It is critical to discover why some people's cognitive abilities age better than others'. We applied multivariate growth curve models to data from a narrow-age cohort measured on a multi-domain IQ measure at age 11 years and a comprehensive battery of thirteen measures of visuospatial, memory, crystallized, and processing speed abilities at ages 70, 73, and 76 years (n = 1091 at age 70). We found that 48% of the variance in change in performance on the thirteen cognitive measures was shared across all measures, an additional 26% was specific to the four ability domains, and 26% was test-specific. We tested the association of a wide variety of sociodemographic, fitness, health, and genetic variables with each of these cognitive change factors. Models that simultaneously included all covariates accounted for appreciable proportions of variance in the cognitive change factors (e.g. approximately one third of the variance in general cognitive change). However, beyond physical fitness and possession of the APOE e4 allele, very few predictors were incrementally associated with cognitive change at statistically significant levels. The results highlight a small number of factors that predict differences in cognitive ageing, and underscore that correlates of cognitive level are not necessarily predictors of decline. Even larger samples will likely be required to identify additional variables with more modest associations with normal-range heterogeneity in aging-related cognitive declines.

BackgroundIntra-individual variability in reaction time (RT IIV) is considered to be an index of central nervous system functioning. Such variability is elevated in neurodegenerative diseases or following traumatic brain injury. It has also been suggested to increase with age in healthy ageing.ObjectivesTo investigate and quantify age differences in RT IIV in healthy ageing; to examine the effect of different tasks and procedures; to compare raw and mean-adjusted measures of RT IIV.Data SourcesFour electronic databases: PsycINFO, Medline, Web of Science and EMBASE, and hand searching of reference lists of relevant studies.Study EligibilityEnglish language journal articles, books or book chapters, containing quantitative empirical data on simple and/or choice RT IIV. Samples had to include younger (under 60 years) and older (60 years and above) human adults.Study Appraisal and SynthesisStudies were evaluated in terms of sample representativeness and data treatment. Relevant data were extracted, using a specially-designed form, from the published report or obtained directly from the study authors. Age-group differences in raw and RT-mean-adjusted measures of simple and choice RT IIV were quantified using random effects meta-analyses.ResultsOlder adults (60+ years) had greater RT IIV than younger (20–39) and middle-aged (40–59) adults. Age effects were larger in choice RT tasks than in simple RT tasks. For all measures of RT IIV, effect sizes were larger for the comparisons between older and younger adults than between older and middle-aged adults, indicating that the age-related increases in RT IIV are not limited to old age. Effect sizes were also larger for raw than for RT-mean-adjusted RT IIV measures.ConclusionsRT IIV is greater among older adults. Some (but not all) of the age-related increases in RT IIV are accounted for by the increased RT means.

Men are often found to have faster and less variable reaction times (RTs) than do women. However, it has not been established whether these differences occur in children. One suggestion is that sex differences in RT variability may be due to the effect of sex hormones on the brain and, by implication, may be expected in adults but not in children. The present study investigates sex differences in RT mean and intraindividual variability in a sample that includes both children and adults (age range = 4-75 years). Mean and intraindividual variability of simple RT (SRT) and 4-choice RT (CRT) were measured in 1,994 visitors to science festivals held in Edinburgh, Scotland, in 2008 and 2009 and in Cheltenham and Cambridge, England, in 2008. The commonly reported pattern of decreasing RT mean and variability in childhood and adolescence, followed by an increase in mean and variability through adulthood and into old age, was confirmed. Greater intraindividual variability for females in SRT and CRT was observed in adults but not in children. Males had significantly faster mean SRT than did females across the life span, but there were no sex differences in mean CRT.

Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=−0.11; high body mass index (BMI)−low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)–GREML; independent samples bivariate GCTA–GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of −0.51 (s.e. 0.15) was observed using the same-sample GCTA–GREML approach compared with −0.10 (s.e. 0.08) from the independent-samples GCTA–GREML approach and −0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10−7) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at P<5 × 10−5, which is significantly more than expected by chance (P=0.007). All these results suggest there are shared genetic contributions to BMI and cognitive function.

In order to assess the degree of cognitive decline resulting from a pathological state, such as dementia, or from a normal aging process, it is necessary to know or to have a valid estimate of premorbid (or prior) cognitive ability. The National Adult Reading Test (NART; Nelson & Willison, 1991) and the Wechsler Test of Adult Reading (WTAR; Psychological Corporation, 2001) are 2 tests developed to estimate premorbid or prior ability. Due to the rarity of actual prior ability data, validation studies usually compare NART/WTAR performance with measures of current abilities in pathological and nonpathological groups. In this study, we validate the use of WTAR scores and extend the validation of the use of NART scores as estimates of prior ability, vis-à-vis the actual prior (childhood) cognitive ability. We do this in a large sample of healthy older people, the Lothian Birth Cohort 1936 (Deary, Gow, Pattie, & Starr, 2012; Deary et al., 2007). Both NART and WTAR scores were correlated with cognitive ability tested in childhood (r = .66-.68). Scores on both the NART and the WTAR had high stability over a period of 3 years in old age (r in excess of .90) and high interrater reliability. The NART accounted for more unique variance in childhood intelligence than did the WTAR.