Interrelations of age, self-reported health, speed, and memory.

Earles, Julie L.; Connor, Lisa Tabor; Smith, Anderson D.; Park, Denise C.

doi:10.1037/0882-7974.12.4.675

Cited by 39 publications

(30 citation statements)

References 38 publications

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“…Age was regressed on the adjusted brain volumes to investigate linear or higher order correlations. The contribution of a quadratic age component was examined by means of the R 2 change when age and age 2 were entered into the model successively (whereas correcting for collinearity between those variables, according to the method described in [11]). To test whether the regional volume changes exceeded that of the total brain, total brain volume and age were entered successively into a model with regional brain volume as the dependent variable.…”

Section: Discussionmentioning

confidence: 99%

The relation between global and limbic brain volumes on MRI and cognitive performance in healthy individuals across the age range

Tisserand

Visser

Boxtel

et al. 2000

Neurobiology of Aging

118

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The present study investigated the range of age-related changes in brain morphology and the relation with performance on memory and other cognitive tests in a healthy population. A group of 61 subjects (21 to 81 years old, mean ϭ 55.7), free from cognitive and medical deficits, underwent MRI scanning and neuropsychological assessment encompassing memory and other cognitive tests. Volumetry of the hippocampus, parahippocampal gyrus, mamillary bodies, third ventricle, and total brain matter was performed. The results indicate that in healthy individuals increases in ventricular volume and volume decreases in total brain matter, hippocampus and parahippocampal gyrus, but not mamillary bodies, are clearly apparent with increasing age. However, no relation could be established between the brain volumes and test performance when controlling for the effects of age. To conclude, variations in total and limbic brain volumes do not seem predictive for cognitive performance independent of age.

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Section: Discussionmentioning

confidence: 99%

The relation between global and limbic brain volumes on MRI and cognitive performance in healthy individuals across the age range

Tisserand

Visser

Boxtel

et al. 2000

Neurobiology of Aging

118

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“…Subjective health also was measured by means of an inventory of subjective health (VOEG-21) [17]. The number of physician-prescribed medications currently taken was used as an objective index of health status [18].…”

Section: Health Measuresmentioning

confidence: 99%

Predictors of attrition in a longitudinal cognitive aging study:The Maastricht Aging Study (MAAS)

Beijsterveldt

Boxtel

Bosma

et al. 2002

Journal of Clinical Epidemiology

114

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A large sample of older participants of the Maastricht Aging Study (MAAS) were compared to drop-outs at the 3-year follow-up with respect to socio-demographic, health, and cognitive characteristics. In addition, the impact of selective drop-out on measures of cognitive change was examined. To this end, hypothetical scores were estimated for drop-outs by using single and multiple imputation methods. Of the initial sample of 539 subjects, aged 49 years and older at baseline, 116 (22 %) did not return for the follow-up ( n ϭ 32 had died, n ϭ 84 refused participation). Drop-outs who refused to participate in the follow-up were more often women, had lower educational levels, and had lower baseline scores on neurocognitive tests. Follow-up drop-outs who had died were more often men, older, and had a poorer performance on cognitive tests than the follow-up participants. Although follow-up participants and drop-outs differed in terms of socio-demographic and cognitive characteristics, attrition appeared to have little effect on the estimates of cognitive change.

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“…Some studies have found virtually no relationship between self-reported health and cognitive performance after controlling for demographic variables including age [2,[14][15][16][17], although there is evidence that self-reported health explains age differences in perceptual speed [18]. Depression has been shown to explain about 1% of the variance in cognitive performance in two large population studies [16,19] and between 3 and 16% in adults aged 60-90 in another study [20].…”

Section: Introductionmentioning

confidence: 99%

Education, Activity, Health, Blood Pressure and Apolipoprotein E as Predictors of Cognitive Change in Old Age: A Review

2000

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Background: Cross-sectional studies have identified a number of health and lifestyle factors that correlate with cognitive function in old age. It is important to know whether these factors also predict change in cognitive function over time. Objective: To evaluate published findings on genetic, health and lifestyle predictors of cognitive change in late adulthood. Methods: Studies reporting data on education, health, blood pressure, activity and apolipoprotein E (APOE) as predictors of cognitive change were reviewed. A total of 34 studies were identified that reported data on these predictors. The average follow-up period of studies reviewed was 7.68 years. Results: Results showed that education, hypertension, objective indices of health and cardiovascular disease, and APOE were associated with cognitive change. Results regarding the effect of physical activity on cognitive change were inconclusive. Conclusion: Despite the lack of data on some predictors, the longitudinal trends are generally consistent with cross-sectional findings on predictors of cognitive performance in old age. More research is required to compare the influence of predictors on different types of cognitive abilities.

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Interrelations of age, self-reported health, speed, and memory.

Cited by 39 publications

References 38 publications

The relation between global and limbic brain volumes on MRI and cognitive performance in healthy individuals across the age range

The relation between global and limbic brain volumes on MRI and cognitive performance in healthy individuals across the age range

Predictors of attrition in a longitudinal cognitive aging study:The Maastricht Aging Study (MAAS)

Education, Activity, Health, Blood Pressure and Apolipoprotein E as Predictors of Cognitive Change in Old Age: A Review

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