensatory processes. The purpose of this review is to present findings from the Betula study and other longitudinal studies, with a focus on clarifying the role of key biological and environmental factors assumed to underlie individual differences in brain and cognitive ageing. We discuss the vital importance of sampling, analytic methods, consideration of non-ignorable dropout, and related issues for valid conclusions on factors that influence healthy neurocognitive ageing.

Education and age-related decline in cognitive performance: Systematic review and meta-analysis of longitudinal cohort studies

Central theories of cognitive aging propose that education is an important protective factor for decline in cognitive performance in older age. We conducted a systematic review and meta-analysis of reported estimates of an association between educational attainment and change in performance in six cognitive domains (episodic memory, processing speed, verbal fluency, crystallized intelligence, fluid intelligence, and global ability) in the general population of older individuals. The systematic search (11^th of October 2019) identified 92 eligible articles. The episodic memory domain had the highest number of estimates (37 estimates from 18 articles, n = 109,281) included in the meta-analysis. The fewest estimates (6 estimates from 6 articles, n = 5263) were included for fluid intelligence. Pooled mean estimates from an inverse-variance weighted random effects analysis were not statistically significant and indicated that any association between education and change in cognitive performance is likely of a negligible magnitude. The estimates for education's role (one additional year) for change in cognitive performance ranged from -0.019 (95 % confidence interval, CI = -0.047, 0.010) to 0.004SD (CI = -0.003, 0.012) per decade. Even if the larger positive point estimates (i.e., protective effects) are selectively considered, the influence of education on change is still at least 12 times less important for the cognitive functioning of an older individual than the association between education and level of cognitive performance. Sensitivity analyses did not substantially alter these results. However, heterogeneity was substantial, and remained largely unexplained by mean age, mean educational attainment, Gini coefficient, GDP per capita, maximum follow-up period, and publication year. Overall, education is an important factor in aging due to its robust association with level of performance, but the current base of empirical evidence is not revealing a consistent and substantial association between educational attainment and changes in cognitive performance in the general population. Theories of cognitive aging must be updated to incorporate this pattern of findings.

School Performance and Educational Attainment as Early-Life Predictors of Age-Related Memory Decline: Protective Influences in Later-Born Cohorts

Objectives

Evidence is accumulating that early-life characteristics and experiences contribute significantly to differences in cognitive aging. This study investigated whether school performance at age 12 predicted late-life level and rate of memory change over 15–25 years, and whether its potential protective influence on memory change was mediated by educational attainment or income.

Methods

Latent growth curve models were fitted to 15–25 year longitudinal memory data from a population-based sample, stratified on age cohorts (n = 227, born 1909–1935; n = 301, born 1938–1954).

Results

A latent-level school grade variable significantly predicted both memory level and slope in later-born cohorts. Higher grades were associated with higher level and reduced decline, measured between ages 45 and 70 years, on average. In the earlier-born cohorts, grades predicted memory level, but not slope, measured between ages 66 and 81 years. Follow-up analyses indicated that the protective influence of higher school grades in later-born cohorts was partially mediated by educational attainment, but independent of income.

Discussion

The results suggest that higher childhood school performance is protective against age-related cognitive decline in younger or later-born cohorts, for which further education has been more accessible. Education may exert such influence through increased cognitive reserve or more well-informed health- and lifestyle decisions.

Augmented Reality and Mobile Devices: A Binominal Methodological Resource for Inclusive Education (SDG 4). An Example in Secondary Education

The rise of so-called emerging technologies is broadening the way in which students access information and in turn changing the way in which they can interact and the experiences to which they are exposed. Mobile devices are regarded as flexible tools that facilitate access to information in different formats and in any environment. For its part, Augmented Reality is a technique that, through mobile tools, can enhance the globalization of content and access to contextual information in various ways. Together, the globalization of mobile devices and Augmented Reality contribute to an inclusive, equitable, and quality education, as mentioned by the United Nations Educational, Scientific, and Cultural Organization (UNESCO) in goal four on Sustainable Development (Sustainable Development Goals 4 (SDG 4)). This article analyses the binomial Augmented Reality-mobile devices, and takes a conceptual approach to these technological environments, both the technique and the tool, in the context of quality education. To assess the potential of Augmented Reality-mobile devices as a methodological learning resource, a learning unit of Secondary Education is presented in the field of Technology, enriched with different materials related with Augmented Reality.